26-12-2010, 10:25 AM
1. INTRODUCTION
FT-IR stands for Fourier Transform Infrared, the preferred method of infrared spectroscopy. In infrared spectroscopy, IR radiation is passed through a sample. Some of the infrared radiation is absorbed by the sample and some of it is passed through (transmitted). The resulting spectrum represents the molecular absorption and transmission, creating a molecular fingerprint of the sample. Like a fingerprint no two unique molecular structures produce the same infrared spectrum. Many of the volatile organic compounds of interest to the environmental, military, and industrial hygiene communities have characteristic spectral features that can be used for identification and quantification. An FTIR (Fourier Transform Infrared) is a method of obtaining infrared spectra by first collecting an interferogram of a sample signal using an interferometer, then performing a Fourier Transform on the interferogram to obtain the spectrum. An FTIR spectrometer is a spectral instrument that collects and digitizes the interferogram, performs the Fourier transform function and displays the spectrum. The resulting spectrum is then processed by the spectral signal processing software which also controls the moving-mirror in the system to move.
A rapid scan spectrometer had been invented by Gao Zhan and Xiang Libin, but the spectrometer did not contain signal processing part. A scanning FTIR system was designed by Harig R. to detect airborne pollutants, but spectral signal processing software of the system was based on PC platforms in which a PC was used to control the whole electronic system. However, in some practical applications, PC based processors cannot be used and hence the SSPS has to be designed with embedded processors. Traditional PC based FTIR spectral signal processing software is unable to meet the demands in real-time applications. An embedded processor, PC104, instead of PC, is used in this system to control spectrometer. A new kind of spectral signal processing module, which uses a high-speed floating point Digital Signal Processor (DSP) as its central processing unit, is devised for this spectrometer. This module is called Spectral Signal Processing System (SSPS). Details on hardware and software design solutions of this SSPS module are discussed in later sections.
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2. WHY INFRARED SPECTROSCOPY?
Infrared spectroscopy has been a workhorse technique for materials analysis in the laboratory for over seventy years. An infrared spectrum represents a fingerprint of a sample with absorption peaks which correspond to the frequencies of vibrations between the bonds of the atoms making up the material. Because each different material is a unique combination of atoms, no two compounds produce the exact same infrared spectrum. Therefore, infrared spectroscopy can result in a positive identification (qualitative analysis) of every different kind of material. In addition, the size of the peaks in the spectrum is a direct indication of the amount of material present. With modern software algorithms, infrared is an excellent tool for quantitative analysis.
The information that FT-IR can provide are:
• It can identify unknown materials
• It can determine the quality or consistency of a sample
• It can determine the amount of components in a mixture
3. OLDER TECHNOLOGY
The original infrared instruments were of the dispersive type. These instruments separated the individual frequencies of energy emitted from the infrared source. This was accomplished by the use of a prism or grating. An infrared prism works exactly the same as a visible prism which separates visible light into its colors (frequencies). A grating is a more modern dispersive element which better separates the frequencies of infrared energy. The detector measures the amount of energy at each frequency which has passed through the sample. This results in a spectrum which is a plot of intensity vs. frequency.
Fourier transform infrared spectroscopy is preferred over dispersive or filter methods of infrared spectral analysis for several reasons:
• It is a non-destructive technique
• It provides a precise measurement method which requires no external calibration
• It can increase speed, collecting a scan every second
• Increase sensitivity-one second scans can be co-added together to ratio out random noise
• It has greater optical throughput
• It is mechanically simple with only one moving part
4. WHY FT-IR?
Fourier Transform Infrared (FT-IR) spectrometry was developed in order to overcome the limitations encountered with dispersive instruments. The main difficulty was the slow scanning process. A method for measuring all of the infrared frequencies simultaneously, rather than individually, was needed. A solution was developed which employed a very simple optical device called an interferometer. The interferometer produces a unique type of signal which has all of the infrared frequencies “encoded” into it. The signal can be measured very quickly, usually on the order of one second or so. Thus, the time element per sample is reduced to a matter of a few seconds rather than several minutes. Most interferometers employ a beam splitter which takes the incoming infrared beam and divides it into two optical beams. One beam reflects off of a flat mirror which is fixed in place. The other beam reflects off of a flat mirror which is on a mechanism which allows this mirror to move a very short distance (typically a few millimeters) away from the beam splitter. The two beams reflect off of their respective mirrors and are recombined when they meet back at the beam splitter.
Because the path that one beam travels is a fixed length and the other is constantly changing as its mirror moves, the signal which exits the interferometer is the result of these two beams “interfering” with each other. The resulting signal is called an interferogram which has the unique property that every data point (a function of the moving mirror position) which makes up the signal has information about every infrared frequency which comes from the source. This means that as the interferogram is measured; all frequencies are being measured simultaneously. Thus, the use of the interferometer results in extremely fast measurements. Because the analyst requires a frequency spectrum (a plot of the intensity at each individual frequency) in order to make identification, the measured interferogram signal cannot be interpreted directly. A means of “decoding” the individual frequencies is required. This can be accomplished via a well-known mathematical technique called the Fourier transformation. This transformation is performed by the computer which then presents the user with the desired spectral information for analysis.
5. THE SAMPLE ANALYSIS PROCESS
Figure 2: The sample analysis process
The normal instrumental process is as follows:
1. The Source: Infrared energy is emitted from a glowing black-body source. This beam passes through an aperture which controls the amount of energy presented to the sample (and, ultimately, to the detector).
2. The Interferometer: The beam enters the interferometer where the “spectral encoding” takes place. The resulting interferogram signal then exits the interferometer.
3. The Sample: The beam enters the sample compartment where it is transmitted through or reflected off of the surface of the sample, depending on the type of analysis being accomplished. This is where specific frequencies of energy, which are uniquely characteristic of the sample, are absorbed.
4. The Detector: The beam finally passes to the detector for final measurement. The detectors used are specially designed to measure the special interferogram signal.
5. The Computer: The measured signal is digitized and sent to the computer where the Fourier transformation takes place. The final infrared spectrum is then presented to the user for interpretation and any further manipulation.
6. THE INTERFEROMETER
The interferometer used is the Michelson interferometer. It is the most common configuration for optical interferometry. An interference pattern is produced by splitting a beam of light into two paths, bouncing the beams back and recombining them. The different paths may be of different lengths or be composed of different materials to create alternating interference fringes on a back detector.
Figure 3: Path of light in Michelson interferometer
Michelson interferometer consists of two highly polished mirrors, a source that emits monochromatic light that hits the surface at point and a beam splitter. The beam splitter splits the wave into two. One travels towards the moving mirror and other towards the fixed mirror. After reflecting from these mirrors, both beams recombine at the beam splitter to produce an interference pattern (assuming proper alignment) visible to the observer at the detector point.
There are two paths from the (light) source to the detector. One reflects off the semi-transparent mirror, goes to the top mirror and then reflects back, goes through the semi-transparent mirror, to the detector. The other first goes through the semi-transparent mirror, to the mirror on the right, reflects back to the semi-transparent mirror, then reflects from the semi-transparent mirror into the detector. The principle is when a parallel beam of light coming from a monochromatic extended light source is incident on a half silvered glass plate, it is divided into two beams of equal intensities by partial reflection and transmission.
Figure 4: The interference pattern
Both beams are coherent. In this experiment coherent waves are thus produced by the method of division of amplitude. If these two paths differ by a whole number (including 0) of wavelengths, there is constructive interference and a strong signal at the detector. If they differ by a whole number and half wavelengths (e.g., 0.5, 1.5, 2.5 ...) there is destructive interference and a weak signal. This might appear at first sight to violate the principle of conservation of energy. However energy is conserved, because there is a redistribution of energy at the detector in which the energy at the destructive sites is re-distributed to the constructive sites. The effect of the interference is to alter the share of the reflected light which heads for the detector and the remainder which heads back in the direction of the source.
6.1 RESOLUTION
The interferogram belongs in the length domain. Fourier transform (FT) inverts the dimension, so the FT of the interferogram belongs in the reciprocal length domain that is the wave number domain. The spectral resolution in wave numbers per cm is equal to the reciprocal of the maximum retardation in cm. The use of corner-cube mirrors in place of the flat mirrors is helpful as an outgoing ray from a corner-cube mirror is parallel to the incoming ray, regardless of the orientation of the mirror about axes perpendicular to the axis of the light beam.
7. CHALLENGES OF HIGH-SPEED DSP DESIGN
Today’s digital signal processors (DSPs) are typically run at a 1GHz internal clock rate while transmit and receive signals to and from external devices operate at rates higher than 200MHz. These fast switching signals generate a considerable amount of noise and radiation, which degrades system performance and creates electromagnetic interference (EMI) problems that make it difficult to pass tests required to obtain certification from the Federal Communication Commission (FCC). Good high-speed system design requires robust power sources with low switching noise under dynamic loading conditions, minimum crosstalk between high-speed signal traces, high- and low-frequency decoupling techniques, and good signal integrity with minimum transmission line effects. This document provides recommendations for meeting the many challenges of high-speed DSP system design.
8. SSPS SYSTEM OVERVIEW
SSPS (Spectral Signal Processing System) need to store large amount of interferogram data, effective processing and identification algorithms, process the stored interferogram data of FTIR system in real-time, and send interferogram data and results to host computer or controller for further processing or to control the electronic and mechanical parts (moving mirror) effectively.
SSPS needs two main abilities:
1. The ability to process interferogram data with high speed.
2. The ability to receive and send interferogram data with high speed.
9. HARDWARE DESIGN OF SSPS
The hardware architecture of the SSPS platform is based on a high-speed, floating-point DSP processor. The hardware architecture is divided into the following main parts.
1. Signal Processing Block
TMS320C6713 DSP Processor
2. Data Transmission Block
Multi channel Buffered Serial Port (McBSP)
Dual port RAM
3. Memory Part
Dual Port RAM
Synchronous Dynamic RAM (SD RAM)
Synchronous Pipelined Cache RAM (SPC RAM)
FLASH Memory
4. Other devices
+5V power supply
Complex Programmable Logic Device (CPLD)
Figure 6: The hardware architecture of SSPS
9.1 SIGNAL PROCESSING BLOCK
The signal processing block is used to analyze the data acquired by FTIR spectrometer automatically, with real-time algorithms. The TMS320C6713 (C6713), which is a high speed floating point DSP processor, is chosen as the central processing unit of this SSPS platform. In this system, the floating-point data sampled by FTIR spectrometer is transmitted to C6713 through dual-port RAM, and stored in the memory part. C6713 is operating at 225MHz, and delivers 1350 million floating-point operations per second. Firstly, interferogram is transformed into a spectrum via Fast Fourier Transform (FFT), processed using some technical methods and the result is obtained using pattern recognition algorithm. All of the real-time algorithms, including FFT, digitally filtering, baseline correction, wave-number correction, phase correction, and pattern recognition, are implemented in floating-point mode.
9.2 DATA TRANSMISSION BLOCK
In spite of being almost completely physically embedded in the DSP, special reference should be made to the interface capabilities of the module. There are two types of interfaces for the communications between SSPS and controller. They are multichannel buffered serial port (McBSP) and Dual port RAM. Two multi-channels buffered serial ports are used for the communication between SSPS and host computer. In this system, McBSPs are configured to the Universal Asynchronous Receiver/Transmitter (UART) standard, which is a well-established protocol for the exchange of serial data.
To interface a UART to the McBSP in serial port mode, the UART’s transmit data line is connected to both the data input and the frame synchronization input on the McBSP. This is because the UART serial data line contains both framing and data information. The UART’s receive data line is connected to the data output of the McBSP. Figure 7 illustrates the UART to McBSP connection. In order to interface McBSP to the RS-232 port of the host computer, the data signal needs to go through a RS-232 converter to translate from the CMOS logic levels to the RS-232 logic levels. A MAX488 device is used in SSPS as the logic levels converter. SSPS gets the interferogram data from spectrometer by Dual-Port RAM. Dual-Port RAM is not only a memory device, but also a data transmission interface in SSPS.
9.3 MEMORY PART
The memory part is used to store blocks of code and data of SSPS. Despite of the internal memory of TMS320C6713 DSP, there are four kinds of external memory devices:
1. Synchronous Dynamic RAM (SDRAM)
SDRAM is dynamic random access memory (DRAM) that has a synchronous interface. SDRAM has a synchronous interface, meaning that it waits for a clock signal before responding to control inputs and is therefore synchronized with the computer's system bus.
2. Synchronous-Pipelined Cache RAM
Cache memory (also called buffer memory) is local memory that reduces waiting times for information stored in the RAM (Random Access Memory).
3. NOR Flash Memory
NOR flash memory is a type of non-volatile storage technology that does not require power to retain data.
4. Dual-port RAM
Dual port RAM has ability to simultaneously read and write different memory cells at different addresses.
The clock to four synchronous devices is given by the internal Phase-Locked-Loop (PLL) of DSP. All of the interferogram and spectrum is stored and processed in floating-point style. The original interferogram sampled by FTIR spectrometer is stored in Dual-port RAM, with floating-point style. Dual-port RAM is a memory shared by SSPS and ADC controller. Both of SSPS and spectrometer can read and write data to Dual-port RAM.
9.4 OTHER DEVICES
The SSPS operates from a single +5V external power supply connected to the main power input. Internally, the +5V input is converted to +1.26V and +3.3V using separate voltage regulators. The +1.26V supply is used for the DSP core while the +3.3V supply is used for the I/O buffers of DSP and all other chips on the board. A Complex Programmable Logic Device (CPLD) device is used to implement functionality specific to SSPS. The CPLD has a register based user interface that lets the user configure the board by reading and writing to its registers.
10. SOFTWARE DESIGN
10.1 SOFTWARE ARCHITECTURE
The system software can be divided into four parts: data transmission software, signal processing software, chip support library, and registers configuration program. The data transmission software deals with the data to be transmitted to the controller or host computer and monitors the data received from the controller or dual port RAM. The chip support library is a collection of functions, macros and symbols used to configure and operate the on-chip peripheral modules. The signal processing software processes the interferogram and transform it into a spectrum through different technical methods like digital filtering, Apodization, baseline correction, pattern recognition etc. The registers of the DSP processor and the complex programmable logic device are configured using the register configuration program.
Figure 8: Software architecture of SSPS
10.2 SIGNAL PROCESSING METHOD
Interferogram data has to be processed in real-time in order to get a result automatically. Figure 7 illustrates the signal processing layout of SSPS.
Figure 9: Signal processing method of SSPS
The different steps in signal processing are the following.
1. FOURIER TRANSFORMATION
Firstly, once interferogram have been collected, signal averaged, and stored, the next step is usually the transformation of the data to a spectrum. The interferogram and spectrum should be regarded as the complex pair. The complex inverse Fourier transform of the spectrum to produce the interferogram is shown in the following equation, where B (∆) in equation refers to spectrum, while I (∆) refer to interferogram.
2. PHASE CORRECTION
Ideally, the interferogram is symmetrical about the zero path difference. Due to optical, electronic, or sampling effects, an additional term called phase error has to be added to the phase angle. As a result, sine components are introduced into the interferogram. The process of removing the phase error, which is called phase correction, is done in SSPS. Phase correction is performed by removing sine components from an interferogram. Usually part of the double-sided interferogram is used for correction.
3. APODIZATION
Because the interferogram cannot be collected from t = -¥ to +¥, and is truncated, some error arises in the resulting spectrum: the line is broadened with side-lobes. An Apodization function is applied to correct the spectral line shape, by weighting the points collected in the interferogram. Boxcar truncation gives no Apodization and the narrowest lines. Common Apodization functions include Beer-Norton, Cosine and Happ-Genzel.
4. BACKGROUND SUBTRACTION
Because there needs to be a relative scale for the absorption intensity, a background spectrum must also be measured. This is normally a measurement with no sample in the beam. This can be compared to the measurement with the sample in the beam to determine the “percent transmittance.” This technique results in a spectrum which has all of the instrumental characteristics removed. Thus, all spectral features which are present are strictly due to the sample. A single background measurement can be used for many sample measurements because this spectrum is characteristic of the instrument itself.
5. BASELINE CORRECTION
It is usual in quantitative infrared spectroscopy to use a baseline joining the points of lowest absorbance on a peak, preferably in reproducibly flat parts of the absorption line. The absorbance difference between the baseline and the top of the band is then used. An example for baseline correction is shown in figure.
6. PATTERN RECOGNITION
At last, pattern recognition algorithms are used to mathematically determine the presence or absence of a target analyses. The pattern recognition inputs are the filtered spectra or interferogram and the outputs are the predicted classification of the pattern.
10.3 SOFTWARE IMPLEMENTATION
The majority of the SSPS software is written in C, using Code Composer Studio (CCS), which provides an integrated development environment to incorporate the software tools. CCS includes tools for code generation, such as a C compiler, an assembler, and a linker. For optimum performance, it is necessary to write some of the code in assembly language. Interrupt service routines that interact with DSP and ADC, is written in assembly.
The C source program is compiled by the C compiler with extension .c to produce an assembly source file with extension .asm. The assembler assembles an .asm source file to produce a machine language object file with extension .obj. The linker combines object files and object libraries as input to produce an executable file with extension .out. This executable file can be loaded and run directly on the C6713 processor.
An emulator is used for debugging the software. Attached to the JTAG port on the SSPS board, the emulator allows the software developer to examine all of the major components in the SSPS, including the C6713 registers, data and program memory, interface controller, and digital I/O controller. The emulator can also be used to load application software, and set breakpoints to halt execution when certain memory spaces are accessed.
11. ADVANTAGES OF FT-IR
Some of the major advantages of FT-IR over the dispersive technique include:
• Speed: Because all of the frequencies are measured simultaneously, most measurements by FT-IR are made in a matter of seconds rather than several minutes. This is sometimes referred to as the Felgett Advantage.
• Sensitivity: Sensitivity is dramatically improved with FT-IR for many reasons. The detectors employed are much more sensitive, the optical throughput is much higher (referred to as the Jacquinot Advantage) which results in much lower noise levels, and the fast scans enable the co addition of several scans in order to reduce the random measurement noise to any desired level (referred to as signal averaging).
• Mechanical Simplicity: The moving mirror in the interferometer is the only continuously moving part in the instrument. Thus, there is very little possibility of mechanical breakdown.
• Internally Calibrated: These instruments employ a HeNe laser as an internal wavelength calibration standard (referred to as the Connes Advantage). These instruments are self calibrating and never need to be calibrated by the user.
These advantages, along with several others, make measurements made by FT-IR extremely accurate and reproducible. Thus, it a very reliable technique for positive identification of virtually any sample. The sensitivity benefits enable identification of even the smallest of contaminants. This makes FT-IR an invaluable tool for quality control or quality assurance applications whether it be batch-to-batch comparisons to quality standards or analysis of an unknown contaminant. In addition, the sensitivity and accuracy of FT-IR detectors, along with a wide variety of software algorithms, have dramatically increased the practical use of infrared for quantitative analysis. Quantitative methods can be easily developed and calibrated and can be incorporated into simple procedures for routine analysis.
Thus, the Fourier Transform Infrared (FT-IR) technique has brought significant practical advantages to infrared spectroscopy. It has made possible the development of many new sampling techniques which were designed to tackle challenging problems which were impossible by older technology. It has made the use of infrared analysis virtually limitless.
12. APPLICATIONS
Figure 13 shows an application of this SSPS module in a FTIR spectrometer, which is designed for a real-time application system. An embedded processor, PC104, is used as the Central Processing Unit of this spectrometer. PC104 controls the moving-mirror to move, and collects the interferogram sampled by ADC device at the same time. Interferograms are then given to SSPS through dual-port RAM, by the way that C6713 and PC104 share the memory of dual-port RAM. The SSPS processes the data, using the signal processing methods mentioned above, and then gives a result of whether the target analytes is present or absent. C6713 works at 200MHz in this system. When the system works, FTIR spectrometer collects 10 interferograms per second and puts them into dual-port RAM. SSPS processes the interferograms with algorithms mentioned above and sends the results to the controller. Here are some timing-characters tested in experiments.
Figure 13: The SSPS module used in a spectrometer
This module can also be used as an effective signal processing platform for other real-time systems which need high-speed signal processing, such as
1. Speech recognition systems
2. Remote medical diagnostics
3. Audio
4. Radar
5. Imaging systems
In these cases, some signal processing algorithms in SSPS may be changed, and some other algorithms should be added to SSPS.
13. CONCLUSION
In this paper, the design and implementation of a novel FTIR spectral signal processing system are described. Both hardware and software of this SSPS module are designed. The use of high-speed floating point DSP in the module effectively accounts for the overall increase of flexibility and performance of FTIR spectrometer. A dual-port RAM is used in the system for vast data transmission. Three kinds of memory are chosen for SSPS to store interferogram and spectral data. In order to process the interferogram data in real time, three steps of effective signal processing methods are designed for SSPS. The software of SSPS is written in C language and assembly language, compiled by the CCS compiler, and stored in FLASH memory. The applications show that the proposed SSPS works quite well for spectral signal processing in FTIR spectrometer.
This module can also be used as an effective signal processing platform for other real-time systems which need high-speed signal processing, such as speech recognition systems, remote medical diagnostics, audio, radar, imaging systems, etc. In these cases, some signal processing algorithms in SSPS may be changed, and some other algorithms should be added to SSPS.
14. REFERENCES
[1] DONG Da-ming, FANG Yong-hua, XIONG Wei, LAN Tian-ge,”Design of a high
Speed spectral Signal processing system with floating point DSP for FTIR spectroscopy”, The Ninth International Conference on Electronic Measurements and Instruments (ICEMI),vol.1, pp.35-39, 2009
[2] Paduart Johan, Schoukens Johan, Rolain Yves ."Fast measurement of quantization
distortions in DSP algorithms", IEEE Transactions on Instrumentation and Measurement, vol.5, pp.1917-1923, October 2007
[3] Donatus ."DSP-based real-time implementation of a hybrid H infinity adaptive fuzzy
racking controller for servo-motor drives“, IEEE Transactions on Industry Applications,
vol 2, pp.476-484, March/April 2007
FT-IR stands for Fourier Transform Infrared, the preferred method of infrared spectroscopy. In infrared spectroscopy, IR radiation is passed through a sample. Some of the infrared radiation is absorbed by the sample and some of it is passed through (transmitted). The resulting spectrum represents the molecular absorption and transmission, creating a molecular fingerprint of the sample. Like a fingerprint no two unique molecular structures produce the same infrared spectrum. Many of the volatile organic compounds of interest to the environmental, military, and industrial hygiene communities have characteristic spectral features that can be used for identification and quantification. An FTIR (Fourier Transform Infrared) is a method of obtaining infrared spectra by first collecting an interferogram of a sample signal using an interferometer, then performing a Fourier Transform on the interferogram to obtain the spectrum. An FTIR spectrometer is a spectral instrument that collects and digitizes the interferogram, performs the Fourier transform function and displays the spectrum. The resulting spectrum is then processed by the spectral signal processing software which also controls the moving-mirror in the system to move.
A rapid scan spectrometer had been invented by Gao Zhan and Xiang Libin, but the spectrometer did not contain signal processing part. A scanning FTIR system was designed by Harig R. to detect airborne pollutants, but spectral signal processing software of the system was based on PC platforms in which a PC was used to control the whole electronic system. However, in some practical applications, PC based processors cannot be used and hence the SSPS has to be designed with embedded processors. Traditional PC based FTIR spectral signal processing software is unable to meet the demands in real-time applications. An embedded processor, PC104, instead of PC, is used in this system to control spectrometer. A new kind of spectral signal processing module, which uses a high-speed floating point Digital Signal Processor (DSP) as its central processing unit, is devised for this spectrometer. This module is called Spectral Signal Processing System (SSPS). Details on hardware and software design solutions of this SSPS module are discussed in later sections.
[attachment=7664]
2. WHY INFRARED SPECTROSCOPY?
Infrared spectroscopy has been a workhorse technique for materials analysis in the laboratory for over seventy years. An infrared spectrum represents a fingerprint of a sample with absorption peaks which correspond to the frequencies of vibrations between the bonds of the atoms making up the material. Because each different material is a unique combination of atoms, no two compounds produce the exact same infrared spectrum. Therefore, infrared spectroscopy can result in a positive identification (qualitative analysis) of every different kind of material. In addition, the size of the peaks in the spectrum is a direct indication of the amount of material present. With modern software algorithms, infrared is an excellent tool for quantitative analysis.
The information that FT-IR can provide are:
• It can identify unknown materials
• It can determine the quality or consistency of a sample
• It can determine the amount of components in a mixture
3. OLDER TECHNOLOGY
The original infrared instruments were of the dispersive type. These instruments separated the individual frequencies of energy emitted from the infrared source. This was accomplished by the use of a prism or grating. An infrared prism works exactly the same as a visible prism which separates visible light into its colors (frequencies). A grating is a more modern dispersive element which better separates the frequencies of infrared energy. The detector measures the amount of energy at each frequency which has passed through the sample. This results in a spectrum which is a plot of intensity vs. frequency.
Fourier transform infrared spectroscopy is preferred over dispersive or filter methods of infrared spectral analysis for several reasons:
• It is a non-destructive technique
• It provides a precise measurement method which requires no external calibration
• It can increase speed, collecting a scan every second
• Increase sensitivity-one second scans can be co-added together to ratio out random noise
• It has greater optical throughput
• It is mechanically simple with only one moving part
4. WHY FT-IR?
Fourier Transform Infrared (FT-IR) spectrometry was developed in order to overcome the limitations encountered with dispersive instruments. The main difficulty was the slow scanning process. A method for measuring all of the infrared frequencies simultaneously, rather than individually, was needed. A solution was developed which employed a very simple optical device called an interferometer. The interferometer produces a unique type of signal which has all of the infrared frequencies “encoded” into it. The signal can be measured very quickly, usually on the order of one second or so. Thus, the time element per sample is reduced to a matter of a few seconds rather than several minutes. Most interferometers employ a beam splitter which takes the incoming infrared beam and divides it into two optical beams. One beam reflects off of a flat mirror which is fixed in place. The other beam reflects off of a flat mirror which is on a mechanism which allows this mirror to move a very short distance (typically a few millimeters) away from the beam splitter. The two beams reflect off of their respective mirrors and are recombined when they meet back at the beam splitter.
Because the path that one beam travels is a fixed length and the other is constantly changing as its mirror moves, the signal which exits the interferometer is the result of these two beams “interfering” with each other. The resulting signal is called an interferogram which has the unique property that every data point (a function of the moving mirror position) which makes up the signal has information about every infrared frequency which comes from the source. This means that as the interferogram is measured; all frequencies are being measured simultaneously. Thus, the use of the interferometer results in extremely fast measurements. Because the analyst requires a frequency spectrum (a plot of the intensity at each individual frequency) in order to make identification, the measured interferogram signal cannot be interpreted directly. A means of “decoding” the individual frequencies is required. This can be accomplished via a well-known mathematical technique called the Fourier transformation. This transformation is performed by the computer which then presents the user with the desired spectral information for analysis.
5. THE SAMPLE ANALYSIS PROCESS
Figure 2: The sample analysis process
The normal instrumental process is as follows:
1. The Source: Infrared energy is emitted from a glowing black-body source. This beam passes through an aperture which controls the amount of energy presented to the sample (and, ultimately, to the detector).
2. The Interferometer: The beam enters the interferometer where the “spectral encoding” takes place. The resulting interferogram signal then exits the interferometer.
3. The Sample: The beam enters the sample compartment where it is transmitted through or reflected off of the surface of the sample, depending on the type of analysis being accomplished. This is where specific frequencies of energy, which are uniquely characteristic of the sample, are absorbed.
4. The Detector: The beam finally passes to the detector for final measurement. The detectors used are specially designed to measure the special interferogram signal.
5. The Computer: The measured signal is digitized and sent to the computer where the Fourier transformation takes place. The final infrared spectrum is then presented to the user for interpretation and any further manipulation.
6. THE INTERFEROMETER
The interferometer used is the Michelson interferometer. It is the most common configuration for optical interferometry. An interference pattern is produced by splitting a beam of light into two paths, bouncing the beams back and recombining them. The different paths may be of different lengths or be composed of different materials to create alternating interference fringes on a back detector.
Figure 3: Path of light in Michelson interferometer
Michelson interferometer consists of two highly polished mirrors, a source that emits monochromatic light that hits the surface at point and a beam splitter. The beam splitter splits the wave into two. One travels towards the moving mirror and other towards the fixed mirror. After reflecting from these mirrors, both beams recombine at the beam splitter to produce an interference pattern (assuming proper alignment) visible to the observer at the detector point.
There are two paths from the (light) source to the detector. One reflects off the semi-transparent mirror, goes to the top mirror and then reflects back, goes through the semi-transparent mirror, to the detector. The other first goes through the semi-transparent mirror, to the mirror on the right, reflects back to the semi-transparent mirror, then reflects from the semi-transparent mirror into the detector. The principle is when a parallel beam of light coming from a monochromatic extended light source is incident on a half silvered glass plate, it is divided into two beams of equal intensities by partial reflection and transmission.
Figure 4: The interference pattern
Both beams are coherent. In this experiment coherent waves are thus produced by the method of division of amplitude. If these two paths differ by a whole number (including 0) of wavelengths, there is constructive interference and a strong signal at the detector. If they differ by a whole number and half wavelengths (e.g., 0.5, 1.5, 2.5 ...) there is destructive interference and a weak signal. This might appear at first sight to violate the principle of conservation of energy. However energy is conserved, because there is a redistribution of energy at the detector in which the energy at the destructive sites is re-distributed to the constructive sites. The effect of the interference is to alter the share of the reflected light which heads for the detector and the remainder which heads back in the direction of the source.
6.1 RESOLUTION
The interferogram belongs in the length domain. Fourier transform (FT) inverts the dimension, so the FT of the interferogram belongs in the reciprocal length domain that is the wave number domain. The spectral resolution in wave numbers per cm is equal to the reciprocal of the maximum retardation in cm. The use of corner-cube mirrors in place of the flat mirrors is helpful as an outgoing ray from a corner-cube mirror is parallel to the incoming ray, regardless of the orientation of the mirror about axes perpendicular to the axis of the light beam.
7. CHALLENGES OF HIGH-SPEED DSP DESIGN
Today’s digital signal processors (DSPs) are typically run at a 1GHz internal clock rate while transmit and receive signals to and from external devices operate at rates higher than 200MHz. These fast switching signals generate a considerable amount of noise and radiation, which degrades system performance and creates electromagnetic interference (EMI) problems that make it difficult to pass tests required to obtain certification from the Federal Communication Commission (FCC). Good high-speed system design requires robust power sources with low switching noise under dynamic loading conditions, minimum crosstalk between high-speed signal traces, high- and low-frequency decoupling techniques, and good signal integrity with minimum transmission line effects. This document provides recommendations for meeting the many challenges of high-speed DSP system design.
8. SSPS SYSTEM OVERVIEW
SSPS (Spectral Signal Processing System) need to store large amount of interferogram data, effective processing and identification algorithms, process the stored interferogram data of FTIR system in real-time, and send interferogram data and results to host computer or controller for further processing or to control the electronic and mechanical parts (moving mirror) effectively.
SSPS needs two main abilities:
1. The ability to process interferogram data with high speed.
2. The ability to receive and send interferogram data with high speed.
9. HARDWARE DESIGN OF SSPS
The hardware architecture of the SSPS platform is based on a high-speed, floating-point DSP processor. The hardware architecture is divided into the following main parts.
1. Signal Processing Block
TMS320C6713 DSP Processor
2. Data Transmission Block
Multi channel Buffered Serial Port (McBSP)
Dual port RAM
3. Memory Part
Dual Port RAM
Synchronous Dynamic RAM (SD RAM)
Synchronous Pipelined Cache RAM (SPC RAM)
FLASH Memory
4. Other devices
+5V power supply
Complex Programmable Logic Device (CPLD)
Figure 6: The hardware architecture of SSPS
9.1 SIGNAL PROCESSING BLOCK
The signal processing block is used to analyze the data acquired by FTIR spectrometer automatically, with real-time algorithms. The TMS320C6713 (C6713), which is a high speed floating point DSP processor, is chosen as the central processing unit of this SSPS platform. In this system, the floating-point data sampled by FTIR spectrometer is transmitted to C6713 through dual-port RAM, and stored in the memory part. C6713 is operating at 225MHz, and delivers 1350 million floating-point operations per second. Firstly, interferogram is transformed into a spectrum via Fast Fourier Transform (FFT), processed using some technical methods and the result is obtained using pattern recognition algorithm. All of the real-time algorithms, including FFT, digitally filtering, baseline correction, wave-number correction, phase correction, and pattern recognition, are implemented in floating-point mode.
9.2 DATA TRANSMISSION BLOCK
In spite of being almost completely physically embedded in the DSP, special reference should be made to the interface capabilities of the module. There are two types of interfaces for the communications between SSPS and controller. They are multichannel buffered serial port (McBSP) and Dual port RAM. Two multi-channels buffered serial ports are used for the communication between SSPS and host computer. In this system, McBSPs are configured to the Universal Asynchronous Receiver/Transmitter (UART) standard, which is a well-established protocol for the exchange of serial data.
To interface a UART to the McBSP in serial port mode, the UART’s transmit data line is connected to both the data input and the frame synchronization input on the McBSP. This is because the UART serial data line contains both framing and data information. The UART’s receive data line is connected to the data output of the McBSP. Figure 7 illustrates the UART to McBSP connection. In order to interface McBSP to the RS-232 port of the host computer, the data signal needs to go through a RS-232 converter to translate from the CMOS logic levels to the RS-232 logic levels. A MAX488 device is used in SSPS as the logic levels converter. SSPS gets the interferogram data from spectrometer by Dual-Port RAM. Dual-Port RAM is not only a memory device, but also a data transmission interface in SSPS.
9.3 MEMORY PART
The memory part is used to store blocks of code and data of SSPS. Despite of the internal memory of TMS320C6713 DSP, there are four kinds of external memory devices:
1. Synchronous Dynamic RAM (SDRAM)
SDRAM is dynamic random access memory (DRAM) that has a synchronous interface. SDRAM has a synchronous interface, meaning that it waits for a clock signal before responding to control inputs and is therefore synchronized with the computer's system bus.
2. Synchronous-Pipelined Cache RAM
Cache memory (also called buffer memory) is local memory that reduces waiting times for information stored in the RAM (Random Access Memory).
3. NOR Flash Memory
NOR flash memory is a type of non-volatile storage technology that does not require power to retain data.
4. Dual-port RAM
Dual port RAM has ability to simultaneously read and write different memory cells at different addresses.
The clock to four synchronous devices is given by the internal Phase-Locked-Loop (PLL) of DSP. All of the interferogram and spectrum is stored and processed in floating-point style. The original interferogram sampled by FTIR spectrometer is stored in Dual-port RAM, with floating-point style. Dual-port RAM is a memory shared by SSPS and ADC controller. Both of SSPS and spectrometer can read and write data to Dual-port RAM.
9.4 OTHER DEVICES
The SSPS operates from a single +5V external power supply connected to the main power input. Internally, the +5V input is converted to +1.26V and +3.3V using separate voltage regulators. The +1.26V supply is used for the DSP core while the +3.3V supply is used for the I/O buffers of DSP and all other chips on the board. A Complex Programmable Logic Device (CPLD) device is used to implement functionality specific to SSPS. The CPLD has a register based user interface that lets the user configure the board by reading and writing to its registers.
10. SOFTWARE DESIGN
10.1 SOFTWARE ARCHITECTURE
The system software can be divided into four parts: data transmission software, signal processing software, chip support library, and registers configuration program. The data transmission software deals with the data to be transmitted to the controller or host computer and monitors the data received from the controller or dual port RAM. The chip support library is a collection of functions, macros and symbols used to configure and operate the on-chip peripheral modules. The signal processing software processes the interferogram and transform it into a spectrum through different technical methods like digital filtering, Apodization, baseline correction, pattern recognition etc. The registers of the DSP processor and the complex programmable logic device are configured using the register configuration program.
Figure 8: Software architecture of SSPS
10.2 SIGNAL PROCESSING METHOD
Interferogram data has to be processed in real-time in order to get a result automatically. Figure 7 illustrates the signal processing layout of SSPS.
Figure 9: Signal processing method of SSPS
The different steps in signal processing are the following.
1. FOURIER TRANSFORMATION
Firstly, once interferogram have been collected, signal averaged, and stored, the next step is usually the transformation of the data to a spectrum. The interferogram and spectrum should be regarded as the complex pair. The complex inverse Fourier transform of the spectrum to produce the interferogram is shown in the following equation, where B (∆) in equation refers to spectrum, while I (∆) refer to interferogram.
2. PHASE CORRECTION
Ideally, the interferogram is symmetrical about the zero path difference. Due to optical, electronic, or sampling effects, an additional term called phase error has to be added to the phase angle. As a result, sine components are introduced into the interferogram. The process of removing the phase error, which is called phase correction, is done in SSPS. Phase correction is performed by removing sine components from an interferogram. Usually part of the double-sided interferogram is used for correction.
3. APODIZATION
Because the interferogram cannot be collected from t = -¥ to +¥, and is truncated, some error arises in the resulting spectrum: the line is broadened with side-lobes. An Apodization function is applied to correct the spectral line shape, by weighting the points collected in the interferogram. Boxcar truncation gives no Apodization and the narrowest lines. Common Apodization functions include Beer-Norton, Cosine and Happ-Genzel.
4. BACKGROUND SUBTRACTION
Because there needs to be a relative scale for the absorption intensity, a background spectrum must also be measured. This is normally a measurement with no sample in the beam. This can be compared to the measurement with the sample in the beam to determine the “percent transmittance.” This technique results in a spectrum which has all of the instrumental characteristics removed. Thus, all spectral features which are present are strictly due to the sample. A single background measurement can be used for many sample measurements because this spectrum is characteristic of the instrument itself.
5. BASELINE CORRECTION
It is usual in quantitative infrared spectroscopy to use a baseline joining the points of lowest absorbance on a peak, preferably in reproducibly flat parts of the absorption line. The absorbance difference between the baseline and the top of the band is then used. An example for baseline correction is shown in figure.
6. PATTERN RECOGNITION
At last, pattern recognition algorithms are used to mathematically determine the presence or absence of a target analyses. The pattern recognition inputs are the filtered spectra or interferogram and the outputs are the predicted classification of the pattern.
10.3 SOFTWARE IMPLEMENTATION
The majority of the SSPS software is written in C, using Code Composer Studio (CCS), which provides an integrated development environment to incorporate the software tools. CCS includes tools for code generation, such as a C compiler, an assembler, and a linker. For optimum performance, it is necessary to write some of the code in assembly language. Interrupt service routines that interact with DSP and ADC, is written in assembly.
The C source program is compiled by the C compiler with extension .c to produce an assembly source file with extension .asm. The assembler assembles an .asm source file to produce a machine language object file with extension .obj. The linker combines object files and object libraries as input to produce an executable file with extension .out. This executable file can be loaded and run directly on the C6713 processor.
An emulator is used for debugging the software. Attached to the JTAG port on the SSPS board, the emulator allows the software developer to examine all of the major components in the SSPS, including the C6713 registers, data and program memory, interface controller, and digital I/O controller. The emulator can also be used to load application software, and set breakpoints to halt execution when certain memory spaces are accessed.
11. ADVANTAGES OF FT-IR
Some of the major advantages of FT-IR over the dispersive technique include:
• Speed: Because all of the frequencies are measured simultaneously, most measurements by FT-IR are made in a matter of seconds rather than several minutes. This is sometimes referred to as the Felgett Advantage.
• Sensitivity: Sensitivity is dramatically improved with FT-IR for many reasons. The detectors employed are much more sensitive, the optical throughput is much higher (referred to as the Jacquinot Advantage) which results in much lower noise levels, and the fast scans enable the co addition of several scans in order to reduce the random measurement noise to any desired level (referred to as signal averaging).
• Mechanical Simplicity: The moving mirror in the interferometer is the only continuously moving part in the instrument. Thus, there is very little possibility of mechanical breakdown.
• Internally Calibrated: These instruments employ a HeNe laser as an internal wavelength calibration standard (referred to as the Connes Advantage). These instruments are self calibrating and never need to be calibrated by the user.
These advantages, along with several others, make measurements made by FT-IR extremely accurate and reproducible. Thus, it a very reliable technique for positive identification of virtually any sample. The sensitivity benefits enable identification of even the smallest of contaminants. This makes FT-IR an invaluable tool for quality control or quality assurance applications whether it be batch-to-batch comparisons to quality standards or analysis of an unknown contaminant. In addition, the sensitivity and accuracy of FT-IR detectors, along with a wide variety of software algorithms, have dramatically increased the practical use of infrared for quantitative analysis. Quantitative methods can be easily developed and calibrated and can be incorporated into simple procedures for routine analysis.
Thus, the Fourier Transform Infrared (FT-IR) technique has brought significant practical advantages to infrared spectroscopy. It has made possible the development of many new sampling techniques which were designed to tackle challenging problems which were impossible by older technology. It has made the use of infrared analysis virtually limitless.
12. APPLICATIONS
Figure 13 shows an application of this SSPS module in a FTIR spectrometer, which is designed for a real-time application system. An embedded processor, PC104, is used as the Central Processing Unit of this spectrometer. PC104 controls the moving-mirror to move, and collects the interferogram sampled by ADC device at the same time. Interferograms are then given to SSPS through dual-port RAM, by the way that C6713 and PC104 share the memory of dual-port RAM. The SSPS processes the data, using the signal processing methods mentioned above, and then gives a result of whether the target analytes is present or absent. C6713 works at 200MHz in this system. When the system works, FTIR spectrometer collects 10 interferograms per second and puts them into dual-port RAM. SSPS processes the interferograms with algorithms mentioned above and sends the results to the controller. Here are some timing-characters tested in experiments.
Figure 13: The SSPS module used in a spectrometer
This module can also be used as an effective signal processing platform for other real-time systems which need high-speed signal processing, such as
1. Speech recognition systems
2. Remote medical diagnostics
3. Audio
4. Radar
5. Imaging systems
In these cases, some signal processing algorithms in SSPS may be changed, and some other algorithms should be added to SSPS.
13. CONCLUSION
In this paper, the design and implementation of a novel FTIR spectral signal processing system are described. Both hardware and software of this SSPS module are designed. The use of high-speed floating point DSP in the module effectively accounts for the overall increase of flexibility and performance of FTIR spectrometer. A dual-port RAM is used in the system for vast data transmission. Three kinds of memory are chosen for SSPS to store interferogram and spectral data. In order to process the interferogram data in real time, three steps of effective signal processing methods are designed for SSPS. The software of SSPS is written in C language and assembly language, compiled by the CCS compiler, and stored in FLASH memory. The applications show that the proposed SSPS works quite well for spectral signal processing in FTIR spectrometer.
This module can also be used as an effective signal processing platform for other real-time systems which need high-speed signal processing, such as speech recognition systems, remote medical diagnostics, audio, radar, imaging systems, etc. In these cases, some signal processing algorithms in SSPS may be changed, and some other algorithms should be added to SSPS.
14. REFERENCES
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Speed spectral Signal processing system with floating point DSP for FTIR spectroscopy”, The Ninth International Conference on Electronic Measurements and Instruments (ICEMI),vol.1, pp.35-39, 2009
[2] Paduart Johan, Schoukens Johan, Rolain Yves ."Fast measurement of quantization
distortions in DSP algorithms", IEEE Transactions on Instrumentation and Measurement, vol.5, pp.1917-1923, October 2007
[3] Donatus ."DSP-based real-time implementation of a hybrid H infinity adaptive fuzzy
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