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In this work, an intelligent optical monitoring system is presented, the operating principle of which is based on natural biological and optical systems. The monitoring system perceives its environment thought optical sensors for goal-directed actions even in dynamic changing environments and exhibits unsupervised and autonomous operation. Chromatic modulation methods are applied extensively to provide information compression in a form suitable for conventional image processing techniques. Chromaticity changes in a number of chromatic parameters are related to changes in physical plasma characteristics and properties (e.g., gas composition). An extensive range of parameters can be monitored with the same system so leading to the realization of a unified intelligent measurement philosophy.
Keywords: chromatic modulation, optical detection, electric arc, electric plasma
Introduction
Intelligent systems use ideas and get inspiration from natural systems and build on both established and novel techniques from a number of scientific fields, such as computer vision, machine learning and artificial intelligence. Intelligent systems may perceive their environment through sensors for goal-directed actions even in dynamic situations while learning and functioning autonomously in order to cope with changing environments or inaccurate a priori knowledge. Many intelligent optical systems incorporate those characteristics but are highly application dependent. Some systems are stand-alone applications which solve a specific measurement or detection problem, while others constitute a sub-system of a larger design. The specific implementation of an intelligent optical system also depends on, if its functionality is pre-specified or if some part of it can be learned or modified during operation.
In many intelligent optical monitoring systems, intensity modulation offers the advantages of inherent simplicity. However, conventional methods involving absolute intensity have associated problems. The most basic intensity monitoring systems use only a single photodiode to produce an output, but these systems tend to be sensitive to spurious changes in intensity resulting from variations in the light source or other components within the system. Removing these spurious effects is difficult and leads to complicated and expensive systems.
Wavelength monitoring systems attempt to deduce the state of a system by taking the ratio of intensities at two different wavelengths. In principle, the two wavelengths should be chosen to be close enough together to ensure that spurious signals affect both wavelengths equally. However, the modulator needs to affect only one of the wavelengths so leading to conflicting demands. Such wavelength modulating systems may be constructed using spectrometers or by using two narrowband optical filters in conjunction with two photodetectors. Systems which make use of a spectrometer are expensive and optically inefficient and require excessive data processing. Systems using filters and photodetectors are wasteful of optical power.
Many of the difficulties inherent in the spectral or two wavelength monitoring methods may be overcome using a chromatic modulation method. A number of sensor systems based upon this approach have been developed (Tomtsis & Kodogiannis, 2003) and shown to possess attractive advantages.
Taking into account the above considerations, it is desirable to develop a general purpose intelligent monitoring system the operation of which is not limited to a single task or application, but it is reusable. In this work, an intelligent optical monitoring system is presented which can be used in many different applications. The systems operation is based on chromatic modulation.
Biological Chromatic Processing
An aspect of the science of photic fields relates to the interaction of the photic field power P(λ), which in general, may be a complex function of wavelength λ with matter of different kinds, via its responsivity R(λ), to produce a physical or chemical effect V (Moon & Spencer, 1981) according to:
The built-in intelligent nature of the monitoring system results from its ability to automatically compensate for any lightness variation as well as its ability to decide the gamma correction process based on the surrounding environment and the event being monitored.
Optical Frequency Response
The optical frequency response of the CCD (charged coupled device) camera was measured using the optical monitoring system and the apparatus shown in Figure 2.
The required part of the spectrum was selected with the alignment slits and was directed to both the camera and the OSA (optical spectrum analyser) using the half silvered mirror. The oscilloscope was used to display information about the light intensity as a function of the selected wavelength incident to the camera and the OSA. Different wavelengths were selected by rotating the diffraction grating on the rotating stand. The resulting information was then processed by the host personal computer to provide color quantification that correlated with the wavelength monitored by the OSA.
diagnosis because of the reduced cylindrical symmetry they provide.
Monitoring electric arc plasma is a difficult process because of the complexity of the phenomena which govern arc behavior. The physics of these processes and properties of the electric arcs are not fully understood, due to the powerful mathematical analysis and considerable experimental effort required to model their complex characteristics (Jones, 1988). For example, the arc plasma column has properties which vary with time and radial, axial and azimuthal coordinates. Phenomena at the arc electrodes are also complex and interactions with the plasma column as well as the interaction of the arc with its environment add to the complications(Jones & Fang, 1980).
Investigation of the electric arc phenomena has led to the identification of independent conditions which are simplified by eliminating some of the complexities, and perform detailed, highly accurate and localized measurements on that condition (Flurscheim, 1975). However, these measurements are made at the expense of determining how the overall electric arc and its environment behave and respond.
Spectroscopic detection and analysis techniques were also used in plasma monitoring applications, but they are cumbersome and slow for on-line process control.
Often, such detailed knowledge is unnecessary for such process applications and all that is required is the identification of particular spectral signatures which are associated with certain quantities or parameters. Experimental Results
Operational conditions in the plasma of such discharges need to be kept within specified tolerances and these conditions may be indicated by the spectral composition of the emission from the discharges.
gases are shown in Figure 6. The argon discharge is characterized by a number of spectral lines in the wavelength range from 300 nm to 475 nm, hydrogen from 300 nm to 650 nm and nitrogen from 300 nm to 500 nm and from 620 nm to 900 nm. For hydrogen and argon, there is continuous emission apparent at the longer wavelengths.
The chromaticity values measured with the tri-stimulus system of Figure 1 are shown in the chromaticity diagram of Figure 7. The dominant wavelengths are 820 nm, 920 nm and 875 nm for the argon, hydrogen and nitrogen respectively. The horse-shoe shaped chromatic boundary is also shown in the same figure. A set of experimental results demonstrating the effect on dominant wavelength and on intensity of changing the composition of the gases forming DC plasma are presented in Figure. 8. The results show the possible utilization of the chromatic approach for discriminating correct and incorrect process conditions.
CIE. (1971). Colorimetry (p. 15). CIE Publication, Official Recommendations of the International Commission on Illumination.
CIE. (1986). Colorimetry, 15(2). CIE publication.
Foley, J. D., van Dam, A., Feiner, S. K., & Hughes, J. F. (1995). Computer graphics: Principles and practice. Addison-Wesley.
Flurscheim, C. H. (1975). Power circuit breaker theory and design. Herts: Peter Peregrinus Ltd..
Hunt, R. W. (1987). Measuring color. New York: J. Wiley and Sons.
Jones, G. R. (1988). High pressure arcs in industrial devices: Diagnostic and monitoring techniques. Cambridge: Cambridge University Press.
Jones, G. R., & Fang, M. T. C. (1980). The physics of high power arcs. Reports on Progress in Physics, 43, 1415-1465.
McCamy, C. S., Marcus, H., & Davidson, J. G. (1976). A color-rendition chart. Scientists Engineers, 2(3), 95-99.
Moon, P., & Spencer, D. E. (1981). The photic field. Cambridge, M. A.: MIT.
Russell, P. C., Cosgrave, J., Tomtsis, D., Vourdas, A., Stergioulas L., & Jones, G. R. (1998). Extraction of information from acoustic vibration signals using Gabor transform type devices. Measurement Science and Technology, 9, 1282-1290.
Tomtsis, D., & Kodogiannis, V. (2002). Digital image processing of axis-symmetric electric arc plasma based on chromatic modulation methods. 6th WSES/IEEE Multi-Conference CSCC-MCP-MCME. Crete, July, 2002.
Tomtsis, D., & Kodogiannis, V. (2003). Optical pH measurement using chromatic modulation. International Conference of Computational Methods in Sciences and Engineering. ICCMSE, Kastoria, Greece, September 12-16, 2003.
Tomtsis, D., & Sapalidis, K. (2004). A CCD-based Tristimulus colorimeter for fast and improved measurement of chromaticity coordinates of displays by matrix correction methods. WSEAS Transactions on Information Science and Applications, 6(1), 1606-1611.
Tomtsis, D., Kodogiannis, V., & Chountas, P. (2004). Distimulus chromatic measurement systems. WSEAS Transactions on Circuits and Systems, 3(2), 211-214.
Tomtsis, D., Sapalidis, K., & Katsanos, C. (2004). Electronic Tristimulus chromatic measurement systems. WSEAS Transactions on Circuits and Systems, 9(3), 1835-1840.
Keywords: chromatic modulation, optical detection, electric arc, electric plasma
Introduction
Intelligent systems use ideas and get inspiration from natural systems and build on both established and novel techniques from a number of scientific fields, such as computer vision, machine learning and artificial intelligence. Intelligent systems may perceive their environment through sensors for goal-directed actions even in dynamic situations while learning and functioning autonomously in order to cope with changing environments or inaccurate a priori knowledge. Many intelligent optical systems incorporate those characteristics but are highly application dependent. Some systems are stand-alone applications which solve a specific measurement or detection problem, while others constitute a sub-system of a larger design. The specific implementation of an intelligent optical system also depends on, if its functionality is pre-specified or if some part of it can be learned or modified during operation.
In many intelligent optical monitoring systems, intensity modulation offers the advantages of inherent simplicity. However, conventional methods involving absolute intensity have associated problems. The most basic intensity monitoring systems use only a single photodiode to produce an output, but these systems tend to be sensitive to spurious changes in intensity resulting from variations in the light source or other components within the system. Removing these spurious effects is difficult and leads to complicated and expensive systems.
Wavelength monitoring systems attempt to deduce the state of a system by taking the ratio of intensities at two different wavelengths. In principle, the two wavelengths should be chosen to be close enough together to ensure that spurious signals affect both wavelengths equally. However, the modulator needs to affect only one of the wavelengths so leading to conflicting demands. Such wavelength modulating systems may be constructed using spectrometers or by using two narrowband optical filters in conjunction with two photodetectors. Systems which make use of a spectrometer are expensive and optically inefficient and require excessive data processing. Systems using filters and photodetectors are wasteful of optical power.
Many of the difficulties inherent in the spectral or two wavelength monitoring methods may be overcome using a chromatic modulation method. A number of sensor systems based upon this approach have been developed (Tomtsis & Kodogiannis, 2003) and shown to possess attractive advantages.
Taking into account the above considerations, it is desirable to develop a general purpose intelligent monitoring system the operation of which is not limited to a single task or application, but it is reusable. In this work, an intelligent optical monitoring system is presented which can be used in many different applications. The systems operation is based on chromatic modulation.
Biological Chromatic Processing
An aspect of the science of photic fields relates to the interaction of the photic field power P(λ), which in general, may be a complex function of wavelength λ with matter of different kinds, via its responsivity R(λ), to produce a physical or chemical effect V (Moon & Spencer, 1981) according to:
The built-in intelligent nature of the monitoring system results from its ability to automatically compensate for any lightness variation as well as its ability to decide the gamma correction process based on the surrounding environment and the event being monitored.
Optical Frequency Response
The optical frequency response of the CCD (charged coupled device) camera was measured using the optical monitoring system and the apparatus shown in Figure 2.
The required part of the spectrum was selected with the alignment slits and was directed to both the camera and the OSA (optical spectrum analyser) using the half silvered mirror. The oscilloscope was used to display information about the light intensity as a function of the selected wavelength incident to the camera and the OSA. Different wavelengths were selected by rotating the diffraction grating on the rotating stand. The resulting information was then processed by the host personal computer to provide color quantification that correlated with the wavelength monitored by the OSA.
diagnosis because of the reduced cylindrical symmetry they provide.
Monitoring electric arc plasma is a difficult process because of the complexity of the phenomena which govern arc behavior. The physics of these processes and properties of the electric arcs are not fully understood, due to the powerful mathematical analysis and considerable experimental effort required to model their complex characteristics (Jones, 1988). For example, the arc plasma column has properties which vary with time and radial, axial and azimuthal coordinates. Phenomena at the arc electrodes are also complex and interactions with the plasma column as well as the interaction of the arc with its environment add to the complications(Jones & Fang, 1980).
Investigation of the electric arc phenomena has led to the identification of independent conditions which are simplified by eliminating some of the complexities, and perform detailed, highly accurate and localized measurements on that condition (Flurscheim, 1975). However, these measurements are made at the expense of determining how the overall electric arc and its environment behave and respond.
Spectroscopic detection and analysis techniques were also used in plasma monitoring applications, but they are cumbersome and slow for on-line process control.
Often, such detailed knowledge is unnecessary for such process applications and all that is required is the identification of particular spectral signatures which are associated with certain quantities or parameters. Experimental Results
Operational conditions in the plasma of such discharges need to be kept within specified tolerances and these conditions may be indicated by the spectral composition of the emission from the discharges.
gases are shown in Figure 6. The argon discharge is characterized by a number of spectral lines in the wavelength range from 300 nm to 475 nm, hydrogen from 300 nm to 650 nm and nitrogen from 300 nm to 500 nm and from 620 nm to 900 nm. For hydrogen and argon, there is continuous emission apparent at the longer wavelengths.
The chromaticity values measured with the tri-stimulus system of Figure 1 are shown in the chromaticity diagram of Figure 7. The dominant wavelengths are 820 nm, 920 nm and 875 nm for the argon, hydrogen and nitrogen respectively. The horse-shoe shaped chromatic boundary is also shown in the same figure. A set of experimental results demonstrating the effect on dominant wavelength and on intensity of changing the composition of the gases forming DC plasma are presented in Figure. 8. The results show the possible utilization of the chromatic approach for discriminating correct and incorrect process conditions.
CIE. (1971). Colorimetry (p. 15). CIE Publication, Official Recommendations of the International Commission on Illumination.
CIE. (1986). Colorimetry, 15(2). CIE publication.
Foley, J. D., van Dam, A., Feiner, S. K., & Hughes, J. F. (1995). Computer graphics: Principles and practice. Addison-Wesley.
Flurscheim, C. H. (1975). Power circuit breaker theory and design. Herts: Peter Peregrinus Ltd..
Hunt, R. W. (1987). Measuring color. New York: J. Wiley and Sons.
Jones, G. R. (1988). High pressure arcs in industrial devices: Diagnostic and monitoring techniques. Cambridge: Cambridge University Press.
Jones, G. R., & Fang, M. T. C. (1980). The physics of high power arcs. Reports on Progress in Physics, 43, 1415-1465.
McCamy, C. S., Marcus, H., & Davidson, J. G. (1976). A color-rendition chart. Scientists Engineers, 2(3), 95-99.
Moon, P., & Spencer, D. E. (1981). The photic field. Cambridge, M. A.: MIT.
Russell, P. C., Cosgrave, J., Tomtsis, D., Vourdas, A., Stergioulas L., & Jones, G. R. (1998). Extraction of information from acoustic vibration signals using Gabor transform type devices. Measurement Science and Technology, 9, 1282-1290.
Tomtsis, D., & Kodogiannis, V. (2002). Digital image processing of axis-symmetric electric arc plasma based on chromatic modulation methods. 6th WSES/IEEE Multi-Conference CSCC-MCP-MCME. Crete, July, 2002.
Tomtsis, D., & Kodogiannis, V. (2003). Optical pH measurement using chromatic modulation. International Conference of Computational Methods in Sciences and Engineering. ICCMSE, Kastoria, Greece, September 12-16, 2003.
Tomtsis, D., & Sapalidis, K. (2004). A CCD-based Tristimulus colorimeter for fast and improved measurement of chromaticity coordinates of displays by matrix correction methods. WSEAS Transactions on Information Science and Applications, 6(1), 1606-1611.
Tomtsis, D., Kodogiannis, V., & Chountas, P. (2004). Distimulus chromatic measurement systems. WSEAS Transactions on Circuits and Systems, 3(2), 211-214.
Tomtsis, D., Sapalidis, K., & Katsanos, C. (2004). Electronic Tristimulus chromatic measurement systems. WSEAS Transactions on Circuits and Systems, 9(3), 1835-1840.