Multi-Sensor Analyzer Detector (MSAD) for Low Cost Chemical and Aerosol Detection and Pattern Fusion

摘要

MSAD is being developed as a low-cost point detection chemical and biological sensor system designed around an information fusion inference engine that also allows additional sensors to be included in the detection process. The MSAD concept is based on "probable cause" detection of hazardous chemical vapors and aerosols of either chemical or biological composition using a small portable unit containing an embeddedcomputer system and several integrated sensors with complementary capabilities. The configuration currently envisioned includes a Surface-Enhanced Raman Spectroscopy (SERS) sensor of chemical vapors and a detector of respirable aerosols based on Fraunhoffer diffraction. Additional sensors employing Ion Mobility Spectrometry (IMS), Surface Acoustic Wave (SAW) detection, Flame Photometric Detection (FPD), and other principles are candidates for integration into the device; also, available commercial detectors implementing IMS, SAW, and FPD will be made accessible to the unit through RS232 ports. Both feature and decision level information fusion is supported using a Continuous Inference Network (CINET) of fuzzy logic. Each class of agents has a unique CINET with information inputs from a number of available sensors. Missing or low confidence sensor information is gracefully "blended out" of the output confidence for the particular agent. This approach constitutes a "plug and play" arrangement between the sensors and the information pattern recognition algorithms. We are currently doing simulant testing and developing out CINETs for actual agent testing at Edgewood Chemical and Biological Center (ECBC) later this year.