Paper
31 December 2008 Multi-sensor cooperative measurement mechanism based on synergetics
Xiaobin Hong, Guixiong Liu, Tiequn Chen, Junchao Liang, Taobo Cheng
Author Affiliations +
Proceedings Volume 7130, Fourth International Symposium on Precision Mechanical Measurements; 71304O (2008) https://doi.org/10.1117/12.819728
Event: Fourth International Symposium on Precision Mechanical Measurements, 2008, Anhui, China
Abstract
According to the nonlinear dynamic characteristics and uncertainty of Multi-sensor Integrated System(MSIS), the Multi-sensor Cooperative Measurement Mechanism(MSCMM) is studied based on Synergetics. By dint of analogy method, the MSCMM is described deeply and its model with the dynamic cooperation-competition-harmony course is proposed. Then dynamics equation of MSCMM model is established. With the Slaving Principle(SP), eliminating stable modes, the potential function of order parameters equation is acquired. Through deducing instability limit of potential function, the cooperative degree ξ is obtained. After the MSIS becomes stable, the uniform expression of accuracy η of multi-dimension uncertainty is achieved. Sequentially, the assessment index system is confirmed, including cooperative degree ξ, accuracy η, iterative error ψ and stability steps L. Finally, the application in multi-parameter safety monitoring for electric transmission line is introduced. The experiment results show that the MSCMM possesses self-association and self- recover, enlarges greatly time-space range of multi-sensor system and decreases effectively uncertainties.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Xiaobin Hong, Guixiong Liu, Tiequn Chen, Junchao Liang, and Taobo Cheng "Multi-sensor cooperative measurement mechanism based on synergetics", Proc. SPIE 7130, Fourth International Symposium on Precision Mechanical Measurements, 71304O (31 December 2008); https://doi.org/10.1117/12.819728
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Cited by 2 scholarly publications.
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KEYWORDS
Multispectral imaging

Cognition

Cognitive modeling

Humidity

Safety

Sensors

Performance modeling

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