Study On Fault Dagnosis Of Nonlinear Circuit Based On Trajectory Polynomial Decomposition

Since the 1980s, with the development of computer and microelectronics technology, the system security and reliability demands in aerospace, military and other fields have been leading the rapid progress of testing-controlling technology. Measurability design, fault diagnosis and tolerant control are becoming more and more important in electronic equipments. Among them, the problem of nonlinear analog circuit fault diagnosis is not only inevitable but also extremely difficult. Fault diagnosis theory and methods of nonlinear analog circuits have become one of the challenging topics in international test research domain.A typical process of nonlinear analog circuit fault diagnosis includes system modeling, stimulation design, feature extraction and fault identification. For the nonlinear mechanism of fault propagation, fault information can be very likely to be overlapped and interleaved, thus the key point of fault diagnosis is fault characteristics extraction. This dissertation is mainly focused on nonlinear system modeling and improvement of characteristics extraction approach, based on the trajectory polynomial decomposition analysis. Author's main work concentrates on five aspects as follows:1. An approach of static trajectory polynomial (STP) for nonlinear resistance network fault diagnosis was studied with ramp power supplies. The purpose is to build the fault diagnosis equation, and to realize multi-faults diagnosis. With the trajectory polynomial decomposition, the iterative relationship of STP's coefficients was discussed, and the properties of STP's coefficients on fault diagnosis were analyzed. Based on STP modeling, nonlinear circuit can be transformed into linear circuit series, and fault diagnosis equation was built with STP's coefficients. Finally, multi-faults diagnosis method of nonlinear resistance network was discussed based on multi-STP analysis.2. A fault diagnosis approach for nonlinear dynamic circuit with some special AM stimulation was studied based on trajectory harmonic polynomial (THP) decomposition. The purpose is to enhance clustering property of fault characteristics. First, the relationship between dynamic trajectory spectrum components and Volterra spectrum components were discussed under some special AM stimulation. Then the holography of fault information in THP components was analyzed. And two approaches of Volterra responses decomposition were represented based on ARMA harmonic decomposition and Volterra sub-band decomposition. Finally, an approach of characteristics extraction was presented based on orthogonal projection of sub-space.3.In order to solve the diagnosis problem of soft-faults and multi-faults for dynamic nonlinear circuit, an approach of fault diagnosis was studied based on coherent measurement. Based on the correlation between Volterra spectrum components and equivalent exciting signals, the phase resident method was presented by coherent measurement, and dynamic circuit can be transformed into static parameter circuit on phase cut-slide. Then the fault information included in phase cut-slide was discussed, and fault diagnosis equation was established based on circuit configuration.4. The dissertation studied fault characteristics extracting method based on dynamic deviation Volterra serise (DDVS), which is designed to improve stability of the process of characteristic extraction for higher dimension nonlinear circuit. Discussion has been done on relationship between DDVS and Volterra series, and DDVS stability in parameter estimation and fault information capability have been analyzed. Then fault characteristics extracting method based on DDVS parameter estimation was represented. DDVS have distinct modularization structure, so it's easy to extend to higher dimension nonlinear system..5. In chapter six, we studied nonlinear circuit fault characteristics extracting method based on basis-function polynomial (BFP), which is to solve the difficult problem for characteristics extraction of high dimension and longer delay nonlinear system. Based on the principle of time-frequency basic function frame, the paper analyzed existing problem of BFP fitting in nonlinear circuit diagnosis. Then an approach for simplifying the basic function tribe of BFP was presented based on fixed scale and joint translation. The virtue of BFP is higher stability in parameter estimation and stronger adaptability of various nonlinear circuits.In one word, this dissertation focuses on the fault characteristic extraction based on trajectory polynomial decomposition. In order to achieve the aim of soft-fault and multi-fault diagnosis of nonlinear circuit, the importance of both the stability and clustering performance of fault characteritics were emphasized in this paper, and the ability for linearization decomposition of nonlinear modeling was also analyzed emphatically. Some examples to illuminate the proposed approaches are available.