Parameter estimation method for artificial circuit fault component based on Hilbert-Huang transforming (HHT)

Abstract

The invention discloses a parameter estimation method for an artificial circuit fault component based on Hilbert-Huang transforming (HHT). The premise of the parameter estimation method for the artificial circuit fault component based on HHT is that a single fault component is already located, a sinusoidal excitation signal is applied on a circuit to be detected, and the output end of the circuit is used as a test point. First of all the relation of the parameters of the component and the Hilbert marginal spectrum total energy of a corresponding output signal is acquired through computer simulation, a relation curve equation is fitted, and the parameter estimation equation of the fault component of an actual circuit can be acquired after errors are compensated. The test point signals acquired by actual measurement are analyzed and calculated through the HHT to acquire the corresponding total Hilbert marginal spectrum energy, and the total Hilbert marginal spectrum energy is substituted into the parameter estimation equation to solve to gain the parameter values. The parameter estimation method for an artificial circuit fault component based on HHT is simple and effective, and is suitable for linear artificial circuits and non-linear artificial circuits, the estimated accuracy of the parameters is up to 95%, and only one accessible test node is needed, and therefore the parameter estimation method for an artificial circuit fault component based on HHT is suitable for practical engineering application.

Description

technical field [0001] The invention belongs to the field of signal processing and analog circuit fault diagnosis research, and relates to an analog circuit fault parameter estimation method, in particular to an analog circuit fault parameter estimation method based on Hilbert-Huang Transform (HHT) . Background technique [0002] In the field of analog circuit fault diagnosis research, the research on fault detection and location is relatively mature, and many effective methods have been proposed. More accurate positioning, such as fault dictionary method, probability statistics method, fault verification method, expert system method, neural network method, fuzzy theory method, wavelet transform method, support vector machine method, etc. However, the purpose of fault diagnosis of analog circuits is not only fault isolation, but the ability to further accurately estimate the parameters of fault components is a higher requirement for fault diagnosis methods. At present, som...

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Problems solved by technology

On the whole, the existing parameter estimation methods for analog circuit fault components usually estimate or solve component parameters according to the topology of the analog circuit after obtaining enough data information, which often requires more diagnostic information than fault location. However, the actual application environment often cannot provide enough diagnostic information, and it is difficult to solve the diagnostic equation. In addition, the topology of the circuit network is increasingly complex, the influence of the tolerance of the analog circuit components, and the existence of test noise interference in the environment. The fault parameter esti

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