Hefei University of Technology

Deqin Zhao

Yigang He

Zhijie Yuan

Lifen Yuan

Zhen Cheng

Lei Wu

Peng Chen

Chaolong Zhang

Shuai Luo

Ying Long

Yesheng Sun

Zhigang Li

Tao Wang

Wei He

Liulu He

Luqiang Shi

Qiwu Luo

Tiancheng Shi

An analog-circuit fault diagnosis method based on continuous wavelet analysis and an ELM network comprises: data acquisition: performing data sampling on output responses of an analog circuit respectively through Multisim simulation to obtain an output response data set; feature extraction: performing continuous wavelet analysis by taking the output response data set of the circuit as training and testing data sets respectively to obtain a wavelet time-frequency coefficient matrix, dividing the coefficient matrix into eight sub-matrixes of the same size, and performing singular value decomposition on the sub-matrixes to calculate a Tsallis entropy for each sub-matrix to form feature vectors of corresponding faults; and fault classification: submitting the feature vector of each sample to the ELM network to implement accurate and quick fault classification. The method of the invention has a better effect on extracting the circuit fault features and can be used to implement circuit fault classification accurately and efficiently.

Analog-circuit fault diagnosis method based on continuous wavelet analysis and ELM neural network

An analog circuit fault mode classification method comprises the following implementation steps: (1) collecting M groups of voltage signal sample vectors Vto each of fault modes Fof the analog circuit by using a data collection board; (2) sequentially extracting fault characteristic vectors Vof the voltage signal sample vectors Vby using subspace projection; (3) standardizing the extracted fault characteristic vectors Vto obtain standardized fault characteristic vectors; (4) constructing a fault mode classifier based on a support vector machine, inputting the standardized fault characteristic vectors, performing learning and training on the classifier, and determining structure parameters of the classifier; and (5) completing determination of fault modes according to fault mode determination rules. The fault mode classifier of the present invention is simple in learning and training and reliable in mode classification accuracy.

Analog circuit fault mode classification method

An analog circuit fault diagnosis method using a single testable node comprises the following steps: (1) obtaining prior sample data vectors under each fault mode; (2) computing a statistical average of the prior sample data vectors under each of the fault modes; (3) decomposing a signal by an orthogonal Haar wavelet filter set; (4) extracting the feature factor of the prior sample fault modes; (5) extracting a fault-mode-to-be-tested feature factor; (6) computing a correlation coefficient matrix and correlation metric parameters between the feature factor of the prior sample fault modes and the feature factor of the fault-mode-to-be-tested; and (7) determining a fault mode according to a maximal correlation principle by comparing the correlation metric parameters. The method can convert a single signal into a plurality of signals without losing original measurement information, and extract an independent fault mode feature factor reflecting variations of a circuit structure in different fault modes, can be used to study an associated mode determination rule and successfully complete classification of circuit fault modes.

Analog circuit fault diagnosis method using single testable node

A wireless sensor network sensor network charging method for multi-charge nodes, including the following steps: (1) establishing a WSNs model; (2) dividing field ranges of charging trolleys; and (3) charging the charging trolleys: (a) initializing: l=0 and j=0, wherein l is the total number of received alarm nodes, and j is the serial number of an alarmed node; (b) receiving an alarm signal, updating values of l and j, generating a shortest charging path s, and computing an energy discriminate vector; (c) if a vector element satisfies Q&#x2264;5% B and j=1, 2, . . . , l, then executing a charging task on l alarm nodes according to the shortest charging path scorresponded thereby, otherwise, returning to continuously update the values of l and j; (d) executing the charging task; and (e) determining whether the charging trolleys are required to go back to a parking lot for recharging, enabling the charging trolleys to go back to the parking lot for recharging if yes, and otherwise, returning to continuously update the values of l and j and the vector element Q.

Wireless sensor network charging method for multi-charge nodes

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Anhui, China

Deqin Zhao