A Fault Diagnosis Method of WSN Wireless Communication Module Based on Fuzzy Neural Network
A wireless communication module and fuzzy neural network technology, applied in the field of information perception and recognition, can solve problems such as networks that are not suitable for topology dynamic changes, and achieve improved reliability and practicability, fast convergence speed, and high accuracy of fault diagnosis Effect
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[0049] The present invention will be described in detail below in conjunction with the accompanying drawings.
[0050] The present invention focuses on the analysis of sensor signals for most of the fault diagnosis methods, and there are few studies on the fault location and analysis of the WSN node itself. According to the voltage and current parameters related to the fault characteristics, the concept of active in the circuit and the direction of inflow and outflow, the abnormality of the current or voltage of a module will affect the state of the parameters of other modules on the entire series circuit, and the abnormality of voltage or current The diagnosis can finally determine the fault location and cause. Establish a fuzzy neural network current model for fault diagnosis of wireless communication modules. Firstly, fuzzy rules are adaptively extracted by subtractive clustering, and then the rule parameters are optimized and adjusted by a hybrid learning method combining...
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