Electromechanical actuator fatal fault detection using fuzzy cluster method

In order to detect electromechanical actuator fatal fault, an electromechanical actuator standard state sample was established according to fuzzy cluster method. Electromechanical actuator state can be classified to certain types by calculating least approximation distance between waiting test state sample and standard sample, so the state detection was realized. First, some original electromechanical actuator state sample data has been normalized. Then fuzzy similar matrix between each sample was established based on angle cosine law. After that iterative calculation of clustering center matrix and membership matrix was started. And iterative process was ended through setting maximum iterative error. So the standard state sample was obtained. Finally, test platform is established for state detection. The real-time state detection program runs in the electromechanical actuator controller in continuous operation test. And the program calculates distance of the sample under test and standard state sample. Experimental results indicate that runtime of electromechanical actuator state detection program just need 0.23us, and detection conclusion is completely right. This state detection method can satisfy the requirements of veracity and real-time for electromechanical actuator fault detection.