The efficient operation of mine drainage system is of great significance to coal mine production.However,the occurrence of fault will lead to abnormal operation of drainage system,which will affect production safety and efficiency.A fault diagnosis algorithm of mine drainage system based on multi-scale feature matching is proposed.Firstly,The algorithm obtains the real-time mine drainage system data through the sensor,and carries on the preprocessing and feature extraction.Then,the multi-scale feature matching method is used to map the data features to different scale spaces.In each scale space,by construc-ting a feature matching model,the current data is compared with the known normal operation data to determine whether there is a fault.In order to improve the accuracy and robustness of fault diagnosis,an ensemble learning method is introduced to deter-mine the fault type and location of the mine drainage system by integrating the feature matching results of multiple scale spaces and using the voting mechanism to make comprehensive decisions.The study results show that the proposed algorithm has good performance in fault diagnosis of mine drainage system.Compared with traditional methods,the proposed algorithm can effi-ciently detect faults,help to timely and accurately discover and solve the problems of mine drainage system,and has certain sig-nificance for ensuring the safety of mine production.
维普
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