Vibration signal, as an important means for diesel engine condition detection and fault diagnosis, has attracted attention for many\nyears. In traditional vibration signal analysis, most processing methods are for single-channel data. However, single-channel\nvibration signal cannot reflect the operating information of the diesel engine comprehensively because diesel engine vibration is\ncoupled by multiple source signals. This paper proposes the MVMD band energy method for fault diagnosis by four channels of\nvibration signals. First, the original multivariate signals are decomposed adaptively by MVMD, which obtains a series of\ncomponents with modal alignment. Then, the band energy values of each measuring point are calculated as the fault characteristics.\nFinally, SVM is used to realize the diagnosis and identification of diesel engine misfire. The working conditions have a\ngreat influence on the vibration signal of the cylinder. In order to obtain the best diagnostic working conditions, six working\nconditions are set for testing. The result shows that the fault identification rate is highest under the 1500 rpm and 50% load\nworking condition. The fault recognition rate of this method reaches more than 99%, which is superior to the other four\ncommon methods.
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