CEEMDAN-ICA-SWT-based diesel engine vibration source multi-information joint identification method

Abstract

The invention discloses a CEEMDAN-ICA-SWT-based diesel engine vibration source multi-information joint identification method, comprising the steps of obtaining a vibration excitation source mixed response signal by utilizing a vibration sensor; determining an amplitude standard deviation coefficient and an overall average number of times of adding the white noise, then performing adaptive decomposition on the vibration signal by adopting a CEEMDAN method, selecting a main intrinsic mode component based on a quadratic correlation similarity coefficient method and a spectral entropy combined method, and estimating a vibration source number; forming a new observation signal as a plurality of virtual channels in independent component analysis by using the obtained eigenmode component and excitation source mixed response signal, performing blind source separation by using an ICA method, and selecting a separation result by using a similarity coefficient method in combination with the estimated number of main vibration sources; and carrying out time-frequency characteristic analysis on each independent component of the separation result by adopting an SWT technology, and identifying thevibration excitation source of the diesel engine. According to the CEEMDAN-ICA-SWT-based diesel engine vibration source multi-information joint identification method, the identification capability ofthe vibration source of the diesel engine is improved.

Description

technical field [0001] The invention relates to the technical field of diesel engine energy saving and environmental protection, in particular to a CEEMDAN-ICA-SWT-based multi-information joint identification method for diesel engine vibration sources. Background technique [0002] Reducing vibration and noise is an important research direction in the field of diesel engine energy conservation and environmental protection research. To effectively control the vibration and noise of diesel engines, it is key to accurately identify the main vibration excitation sources of diesel engines. There are many excitation sources for diesel engine vibration, mainly from mechanical excitations such as the periodically changing combustion pressure in the cylinder, valve impact and piston knocking, and the inertial force generated by the movement of the piston-crank linkage mechanism. Various vibration sources are coupled to each other. Different vibration paths are transmitted, and the pr...

AI Technical Summary

Problems solved by technology

[0005] Aiming at the problems existing in the prior art, the present invention provides a diesel engine vibration source multi-information joint identification method based on CEEMDAN-ICA-SWT. The CEEMDAN method in this method can better solve the problem of EMD method mode aliasing, At the same time, it can solve the problems of large average error caused by the different number of eigenmode components generated by the decomposition of EEMD method and the large amount of calculation caused by increasing the integration times.

Combining the CEEMDAN method with the ICA method solves the problems of high test cost and increased test difficulty caused by infinitely increasing the number of sensors and acquisition channels, and can transform the underdetermined problem of blind source separation into a well-posed problem, satisfying blind separation Requirements, to achieve the same vibration source separation effect

On the basis of obtaining the time-domain characteristic information of the vibration source through the CEEMDAN-ICA method, SWT technology can solve the problems of time-frequency ambiguity after wavelet transform, which leads to poor time-frequency aggregation, effectively reduce the distortion of the instantaneous frequency curve, improve the ambiguity of the scale direction, and improve the time-frequency ambiguity. Frequency aggregation and readability

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