Internal combustion engine abnormal sound identification and diagnosis method based on EWT-SCWT

Abstract

The invention discloses an EWTSCWT-based internal combustion engine abnormal sound identification and diagnosis method, which can accurately extract time-frequency related detail features of excitation input and abnormal sound output signals of an internal combustion engine, locate and identify an abnormal sound radiation part and further diagnose the cause of abnormal sound of the internal combustion engine. According to the improved EWT method, the phenomena of mode aliasing and endpoint effect can be avoided, abnormal sound signal characteristic components of the internal combustion enginecan be accurately extracted from a noise environment, and the reliability of signal separation is improved. According to the EWTSCWT method, cross interference terms and noise components in excitationinput and abnormal sound output components can be well eliminated, related characteristics of time-frequency localization information between the cross interference terms and the excitation input andabnormal sound output components are accurately extracted, and the effect of identifying and diagnosing the abnormal sound of the internal combustion engine is further improved.

Description

technical field [0001] The invention relates to an internal combustion engine fault diagnosis technology, in particular to an EWT-SCWT-based identification and diagnosis method for abnormal sound of an internal combustion engine. Background technique [0002] Internal combustion engine is a typical reciprocating-rotating motion conversion power machine. Due to many vibration excitation sources, complex transmission paths, and many moving parts, its dynamic response characteristics are complex. When certain components such as pistons, connecting rods, crankshafts, timing gears and valves are affected by factors such as engine speed, load, temperature and lubrication due to wear, increased fit clearance, loose parts, and weak rigidity, etc. The excitation characteristics and transmission characteristics of the internal combustion engine cause abnormal noises such as piston knocking, crankshaft main bearings and connecting rod bearings, gear chambers and valves, and structural ...

AI Technical Summary

Problems solved by technology

The EEMD method has problems such as the large average error caused by the different number of Intrinsic Mode Functions (IMF) generated by each empirical mode decomposition, and the large amount of calculation caused by increasing the number of integrations, especially in noisy environments. The effect is not ideal when extracting useful signal components from

Because the VMD method needs to preset the number of decompositions, when the noise is complex and variable and there are many noise components, there are disadvantages such as difficulty in determining the number of decompositions and low accuracy of sound source separation.

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