Mechanical impact signal extraction method based on time-frequency reassigned multisynchrosqueezing transform

Abstract Adaptive decomposition methods for vibration signals have predominantly concentrated on the extraction of fault frequency components in rotational machinery, often overlooking the time-domain impact characteristics of reciprocating machinery. These methods struggle to effectively isolate the periodic, multi-source impact features of reciprocating machinery faults, such as those induced by valve opening or closing, and connecting rod bearing wear. To address the non-stationary, strongly coupled, and interference-prone time–frequency characteristics of casing vibration signals in reciprocating machinery, this study proposes a novel adaptive decomposition method tailored for multi-impact signal analysis. The approach leverages the time–frequency reassigned multisynchrosqueezing transform to enhance the representation of impacts in the time-frequency domain. An optimization criterion based on the squared L2-norm of time-frequency spectral moments is formulated to accurately locate the energy centroids of decomposed components. A recursive decomposition framework is introduced, eliminating the need to predefine decomposition levels while simultaneously improving computational efficiency. To further refine decomposition accuracy, a weight factor optimization strategy employing a q-order time-frequency distance metric is developed to adaptively shape decomposition windows according to impact characteristics. Validation on both simulated and experimental datasets involving diesel engine valve clearance faults demonstrates that the proposed method significantly improves the precision of adaptive impact component extraction and offers enhanced computational performance.