Abstract
In this paper, a novel fuzzy‐based analytic hierarchy process (FAHP) is proposed for identifying noise sources of diesel engine and sorting their contributions. The hierarchy tree consists of 5 levels including the component level, the frequency band level, the test point level, the operating condition level, and the overall noise level. The variational mode decomposition (VMD) is employed to decompose the overall noise into several frequency bands. The factor weights between levels are determined by the partial coherence analysis (PCA) to consider the correlation of component vibration and radiated noise in different frequency bands. A fuzzy consistency matrix is then constructed to order the corresponding factors level by level that can avoid the consistence problem of the traditional AHP. Based on the rig test of a diesel engine, the proposed approach is implemented to weight the noise sources identified. It is shown the overall weighting order of the six major noise sources is (in descending order) the oil pan, the left block, the valve cover, the flywheel housing, and the right block.
Highlights
NVH problems are increasingly important in nowadays automobile industry, and reduction in engine noise is one of the most concerns
Zhang et al [19] proposed a combined analytic hierarchy process (AHP) approach to analyse the contribution of different engine parts to the overall radiated noise in different engine speeds. e decomposition by ensemble empirical mode decomposition (EEMD) was affected by the modal aliasing problem in intrinsic mode functions (IMFs)
An integrated approach of variational mode decomposition (VMD)-partial coherence analysis (PCA)-fuzzy-based analytic hierarchy process (FAHP) is proposed for noise source weighting of the diesel engine
Summary
NVH problems are increasingly important in nowadays automobile industry, and reduction in engine noise is one of the most concerns. Lots of method have been proposed, such as the cyclic Wiener filtering [8, 9], the timefrequency analysis [10,11,12], the blind source separation [13, 14], and the coherent spectrum analysis (CSA) [15] It is still very difficult for only using one signal processing method to perfectly handle the complex noise problem. For this reason, the analytic hierarchy process (AHP) [16, 17] has been proved suitable for decision-making of complex systems. The coherent spectrum analysis (CSA) is limited in the case that multiple inputs are not independent from each other
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