A Detecting Method for \"Weak\" Friction-Induced Vibration Based on Cross-Correlation Analysis between Vibration and Sound Signals  
[PERSON]  
1 Marine Engineering College, Dalian Maritime University, Dalian 116026, China; wlyxpfddlmu.edu.cn (P.X. ); [EMAIL_ADDRESS] (Y.Z. ); [EMAIL_ADDRESS] (H.G. ); [EMAIL_ADDRESS] (Y.S. ); [EMAIL_ADDRESS] (H.Z.) [PERSON]  
1 Marine Engineering College, Dalian Maritime University, Dalian 116026, China; wlyxpfddlmu.edu.cn (P.X. ); [EMAIL_ADDRESS] (Y.Z. ); [EMAIL_ADDRESS] (H.G. ); [EMAIL_ADDRESS] (Y.S. ); [EMAIL_ADDRESS] (H.Z.) [PERSON]  
1 Marine Engineering College, Dalian Maritime University, Dalian 116026, China; wlyxpfddlmu.edu.cn (P.X. ); [EMAIL_ADDRESS] (Y.Z. ); [EMAIL_ADDRESS] (H.G. ); [EMAIL_ADDRESS] (Y.S. ); [EMAIL_ADDRESS] (H.Z.) [PERSON]  
2 College of Mechanical and Electronic Engineering, Dalian Mirzu University, Dalian 116600, China 2211600, China  
such as friction squeal, is typically undesirable because it is related to the system's dynamic instabilities and is accompanied by a high vibration and an annoying sound; moreover, it can reduce machine accuracy and increase the wear of friction pairs [8]. Therefore, in the last few decades, scholars have studied the mechanism and influencing factors by combining theoretical and experimental methods to provide basic information for controlling and predicting the \"strong\" FIV [9]. The \"weak\" FIV is highly dependent on the impacts of the asperities between the friction surfaces; one is known as surface or roughness sound [10]. As a result, some scholars believe that the \"weak\" FIV can help monitor the change in friction and wear state of friction pairs [11] and detect the failure of surface damage [12]. Therefore, studying the correspondence between \"weak\" FIV and the wear behaviors of friction pairs can be used to monitor the wear state of friction pairs online. Nevertheless, due to the coupling effect of system dynamics, background noise, and wear behavior, the accurate \"weak\" FIV is often submerged in complex interference components in the friction process. Moreover, studies show that the \"weak\" FIV that reflects the wear state distributes in a wide frequency range [13]. Therefore, analyzing and monitoring the wear state using the \"weak\" FIV requires eliminating interference components and determining the frequency distribution ranges of the \"weak\" FIV. It is for this reason that scholars have conducted considerable research into the detection method of \"weak\" FIV methods. For example, [PERSON] et al. [14] decomposed the vibration signals of a pin-disk wear test into several frequency bands by harmonic wavelet packet transform (HWPT). The \"weak\" FIV was reconstructed from the frequency band whose root mean square (RMS) of the corresponding waveform followed the same trend as the friction coefficient. [PERSON] et al. [15,16] filtered the original sound pressure signal to obtain friction-induced sound (FIS) by empirical mode decomposition (EMD). By decomposing the original signals into 11 intrinsic mode functions (IMFs), they were able to reconstruct the FIS using IMF5 to IMF11 without frequency peaks. Researchers [17,18] decomposed the original vibration signals of piston rings and dry gas seal rings in a wear process using ensemble empirical mode decomposition (EEMD) and both extracted the first two IMFs with high-frequency to reconstruct the \"weak\" FIV (whose RMS changing trend was consistent with that of the friction coefficient) from the original vibration signals. By controlling the operation of the three main moving components one at a time, [PERSON] et al. [19] analyzed the time-frequency characteristics of vibration signals recorded by a roller ring test rig operating at different rotating speeds. They found that vibration energy in the frequency range of 6000-7000 Hz was significant when the ring roller was working.