Quantitative evaluation of the impurity content of grease for low-speed heavy-duty bearing using an acoustic emission technique

Jiang, Kuosheng; Han, Liubang; Zhou, Yuanyuan

doi:10.1177/0020294019858214

Cited by 8 publications

(8 citation statements)

References 26 publications

(18 reference statements)

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“…This microseismic data processing is mainly through MATLAB signal processing and visualization modules. The analysis method is based on the classic parameter analysis method of microseismic and acoustic emission signals [11], as shown in Fig. 5.…”

Section: Microseismic Data Analysis Methodsmentioning

confidence: 99%

An Experimental Research on Microseismic Monitoring Technology in Detecting the Contact Time of Badminton Amateurs’ Lunge

Yang¹,

Cui²,

Yan³

2021

Preprint

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The fast and flexible characteristics of badminton determine the necessity of its lunge, and fast lunge will have an important impact on the results of the game in actual combat. In lunge evaluation, the contact time to the ground is a key indicator. This article selects two middle-aged male badminton amateurs with similar body shape and age， but different skill levels as the research objects to carry out comparative experiments. The microseismic equipment is used to record the floor vibration which is caused by the running of badminton amateurs in sports. The microseismic signals of lunge are processed and analyzed by MATLAB software. And we evaluate the pro and cons of various time to touch the ground from amateurs with different skill levels. The research found that 1. Microseismic technology can detect the contact time to the ground. 2. High-level badminton amateurs have obvious advantages in the footwork contact time. Microseismic technology has a certain feasibility as a tool for evaluating the footwork contact time of badminton.

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Section: Microseismic Data Analysis Methodsmentioning

confidence: 99%

An Experimental Research on Microseismic Monitoring Technology in Detecting the Contact Time of Badminton Amateurs’ Lunge

Yang¹,

Cui²,

Yan³

2021

Preprint

View full text Add to dashboard Cite

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“…Therefore, it can be concluded that the collected fourth signal is the best one in this test process. To further validate the effectiveness, order spectrum analysis [37,38] is employed the collected signals. Figure 11 shows the corresponding envelope order spectrums those bearing signals.…”

Section: Data Processing and Verificationmentioning

confidence: 99%

“…The data statistics of correlation are given in Table 3. From the statistical resu it can reveal that the effective sensor placements are located in the first, second, fou To further validate the effectiveness, order spectrum analysis [37,38] is employed for the collected signals. Figure 11 shows the corresponding envelope order spectrums of those bearing signals.…”

Section: Data Processing and Verificationmentioning

confidence: 99%

Optimal Placement of Sensors Based on Data Fusion for Condition Monitoring of Pulley Group under Speed Variation Condition

et al. 2022

Machines

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Pulley group plays an important role in the transmission of large mechanical equipment. To obtain informative data for condition monitoring, it is very important to optimize sensor placement on the pulley group. However, due to sharp speed fluctuation, heavy load and complex internal structure, sensor placement for acquiring optimal monitoring points is still a challenging task. Therefore, a novel sensor optimization method based on data fusion is proposed. In this method, the Kalman filter is firstly used to refine the collected signal for dealing with the variable noises. Subsequently, the variable periodicity strength of the signal is calculated to recognize the non-stationary characteristics of the measured signal. A data fusion technique based on maximum likelihood estimation (MLE) is then introduced to estimate sensitive components from the multi-source sensor signals for finding out optimal sensor placement points. The method is validated experimentally on a test rig of the pulley group with variable speed conditions. Analysis results show that the proposed method can recognize the optimal sensor placement points for the pulley group.

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“…The data types of data-driven method can be divided into single signal and multi-signal fusion. Single signal, such as vibration signal [3,18,[28][29][30], acoustic signal [31][32][33][34], current signal [24], [25], temperature signal [21], pressure signal [35], and instantaneous phase signal [36], etc., have been successfully applied to RC fault diagnosis. Although good diagnosis results have been achieved, the difficulty of data processing is increased because of the singleness of signal and the few effective fault features.…”

Section: Introductionmentioning

confidence: 99%

Quantitative Evaluation on Valve Leakage of Reciprocating Compressor Using System Characteristic Diagnosis Method

et al. 2020

Self Cite

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High impact and strong noise complicate the response of reciprocating compressor (RC). It requires a complex signal processing method that is a single response-based or excitation-based fault diagnosis method applied to RC valve leakage fault diagnosis. This paper proposes a quantitative diagnosis method of RC valve leakage that is based on system characteristic diagnosis method. First, the current signal of the RC induction motor and the cylinder vibration signal are introduced as the excitation and response signals, the mathematical model of the RC motor current is established, and the influence mechanism of the valve leakage on the RC vibration is analyzed. Subsequently, the ensemble empirical mode decomposition and comb filter are respectively used to extract the fault characteristic information of excitation signal and response signal to obtain the excitation condition indicators (CIs), response CIs, and system CIs. Finally, the support vector machine based on the obtained CIs classified the valve leakage failure patterns of different severity, and a fault diagnoser was constructed for the quantitative diagnosis of valve leakage fault. The results of experiment and application proved that the proposed method could realize the quantitative diagnosis of RC valve leakage fault while using simple signal processing technology.

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Quantitative evaluation of the impurity content of grease for low-speed heavy-duty bearing using an acoustic emission technique

Cited by 8 publications

References 26 publications

An Experimental Research on Microseismic Monitoring Technology in Detecting the Contact Time of Badminton Amateurs’ Lunge

An Experimental Research on Microseismic Monitoring Technology in Detecting the Contact Time of Badminton Amateurs’ Lunge

Optimal Placement of Sensors Based on Data Fusion for Condition Monitoring of Pulley Group under Speed Variation Condition

Quantitative Evaluation on Valve Leakage of Reciprocating Compressor Using System Characteristic Diagnosis Method

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