Extraction of fault component from abnormal sound in diesel engines using acoustic signals

Ning, Dayong; Sun, Chao; Gong, Yongjun; Zhang, Zengmeng; Hou, Jun

doi:10.1016/j.ymssp.2015.10.037

Cited by 36 publications

(14 citation statements)

References 13 publications

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“…Therefore, engineers are doing continuous researches to find optimal fault detection system for diesel engine in order to monitor the health condition of the engine. Several types of signals can be measured for monitoring purpose including rotational angle speed [1], temperature [2], fuel and oil quality [3] [4], and vibration [5] [6] [7].…”

Section: Introductionmentioning

confidence: 99%

Diesel Engine Fault Diagnosis with Vibration Signal

Tharanga¹,

Liu²,

Zhang³

et al. 2020

JAMP

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When the vibration of diesel engine structure is measured, the signal is composed of a very complex superposition of the contributions of different vibratory sources modified by their respective transmission paths. These sources originate from several internal phenomenons in the engine such as combustion pressure variation, unbalanced reciprocating and rotating parts. In a diesel engine, movement parts work in a specific order. Once the starting point is determined, occurrence of work order in different cycle phases can be determined. This could successfully use to identifying of impulses in complex vibration signal of a diesel engine. From the variation of features of those impulses, it is possible to determine the working condition of the engine. This can use to fault diagnosis of diesel engine, specially faults related to combustion process.

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Section: Introductionmentioning

confidence: 99%

Diesel Engine Fault Diagnosis with Vibration Signal

Tharanga¹,

Liu²,

Zhang³

et al. 2020

JAMP

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“…The traditional signal denoising method uses a Fourier transform-based filter to filter the frequency components of noise but has apparent defects in the case of non-stationary signals and short-term transient signals. Currently, popular methods of noise reduction include wavelet transform (WT) [5], empirical mode decomposition (EMD) [6], Savitzky-Golay (S-G) filter [7], dislocation superposition method (DSM) [8] et al…”

Section: Introductionmentioning

confidence: 99%

“…But when the SNR is low, the noise reduction effect of the S-G method is not good enough. Ning et al [8] proposed the DSM in 2015. Compared with other methods, DSM only has time-domain calculation.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Noise Reduction Method of Synchronous Hydraulic Motor Acoustic Signal Based on Improved Dislocation Superposition Method

Ning

Sun

et al. 2020

IEEE Access

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Acoustic signal contains information on the state of mechanical motion, but the disadvantage of low signal-to-noise ratio (SNR) is that acoustic signal without noise reduction is difficult to apply to fault diagnosis directly. This study proposes an adaptive noise reduction method based on the dislocation superposition method (DSM), which can realize automatic noise reduction for acoustic signals of low SNR synchronous hydraulic motors. First, the theoretical rotation period of the synchronous hydraulic motor is obtained according to the flow meter. Then, the actual signal is subjected to DSM processing according to the measurement accuracy of the flow meter and the theoretical rotation period to adjust the exact superposition length and the initial position of the actual signal. Finally, when the stop condition is not satisfied, the number of superposition is increased and the above process is repeated. The superimposed signal satisfying the stop condition is taken as the noise reduction signal. According to experimental results, the proposed method has good noise reduction effect on the acoustic signals of the synchronous hydraulic motor health state, wear out state of gear and end cover, and rust state of the gear. The noise reduction signal has been verified to have higher accuracy than the actual signal. Therefore, the proposed automatic noise reduction method can be applied to the noise reduction processing of other kinds of rotating mechanical acoustic signals.

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“…However, similar to the EMD, the LMD and ITD have the disadvantage of mode mixing. In 2015, Dayong et al [25] proposed a dislocation superimposed method (DSM) on the basis of the random decrement technique. In comparison with other methods, the DSM is simple and will not change the concerned component in the mixed signal.…”

Section: Introductionmentioning

confidence: 99%

Separation Method of Impulsive Fault Component for Gasoline Engine Based on Acoustic Signal Analysis

Ning

Jiang

Sun

et al. 2019

Shock and Vibration

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This paper presents a developed dislocation superimposed method (DSM) for automatically extracting the component of impulsive signals from abnormal noise signals of an engine at a single speed range on the basis of the initial DSM. This method consists of three steps: using a correlation analysis to select an appropriate starting superposition point, superimposing abnormal sound signals to improve the signal-to-noise ratio, and intercepting superimposed signals to separate the fault component. Experimental results show that the developed DSM can effectively extract the fault characteristics of cylinder knocking and connecting rod bearing knocking. The developed approach can be applied to separate the fault characteristics of other types of rotating machines.

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Extraction of fault component from abnormal sound in diesel engines using acoustic signals

Cited by 36 publications

References 13 publications

Diesel Engine Fault Diagnosis with Vibration Signal

Diesel Engine Fault Diagnosis with Vibration Signal

Adaptive Noise Reduction Method of Synchronous Hydraulic Motor Acoustic Signal Based on Improved Dislocation Superposition Method

Separation Method of Impulsive Fault Component for Gasoline Engine Based on Acoustic Signal Analysis

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