Performance evaluation of decomposition methods to diagnose leakage in a reciprocating compressor under limited speed variation

Sharma, Vikas; Parey, Anand

doi:10.1016/j.ymssp.2018.07.029

Cited by 35 publications

(27 citation statements)

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“…The three-component signal we consider is given by Note that the durations of the three components in (66) are different, that is K in (1) can be timevarying. The sampling rate for this experiment is 512Hz, namely we have 512 discrete samples for z(t).…”

Section: Experiments With a Three-component Synthetic Signalmentioning

confidence: 99%

“…We also consider FSSTs in noise environment. We add Gaussian noises to the original signal given in (66) with different signal-to-noise ratios (SNRs). Fig.5 shows the conventional 2nd-order FSST and our proposed 2nd-order adaptive FSST under different noise levels.…”

Section: Experiments With a Three-component Synthetic Signalmentioning

confidence: 99%

“…Three-component signal in (66): its waveform (Left panel) and IFs of its components (Right panel).We calculate various time-varying parameters as those shown inFig.2and σ est2 (t) as well. In this experiment, to obtain σ est2 (t) with Algorithm 2, we consider a time-varying (t) with ∈ [0.2, 0.8] Experimental results on the three-component signal in(66). Top-row (from left to right): conventional FSST with constant σ = 0.04, regular-PT adaptive FSST with σ Re (t) and adaptive FSST with σ est2 (t); Bottom-row (from left to right): conventional 2nd-order FSST with constant σ = 0.04, 2nd-order regular-PT adaptive FSST with σ Re2 (t) and 2nd-order adaptive FSST with σ est2 (t).…”

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confidence: 99%

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Adaptive short-time Fourier transform and synchrosqueezing transform for non-stationary signal separation

et al. 2020

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The synchrosqueezing transform, a kind of reassignment method, aims to sharpen the timefrequency representation and to separate the components of a multicomponent non-stationary signal. In this paper, we consider the short-time Fourier transform (STFT) with a time-varying parameter, called the adaptive STFT. Based on the local approximation of linear frequency modulation mode, we analyze the well-separated condition of non-stationary multicomponent signals using the adaptive STFT with the Gaussian window function. We propose the STFT-based synchrosqueezing transform (FSST) with a time-varying parameter, named the adaptive FSST, to enhance the time-frequency concentration and resolution of a multicomponent signal, and to separate its components more accurately. In addition, we also propose the 2nd-order adaptive FSST to further improve the adaptive FSST for the non-stationary signals with fast-varying frequencies. Furthermore, we present a localized optimization algorithm based on our well-separated condition to estimate the time-varying parameter adaptively and automatically. Simulation results on synthetic signals and the bat echolocation signal are provided to demonstrate the effectiveness and robustness of the proposed method.where A k (t), φ k (t) > 0, has been a very active research area over the past few years. Note that the number of component K may change with time t, but it should be constant for long enough time intervals. The representation of x(t) in (1) with A k (t) and φ k (t) varying slowly or more slowly than φ k (t) is called an adaptive harmonic model (AHM) representation of x(t), where A k (t) are called the instantaneous amplitudes and φ k (t) the instantaneous frequencies (IFs). To decompose x(t) as an AHM representation (1) is important to extract information, such as the underlying dynamics, hidden in x(t). Time-frequency (TF) analysis is widely used in engineering fields such as communication, radar and sonar as a powerful tool for analyzing time-varying non-stationary signals [1]. Time-frequency analysis is especially useful for signals containing many oscillatory components with slowly timevarying amplitudes and instantaneous frequencies. The short-time Fourier transform (STFT), the continuous wavelet transform (CWT) and the Wigner-Ville distribution are the most typical TF analysis, see details in [1]-[6]. Other TF distributions of Cohen's class include the exponential distribution [7], a smoothed pseudo Wigner distribution [8] and the complex-lag distribution [9].In addition, the TF signal analysis and synthesis using the eigenvalue decomposition method has been studied [10,11]. In particular, an eigenvalue decomposition-based approach which enables the separation of non-stationary components with overlapped supports in the TF plane has been proposed in [12].Recently a number of new TF analysis methods such as the Hilbert spectrum analysis with empirical mode decomposition (EMD) [13], the reassignment method [14] and synchrosqueezed wavelet transform (SST) [15] have also been proposed ...

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Section: Experiments With a Three-component Synthetic Signalmentioning

confidence: 99%

Section: Experiments With a Three-component Synthetic Signalmentioning

confidence: 99%

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confidence: 99%

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Adaptive short-time Fourier transform and synchrosqueezing transform for non-stationary signal separation

et al. 2020

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“…As one of the most commonly used FDM, vibration-based pattern recognition method has attracted significant attention in the field of rotating equipment fault diagnosis. However, the vibration characteristics of RC have non-linear, non-stationary, and multi-component coupling factors [3,9], which pose challenges for RC fault diagnosis. Generally, the FDM of RC can be divided into three categories: model-based, data-driven, and a combination of the two [2,10,11].…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2020

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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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“…Without claiming to be an exhaustive exposition of all the questions of an experimental study of valve tightness and increasing their operational efficiency, let's highlight only some aspects of this important problem. Problems of maintaining the performance of a reciprocating compressor unit operating in gas lift and gas transport systems [5,6].…”

Section: Introductionmentioning

confidence: 99%

Methodology of Experimental Investigations of Valve Operation

Seyidahmadov¹

2019

EUREKA: Physics and Engineering

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Tightness, as well as the reliability of the valve plate, is a complex property of the effective operation of compressor cylinders of the first stage and, in general, gas-engine reciprocating compressors. The issue of valve plate tightness is a subject of independent study, since technical and economic efficiency depends on their work. In this connection, only some data obtained under operating conditions are presented in this work. As a research result, it is found that, taking into account the identified requirements for the gas lift system, in order to effectively increase the operating hours of valves with increased tightness of the plate, it is necessary to check and purge the valves. Therefore, each valve in the gas lift compressor station, without subjecting them to cleaning, is first recommended to check for leaks. To confirm the feasibility of checking valve tightness, special equipment is offered for each gas-lift compressor station, a purge chamber, on which the tightness of valve plates is checked. The usefulness and importance of the purge chamber is in preparation of the valve at the gas lift compressor station, which contributes to increased efficiency, safe operation, normal tightness and reliability of its operation.

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Performance evaluation of decomposition methods to diagnose leakage in a reciprocating compressor under limited speed variation

Cited by 35 publications

References 35 publications

Adaptive short-time Fourier transform and synchrosqueezing transform for non-stationary signal separation

Adaptive short-time Fourier transform and synchrosqueezing transform for non-stationary signal separation

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

Methodology of Experimental Investigations of Valve Operation

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