Bearing Condition Monitoring via Multiple Instantaneous Frequency Path Extraction from Enhanced Time Frequency Representation

2019 ◽  
Author(s):  
Rongmei Ding ◽  
Juanjuan Shi ◽  
Jun Wang ◽  
Changqing Shen ◽  
Zhongkui Zhu
Keyword(s):  
Condition Monitoring ◽  
Instantaneous Frequency ◽  
Time Frequency ◽  
Frequency Representation ◽  
Bearing Condition Monitoring ◽  
Path Extraction

scholarly journals Time Frequency Representation Enhancement via Frequency Matching Linear Transform for Bearing Condition Monitoring under Variable Speeds

2019 ◽  
Vol 9 (18) ◽  
pp. 3828 ◽  
Author(s):  
Juanjuan Shi ◽  
Guifu Du ◽  
Rongmei Ding ◽  
Zhongkui Zhu
Keyword(s):  
Condition Monitoring ◽  
Frequency Resolution ◽  
Vibration Signals ◽  
Time Frequency ◽  
Frequency Matching ◽  
Frequency Representation ◽  
Bearing Condition Monitoring ◽  
Before And After ◽  
Linear Transform ◽  
Short Time

Instantaneous frequency (IF) of shaft rotation is pivotal for bearing fault diagnosis under variable speed operations. However, shaft IF cannot always be measured as tachometers are not allowed to be installed in every case due to design reasons and cost concerns. Extracting the shaft IF ridge from time frequency representation (TFR) of vibration signals, therefore, becomes an alternative. Linear transform (LT), such as short time Fourier transform (STFT), has been widely adopted for such a purpose. Nevertheless, the accuracy of extracted IF ridges relies on the readability of TFR. Unfortunately, readability of TFR from STFT is often impaired by the smearing effect caused by non-synchronous frequencies between bases and signal components and limited time frequency resolution capability, which in turn adversely influences the accuracy of IF ridge extraction. To accurately extract IF ridges from vibration signals, this paper focuses on the first factor, which causes the smearing problem, and proposes a method named frequency matching linear transform (FMLT) to enhance the TFR, where transforming bases with frequencies varying with the shaft IF are constructed to alleviate the smearing effects. To construct the transforming bases with frequencies synchronous with shaft IF, a fast path optimization (FPO) algorithm, which generates all possible optimization paths among amplitude peaks and thereby ensures the continuity of extracted IF ridges, is adopted for IF pre-estimation. The TFR with improved readability can be subsequently obtained via FMLT, paving the way for accurate IF ridge extraction. Then, multiple IF ridges can be iteratively extracted using the FPO algorithm. The accuracy of extracted IF ridges before and after TFR enhancement is compared, indicating that the proposed FMLT can enhance the readability of TFR and lead to more accurate IF ridge extraction for bearing condition monitoring.

Instantaneous Frequency Estimation of Ultrasonic Testing Signal Based on Matching Pursuits

2013 ◽  
Vol 631-632 ◽  
pp. 1367-1372 ◽  
Author(s):  
Xiu Li Du
Keyword(s):  
Instantaneous Frequency ◽  
Ultrasonic Testing ◽  
Frequency Estimation ◽  
Signal To Noise Ratio ◽  
Instantaneous Frequency Estimation ◽  
Time Frequency ◽  
Frequency Representation ◽  
Matching Pursuits ◽  
Testing Signal ◽  
Suppress Noise

The differences of instantaneous frequency (IF) characteristics between the defect echo and the noise can be used to detect defect and suppress noise for ultrasonic testing signal. Therefore, the IF is one of the important instantaneous parameters of ultrasonic testing signal. To estimate the IF of ultrasonic testing signals more effectively, the peak of time-frequency representation (TFR) from matching pursuits (MP) decomposition is proposed. The performances of IF estimators are compared on the simulated signals at different signal-to-noise ratio (SNR) and the real ultrasonic testing signal. The simulation results present that the proposed method can estimate accurate IF at different SNR.

scholarly journals Rolling Element Bearing Condition Monitoring using Filtered Acoustic Emission

2018 ◽  
Vol 8 (5) ◽  
pp. 3560
Author(s):  
Sudarsan Sahoo ◽  
J. K. Das ◽  
Bapi Debnath
Keyword(s):  
Condition Monitoring ◽  
Acoustic Signal ◽  
Rolling Element Bearing ◽  
Time Frequency ◽  
Second Stage ◽  
Acoustic Signature ◽  
Bearing Condition Monitoring ◽  
Rolling Element ◽  
Element Bearing ◽  
Two Stages

The defect present in the bearing of a rolling element may affect the performance of the rotating machinery and may reduce its efficiency. For this reason the condition monitoring of a rolling element bearing is very essential. So many measuring parameters are there to diagnose the fault in a rolling element bearing. Acoustic signature monitoring is one of them. Every rolling element bearing has its own acoustic signature when it is in healthy condition and when the bearing get defected then there is a change in its original acoustic signature. This change in acoustic signature can be monitored and analyzed to detect the fault present in the bearing. But the noise present in the acquired acoustic signal may affect the analysis. So the noisy acoustic signal must be filtered before the analysis. In this work the experiment is performed in two stages. In first stage the filtration of the acquired acoustic signal is done by employing the active noise cancellation (ANC) filtering techniques. In second stage the filtered signal is used for the further analysis. For the analysis initially the static analysis is done and then the frequency and the time-frequency analysis is done to diagnose the defect in the bearing. From all the three analysis the information about the defect present in the bearing is well detected.

scholarly journals NOISE CORRUPTION OF EMPIRICAL MODE DECOMPOSITION AND ITS EFFECT ON INSTANTANEOUS FREQUENCY

2010 ◽  
Vol 02 (03) ◽  
pp. 373-396 ◽  
Author(s):  
DANIEL N. KASLOVSKY ◽  
FRANÇOIS G. MEYER
Keyword(s):  
Empirical Mode Decomposition ◽  
Instantaneous Frequency ◽  
Poor Performance ◽  
Specific Mechanism ◽  
Time Frequency ◽  
Seismic Waveform ◽  
Mode Decomposition ◽  
Frequency Representation ◽  
Transition Modes ◽  
Nonstationary Data

Huang's Empirical Mode Decomposition (EMD) is an algorithm for analyzing nonstationary data that provides a localized time-frequency representation by decomposing the data into adaptively defined modes. EMD can be used to estimate a signal's instantaneous frequency (IF) but suffers from poor performance in the presence of noise. To produce a meaningful IF, each mode of the decomposition must be nearly monochromatic, a condition that is not guaranteed by the algorithm and fails to be met when the signal is corrupted by noise. In this work, the extraction of modes containing both signal and noise is identified as the cause of poor IF estimation. The specific mechanism by which such "transition" modes are extracted is detailed and builds on the observation of Flandrin and Goncalves that EMD acts in a filter bank manner when analyzing pure noise. The mechanism is shown to be dependent on spectral leak between modes and the phase of the underlying signal. These ideas are developed through the use of simple signals and are tested on a synthetic seismic waveform.

GENERALIZED INSTANTANEOUS AMPLITUDE AND FREQUENCY FUNCTIONS AND THEIR APPLICATION FOR PITCH FREQUENCY DETERMINATION

1995 ◽  
Vol 05 (02) ◽  
pp. 145-165 ◽  
Author(s):  
RUDOLF FÖLDVÁRI
Keyword(s):  
Instantaneous Frequency ◽  
Signal To Noise Ratio ◽  
Frequency Function ◽  
Instantaneous Amplitude ◽  
Time Frequency ◽  
Frequency Representation ◽  
Pitch Frequency ◽  
True Time ◽  
Human Hearing ◽  
Frequency Detector

By defining an instantaneous frequency function it could be shown that if a signal is analytic, instantaneous frequency is analytic, too. A generalized instantaneous amplitude function could then be introduced which is also analytic in character. These functions — apart from an arbitrary constant phase — uniquely define the analytic time function. It could be proved that the transformation gives a true time-frequency representation which fulfills all the necessary requirements. Moreover, the application of instantaneous parameters in connection with a Zwicker's filter bank makes it possible even to model human hearing. By applying a simplified hearing model, an efficient pitch-frequency detector able to decide between voiced-unvoiced signals with the same reliability as visual detection even at a 0 dB signal-to-noise ratio could be developed.

scholarly journals An Improved Time-Frequency Analysis Method for Instantaneous Frequency Estimation of Rolling Bearing

2018 ◽  
Vol 2018 ◽  
pp. 1-18 ◽  
Author(s):  
Zengqiang Ma ◽  
Wanying Ruan ◽  
Mingyi Chen ◽  
Xiang Li
Keyword(s):  
Frequency Analysis ◽  
Instantaneous Frequency ◽  
Frequency Estimation ◽  
Rolling Bearing ◽  
Analysis Method ◽  
Instantaneous Frequency Estimation ◽  
Time Frequency Analysis ◽  
Noise Interference ◽  
Time Frequency ◽  
Frequency Representation

Instantaneous frequency estimation of rolling bearing is a key step in order tracking without tachometers, and time-frequency analysis method is an effective solution. In this paper, a new method applying the variational mode decomposition (VMD) in association with the synchroextracting transform (SET), named VMD-SET, is proposed as an improved time-frequency analysis method for instantaneous frequency estimation of rolling bearing. The SET is a new time-frequency analysis method which belongs to a postprocessing procedure of the short-time Fourier transform (STFT) and has excellent performance in energy concentration. Considering nonstationary broadband fault vibration signals of rolling bearing under variable speed conditions, the time-frequency characteristics cannot be obtained accurately by SET alone. Thus, VMD-SET method is proposed. Firstly, the signal is decomposed into several intrinsic mode functions (IMFs) with different center frequency by VMD. Then, effective IMFs are selected by mutual information and kurtosis criteria and are reconstructed. Next, the SET method is applied to the reconstructed signal to generate the time-frequency representation with high resolution. Finally, instantaneous frequency trajectory can be accurately extracted by peak search from the time-frequency representation. The proposed method is free from time-varying sidebands and is robust to noise interference. It is proved by numerical simulated signal analysis and is further validated by lab experimental rolling bearing vibration signal analysis. The results show this method can estimate the instantaneous frequency with high precision without noise interference.

scholarly journals Bearing Condition Monitoring based on the Indicator Generated in Time-frequency Domain

2019 ◽  
Vol 11 (1) ◽  
Author(s):  
Teng Wang ◽  
Zheng Liu ◽  
Guoliang Lu
Keyword(s):  
Condition Monitoring ◽  
Vibration Signal ◽  
Rolling Bearing ◽  
Data Driven ◽  
Time Frequency ◽  
Vibration Data ◽  
Bearing Condition Monitoring ◽  
Condition Monitoring Systems ◽  
Early Fault Detection ◽  
Condition Indicator

Most condition monitoring systems rely on system-driven generation of indicators or features for early fault detection. However, this strategy requires the prior knowledge on the system kinematics and/or exact structure parameters of monitored system. To address this problem, this paper presents a novel condition monitoring framework where the condition indicator is generated via data-driven method. In this framework, the time-frequency periodogram is extracted from raw vibration signal first. Then, the acquired time-frequency periodogram is mapped by pseudo Perron vector, which is learned from vibration data, to generate the condition indicator. Finally, the bearing can be monitored via analyzing this indicator using gaussian based control chart. Based on experimental results on a publicly-available database, we show the effectiveness of presented framework for early fault detectionin the continuous operation of rolling bearing, indicating its great potentials in real engineering applications.

Operating Investigation of Transmission Systems Using Advanced Time-Frequency Representations

2003 ◽  
Author(s):  
Min-Chun Pan ◽  
Jeng-Yi Huang
Keyword(s):  
Condition Monitoring ◽  
Dynamic Characteristics ◽  
Mechanical Systems ◽  
Test Rig ◽  
Transmission Systems ◽  
Shape Distribution ◽  
Time Frequency ◽  
Frequency Representation ◽  
Component Test ◽  
Electro Magnetic

This study aims at developing and implementing advanced time -frequency representation algorithms, i.e., Choi-William distribution, and cone-shape distribution, based on the spectrogram and the smoothed Wigner- Ville distribution to both improve time and frequency resolutions as compared with the spectrogram, and soothe interferences resulting from the Wigner-Ville distribution. Synthetic signals were designed to assess the effectiveness of these algorithms, and compare computing features of these schemes as well. A transmission-component test rig was built up to investigate dynamic characteristics of the gearbox, belt set and electro-magnetic brake during operation. Conducted experimentation highlights the justification of applying these advanced schemes in condition monitoring tasks of mechanical systems.

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