Extended Sliding Time Synchronous Averaging for Enhancing Weak Fault Feature of Rolling Bearings

In the early failure stage of bearings, weak fault features are often obfuscated by strong background noise, making their detection a focal point of current research. Time synchronous averaging (TSA) is recognized as an effective method for enhancing periodic pulses. However, the presence of jitter and the single-pulse nature of the TSA output limit its application. To address this issue, the concept of a sliding window has been introduced, leading to the development of sliding TSA (STSA). This approach generates a series of pulses but is accompanied by the empirical selection of window length and signal loss. In response, this study proposes a novel algorithm, termed extended STSA (ESTSA), introducing an extension operation to the STSA. The ESTSA algorithm not only produces an enhanced signal of the same length as the original but also tends to achieve optimal enhancement effects. Besides, the bad effect of jitter for enhancing fault signal can also be suppressed. A comparative analysis, utilizing various sets of simulated signals and experimental data, underscores ESTSA’s superior capability in extracting fault characteristics compared to conventional enhancement methods.

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Publication Details

Journal
IEEE Transactions on Instrumentation and Measurement
Published
2025-01-01
DOI
https://doi.org/10.1109/tim.2025.3552473
Citations
1
Primary Topic
Gear and Bearing Dynamics Analysis
Type
article
Field-Weighted Citation Impact
0.71
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article

Extended Sliding Time Synchronous Averaging for Enhancing Weak Fault Feature of Rolling Bearings

Khandaker Noman, Laixing Li, Yongbo Li, Shi Shuai et al.
1 citations
IEEE Transactions on Instrumentation and Measurement
Gear and Bearing Dynamics Analysis
0.71
article

Extended Sliding Time Synchronous Averaging for Enhancing Weak Fault Feature of Rolling Bearings

Khandaker Noman, Laixing Li, Yongbo Li, Shi Shuai, Hongbo Shi, Tao Liu
article en
1 citations

Abstract

In the early failure stage of bearings, weak fault features are often obfuscated by strong background noise, making their detection a focal point of current research. Time synchronous averaging (TSA) is recognized as an effective method for enhancing periodic pulses. However, the presence of jitter and the single-pulse nature of the TSA output limit its application. To address this issue, the concept of a sliding window has been introduced, leading to the development of sliding TSA (STSA). This approach generates a series of pulses but is accompanied by the empirical selection of window length and signal loss. In response, this study proposes a novel algorithm, termed extended STSA (ESTSA), introducing an extension operation to the STSA. The ESTSA algorithm not only produces an enhanced signal of the same length as the original but also tends to achieve optimal enhancement effects. Besides, the bad effect of jitter for enhancing fault signal can also be suppressed. A comparative analysis, utilizing various sets of simulated signals and experimental data, underscores ESTSA’s superior capability in extracting fault characteristics compared to conventional enhancement methods.

IEEE Transactions on Instrumentation and MeasurementVol. 74
Northwestern Polytechnical University (CN)
Climate action
Openalex Percentile: Top 35%
Gear and Bearing Dynamics Analysis
0.71
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Extended Sliding Time Synchronous Averaging for Enhancing Weak Fault Feature of Rolling Bearings — Khandaker Noman, Laixing Li, et al. · IEEE Transactions on Instrumentation and Measurement (2025) | TGRS Research Map | TGRS