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, due to 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 time synchronous averaging (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 sliding time synchronous averaging (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 tend 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.