Exploitation of long-range acoustic dependence for early change detection in dynamic machine running status

Exploitation of long-range acoustic dependence for early change detection in dynamic machine running status

Blog Article

This paper suggests that the long-range dependence (LRD) in acoustic signal is an important indicator of dynamic behavior in data.Considering this information, a novel framework based on LRD in acoustic is proposed for detecting change-points in machine running status.Initially, the LRD phenomenon in acoustic beetroot birkenstock is demonstrated.Subsequently, a change-point detection framework is developed, leveraging LRD to monitor machine running states.The framework includes two phases: (1) characteristic data prediction: the LRD value is predicted by the fractional autoregressive integrated moving average (FARIMA) model, which is applied to reflect changes in machine operation states.

(2) date change spidertattooz.com detection: based on residual analysis, a null hypothesis testing based automatic analysis method for acoustic signals during machine successive operations is used to make decision.Experiments in real-world applications demonstrated the good potential of the proposed framework in practical engineering scenarios.