Abstract: Disclosed are approaches for analyzing vibration data to determine and mitigate an occurrence of an anomaly with respect to an industrial machine. In one embodiment, time-series vibration data is received from a sensor measuring vibration of a machine. First outliers are detected in a short-term window of the time-series vibration data. Second outliers are detected in a long-term window of the time-series vibration data. The sensor is determined to be associated with an anomaly based at least in part on a quantity of the first outliers and a quantity of the second outliers.

Abstract: Methods, systems, and devices for analyzing vibration data to determine and mitigate an occurrence of an anomaly at an industrial asset. A device may obtain and preprocess vibration data, which may include grouping the vibration data according to respective time intervals, and the device may filter the grouped data to obtain the most recent measurement readings. The device may use an anomaly detection algorithm to detect outliers in the datasets for each group of vibration data and compare an amplitude of the outliers to a threshold for the respective group. The device may determine that the vibration data includes an anomaly based on quantities of outliers in first and second subsets of the vibration data that are within a detection window. The device may generate a report including an indication of the anomaly and transmit the report to an operator or engineer for the facility.

Abstract: Methods, systems, and devices for analyzing vibration data to determine and mitigate an occurrence of an anomaly at an industrial asset. A device may obtain and preprocess vibration data, which may include grouping the vibration data according to respective time intervals, and the device may filter the grouped data to obtain the most recent measurement readings. The device may use an anomaly detection algorithm to detect outliers in the datasets for each group of vibration data and compare an amplitude of the outliers to a threshold for the respective group. The device may determine that the vibration data includes an anomaly based on quantities of outliers in first and second subsets of the vibration data that are within a detection window. The device may generate a report including an indication of the anomaly and transmit the report to an operator or engineer for the facility.