Bentley Systems has patented a method for detecting anomalies in water distribution systems using flow and pressure data. The technique involves decomposing time series data, detecting outliers, classifying sensor events, determining anomaly events, and assigning quantitative scores. This innovation aims to enhance efficiency and reliability in anomaly detection. GlobalData’s report on Bentley Systems gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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According to GlobalData’s company profile on Bentley Systems, AI assisted CAD was a key innovation area identified from patents. Bentley Systems's grant share as of March 2024 was 65%. Grant share is based on the ratio of number of grants to total number of patents.
Efficient anomaly detection and evaluation in water distribution systems
A recently granted patent (Publication Number: US11960254B1) outlines a method for detecting and evaluating anomaly events in a water distribution system. The method involves receiving time series data from sensors in the system, decomposing the data to remove seasonality, detecting outliers using statistical process control algorithms, classifying sensor events based on flow and pressure thresholds, correlating sensor events to identify anomaly events, assigning quantitative scores to these anomalies, and providing a report with the detected events and scores. The method also includes cleaning the data to correct errors and utilizing various algorithms such as x-bar, CUSUM, EWMA, and SH-ESD for anomaly detection and evaluation.
Furthermore, the patent describes the use of a decomposition algorithm to render the time series data stationary, the classification of sensor events based on flow and pressure thresholds, and the correlation of high flow and low pressure sensor events to identify anomalies. The method also involves deploying maintenance or repair personnel based on the classification of detected anomalies. Additionally, the patent highlights the importance of cleaning the data to address missing, duplicate, irregular, or sensor failure time steps, and the utilization of SPC algorithms like x-bar, CUSUM, EWMA, and SH-ESD for effective anomaly detection and evaluation in water distribution systems.
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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.
