Temasek Holdings (Private) has been granted a patent for a method to detect rotor bar faults in electrical machines. By analyzing vibration and magnetic flux signals, deviations from baseline values indicate potential rotor damage. This innovation enhances maintenance efficiency and reduces downtime in industrial operations. GlobalData’s report on Temasek Holdings (Private) gives a 360-degree view of the company including its patenting strategy. Buy the report here.

According to GlobalData’s company profile on Temasek Holdings (Private), was a key innovation area identified from patents. Temasek Holdings (Private)'s grant share as of May 2024 was 48%. Grant share is based on the ratio of number of grants to total number of patents.

Method for detecting rotor bar fault in electrical machines

Source: United States Patent and Trademark Office (USPTO). Credit: Temasek Holdings (Private) Ltd

A recently granted patent (Publication Number: US11959978B2) discloses a method for detecting rotor bar faults in electrical machines. The method involves acquiring online signals, including vibration and magnetic flux signals, from the machine over a period. By comparing the anomaly indicator value extracted from these signals with a baseline value under corresponding loading conditions, the presence of a broken or cracked rotor can be determined when the deviation exceeds a threshold. The method is particularly useful for motors or generators with stators and rotors, providing a comprehensive approach to identifying faults and ensuring timely maintenance.

Furthermore, the patent also covers a method for estimating additional operating expenditure due to mechanical anomalies in electrical machines. By analyzing online signals, including vibration, magnetic flux, and current signals, an anomaly indicator value is extracted and compared with a baseline value. This comparison helps in determining the presence of mechanical anomalies and computing the additional operating expenditure over a specified time frame. The method includes steps for initial calibration of the machine, inputting parameter values, and monitoring overall vibration velocity to trigger maintenance signals when deviations occur, offering a comprehensive solution for managing and predicting maintenance costs in electrical machines.

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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.