Review summary on HV Motor Testing Technique.

This paper introduces a new approach for comprehensive Health Index (HI) assessment of high-voltage (HV) induction motors used in oil and gas plants. The proposed method is designed to be practical, relying on readily available operational and maintenance data without requiring the installation of additional sensors. It accounts for real-world limitations in data acquisition and incorporates internationally recognized criteria from IEC, IEEE, and CIGRE standards. The Health Index calculation integrates both conventional diagnostic test results, such as Partial Discharge (PD), Insulation Resistance (IR), Polarization Index (PI), Tan Delta (TD), vibration measurements, and complementary information/ Conditional Factors CF, including physical condition, maintenance history recorded in the Standard Assessment Procedure (SAP), and aging factors. Condition ratings, weighting factors, and parameter-specific scoring are systematically applied to provide a balanced assessment. By adopting a multi-criteria analysis framework, the proposed method consolidates diverse parameters into a unified, condition-based Health Index. The significance of this work lies in its ability to support proactive asset management, minimize unexpected failures, and ensure the reliable and efficient operation of HV motors. Experimental case studies further demonstrate the applicability and robustness of the approach.本论文提出了一种面向油气厂用高压（high-voltage, HV）感应电机的综合健康指数（Health Index, HI）评估新方法。该方法具备实用特性，可依托现有可获取的运行与维护数据开展评估，无需额外加装传感器。其兼顾了数据采集过程中的实际局限性，并纳入了国际电工委员会（International Electrotechnical Commission, IEC）、电气和电子工程师协会（Institute of Electrical and Electronics Engineers, IEEE）以及国际大电网委员会（International Council on Large Electric Systems, CIGRE）的公认标准准则。健康指数的计算整合了局部放电（Partial Discharge, PD）、绝缘电阻（Insulation Resistance, IR）、极化指数（Polarization Index, PI）、介质损耗因数（Tan Delta, TD）、振动测量等常规诊断测试结果，以及状态因子（Conditional Factors, CF）等补充信息——后者涵盖设备物理状态、标准评估程序（Standard Assessment Procedure, SAP）记录的维护历史与老化因子。研究系统地应用了状态评级、权重因子与参数专属评分机制，以实现均衡全面的评估。通过采用多准则分析框架，所提方法将多样化的参数整合为统一的基于状态的健康指数。本研究的核心价值在于可支撑主动资产管理、降低意外故障发生率，保障高压电机的可靠高效运行。最终通过实验案例研究，进一步验证了该方法的适用性与鲁棒性。