Many electrical equipment malfunction text messages are collected during power system operation and maintenance procedures. These texts usually contain crucial information for maintenance and condition monitoring. Because these power system malfunction texts are characterized by multidomain vocabularies, complex-syntactic structures, and long sentences, it is challenging to for automated systems to capture their semantic meaning and essential information. To address this issue, we propose a hybrid natural language processing (hybrid-NLP) algorithm to extract entities that represent electrical equipment. This algorithm is composed of a dictionary-based method, a language technology platform (LTP) tool, and the bidirectional encoder representations from a transformers-conditional random field (BERT-CRF) model. Significantly, the softmax output layer of the bidirectional encoder representations from the transformers (BERT) model is replaced by the conditional random field (CRF) algorithm to strengthen the contextual relationships between words and thus solve the local optimization of the preferred word label. The effectiveness of the proposed hybrid-NLP method is verified on a realistic dataset. Moreover, a statistical analysis is conducted to provide a reference for the operation and maintenance of power systems. INDEX TERMS electrical equipment malfunction text, natural language processing, entity extraction, BERT-CRF model.

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The DC-link filter which includes a magnetic inductor and a storage capacitor is one of the key parts of adjustable speed drives in the market. It significantly affects the stability, reliability, and power density of the motor-drive system. This paper proposes a novel, variable active inductor to improve the performance of DC links in terms of stability, reliability, size, and cost. In contrast to conventional DC-link magnetic inductors, the variable active inductor is made of power electronic circuits, including active switches, passive filters, and smart controllers, which no longer rely on magnetic material. The demonstration shows that the inductor can emulate the electrical characteristics of the magnetic inductor for filtering harmonics and stabilizing the DC link, meanwhile representing a smaller size, lighter weight, and lower cost compared with a conventional one. Furthermore, this paper proposes a variable inductance control method which is able to adaptively tune the inductance value with the operating conditions of the drive system. The DC link can be stabilized, and high performance can be maintained in both balanced and unbalanced grid voltage conditions. A case study of the proposed variable inductor in a motor drive with a three-phase diode-bridge rectifier as the front end is discussed. Experimental results are given to verify the functionality and effectiveness of the proposed variable inductor.

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