Advances and Prospects of Knowledge-Base-Driven Intelligent Applications for Electronic Test Instruments

Authors

  • Jie Hu National Key Laboratory of Science and Technology on Electronic Test and Measurement, Qingdao, China ; The 41st Institute of China Electronic Technology Group Corporation, Qingdao, China
  • Yuanjun Li National Key Laboratory of Science and Technology on Electronic Test and Measurement, Qingdao, China ; The 41st Institute of China Electronic Technology Group Corporation, Qingdao, China
  • Chunhui Li National Key Laboratory of Science and Technology on Electronic Test and Measurement, Qingdao, China ; The 41st Institute of China Electronic Technology Group Corporation, Qingdao, China
  • Lingzi Chen National Key Laboratory of Science and Technology on Electronic Test and Measurement, Qingdao, China ; The 41st Institute of China Electronic Technology Group Corporation, Qingdao, China
  • Fei Li National Key Laboratory of Science and Technology on Electronic Test and Measurement, Qingdao, China ; The 41st Institute of China Electronic Technology Group Corporation, Qingdao, China

DOI:

https://doi.org/10.54097/fngpv338

Keywords:

Electronic test instruments, Knowledge base, Intelligent application, Fault diagnosis, Parameter optimization, Test automation, Ontology modeling

Abstract

A paradigm shift is transforming electronic test instruments from rule-based systems into knowledge-base-driven intelligent platforms. This survey reviews intelligent application technologies for such instruments built on knowledge-base architectures. We delineate the domain's knowledge-intensive characteristics, examine knowledge-base construction (architecture design, multi-source acquisition, ontology modeling, and heterogeneous data fusion), and analyze three core technologies—intelligent fault diagnosis combining case-based and rule-based reasoning, intelligent parameter configuration through data-driven recommendation, and intelligent test process planning via automated task decomposition. We then identify key challenges in data security, knowledge maintenance, and technical compatibility, and outline trends including Internet of Thing (IoT) and cloud computing convergence, expansion into fields such as 5G/6G and aerospace, and industrial standardization.

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Published

10-10-2026

Issue

Vol. 23 No. 1 (2026)

Section

Articles

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