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

Jie Hu, Yuanjun Li, Chunhui Li, Lingzi Chen, Fei Li
Journal of Computing and Electronic Information Management, (2026), Vol.23, No.1, pp.1-4
Published: October 10, 2026
DOI: 10.54097/fngpv338
PDF: Download Full Text PDF
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.

Keywords: Electronic test instruments, Knowledge base, Intelligent application, Fault diagnosis, Parameter optimization, Test automation, Ontology modeling
APA Citation: Jie Hu, Yuanjun Li, Chunhui Li, Lingzi Chen, Fei Li (2026). Advances and Prospects of Knowledge-Base-Driven Intelligent Applications for Electronic Test Instruments. Journal of Computing and Electronic Information Management, 23(1), 1-4. https://doi.org/10.54097/fngpv338

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