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Verification and validation optimization method for signal quality bits in digital control system application software of nuclear power plant

  • Lingzhi Wang and Yichun Wu EMAIL logo
Published/Copyright: March 15, 2024
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Abstract

The digitalization enhances nuclear power plant (NPP) instrumentation and control (I&C) system performance, while simultaneously introducing safety and reliability challenges. To enhance the stability of distributed control system (DCS), and minimize the dangerous failure rate and safe failure rate of safety system, signal quality bits (SQBs) are widely used in NPP DCS to identify the validity of important signals. However, in the past decade or so, numerous unscheduled turbine shutdowns and/or reactor trips have resulted from incorrect SQB design or settings. Therefore, it is necessary to conduct optimization research on the design methods and setting principles of SQBs, establish an optimization method for DCS application software SQB verification and validation (V&V), then minimize DCS faults attributed to SQB. With the aim, this work conducts an in-depth investigation and analysis of the definition, design, setting and transmission of SQB in NPP. A specific optimization method for software V&V to conduct SQB on NPP safety DCS application software is proposed. Twelve concerns in the SQB V&V work are detailed. The reactor trip system ΔT protection logic is utilized as a case to illustrate the detail implementation process of this optimization method. This work provides an engineering technical reference and operational guidance for SQB software V&V, conducive to ensuring the safe and economical operation of NPPs.


Corresponding author: Yichun Wu, College of Energy, Xiamen University, Xiang’an Nan Road 4221, Xiang’an District, Xiamen, Fujian 361102, China, E-mail:

Funding source: The Fund for High-level Talents of Xiamen City University

Award Identifier / Grant number: No. G3R2022-9

Funding source: The Science and Technology Project of Fujian Province

Award Identifier / Grant number: No. 2022H0004

  1. Research ethics: Not applicable.

  2. Author contributions: Lingzhi Wang: Conceptualization, Methodology, Writing – Original Draft, Writing – Review & Editing, Funding acquisition. Yichun Wu: Methodology, Validation, Writing – Review & Editing, Supervision, Funding acquisition. The authors have accepted responsibility for the entire content of this manuscript and approved its submission.

  3. Competing interests: The authors state no conflict of interest.

  4. Research funding: This work was supported by the Fund for High-level Talents of Xiamen City University (No. G3R2022-9), and the Science and Technology Project of Fujian Province (No. 2022H0004).

  5. Data availability: Not applicable.

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Received: 2024-02-05
Accepted: 2024-02-24
Published Online: 2024-03-15
Published in Print: 2024-06-25

© 2024 Walter de Gruyter GmbH, Berlin/Boston

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