• 论文 •

### 不可靠测试条件下基于NSGA-Ⅱ的多目标测试优化选择

1. 1. 海军航空大学 岸防兵学院, 烟台 264001;
2. 中国人民解放军 78102部队, 成都 610000
• 收稿日期:2020-02-04 发布日期:2021-04-30
• 通讯作者: 史贤俊 E-mail:sxjaa@sina.com
• 作者简介:翟禹尧,男,博士研究生。主要研究方向:测试性、故障诊断;史贤俊,男,博士,教授,博士生导师。主要研究方向:自动控制、测试性和故障诊断。
• 基金资助:
国家自然科学基金（61903374）

### Multi-objective test optimization selection based on NSGA-Ⅱ under unreliable test conditions

ZHAI Yuyao1, SHI Xianjun1, YANG Shuai2, QIN Yufeng1

1. 1. Coast Guard Academy, Naval Aviation University, Yantai 264001, China;
2. PLA Unit 78102, Chengdu 610000, China
• Received:2020-02-04 Published:2021-04-30
• Supported by:
National Natural Science Foundation of China (61903374)

Abstract: Since test optimization selection plays a vital role in the test design of various equipment systems, in the testability design of various types of equipment, test unreliable factors seriously affect the optimization of test selection. First, this paper describes the mathematical model of the multi-objective optimization selection problem under unreliable test conditions. Second, under this mathematical model, the test cost, missed detection rate, and false alarm rate are used as the optimization goals, and the fault detection rate and isolation rate are constraints. Thus, a multi-objective optimization problem was established. Third, the NSGA-Ⅱ algorithm, a fast Non-dominated multi-objective optimization Sorting Genetic Algorithm-Ⅱ with an elite retention strategy, was proposed to optimize the proposed multi-objective problem. Using the NSGA-Ⅱ algorithm, a set of Pareto optimal solutions are obtained, and the optimal test combination can be selected according to actual needs. Finally, an example analysis is performed on a certain equipment, three sets of optimal solutions are obtained, which can meet the optimal selection under different needs, and the feasibility and effectiveness of the mathematical model and multi-objective optimization algorithm are verified.