基于离散粒子群优化算法的多值属性系统故障诊断策略

doi:10.12382/bgxb.2021.0673

兵工学报 ›› 2022, Vol. 43 ›› Issue (12): 3240-3246.doi: 10.12382/bgxb.2021.0673

基于离散粒子群优化算法的多值属性系统故障诊断策略

田恒^1,2，许荣滨²，姜艳红³，张文虎¹，邓四二¹

（1.河南科技大学机电工程学院，河南洛阳 471003； 2.浙江五洲新春集团股份有限公司，浙江绍兴 312500；3.中浙高铁轴承有限公司，浙江衢州 324407）

上线日期:2022-05-21
通讯作者: 许荣滨（1968—），男，高级工程师 E-mail:xurongbin@xcc-zxz.com
作者简介:田恒（1988—），男，讲师，博士。E-mail:tianheng_1988@163.com
基金资助:
国家自然科学基金项目(52105182、51905152)；河南省高等学校重点科研项目（21A460011）；河南省科技攻关项目(222102240050)

Fault Diagnosis Strategy for Multi-valued Attribute System Based on a Discrete Particle Swarm Optimization Algorithm

TIAN Heng^1,2, XU Rongbin², JIANG Yanhong³, ZHANG Wenhu¹, DENG Si'er¹

(1. School of Mechatronics Engineering, Henan University of Science and Technology, Luoyang 471003, Henan, China; 2. Zhejiang XCC Group Co., Ltd., Shaoxing 312500, Zhejiang, China; 3. Zhongzhe High-speed Railway Bearing Co., Ltd., Quzhou 324407, Zhejiang, China)

Online:2022-05-21

摘要/Abstract

摘要： 针对传统离散粒子群优化（PSO）算法仅能搜索多值属性系统（MVAS）最小完备测试集的问题，通过重塑离散PSO算法，提出一种测试序列寻优算法—PSO-测试(TS)算法。在多值D矩阵和五元组的基础上，公式化处理MVAS的诊断策略。重塑离散粒子群的过程，将离散PSO算法与MVAS的故障诊断策略融合。设置PSO-TS算法的自身认知和社会知识阶段的计算规则，并通过引入交换序提升PSO-TS算法中粒子的多样性。采用实例和随机仿真实验验证PSO-TS算法。研究结果表明：与MV-Rollout和MV-IG算法相比，PSO-TS算法的期望测试费用少，能够获得较优的诊断策略，但是运行时间较长。

关键词: 多值属性系统, 离散粒子群优化算法, 诊断策略, 序贯诊断

Abstract: To solve the problem that the traditional discrete particle swarm optimization (DPSO) algorithm can only find the minimum complete test set for a multivalued attribute system (MVAS), particle swarm optimization for test sequencing (PSO-TS) algorithm is proposed. The diagnosis strategy for MVAS is formulated based on multi-valued D matrix and five-tuple. The implementation process of DPSO is remodeled, and DPSO algorithm is combined with the fault diagnosis strategy of MVAS. Subsequently, a set of calculation rules for self-cognition and the social knowledge are set, and the exchange order is introduced to increase particle diversity. The PSO-TS algorithm is verified using experiments and stochastic simulations. Compared with the MV-Rollout algorithm and MV-IG algorithm, the PSO-TS algorithm can obtain an optimal fault diagnosis strategy with a relatively lower expected test cost, but with a longer running time.

Key words: multi-valuedattributesystem, discreteparticleswarmalgorithm, diagnosisstrategy, sequentialfaultdiagnosis

中图分类号:

TP206

田恒，许荣滨，姜艳红，张文虎，邓四二. 基于离散粒子群优化算法的多值属性系统故障诊断策略[J]. 兵工学报, 2022, 43(12): 3240-3246.

TIAN Heng, XU Rongbin, JIANG Yanhong, ZHANG Wenhu, DENG Si'er. Fault Diagnosis Strategy for Multi-valued Attribute System Based on a Discrete Particle Swarm Optimization Algorithm[J]. Acta Armamentarii, 2022, 43(12): 3240-3246.

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基于离散粒子群优化算法的多值属性系统故障诊断策略

Fault Diagnosis Strategy for Multi-valued Attribute System Based on a Discrete Particle Swarm Optimization Algorithm

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