Development and Trend of Research on Fault Diagnosis Methods for Ammunition Loading System

doi:10.12382/bgxb.2024.0506

Abstract

Abstract:

The ammunition loading system is the key system to realize the automation of artillery. The system has a high level of complexity due to the tight coupling among its mechanical, electrical and hydraulic subsystems. The harsh operating environment results in the increased failure rate and reduced reliability of ammunition loading system, which in turn affects the overall performance of the artillery. Given these influences on system functionality, the focused research into fault diagnosis methods is of particular importance. Therefore, this study focuses on the ammunition loading system, analyzes the characteristics of faults in the ammunition loading system, and summarizes the typical fault analysis methods for the system. The study also provides an overview of the research progress and existing problems in the fault diagnosis methods for ammunition loading system. In addition, the development and application of current fault diagnosis technologies provide effective approaches to improve the reliability of ammunition loading system. By understanding the research progress of multi-domain fault diagnosis methods, this paper discusses the future development trends of fault diagnosis technologies for the ammunition loading system, summarizes the individual factors influencing the research on fault diagnosis of ammunition loading system, and provides a research perspective for future exploration.

Key words: artillery, ammunition loading system, fault analysis, fault diagnosis, prognostics and health management

CLC Number:

TJ30

WANG Bin, XU Yadong, WANG Liangkuan. Development and Trend of Research on Fault Diagnosis Methods for Ammunition Loading System[J]. Acta Armamentarii, 2024, 45(11): 3765-3780.

Figures/Tables 13

References 88

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故障现象	主要故障模式
协调机构动作缓慢	液压油缸内泄漏,内部进入空气,或内部有磨损
	液压泵体泄漏或泵体内零件损坏严重,导致系统压力和流量降低
	伺服阀阀芯与阀套间隙变小,启动摩擦大,导致响应时间变长
	连接油管泄漏
协调机构动作不到位	协调机构零件磨损、变形
协调机构动作不到位	液压油缸内泄漏
协调机构无法动作	伺服阀放大器内元件损坏
协调机构无法动作	测角器、编码器等元器件损坏,无控制指令信号传输
摆弹机构动作缓慢	液压泵泵体异常,系统压力低
摆弹机构动作缓慢	液压油缸泄漏
摆弹机构无法动作	控制元件故障无指令传输
输弹机构动作缓慢	输弹链条卡滞、磨损,链轮与链条装配有误
	液压伺服阀阀芯损坏
	液压油缸泄漏,油缸内部进入空气
	液压系统压力低
输弹机构无法动作	控制元件、传感器损坏,无指令传输
输弹机构无法动作	伺服阀无法正常工作

故障现象	主要故障模式
协调机构动作缓慢	液压油缸内泄漏,内部进入空气,或内部有磨损
	液压泵体泄漏或泵体内零件损坏严重,导致系统压力和流量降低
	伺服阀阀芯与阀套间隙变小,启动摩擦大,导致响应时间变长
	连接油管泄漏
协调机构动作不到位	协调机构零件磨损、变形
协调机构动作不到位	液压油缸内泄漏
协调机构无法动作	伺服阀放大器内元件损坏
协调机构无法动作	测角器、编码器等元器件损坏,无控制指令信号传输
摆弹机构动作缓慢	液压泵泵体异常,系统压力低
摆弹机构动作缓慢	液压油缸泄漏
摆弹机构无法动作	控制元件故障无指令传输
输弹机构动作缓慢	输弹链条卡滞、磨损,链轮与链条装配有误
	液压伺服阀阀芯损坏
	液压油缸泄漏,油缸内部进入空气
	液压系统压力低
输弹机构无法动作	控制元件、传感器损坏,无指令传输
输弹机构无法动作	伺服阀无法正常工作

方法	介绍	应用
故障模式和影响分析	一种“自上而下”的分析方法,用于产品设计和开发阶段的可靠性研究,可以预防性地确定零件的缺陷状况^[9],更适合局部故障分析	文献 [9⇓-11]
故障树分析	侧重于定量分析,通过树状图展示故障事件的逻辑关系,并计算顶事件发生的概率,顶事件选择主观性强	文献 [12-13]
故障模式、影响及危害性分析	不仅关注故障模式对系统的影响,还关注故障模式的严重性,定量和定性分析相结合,分析工作量大	文献 [14⇓-16]
虚拟样机建模分析	利用计算机仿真技术,将系统建模为虚拟样机,模拟系统运行过程中可能出现的各种故障情况	文献 [17⇓⇓⇓⇓-22]

方法	介绍	应用
故障模式和影响分析	一种“自上而下”的分析方法,用于产品设计和开发阶段的可靠性研究,可以预防性地确定零件的缺陷状况^[9],更适合局部故障分析	文献 [9⇓-11]
故障树分析	侧重于定量分析,通过树状图展示故障事件的逻辑关系,并计算顶事件发生的概率,顶事件选择主观性强	文献 [12-13]
故障模式、影响及危害性分析	不仅关注故障模式对系统的影响,还关注故障模式的严重性,定量和定性分析相结合,分析工作量大	文献 [14⇓-16]
虚拟样机建模分析	利用计算机仿真技术,将系统建模为虚拟样机,模拟系统运行过程中可能出现的各种故障情况	文献 [17⇓⇓⇓⇓-22]

方法	原理	扩展研究	应用
基于ES的故障诊断方法	ES具有模拟人类专家在其专业领域以专家思维解决复杂问题的能力,通过知识库和推理能力来提供决策支持,核心是知识表示和规则推理^[30]	引入案例的ES、基于框架的ES、引入模糊逻辑的ES、引入D-S证据理论的ES、引入人工神经网络和遗传算法的ES	文献 [31⇓⇓⇓-35]
基于信号处理的故障诊断方法	对供输弹系统开展故障诊断工作时,先采集多源信号,利用时域、频域、时频域分析方法对测试信号进行必要的分析和处理,为诊断推理和判别故障提供依据^[36]	引入图像特征、信息论、频响特性等	文献 [38⇓⇓-41]
基于数据驱动的故障诊断方法	通常依赖大量的传感器数据,通过机器学习和人工智能技术,对数据进行分析和学习,从大量复杂的数据中提取有用的信息,识别出不易察觉的故障模式^[42]	结合信号处理方法、迁移学习、BP神经网络、压缩感知等	文献 [43⇓⇓⇓⇓⇓⇓⇓-51]