计算机集成制造系统 ›› 2015, Vol. 21 ›› Issue (第11期): 2869-2884.DOI: 10.13196/j.cims.2015.11.006

• 产品创新开发技术 • 上一篇    下一篇

复杂机械产品装配过程质量门监控系统与关键技术

王小巧,刘明周,葛茂根,凌琳,马靖,刘从虎   

  1. 合肥工业大学机械与汽车工程学院
  • 出版日期:2015-11-30 发布日期:2015-11-30
  • 基金资助:
    国家973计划资助项目(2011CB013406)。

Quality gates monitoring system and key technologies for assembly process of complex mechanical products

  • Online:2015-11-30 Published:2015-11-30
  • Supported by:
    Project supported by the National Basic Research Program,China(No.2011CB013406).

摘要: 为及时甄别出复杂机械产品装配过程中的质量问题,提出一种质量门监控系统。分析了复杂机械产品装配流程及特点,提出装配过程质量门控制方法,并定义了质量门的内涵。研究了装配过程质量主动控制的体系架构,构建了一套使能装配过程质量控制的系统和关键技术,包括质量门资源标识和主动感知技术、质量门监控和数据采集技术、基于分层推理的专家知识系统、基于状态空间模型的装配误差分析技术、动态工序能力分析、基于粒子群优化算法的误差逆传播神经网络的分层装配性能预测、基于机器视觉的防误技术。应用J2EE构架开发了某型发动机的装配过程质量门监控系统,验证了该方法的可行性和有效性。

关键词: 复杂机械产品, 质量门监控系统, 装配质量主动控制, 专家系统, 装配误差, 装配性能预测

Abstract: To screen the quality problem timely in complex mechanical product assembly process,a quality gates monitoring system was put forward.The complex mechanical product assembly process and characteristics were analyzed,the Quality gate (Q-gate) method for controlling the assembly process quality was proposed,and the meaning of Q-gate was defined.The overall architecture of quality active control for assembly process was researched,and the assembly process quality gates monitoring system for complex mechanical products assembly was presented.Under this architecture,the key technologies included Q-gate resource identification and multi-source information sensing technology,Q-gate monitor and control and data collection technology,expert system based on hierarchical reasoning,technology of assembly error analysis based on state space model,dynamic analysis of process capability,hierarchical assembly performance prediction based on PSO-BP neural network,error prevention based on machine vision technology.An example of assembly process quality gates monitoring system in assembly process of the engine was given and developed with J2EE framework to demonstrate the feasibility and effectiveness of the proposed method.

Key words: complex mechanical products, quality gate monitor and control system, assembly quality active control, expert system, assembly error, assembly performance prediction

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