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Intelligent Fault-Diagnosis System for Acoustic Logging Tool Based on Multi-Technology Fusion

机译:基于多技术融合的声波测井仪智能故障诊断系统

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摘要

To improve the performance of acoustic logging tool in detecting three-dimensional formation, larger and more complicated transducer arrays have been used, which will greatly increase the difficulty of fault diagnosis during tool assembly and maintenance. As a result, traditional passive diagnostic methods become inefficient, and very skilled assemblers and maintainers are required. In this study, fault-diagnosis requirement for the acoustic logging tool at different levels has been analyzed from the perspective of the tool designer. An intelligent fault-diagnosis system consisting of a master-slave hardware architecture and a systemic diagnosis strategy was developed. The hardware system is based on the embedded technology, while the diagnosis strategy is built upon fault-tree analysis and data-driven methods. Diagnostic practice shows that this intelligent system can achieve four levels of fault diagnosis for the acoustic logging tool: System, subsystem, circuit board, and component. This study provided a more rigorous and professional fault diagnosis during tool assembly and maintenance. It is expected that this proposed method would be of great help in achieving cost reduction and improving work efficiency.
机译:为了提高声波测井仪检测三维构造的性能,使用了更大,更复杂的换能器阵列,这将大大增加工具组装和维护过程中故障诊断的难度。结果,传统的被动诊断方法变得效率低下,并且需要非常熟练的组装者和维护者。在这项研究中,从工具设计者的角度分析了不同级别的声波测井仪的故障诊断要求。开发了由主从硬件架构和系统诊断策略组成的智能故障诊断系统。硬件系统基于嵌入式技术,而诊断策略则基于故障树分析和数据驱动方法。诊断实践表明,该智能系统可以对声波测井工具实现四个级别的故障诊断:系统,子系统,电路板和组件。这项研究为工具组装和维护过程中的故障提供了更为严格和专业的诊断。预期该提议的方法将对降低成本和提高工作效率有很大帮助。

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