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首页> 外文会议>Computers and information in engineering conference >A FUNCTIONAL MODELLING BASED METHODOLOGY FOR TESTING THE PREDICTIONS OF FAULT DETECTION AND IDENTIFICATION SYSTEMS
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A FUNCTIONAL MODELLING BASED METHODOLOGY FOR TESTING THE PREDICTIONS OF FAULT DETECTION AND IDENTIFICATION SYSTEMS

机译：基于功能建模的测试方法，用于测试故障检测和识别系统的预测

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摘要

Fault detection and identification (FDI) systems, which are based on data mining and artificial intelligence techniques, cannot guarantee a perfect success rate or provide analytical proof for their predictions. This characteristic is problematic when such an FDI system is monitoring a safety-critical process. In these cases, the predictions of the FDI system need to be verified by other means, such as tests on the process, to increase trust in the diagnosis. This paper contributes an extension of the Hierarchical Functional Fault Detection and Identification (HFFDI) system, a combination of a plant-wide and multiple function-specific FDI modules, developed in past research. A test preparation and test-based verification phase is added to the HFFDI methodology. The functional decomposition of the process and the type of the faulty components guides the preparation of specific tests for every fault to be identifiable by the HFFDI system. These tests have the potential to confirm or disprove the existence of the fault(s) in the target process. The target is minor automation faults in redundant systems of the monitored process. The proposed extension of the HFFDI system is applied to a case study of a generic Nuclear Power Plant model. Two HFFDI predictions are tested (a successful and an incorrect prediction) in single fault scenarios and one prediction is tested in a in a two fault scenario. The results of the case study show that the testing phase introduced in this paper is able to confirm correct fault predictions and reject incorrect fault predictions, thus the HFFDI extension presented here improves the confidence of the HFFDI output.
机译：基于数据挖掘和人工智能技术的故障检测和识别（FDI）系统无法保证完美的成功率或为其预测提供分析证据。当这种FDI系统监视安全关键过程时，该特性是有问题的。在这些情况下，需要通过其他方式验证FDI系统的预测，例如对过程的测试，以增加对诊断的信任。本文有助于扩展分层功能故障检测和识别（HFFDI）系统，在过去的研究中开发的植物范围和多种功能特定的FDI模块的组合。将测试制剂和基于测试的验证阶段添加到HFFDI方法中。该过程的功能分解和故障组件的类型指导为HFFDI系统识别每个故障的特定测试的制备。这些测试有可能确认或反驳目标过程中的故障存在。目标是受监控过程的冗余系统中的小型自动化故障。拟议的HFFDI系统的延伸适用于通用核电站模型的案例研究。在单个故障场景中测试两个HFFDI预测（成功和不正确的预测），在两个故障方案中测试了一个预测。案例研究结果表明，本文中引入的测试阶段能够确认正确的故障预测并拒绝不正确的故障预测，因此此处提出了HFFDI输出的置信度。

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