This paper proposes an enhanced faulty node detection method using interval weighting factor, which monitors node behavior using pseudo-random Bose-Chaudhuri-Hocquenghem (BCH) code for distributed networked control systems. Master node collects the replacement of the cyclic redundancy check (CRC) codes by a single-bit BCH code of each slave node. How ever, BCH code can only obtain error position of the suspected faulty node without consideration of channel nodes. Hence, suspected error nodes are saved within the detected error interval andnormalized using the weighting factor, which is carried out during sequential check, for interpretation. Fault judgement is carried outto adequately interpret the data, to guarantee detection accuracy of the detected error. The data is represented by statistical characteristic of the raw data and filtered data. This scheme can be appliedto detect and prevent the severe damage by node failure. The simulation results prove the effectiveness of the interval faulty weighting factor, in obtaining raw data from the monitoring of the BCH codeand filtered data, which are more accurate representation than the raw data. Moreover, the characteristics of the observed data were verified as the evaluation result of the suspected faulty node.

中文翻译：

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带有间隔加权因子的分布式系统增强的故障节点检测

本文提出了一种使用间隔加权因子的增强型故障节点检测方法，该方法使用伪随机Bose-Chaudhuri-Hocquenghemhem（BCH）代码监视分布式网络控制系统的节点行为。主节点收集每个从节点的一位BCH码对循环冗余校验（CRC）码的替换。但是，BCH代码只能获得可疑故障节点的错误位置，而无需考虑通道节点。因此，可疑错误节点将保存在检测到的错误间隔内，并使用权重因子进行归一化（在顺序检查期间执行）以进行解释。进行故障判断以充分解释数据，以确保检测到的错误的检测准确性。数据由原始数据和过滤后数据的统计特性表示。该方案可用于检测和防止节点故障造成的严重损害。仿真结果证明了区间错误加权因子在从BCH码监控中获取原始数据和滤波数据的有效性，比原始数据更准确地表示。此外，将观测数据的特征验证为可疑故障节点的评估结果。