BS ISO 13379-2:2015给出了实施数据驱动监测和诊断方法的程序 促进通常位于监测中心的专业人员进行的分析工作。尽管一些步骤已经嵌入到现有的工具中，但必须注意以下几点 最佳使用步骤:选择资产、关键故障和可用工艺参数；数据清理和重采样；模型开发；模型初始化和调整；模型绩效评估；诊断过程。这些步骤的实施不需要对统计方法有透彻的了解。它确实需要能力，首先建立培训模型，然后进行监控和评估 诊断过程。数据驱动监控培训是在表现出正常行为的设备上进行的。在这种情况下，故障检测的原则是将观测数据与估计数据进行比较。 区别 （称为残差）在参数的观测值和预期值之间显示 异常现象，可能与设备或仪器有关。数据驱动诊断方面的培训是在显示正常的设备上进行的 行为和失败。该方法的原理不是检测参数的偏差，而是 通过将观察到的情况与培训阶段学习到的故障进行比较，识别故障。通常采用的技术是模式识别，然后是模式分类。数据可从分布式控制系统（DCS）的数据历史记录程序或专业数据库获取 监控系统。交叉引用:ISO 13372ISO 13379-1ISO 17359:2011取代了BS ISO 13379:2003，该标准仍然有效。购买本文件时，所有当前可用的修订均包含在购买本文件中。

BS ISO 13379-2:2015 gives procedures to implement data-driven monitoring and diagnostic methods to facilitate the work of analysis carried out by specialist staff typically located in a monitoring centre.Although some of the steps are embedded in existing tools, it is essential to be aware of the following steps for optimum use:selection of the asset, the critical failures and the available process parameters;data cleaning and resampling;model development;model initialization and tuning;model performance evaluation;diagnostics process.The implementation of these steps does not require a thorough knowledge of the statistical methods.It does require the competence first to build the training models and then to carry out monitoring and diagnostics processes.The training in data-driven monitoring is carried out on equipment that is exhibiting normal behaviour.In that case, the principle of fault detection is to compare observed data to estimated data. A difference (called residuals) between an observed and expected values of the parameters reveals the presence of an anomaly, which can be related either to equipment or instrument.The training in data-driven diagnosis is carried out both on equipment that is exhibiting normal behaviour and failures. The principle of the method is not to detect the deviation of a parameter but to identify a fault by comparison of the observed situation to the faults learnt during the training phase.The technique usually applied is pattern recognition followed by pattern classification.Data can be available from the data historian of the distributed control system (DCS) or from specialized monitoring systems.Cross References:ISO 13372ISO 13379-1ISO 17359:2011Replaces BS ISO 13379:2003 which remains currentAll current amendments available at time of purchase are included with the purchase of this document.