Failure diagnosis is a crucial task in modern industrial systems, and several works in the literature address this problem by modeling the system as a Discrete-Event System (DES). Most of them assume perfect communication between sensors and diagnosers, i.e., no loss of observation of events, or event communication delays between the measurement sites and the diagnosers. However, industrial systems can be large and physically distributed, in which cases, communication networks are used to provide an efficient way to establish communication between devices. In diagnosis systems, the use of networks can introduce delays in the communication of event occurrences from measurement sites to the local diagnosers, leading to an incorrect observation of the order of occurrence of events generated by the system and, as a consequence, to an incorrect diagnosis decision by the local diagnoser. In this paper, we address the problem of decentralized diagnosis of networked Discrete-Event Systems subject to event communication delays, and we introduce the definition of network codiagnosability of the language generated by a DES subject to both event communication delays and intermittent loss of observation, and present necessary and sufficient conditions for a language to be network codiagnosable, for short. We also propose an algorithm to verify this property.

中文翻译：

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受通信延迟和间歇性观察丢失影响的网络离散事件系统的可共同诊断性

故障诊断是现代工业系统中的一项关键任务，文献中的一些工作通过将系统建模为离散事件系统 (DES) 来解决这个问题。他们中的大多数假设传感器和诊断人员之间的通信完美，即没有丢失事件观察，或测量站点和诊断人员之间的事件通信延迟。然而，工业系统可能很大，而且物理上是分布式的，在这种情况下，通信网络被用来提供一种在设备之间建立通信的有效方式。在诊断系统中，网络的使用会在从测量站点到本地诊断人员的事件发生通信中引入延迟，导致对系统生成的事件发生顺序的错误观察，因此，本地诊断人员做出错误的诊断决定。在本文中，我们解决了受事件通信延迟影响的网络离散事件系统的分散诊断问题，并介绍了受事件通信延迟和间歇性观察丢失影响的 DES 生成的语言的网络可诊断性定义，简而言之，为一种语言可被网络共同诊断提供必要和充分条件。我们还提出了一种算法来验证此属性。并且我们介绍了由 DES 生成的语言的网络可诊断性的定义，该语言受事件通信延迟和间歇性观察丢失的影响，并简要地提出了语言可网络可诊断性的充分必要条件。我们还提出了一种算法来验证此属性。并且我们介绍了由 DES 生成的语言的网络可诊断性的定义，该语言受事件通信延迟和间歇性观察丢失的影响，并简要地提出了语言可网络可诊断性的充分必要条件。我们还提出了一种算法来验证此属性。