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Diagnosis and debugging of programmable logic controller control programs by neural networks

机译:神经网络对可编程控制器控制程序的诊断与调试

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Ladder logic diagram (LLD) as the interfacing programming language of programmable logic controllers (PLCs) is utilized in modern discrete event control systems. However, LLD is hard to debug and maintain in practice. This is due to many factors such as non-structured nature of LLD, the LLD programmers' background, and the huge sizes of real world LLD. In this paper, we introduce a recurrent neural network (RNN) based technique for PLC program diagnosis. A manufacturing control system example has been presented to illustrate the applicability of the proposed algorithm. This method could be very advantageous in reducing the complexity in PLC control programs diagnosis because of the ease of use of the RNN compared to debugging the LLD code.
机译:梯形逻辑图(LLD)作为可编程逻辑控制器(PLC)的接口编程语言,在现代离散事件控制系统中得到了利用。但是,实际上很难对LLD进行调试和维护。这是由于许多因素引起的,例如LLD的非结构化性质,LLD程序员的背景以及现实世界中LLD的庞大规模。在本文中,我们介绍了一种基于递归神经网络(RNN)的PLC程序诊断技术。给出了一个制造控制系统示例,以说明所提出算法的适用性。由于与调试LLD代码相比,RNN的易用性,该方法在降低PLC控制程序诊断的复杂度方面可能非常有利。

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