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Automatic validation of vibration signals in wind farm distributed monitoring systems

机译:在风电场分布式监控系统中自动验证振动信号

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A rapid growth of wind farms as a leading renewable energy sector has compelled a number of companies to develop dedicated distributed systems of monitoring and diagnosis (SM&D). Such systems are capable of early mechanical faults detection, which prevents from costly critical repairs. Fault detection of wind turbines is based on vibration and process signals analysis. Modern SM&D are usually advanced hardware and software technological products, which on the basis of collected data are capable of continuous execution of enormous number of analyses. However, the expansion of distributed systems has disclosed new challenges accompanying the transition from a singular signal analysis to automatic interpretation of large data sets. The paper deals with the assessment of data acquisition final products, namely the correctness of vibration signals recording process. The proposed validation, which is to be implemented a priori to data analysis, is required for significant calculation of any signal features as well as for legitimate storage of raw waveforms in the system database. The latter aspect is especially important in terms of gigabytes of disk space frequently wasted for corrupted data. The paper presents a step-by-step method for automatic signal validation, which can be implemented on a personal computer. Finally, the algorithm is evaluated on a real wind turbine database.
机译:作为领先的可再生能源行业,风电场的快速发展迫使许多公司开发专用的分布式监测和诊断系统(SM&D)。这种系统能够及早发现机械故障,从而避免进行昂贵的重大维修。风力涡轮机的故障检测基于振动和过程信号分析。现代SM&D通常是先进的硬件和软件技术产品,它们在收集的数据的基础上能够连续执行大量分析。然而,随着从单一信号分析到大型数据集的自动解释的过渡,分布式系统的扩展已经揭示了新的挑战。本文主要对数据采集最终产品进行评估,即振动信号记录过程的正确性。要对任何信号特征进行大量计算以及将原始波形合法存储在系统数据库中,都需要进行建议的验证,该验证将在数据分析之前进行。对于经常被损坏的数据浪费的GB磁盘空间,后一个方面尤其重要。本文提出了一种自动信号验证的分步方法,该方法可以在个人计算机上实现。最后,在真实的风力涡轮机数据库上评估该算法。

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