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A Cuscore Statistic for Monitoring Degradation Paths

机译：用于监视降级路径的Cuscore统计信息

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The main objective of modeling the degradation path of a device is to predict its eventual time-to-failure. When a system is operated on-field, abrupt and unexpected changes in ambient conditions could potentially cause deviations from the expected degradation riath, such as an acceleration to a state of failure. Previous estimates of lifetime distributions become inaccurate because the fitted model may no longer be a satisfactory representation of the degradation path. This paper shows the application of a Cuscore statistic to detect a dojvnward shift in the gradient of a deterministic trend buried in autocorrelated noise. The proposed diagnostic methodology finds an application in monitoring the natural degradation of solar photovoltaic modules installed on-field.
机译：对设备的降级路径进行建模的主要目的是预测其最终的故障时间。当系统在现场运行时，周围环境的突然和意外变化可能会导致与预期退化范围的偏离，例如加速到故障状态。寿命分布的先前估计变得不准确，因为拟合的模型可能不再是退化路径的令人满意的表示。本文显示了Cuscore统计量在检测掩埋在自相关噪声中的确定性趋势的梯度中的下移的应用。提出的诊断方法论可用于监测现场安装的太阳能光伏组件的自然退化。

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