As key components of low-cost sensor systems in air quality monitoring, electrochemical gas sensors have recently received a lot of interest but suffer from unit-to-unit variability and different drift components such as aging and concept drift, depending on the calibration approach. Magnitudes of drift can vary across sensors of the same type, and uniform recalibration intervals might lead to insufficient performance for some sensors. This publication evaluates the opportunity to perform predictive maintenance solely by the use of calibration data, thereby detecting the optimal moment for recalibration and improving recalibration intervals and measurement results. Specifically, the idea is to define confidence regions around the calibration data and to monitor the relative position of incoming sensor signals during operation. The emphasis lies on four algorithms from unsupervised anomaly detection—namely, robust covariance, local outlier factor, one-class support vector machine, and isolation forest. Moreover, the behavior of unit-to-unit variability and various drift components on the performance of the algorithms is discussed by analyzing published field experiments and by performing Monte Carlo simulations based on sensing and aging models. Although unsupervised anomaly detection on calibration data can disclose the reliability of measurement results, simulation results suggest that this does not translate to every sensor system due to unfavorable arrangements of baseline drifts paired with sensitivity drift.

中文翻译：

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低成本电化学传感器系统在空气质量监测中的预测性维护中漂移组件和单元间可变性的相关性

作为...的关键组成部分 在空气质量监测中的低成本传感器系统中，电化学气体传感器近来引起了广泛关注，但由于校准方法的不同，单元间的可变性以及诸如老化和概念漂移之类的不同漂移成分也受到了影响。同一类型的传感器的漂移幅度可能会有所不同，并且统一的重新校准间隔可能会导致某些传感器的性能不足。该出版物评估了仅通过使用校准数据执行预测性维护的机会，从而检测了重新校准的最佳时刻，并改善了重新校准间隔和测量结果。具体而言，该想法是在校准数据周围定义置信区域，并在操作期间监视传入传感器信号的相对位置。重点放在来自无监督异常检测的四种算法上，即鲁棒协方差，局部离群因子，一类支持向量机和隔离林。此外，通过分析已公开的现场实验并基于感测和老化模型执行蒙特卡洛模拟，讨论了单元间可变性和各种漂移成分对算法性能的影响。尽管对校准数据进行无监督的异常检测可以揭示测量结果的可靠性，但模拟结果表明，由于基线漂移与灵敏度漂移的组合不当，这不能转化为每个传感器系统。通过分析公开的现场实验并基于感测和老化模型执行蒙特卡洛模拟，讨论了单元间可变性和各种漂移成分对算法性能的影响。尽管对校准数据进行无监督的异常检测可以揭示测量结果的可靠性，但模拟结果表明，由于基线漂移与灵敏度漂移的组合不当，这不能转化为每个传感器系统。通过分析公开的现场实验并基于感测和老化模型执行蒙特卡洛模拟，讨论了单元间可变性和各种漂移成分对算法性能的影响。尽管对校准数据进行无监督的异常检测可以揭示测量结果的可靠性，但模拟结果表明，由于基线漂移与灵敏度漂移的组合不当，这不能转化为每个传感器系统。