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Fire detection using a gas sensor array with sensor fusion algorithms

机译:使用带有传感器融合算法的气体传感器阵列的火灾探测

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Conventional fire alarms are based on smoke detection. Nevertheless, in some fire scenarios volatiles are released before smoke. Fire detectors based only on chemical sensors have already been proposed as they may provide faster response, but they are still prone to false alarms in the presence of nuisances. These systems rely heavily on pattern recognition techniques to discriminate fires from nuisances. In this context, it is important to test the systems according to international standards for fires and testing the system against a diversity of nuisances. In this work, we investigate the behavior of a gas sensor array coupled to sensor fusion algorithms for fire detection when exposed to standardized fires and several nuisances. Results confirmed the ability to detect fires (97% Sensitivity), although the system still produces a significant rate of false alarms (35%) for nuisances not presented in the training set.
机译:传统的火警基于烟雾检测。尽管如此,在一些火灾情景中,挥发物在烟雾前释放。仅基于化学传感器的消防探测器已经提出,因为它们可以提供更快的反应,但它们仍然在存在滋扰的情况下容易出现误报。这些系统严重依赖于模式识别技术,以区分滋扰的火灾。在这种情况下,重要的是根据国际标准测试系统,并针对滋扰的多样性测试系统。在这项工作中,我们调查气体传感器阵列的行为,耦合到传感器融合算法,以便在暴露于标准化的火灾时进行火灾探测和若干滋扰。结果证实了检测火灾(97 %的灵敏度)的能力,尽管系统仍然产生训练集未呈现的滋扰的误报(35 %)。

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