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Multisensor cargo bay fire detection system

机译:多传感器货运湾火灾探测系统

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Current aircraft cargo bay fire detection systems are generally based on smoke detection. Smoke detectors in modern aircraft are predominately photoelectric particle detectors that reliably detect smoke, but also detect dust, fog, and most other small particles. False alarms caused by these contaminants can be very costly to the airlines because they can cause flights to be diverted needlessly. To minimize these expenses, a new approach to cargo bay fire detection is needed. This paper describes a novel fire detection system developed by the Goodrich Advanced Sensors Technical Center. The system uses multiple sensors of different technologies to provide a way of discriminating between real fire events and false triggers. The system uses infrared imaging along with multiple, distributed chemical sensors and smoke detectors, all feeding data to a digital signal processor. The processor merges data from the chemical sensors, smoke detectors, and processed images to determine if a fire (or potential fire) is present. Decision algorithms look at all this data in real-time and make the final decision about whether a fire is present. In the paper, we present a short background of the problem we are solving, the reasons for choosing the technologies used, the design of the system, the signal processing methods and results from extensive system testing. We will also show that multiple sensing technologies are crucial to reducing false alarms in such systems.
机译:目前飞机货舱火警探测系统一般基于烟雾探测。在现代飞机烟雾探测器主要光电粒子探测器可靠地检测烟雾,而且还检测灰尘,雾,和大多数其他小颗粒。造成这些污染物的误报可能是非常昂贵的航空公司,因为它们可能会导致被不必要改行航班。为了尽量减少这些费用,是需要货舱火警探测的新方法。本文介绍了由古德里奇先进的传感器技术中心开发了一种新型的火灾探测系统。该系统采用不同技术的多个传感器提供真火事件和假触发区分的一种方式。该系统采用具有多个沿红外成像,分布式化学传感器和烟雾探测器,所有馈送数据到一个数字信号处理器。从化学传感器,烟雾探测器,和处理过的图像处理器的合并数据,以确定是否发生火灾(或潜在的火灾)的存在。决策算法看,所有这些数据的实时,并就火灾是否存在最终决定。在本文中,我们提出我们正在解决这个问题的一个简短的背景,原因选择所使用的技术,系统设计,信号处理从广泛的系统测试方法和结果。我们还将展示多个传感技术是减少在这样的系统误报警的关键。

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