Abstract
Aiming at the high false alarm rate when using single sensor to detect fire in aircraft cabin, a multisensor data fusion method is proposed to detect fire. First, the weights of multiple factors, that is, temperature, smoke concentration, CO concentration, and infrared ray intensity in the event of fire, were calculated by using the improved analytic hierarchy process (AHP) method on each sensor node of wireless sensor network, and the probability of fire event in the cabin was evaluated by multivariable-weighted fusion method. Second, based on the mutual support among the evaluation data of fire probabilities of each node, the adaptive weight coefficient is assigned to each evaluation value, and the weighted fusion of all evaluation values of each node is conducted to obtain the fire probability. In the end, compared to the threshold of probability, the fire alarm is determined. Comparing the proposed algorithm to the grey fuzzy neural network fusion algorithm and fuzzy logic fusion algorithm in terms of the time consumption for fire detection and sending alarm and the accuracy of fire alarm perspectives, the experiments demonstrate that the proposed fire detection algorithm can detect the fire within 10s and reduce the false alarm rate to less than 0.5%, which verifies the superiority of the algorithm in promptness and accuracy. In the meanwhile, the fault tolerance of the algorithm is proved as well.
Highlights
It is well known that safety is always the priority for aircrafts flights; fire is a big threat for flight safety. erefore, fire detection issues for aircrafts have become the focus for aircraft environmental monitoring
WSN-based multisensor indoor fire detection technology usually uses the data detected by multiple sensors to fuse and obtain the probability of fire event, which greatly improves the accuracy of fire alarms
Online and offline fire event detection processes, are included in the proposed algorithm for aircraft cabins in the paper. e specific steps are listed in ird, use the adaptive-weighted fusion algorithm to calculate the actual fire probability pk in the aircraft and compare it with the threshold probability to determine whether a fire alarm is released or not (Figure 1)
Summary
It is well known that safety is always the priority for aircrafts flights; fire is a big threat for flight safety. erefore, fire detection issues for aircrafts have become the focus for aircraft environmental monitoring. WSN-based multisensor indoor fire detection technology usually uses the data detected by multiple sensors to fuse and obtain the probability of fire event, which greatly improves the accuracy of fire alarms. In order to shorten the fusion time to some extent, the weight of each fusion variable in the probability assessment of fire event can be considered; the sensor data can be estimated. This paper develops an adaptive-weighted fusion method to fuse the multiple variables for each sensor node when some sensors malfunction. By constructing the support degree matrix as the adaptive distribution weight coefficient of each node, to a certain extent, the proposed method avoids the low fusion accuracy due to the measurement deviation coming from the faulty sensors.
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