Real-Time Weighted Data Fusion Algorithm for Temperature Detection Based on Small-Range Sensor Network

Biological oxidation pretreatment, which can improve the yield of gold, is the main gold extraction technology for disposing refractory gold ore with high arsenic and sulfur. The temperature of the oxidation tank influences the oxidation efficiency between the ore pulp and bacteria, including the yi...

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Veröffentlicht in:Sensors (Basel, Switzerland) Jg. 19; H. 1; S. 64
Hauptverfasser: Zhang, Ziling, Nan, Xinyuan, Wang, Cong
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Switzerland MDPI AG 25.12.2018
MDPI
Schlagworte:
Accuracy
Algorithms
distributed sensor fusion
Electricity distribution
Engineering
Fuzzy sets
Humidity
Information technology
International conferences
iterative operation
Kalman filters
Monitoring systems
multi-fading factor
Sensors
small-range sensor network
weighted fading memory index
Wireless networks
Beijing China
China
distributed sensor fusion
small-range sensor network
multi-fading factor
weighted fading memory index
iterative operation
ISSN:1424-8220, 1424-8220
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Zusammenfassung:Biological oxidation pretreatment, which can improve the yield of gold, is the main gold extraction technology for disposing refractory gold ore with high arsenic and sulfur. The temperature of the oxidation tank influences the oxidation efficiency between the ore pulp and bacteria, including the yield of gold. Therefore, measurement has consistently been an important subject for researchers. As an effective data processing method, data fusion has been used extensively in many fields of industrial production. However, the interference of equipment or external factors such as the diurnal temperature difference or powerful wind may constantly increase measurement errors and damage certain sensors, which may transmit error data. These problems can be solved by following a pretreatment process. First, we establish a heat transfer mechanism model. Second, we design a small-range sensor network for the pretreatment process and present a layered fusion structure of sharing sensors using a multi-connected fusion structure. Third, we introduce the idea of iterative operation in data processing. In addition, we use prior data for predicting state values twice in order to improve the effectiveness of extended Kalman filtering in one time step. This study also proposes multi-fading factors on the basis of a weighted fading memory index to adjust the prediction error covariance. Finally, the state estimation accuracy of each sensor can be used as a weighting principle for the predictive confidence of each sensor by adding a weighting factor. In this study, the performance of the proposed method is verified by simulation and compared with the traditional single-sensor method. Actual industrial measurement data are processed by the proposed method for the equipment experiment. The performance index of the simulation and the experiment shows that the proposed method has a higher global accuracy than the traditional single-sensor method. Simulation results show that the accuracy of the proposed method has a 55% improvement upon that of the traditional single-sensor method, on average. In the equipment experiment, the accuracy of the industrial measurement improved by 37% when using the proposed method.
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ISSN:1424-8220
1424-8220
DOI:10.3390/s19010064