Abstract
The process of extracting gold by biological oxidation involves oxidizing the refractory high-sulfur and high-arsenic ore with the help of bacteria to decompose the wrapping material of gold to extract the gold. Therefore, maximizing the activity of bacteria will directly affect the efficiency of gold extraction, for which it is particularly important to maintain the pulp temperature in the oxidation tank at the optimal bacteria breeding temperature. However, gold mines are generally located in mountainous areas, and the large temperature difference between day and night in winter, coupled with the influence of wind and snow, creates variations in the temperature in the oxidation tank. The traditional temperature measurement method cannot fully reflect the temperature change of the oxidation tank. As a multi-field application method, sensor information fusion can effectively address the problem of pulp temperature measurement. First, we analyzed the heat transfer principle inside the oxidation tank, and designed the cluster hierarchical sensor network according to the spatial position of each oxidation tank and the environmental interference factors. The network structure is divided into three layers; the bottom of the sensor to collect pulp temperature data shows a spiral distribution in the inner wall of the oxidation tank. Each cluster head node sensor is used as an intermediate layer to complete local measurement fusion estimation. Finally, the fusion center is taken as the upper layer to realize the global state fusion estimation. Secondly, in the data processing of the bottom temperature sensor, the traditional unscented Kalman filter (UKF) algorithm is improved and the fading memory matrix is added to improve the identification of nonlinear modeling errors. The sequential observation fusion estimator (SOFE) algorithm is embedded in the measurement update to improve the performance of local measurement fusion. Finally, in the global state fusion estimation, the sequential analysis is combined with the inverse covariance intersection, and the sequential analysis and inverse covariance intersection-global state fusion estimation (SICI-GSFE) algorithm is proposed. Through calculation and simulation, the results show that the external interference can be reduced by combining all the temperature state estimations, and the accuracy of the best global temperature state estimation is improved.
Highlights
The versatility of low-cost wireless sensor networks and the diversity of multi-sensor fusion applications have aroused increasing research interest in the past decade, including for air target tracking and spacecraft navigation in military fields, and environment monitoring and video image processing in the civil field
The results show that the external interference can be reduced by combining all the temperature state estimations, and the accuracy of the best global temperature state estimation is improved
The goal of this research was to improve the accuracy of pulp temperature state estimation of Performance Index the primary oxidation tank in the oxidation gold extraction process to propose a clustered
Summary
The versatility of low-cost wireless sensor networks and the diversity of multi-sensor fusion applications have aroused increasing research interest in the past decade, including for air target tracking and spacecraft navigation in military fields, and environment monitoring and video image processing in the civil field. As a new technology in the process of extracting gold from refractory ores [1], biological oxidation pretreatment can expose gold through the pretreatment of gold inclusion by bacterial oxidation. Sensors 2020, 20, x FOR PEER REVIEW activity, activity, and temperature is an important factor factor affecting bacterial activity and and reproduction [2]. Research on using wireless sensor networks to monitor the temperature parameters in the [2]. Research on using wireless sensor networks to monitor the temperature parameters in biological oxidation gold gold extraction process to improve the accuracy is needed. Biological oxidation the biological oxidation extraction process to improve the accuracy is The needed. 1: The interior of the dotted line is primary oxidation and the oxidation pretreatment process is shown in Figure 1: The interior of the dotted line is primary structure adopts No.
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