An Initial Alignment Technology of Shearer Inertial Navigation Positioning Based on a Fruit Fly-Optimized Kalman Filter Algorithm

The shearer is one of the core equipment of the fully mechanized coal face. The fast and accurate positioning of the shearer is the prerequisite for its memory cutting, intelligent height adjustment, and intelligent speed adjustment. Inertial navigation technology has many advantages such as strong autonomy, good concealment, and high reliability. The accurate positioning of the shearer based on inertial navigation can not only determine its operating position but also measure the direction of movement. However, when inertial navigation is used to locate the shearer in motion, the cumulative errors will occur, resulting in inaccurate positioning of the shearer. The accuracy of the initial alignment is directly related to the working precision of the inertial navigation system. In order to improve the efficiency and accuracy of initial alignment, an improved initial alignment method is proposed in this paper, which uses a fruit fly-optimized Kalman filter algorithm for initial alignment. In order to improve the filtering performance, the fruit fly-optimized Kalman filter algorithm uses an improved fruit fly algorithm to realize the adaptive optimization of system noise variance. Finally, simulation and experiments verify the effectiveness of the fruit fly-optimized Kalman filter algorithm.

An Improved Genetic Fuzzy Logic Control Method to Reduce the Enlargement of Coal Floor Deformation in Shearer Memory Cutting Process

In order to reduce the enlargement of coal floor deformation and the manual adjustment frequency of rocker arms, an improved approach through integration of improved genetic algorithm and fuzzy logic control (GFLC) method is proposed. The enlargement of coal floor deformation is analyzed and a model is built. Then, the framework of proposed approach is built. Moreover, the constituents of GA such as tangent function roulette wheel selection (Tan-RWS) selection, uniform crossover, and nonuniform mutation are employed to enhance the performance of GFLC. Finally, two simulation examples and an industrial application example are carried out and the results indicate that the proposed method is feasible and efficient.

Research on the Memory Cutting Model of Shearer

Automatic" and "less people" in fully mechanized working face is the target of China's coal industry development, and the key to achieve this goal is the automation of coal mining. According to the previous technology of memory cutting cannot adapt to the complicated geological condition in China, this paper proposed the technology of shearer self-adaptive memory cutting based on fuzzy control theory, the shearer positioning system and fuzzy control system of self-adaptive cutting. These systems can get the message of shearer's position and attitude at any point, trace the memorial cutting path automatically, judge whether the shearer cuts rocks based on fuzzy control theory and find the optimal scheme when it works. The authors make the experiments of path tracing in laboratory and the experiment of shelf-adaptive adjust in Xi'an Coal Mining Machinery. All the experimental results show that this technology not only can realize the shearer memory cutting, but also can discriminate the abnormal state of shearer cutting rocks, then adjust the drawing speed and drum height automatically.

Research on the Cutting Path Planning of Shearer Based on Expert System

According to the characteristics of shearer working environment and cutting work, on the base of analyze the working principle of shearer working, use the expert system theory to achieve cutting path planning. Used rule-based knowledge representation, adopted PROLOG language to compile the path planning network, knowledge acquisition used the design method based on rule skeleton and rule body and generated shearer cutting path planning knowledge base, through modifying the internal predicates can be easily achieved the knowledge base modify, storage and maintenance. Experimented in the model of MG900/2210 electrical haulage shearer 1:6 prototype, the experimental results showed that the cutting path planning can effectively improve the working reliability of shearer, by combining with human-machine interaction and remote path correction to solve the problem which can’t be solved through memory cutting and drum automatic adjustment height.