In order to research the identification methods for shearer cutting status,
some relevant patents and scientific references are studied and analyzed. A new
method based on the integration of particle swarm optimization (PSO) and support
vector data description (SVDD) is proposed to identify the shearer cutting status. The PSO is provided to solve the constraint
optimization problem of SVDD. Some key technologies are proposed to balance the search ability and enhance the
population diversity of PSO, and the flowchart of proposed method is designed. Furthermore, some simulation examples
are carried out and the compared results indicate that the proposed method is feasible and efficient. Finally, an industrial
application example of coal mining face is demonstrated to specify the effect of proposed system.
Keywords: Dissipative operation, identification method, inertia weight, particle swarm optimization algorithm, shearer cutting
status, support vector data description.
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