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Due to the speed data distortion caused by the surface factor and measuring environment of the steel plate in the process of the steel plate length measurement using Laser Doppler Velocimetry, a data processing model of steel plate velocity measurement based on BP neural network which optimized by L-M has been designed. Adjust The BP network structure and parameters through analyzing the Doppler velocity data. Then the velocity data are adaptive nonlinear fitting based on the error back propagation theory and so correct the gross errors. Finally calculate the steel plate length accurately. Compared with LS, the results of the experiment show that this method can correct the fuzzy data more accurately. Results of field operation indicate that the steel plate length measurement accuracy can be increased by more than 10%, and meet the accuracy requirement of the steel plate length measurement.