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为提高光电轴角编码器的细分精度及莫尔条纹光电信号的细分倍数,设计了一种基于改进粒子群算法的信号正弦性修正方法。首先,根据莫尔条纹光电信号的数学模型,分析信号质量指标对细分误差的影响;并从编码器的制作、调试、使用等环节出发,指出信号细分误差产生的根本原因;然后,对改进粒子群算法的基本原理和实现步骤做了具体阐述;最后,以21位光电编码器为实验对象,依据其精码转换的方波信息实现精码信号的自适应采样,同时应用改进算法对采集的编码器原始光电信号进行数据预处理,通过辨识信号模型中的3个待定参量,直接实现信号等幅性偏差、稳定性偏差、正交性偏差的修正;对算法处理后的莫尔条纹信号进行细分精度检测,实验结果表明:编码器细分误差峰值由19.08″降低到2.86″,细分精度明显提高。
In order to improve the subdivision precision of optical axial encoder and the subdivision factor of moiré fringe photoelectric signal, a sinusoidal correction method based on improved particle swarm optimization is designed. Firstly, according to the mathematic model of moire fringe photoelectric signal, the influence of signal quality index on subdivision error is analyzed; and the root cause of signal subdivision error is pointed out from the aspects of making, debugging and using of the encoder. Secondly, Finally, taking 21 optical encoder as the experimental object, the adaptive sampling of the refined signal is realized based on the square wave information converted from the fine code. At the same time, the improved algorithm is applied to improve the performance of the particle swarm optimization algorithm. The original photoelectric signals collected by the encoder are used to preprocess the data. By identifying the three parameters to be determined in the signal model, the amplitude variation, stability deviation and orthogonality deviation of the signal can be directly corrected. After processing the moire fringes The results show that the peak value of encoder subdivision error is reduced from 19.08 “to 2.86”, and the subdivision precision is obviously improved.