# A \"Double Accuracy Theory\" and Experimental Research on Precision Grinding
## 1 Introduction  
Accuracy has always been one of the main goals of today's manufacturing technology. Grinding accuracy directly affects the quality of the workpiece. Therefore, some scholars worldwide are committed to the research of geometric precision control, machine tool spindle error test, grinding precision monitoring, and other aspects in the grinding process [1; 2; 3]. Aiming to control the geometric accuracy of high-speed grinding, [PERSON] et al. [4] proposed a geometric accuracy analysis and design method. According to the specific structure of a three-axis numerical control surface grinder, an aging error propagation model including 21 parameters and a cost-quality model of key geometric error variables are established. It is proved that the model has good prediction accuracy. [PERSON] et al. [5] proposed a constraint-force controller based on algebraic equations, which has the ability to realize force control without time delay. Through analysis and derivation, the relationship between contact force and grinding resistance is used to control grinding force and improve grinding accuracy. At present, the rotation accuracy measurement method of the machine tool spindle has developed very maturely. However, as a kind of finishing, the grinding spindle usually has high precision, which makes it difficult to measure by traditional methods. [PERSON] et al. [6] used response surface methodology (RSM) to carry out experimental research on horizontal surface grinder. In addition, the evaluation of grinding performance parameters such as friction coefficient, cutting force, temperature and specific grinding energy under different processing environments is also discussed. The surface roughness and friction coefficient of MQL grinding are the lowest, which are 0.1236 \(\upmu\)m and 0.3906 \(\upmu\)m respectively, while the specific grinding energy of wet grinding is the lowest, which is 18.95 N/mm\({}^{2}\). The temperature of MQL grinding is 29.07 \({}^{\circ}\)C, which is slightly higher than thatof wet grinding. At the same time, the measurement technology of high-precision ultra-precision shaft and the rotation error separation technology have been hot topics in recent years. [PERSON] et al. [7] introduced a new concept on the basis of the common separation methods of roundness error and rotation error of spindle, put forward the idea of secondary separation of rotation error, and established the mathematical model of this method. In order to solve the harmonic suppression problem of the three-point error separation technology, [PERSON] et al. [8] optimized the installation angle of the sensor. The common optimization method adopted is to maximize W (k). [PERSON] et al. [9] proposed a method to predict the width of the dresser using indirect monitoring method. Acoustic emission signals are collected during the trimming process, and the width of the trimmer is correlated with the processed signal by using the estimation neural network to estimate the current value of the width. Using the program, an automatic system will be generated to readjust the dressing parameters while avoiding stop, reducing cost and improving grinding accuracy. [PERSON] et al. [10] studied the grinding force and the material of the machined parts and obtained the correlation between the grinding force and the material. At the same time, the exploration of machine tool accuracy has also introduced acoustic emission monitoring technology, and it has become a hot topic in the field of advanced processing. Acoustic emission technology has been used for on-line monitoring of grinding processes such as end grinding [11], cylindrical transverse grinding [12], centerless grinding [13], etc. However, most of the authors have neglected the most important step in ensuring the precision of parts while studying the frontier of grinding precision technology. That is the accuracy of the machine tool itself and the testing accuracy of parts. In view of the accuracy of machine tools, many authors have also studied it. For example, [PERSON] et al.