## 1 Introduction  
As the essential component of steam turbines, steam turbine blades must be constructed with extreme precision to withstand demanding working conditions. However, when traditional processing methods are used by workers to grind the blade, the grinding precision is solely dependent on the worker's subjective perception [1, 2]. Due to the inadequate grinding environment, manual grinding is ineffective, unable to produce accurate material removal and unhealthy for workers. Instead, robotic grinding has emerged as a competitive option to hand grinding of workpieces with complex surfaces, because of its adaptability, intelligence and lower cost [3, 4, 5]. Furthermore, the enormous curve of the blade profile and the intricate microscopic material removal mechanism make it challenging to quantify the quantity of blade grinding removal under certain grinding conditions [6]. Therefore, it is especially important to develop a model that can predict material removal correctly. Over the years, there has been considerable interest in the prediction of material removal depth (MRD) based on complicated profiles. Likewise, numerous approaches have been tested to address this bottleneck issue [7, 8]. However, the majority of material removal research is primarily modeled by simulating the contact conditions between the workpiece surface and the abrasive tool. These models are prone to significant mistakesbecause they frequently overlook the state of the abrasive tool itself and base assumptions on ideal circumstances. In order to study the relationship between material removal depth and process parameters, [PERSON] [9] proposed a mathematical model:  
\[r=C_{A}K_{A}k_{t}\frac{V_{b}}{V_{w}L_{w}}F_{A} \tag{1}\]  
where \(C_{A}\) is the grinding process constant, \(K_{A}\) represents the resistance constant of abrasive belt grinding ability, \(k_{t}\) is the abrasive belt wear coefficient, \(V_{b}\) is the abrasive belt rate, \(V_{w}\) is the feed rate, \(L_{w}\) is the width of the grinding path, \(F_{A}\) is the normal force between the workpiece and the grinding tool. Since [PERSON]'s model is only suitable for workpieces with relatively flat surfaces, it is no longer applicable to workpieces with complex profiles. A model proposed by [PERSON] [10] for material removal depth versus pressure and relative velocity between workpiece and grinding tool is widely used in the grinding industry:  
\[\frac{dh}{dt}=k_{p}P(V_{s}\pm V_{w}) \tag{2}\]  
where \(k_{p}\) is the Preston coefficient, \(P\) is the normal force between the workpiece and the grinding tool, \(V_{s}\) is the grinding tool speed, \(V_{w}\) is the workpiece feed speed, and \"\(\pm\)\" indicates the contact direction between workpiece and grinding tool. The grinding equation has a more comprehensive summary of the grinding process, but the dimensionless constant \(k_{p}\) used in the formula can only be determined through very detailed physical experiments, which are not universal. In order to solve the problem of free-form surface material removal, [PERSON] et al. [3] proposed a local material removal grinding model for turbine blades. [PERSON]'s model is a local process model with force as the main influencing factor of final local removal, which is convenient in understanding and defining the free-form surface process model. In order to address the low grinding accuracy of complex blade profiles, [PERSON] [6] suggested an equal residual height technique, based on the material removal profile (MRP) model. [PERSON]'s model designs the workpiece's grinding path, while taking into account the contact wheel's elastomeric deformation. Therefore, the accuracy of grinding for some blades is significantly improved. In the actual grinding process, many factors impact on the final grinding removal rate, including abrasive belt mesh number, rotational speed, and grinding force [11; 12; 13]. In order to achieve accurate material removal depth, these key parameters must be taken into account.