# Cutting Path Planning Technology of Shearer Based on Virtual Reality
## 5 Simulation Experiment
### Analysis of Simulation Results  
In scheme 1, the actual cutting curve coincides with the preset roof curve, and the maximum error was obtained to be 12 cm. However, in schemes 2 and 3, an increase in the minimum traction speed of shearer decreased the coincidence, and the maximum error was obtained to be 48 cm. This could be attributed to the fact that the direction of the drum movement cannot meet the changing trend of the preset roof curve when the shearer is at the minimum traction speed. During the height-adjusting of the shearer while walking, if the shearer is running at a relatively large traction speed, K (the angle of the direction of drum movement) is relatively small, and the drum height-adjusting cannot be performed in a large scale. At the position where the roof and floor of the coal seam fluctuates greatly, the cutting curve will produce a large error. The effect in Unity3D is shown in Figure 12a and the cutting errors of the four schemes are shown in Figure 12b. Figure 12: Simulation results: (**a**) three-dimensional graph of cutting curve (**b**) error of the actual cutting points and the preset points. In production, scientific research and our daily life, we need to evaluate the quality of goods, the reasonable degree of some engineering design parameters, etc. to determine the best way to deal with them. In the cutting process of the fully mechanized mining face, there are many indexes to measure the quality of the cutting results, including the coal quality, recovery rate, production efficiency, economic benefit, and safety degree. Evaluating coal production is not an easy task, as it involves dimensionless index, human decision making, which are imprecise, fuzzy, and uncertain. Hence, using a scientific method to evaluate coal production comprehensively and effectively plays a crucial role in the analysis of simulation results. The evaluation that needs to be made according to many factors is called comprehensive evaluation. When some specific evaluation factors are fuzzy, the comprehensive evaluation is called a fuzzy comprehensive evaluation. The fuzzy theory bridges the gap between the precise classical mathematics and the fuzzy real world. Fuzzy comprehensive evaluation method is a method which transforms qualitative evaluations into quantitative evaluations through the membership degree theory of fuzzy mathematics. It, therefore, has a good theoretical basis for the overall evaluation of things or objects having many constraints. Hence, the fuzzy comprehensive evaluation method is suitable for evaluating the cutting results. The general steps of fuzzy comprehensive evaluation include the construction of evaluation indexes, the determination of the weight of each index, the construction of the evaluation matrix, the synthesis of evaluation matrix and weight. The specific steps for evaluating the cutting results using the fuzzy comprehensive evaluation are as follows:  
* Determine the evaluation object \[X=\{x_{1},x_{2},x_{3},x_{4}\}= \{\text{scheme1},\text{scheme2},\text{scheme3},\text{scheme4}\}.\] (12)
* Determine the index set \[U=\{u_{1},u_{2},u_{3}\}\] (13) \[=\{\text{recovery rate, production efficiency, others( safety degree, labor \cos t, etc) }\}.\]  
When the index set is determined, each of the indicators of each scheme is analyzed quantitatively. The recovery rate is expressed by the sum of the squares due to the error of the cutting points thus: \(SSE=\sum\limits_{i=1}^{n}w_{i}(y_{i}-y)^{2}\), where \(y_{i}\) and \(y\) are the heights of the actual cutting point and the preset roof point, respectively. The efficiency of production is represented by the time used for cutting one knife, however, other factors are scored according to the production experience of the general enterprises (0-9 point). The scores of each index are shown in Table 2.  
* Determine the weight vector of the evaluation index Set the weight vector to \(A=(W_{1},W_{2}\dots W_{n})\), where \(W_{i}\) indicates the \(i\)-th index weight coefficient.