No abstract

In recent years, virtual simulation experiments have been widely used in education. However, at present, academic research on virtual simulation experiments mostly focuses on key technologies, and there are few emotional studies on virtual experiments. Based on the three-layer model of emotional design theory, this paper puts forward the method strategy of emotional simulation design in virtual simulation experiment, in order to provide some reference value for the design of virtual simulation experiment.

Predicting the temperatures of drive motors of important equipment can help to detect motor failure timely, avoiding the losses caused by the motor faults. Against the nonlinear characteristics of the equipment temperature changes, according to phase space reconstruction principle of chaos theory, the motor front axle temperature series were analyzed and the chaotic nature of the motor front axle temperature series is verified. In order to predict the trend of the motor axle temperature more accurately, the prediction based on BP neural network is conducted, and the embedding dimension of phase space reconstruction is chosen to be the number of input nodes. Simulation shows that this method has higher prediction accuracy and can be used to predict the motor axle temperature.

The coal safety has always been the focus of attention. So it is important to monitor the location of the mine personnel and display it on the the monitoring computer for the timely and effective rescue when the mine disaster occurs. The mine personnel positioning system is made up of Zigbee and LabVIEW software. The system has a better performance in system security, data storage, positioning accuracy, report printing, etc. It has a higher degree of automation and more apparent display. The research focus on the communication of LabVIEW software and the lower computer, the data processing, real-time reports and historical data.

In the process of coal-mine production, the self-ignition of left coal in goaf area has always been major disasters, and spawns amount of economic loss. As a consequence, it is necessary and essential to monitor the self-ignition of left coal in goaf. In consideration of the complex and poor environment of the goaf area, this thesis adopts ZigBee wireless sensor network instead of traditional fixed cable sensor network to monitor the self-ignition of coal goaf area. It has the advantages of wild covering, convenient layout and easy adapting to environment. In addition, counting on the revised routing algorithm, the whole wireless sensor network has obvious advantages of its network performance and low consumption, which makes the whole system monitor the self-ignition of left coal steadily and permanently.