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Abstract
An automatic warning system for geological disasters based on the dynamic data driven technique is established in consideration of inducing factors of geological disaster and formation mechanisms, traditional data management, real-time monitoring data processing and analysis, early- warning model database for geological disasters, multi-source data visualization technologies, and the real-time transmission technology of monitoring data. Methods of early warning by threshold value discrimination, early warning by process tracking and early warning by comprehensive analysis of spatio-temporal information are used, combined with the application of service flow engine technology and databases. A new type of geological disaster dynamic monitoring system based on the network environment is proposed in order to achieve real-time query, processing and analysis of disaster information obtain dynamic monitoring curve and automatic warning of disaster as well as other functions. This method is used for the study of the Heifangtai Loess Landslide Monitoring Demonstration Zone in Gansu Province and the real-time monitoring data and early warning model service flow for geological disasters are verified. The system reflected the deformation of the disaster body in real time and successfully alerted the Heifangtai Chenjia 6s landslide.
... However, the current configuration software occupies the majority of the market share, and some small companies mainly develop Chinese products. Due to the limitations of human and material resources, there is a large gap between the key technologies and foreign products; hence, they can only be applied to very limited occasions [2]. Therefore, it is necessary to continue to analyze the general structures and development methods of industrial data acquisition and monitoring software and design a set of configuration tools to develop a reliable monitoring system quickly and stably. ...
In order to realize and design a software monitoring and early warning system for the Internet of Things (IoT), this paper establishes a “trinity” control platform integrating PLC, WINCC, and MATLAB based on nonlinear technology and realizes the proportion integration differentiation (PID) control based on the RBF neural network tuning on this platform. Based on the framework of the trinity control platform, the PID control system set by the radial basis function (RBF) neural network and the STEP7 virtual object programming of the control platform are designed and realized. The experimental data update cycle is 0.5 s to record 1,000 data item objects, U is the control quantity, which is associated with the U communication driver variable in WINCC, and the corresponding storage address in the PLC is MD200; Yout is the controlled quantity, which is related to the Yout communication driver variable in WINCC, and the corresponding storage address in the PLC is MD100; start is the control switch, associated with the start communication driver variable in WINCC, corresponding to the storage address in the PLC of M0.1; reset is the reset control switch, It is associated with the reset communication driver variable in WINCC, and corresponds to the storage address in the PLC as M0.0. KP, KI, KD, and TIME correspond to three real-time PID parameters and are the cycle time in MATLAB (used for the X-axis of trend graphing), and are the variables of the communication driver. The addresses in the PLC are MD20, MD24, MD28, and MD32. It shows that for these three software programs, the update cycle of the data in the respective storage areas must be consistent, the program control cycles in MATLAB and PLC need to be consistent, and the transmission of parameters must be correctly implemented in a control cycle according to the programming logic sequence, in order to realize the design of an IoT software monitoring and early warning system.
... In the game, the use of dribbling breakthrough technology can basically account for about one-third of the number of shots of the team. In terms of the number of successful dribble breakthroughs, due to the strength constrained by other factors, the success rate is still relatively low [19]. Students majoring in basketball in the Department of Sports of Nanchang Institute of Physical Education, whether boys or girls, can shoot more than 30% of the total shots in each game after using the dribbling breakthrough technology in the game. ...
Data-driven technology is a problem-solving method, starting from the initial data or observations, using heuristic rules to find and establish the relationship between internal features, to discover some theorems or laws. With the sharp increase in the number of basketball players, there are increasingly studies on the dribbling action of its trajectory and placement. Data-driven technology usually also refers to natural language processing methods based on large-scale statistical data. This paper proposes to use this technology to monitor the trajectory of basketball dribbling, which can more effectively reduce the pain caused by improper dribbling when teenagers play basketball, and can also more effectively improve a shooting percentage. The invention also relates to the field of Internet of Things technology, moving target detection, and the algorithm of target movement trajectory. The Internet of Things technology originated in the media field and is the third revolution in the information technology industry. The Internet of Things refers to the connection of any object with the network through the information-sensing equipment and according to the agreed protocol, and the objects exchange and communicate information through the information dissemination medium to realize intelligent identification, positioning, tracking, supervision, and other functions. After that, a lot of experiments were carried out, and the results showed that the number of breakthroughs after using this technology accounted for 30%, and the hit rate after the breakthrough was also above 70%. The TFHBase system and its optimization strategy are efficient and can effectively solve the problem of basketball trajectory monitoring, and we also do some exploration on trajectory visualization, to further control the landing point of the basketball trajectory.
... Landslide is the shear damage caused by the rock and soil mass on the slope along the internal weak structural plane or the maximum shear stress band, which will cause large horizontal displacement and sliding towards the slope direction [1][2][3][4][5]. The route corridor passes through xindiqu, TALU River, Yuqu and other major rivers from east to west. ...
Landslide is a kind of common geological disaster in mountainous areas. The soil and rock mass on the slope have been scoured by rivers or artificially cut slope for a long time. Under the action of gravity, it will slide downward. Landslides are developed in the third section of the highway from Zhubarong to Bangda Bingzhan along G4218 line (Zuogong Highway), but the distribution of hazardous landslides is relatively concentrated. The landslide shear outlet is above the highway, then a large number of gravel and blocks of sliding bodies are piled up and buried on the road surface. Not only is the workload of cleaning up the earth and stones huge and takes a long time, but also after the slope foot is cleared, it will cause the slide of the upper body to further slide, causing the slope of the highway to be moved together with the highway, so that the highway is completely damaged. Therefore, it is of great significance to strengthen the research on the development and prevention of landslide disaster.
The platform safety gate is important safety protection equipment in urban rail transit, which makes the rail area relatively independent from the platform waiting area, ensures the safety of passengers, reduces the noise pollution brought by the subway train to the platform, and provides a comfortable waiting environment for passengers. In order to solve the problems of low intelligent degree and single debugging method of railway station safety door equipment data monitoring, a correction algorithm using machine learning based on image grid is proposed. Firstly, based on virtual instrument technology, a set of acoustic signal acquisition and processing systems for sound field visualization is designed and implemented. Then, based on the analysis of requirements, the hardware configuration and system software design are carried out. Finally, the extraction technology of image feature information is adopted, which can reduce the operation time of image target recognition and make the security door control system have real time. The experimental results show that the calibration algorithm is used to calculate the coordinate values of the actual road by using the third-order fitting method. Compared with the coordinate values of the standard grid, the average error of X is 0.0662%, and the average error of Y is 0.0011%. It can not only improve the accuracy of judgment, but also meet the real-time requirements of video monitoring. The system can realize wireless monitoring on the status of platform safety door equipment using machine learning, improve the efficiency of subway operation and the flexibility of station staff maintenance and protection, and ensure the safety and reliability of the platform safety door system.
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