Research on intelligent control theory and strategy of gas drainage pipe network based on graph theory

The core of comprehensive treatment effect of water environment in river basin lies in pipe network system. The blockage of urban drainage pipe network is one of the main reasons affecting the healthy operation of urban drainage network system. So the intelligent analysis method of urban drainage pipe network blockage diagnosis can quickly find the problems of urban drainage pipe network and improve the operation and maintenance efficiency of urban drainage pipe network. In this paper, through the analysis of rainfall data, rainfall and sewage pipe network flow variation regular pattern, the change range, the essay obtains the rain and sewage pipe network blockage diagnosis threshold. Combined with the urban intelligent drainage pipe network system, through the customized setting of pipe network blockage threshold, the rapid diagnosis and early warning of the blockage problem of the drainage pipe network are realized, and the healthy operation of the urban drainage network is guaranteed.

Urban drainage pipe network is the backbone of urban drainage, flood control and water pollution prevention, and is also an essential symbol to measure the level of urban modernization. A large number of underground drainage pipe networks in aged urban areas have been laid for a long time and have reached or practically reached the service age. The repair of drainage pipe networks has attracted extensive attention from all walks of life. Since the Ministry of ecological environment and the national development and Reform Commission jointly issued the action plan for the Yangtze River Protection and restoration in 2019, various provinces in the Yangtze River Basin, such as Anhui, Jiangxi and Hunan, have extensively carried out PPP projects for urban pipeline restoration, in order to improve the quality and efficiency of sewage treatment. Based on the management practice of urban pipe network restoration project in Wuhu City, Anhui Province, this paper analyzes the problems of lengthy construction period and repeated operation caused by the mismatch between the design schedule of the restoration scheme and the construction schedule of the pipe network restoration in the existing project management mode, and proposes a model of urban drainage pipe network restoration scheme selection based on the improved support vector machine. The validity and feasibility of the model are analyzed and verified by collecting the data in the project practice. The research results show that the model has a favorable effect on the selection of urban drainage pipeline restoration schemes, and its accuracy can reach 90%. The research results can provide method guidance and technical support for the rapid decision-making of urban drainage pipeline restoration projects.

Combined with the development of computer digital control technology and intelligent control theory, an advanced intelligent fuzzy control method with self-study ability used in SVC (static VAr compensator), was put forward in the paper. The control system can acquire and adjust control rules automatically according to the controlled object. Therefore, the reactive power parameters can be detected quickly, the capacitors can be put or cut rapidly, and unnecessary operation of capacitors can be avoided. The SVC system model based on the intelligent controller was given in the paper. The principle of intelligent fuzzy control algorithm and its software development platform were introduced in detail. The platform provided a simple and effective way for the application of intelligent fuzzy control in SVC

Graph Theory and Its Application in Optimization of Gas Drainage System in Coal Mine

With the rapid development of urban construction, smart city has become an important trend in the future, which is inseparable from the intellectualization of drainage pipe network. At the same time, with the increasing frequency of urban flood disasters, the old drainage pipe network system will cause significant economic losses, which requires modern cities to establish intelligent management and control of drainage pipe network. However, the situation of drainage facilities in most cities in China is complex, which requires strengthening modern means such as monitoring, operation management and planning services. Therefore, the research on intelligent management and control system of drainage pipe network based on big data technology is of great significance. Firstly, this paper analyzes the importance of intelligent management and control system. Then, this paper puts forward the main algorithms for big data processing. Finally, this paper constructs the intelligent management and control system of drainage pipe network.

In drainage engineering design, particularly, in analysis, check and hydraulic calculation of drainage pipe network, recognition and acquisition of drainage pipe network is the first and foremost task (Li et al., 2007).To implement the auto-generation of drainage pipe network drawing, this paper applies the graph theory to model the composition and data structure of a drainage pipe network. An effective method is proposed to automatically generate the directed drainage pipe network given a sink. The Breadth-first Search algorithm, Incidence-edge calculation algorithm and Transpose-graph algorithm from Boost Graph Library (BGL) are applied to implement the algorithm for the proposed method. The method provides greater automation and more efficiency but requires less inputs in the process of obtaining the practical drainage pipe network than other commonly used software do. It also lays a foundation for drainage pipe network analysis and related to hydraulic calculations. The accuracy and efficiency of the method is verified by the engineering practices described in this paper.

Based on the one-dimensional channel conservancy model, this paper considers the factor of urban pipe network drainage, and couples the pipe network model with the one-dimensional channel conservancy model to fully analyse the interaction between the channel water level and the drainage pipe network displacement. Taking a coastal city as an example, the model simulation results show that when the water level of the river is high, it will cause the drainage of the pipe network; the lower part of the terrain will become waterlogged because of the aging of the urban pipe and rainstorm. It is impossible to effectively solve the problem of flood control and drainage by widening the river channel. It is necessary to adopt the coordinated improvement of the pipe network and the river channel to achieve effective targets.

For a long time, the serious mismatch between negative pressure and drainage parameters of underground gas drainage has been the main reason for the standing engineering problems in coal mines, such as low gas drainage concentration, fast decay, and low-utilization rate. Aiming at these problems, an innovative method by adding micro-frequency conversion drainage pumps and electronically controlled valves at the key nodes of the conventional pipe network system of gas drainage and the joint quantitative regulation of underground regulation facilities and surface drainage pumps based on the intrinsic correlation between the drainage parameters and negative pressure is proposed in this paper to solve the difficulty of how to regulate increasing pressure or resistance in the on-site gas-drainage system and to realize energy matching in the whole drainage system on demand. For this method, the study further defines the safety and efficiency criteria of gas drainage, proposes the adaptive control strategy of gas-drainage parameters, and establishes the adaptive control model based on particle swarm optimization. The model took the safety and efficiency criteria of gas drainage as the constraint conditions and the maximum gas-drainage flow or concentration as the objective function to adaptively adjust the operating conditions of drainage pumps, micro-frequency conversion drainage pumps, and electric control valves to realize the adaptive regulation of gas-drainage parameters. Finally, based on the adaptive control strategy and model of gas-drainage parameters, the numerical simulation research was carried out through Comsol with Matlab. The results show that the gas-drainage concentration and high-concentration drainage period can be increased many times, and the adaptive drainage parameters of valves and micro pumps can be adjusted intelligently, which provides a theoretical basis for the intelligent field implementation of gas.

The electro-fused magnesia furnace is one of the main equipments used to produce electro-fused magnesia which is high performance refractory. Due to the multivariable, strong nonlinearity and coupling among the variables, strongly random disturbances of the fused magnesia production process, it is generally difficult or insufficient to only use one independent method to achieve satisfactory control performances. This paper proposes an intelligent optimization control strategy which combines optimization setting technique and intelligent control theory. Furthermore, the electric current presetting model, the setting compensation model and electric pole fluctuation fuzzy control strategy are described in details. The hybrid intelligent optimization control system based on the proposed control strategy is implemented on site. The data acquired from field demonstrates that the hybrid intelligent optimization control system can provides reliable, accurate and timely control performances.

In this paper, intelligent fuzzy control theory is introduced in the model of neural network algorithm, and the neural network system is improved by the PID controller, which has realized the feedback and adjustment function of neural network system, and has made the reaction of the system be more accurate and stable. In order to verify the validity and reliability of the designed intelligent control PID algorithm based on the fuzzy neural network in this paper, the algorithm is carried on the programming by using Matlab programming software, and the control process of PID is calculated by NNbox simulation toolbox, at last, it has obtained the curve of PID control response changing over time. From the response curve, it can be seen that after the PID proportional coefficient is regulated by using fuzzy neural network intelligent control algorithm, it can quickly and steadily obtain the control curve, which has realized better intelligent control effect, and has provided technical reference for the research of intelligent PID controller.

Urban waterlogging control: A novel method to urban drainage pipes reconstruction, systematic and automated

Quantitative simulation of urban waterlogging using computer models is an effective technical means for urban storm water management, especially for predicting and preventing waterlogging. In this study, a city in the northern Anhui Plain, China, was selected as the study site. The Storm Water Management Model was applied to simulate the dynamic changes in the pipeline overload, node overflow, and discharge port runoff characteristics from three perspectives: surface runoff, pipe network transmission, and flow control of low-impact development. The operation of the rainwater pipe network under different return periods and the real-time operation of the rainwater pipe network were simulated to seek solutions to urban waterlogging problems caused by flat terrain and slow drainage. The results revealed that surface runoff is the primary source of rainfall in the study area, with a runoff coefficient of 0.599. The drainage pipe network was optimized by expanding the diameter of the pipe from ≤1.5 mm to ≥2 mm. The water reduction rate was more than 50%, and overload did not occur after optimization. Therefore, sinking green space technology and optimization methods for expanding a pipe diameter can reduce urban waterlogging.

The techniques of stress relief mining in low-permeability coal seams and pillarless gob side retained roadway entry using Y-type ventilation and gas drainage systems were developed to control gas outbursts and applied successfully. However, as the mining depth increasing, parts of the gas drainage system are not suitable for mines with high gas emissions. Because larger mining depths cause higher ground stresses, it becomes extremely difficult to maintain long gob side roadways. The greater deformation suffered by the roadway is not favorable for borehole drilling for continuous gas drainage. To solve these problems, Y-type ventilation and gas drainage systems installed from a roof roadway were designed for drainage optimization. This system was designed based on a gas-enrichment zone analysis developed from mining the 11-2 coal seam in the Zhuji Mine at Huainan, Anhui Province, China. The method of Y-type gas extraction from different mine areas was applied to the panel 1112(1) in the Zhuji Mine. The absolute gas emission rate was up to 116.3 m3/min with an average flow of 69.1 m3/min at an average drainage concentration of nearly 85 %. After the Y-type method was adopted, the concentration of gas in the return air was 0.15 %–0.64 %, averaging 0.39 % with a ventilation rate of 2100–2750 m3/min. The gas management system proved to be efficient, and the effective gas control allowed safe production to continue.

LED lighting is widely used; in order to adapt to a variety of applications, an intelligent LED lighting control system is designed. The system takes an STM32 intelligent chip as the core, including a voice module, Bluetooth module, and LED constant current driver chip. It can use voice to control the opening and closing of the lighting system and grade set LED brightness. It can be switched to automatic mode, and control LED lighting brightness automatically adjusted with the light. With the cell phone Bluetooth assistant, the switch time of the LED lighting system can be set wirelessly and in other functions. Through actual testing, the system realizes intelligent LED control and various control methods operate normally. Through intelligent control, you can choose different control methods in combination with the actual application, flexible application to a variety of scenes, and with practical value.

The rapid expansion of urban drainage pipe networks, driven by economic development, poses significant challenges for efficient monitoring and management. The complexity and scale of these networks make it difficult to effectively monitor and manage the discharge of urban domestic sewage, rainwater, and industrial effluents, leading to illegal discharges, leakage, environmental pollution, and economic losses. Efficient management relies on a rational layout of drainage pipe network monitoring points. However, existing research on optimal monitoring point layout is limited, primarily relying on manual analysis and fuzzy clustering methods, which are prone to human bias and ineffective monitoring data. To address these limitations, this study proposes a coupled model approach for the automatic optimization of monitoring point placement in drainage pipe networks. The proposed model integrates the information entropy index, Bayesian reasoning, the Monte Carlo method, and the stormwater management model (SWMM) to optimize monitoring point placement objectively and measurably. The information entropy algorithm is utilized to quantify the uncertainty and complexity of the drainage pipe network, facilitating the identification of optimal monitoring point locations. Bayesian reasoning is employed to update probabilities based on observed data, while the Monte Carlo method generates probabilistic distributions for uncertain parameters. The SWMM is utilized to simulate stormwater runoff and pollutant transport within the drainage pipe network. Results indicate that (1) the relative mean error of the parameter inversion simulation results of the pollution source tracking model is linearly fitted with the information entropy. The calculation shows that there is a good positive linear correlation between them, which verifies the feasibility of the information entropy algorithm in the field of monitoring node optimization; (2) the information entropy algorithm can be well applied to the optimal layout of a single monitoring node and multiple monitoring nodes, and it can correspond well to the inversion results of the tracking model parameters; (3) the constructed monitoring point optimization model can well realize the optimal layout of monitoring points of a drainage pipe network. Finally, the pollution source tracking model is used to verify the effectiveness of the optimal layout of monitoring points, and the whole process has less human participation and a high degree of automation. The automated monitoring point optimization layout model proposed in this study has been successfully applied in practical cases, significantly improving the efficiency of urban drainage network monitoring and reducing the degree of manual participation, which has important practical significance for improving the level of urban water environment management.