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Name: MatlabVersion: R2015b (126.96.36.1997246)Mac Platform: IntelIncludes: KOS version: OS X 10.9.5 or laterProcessor type(s) & speed: Intel, 64 bitRAM minimum: 2 GBInstall using provided key and crackMATLAB is the high-level language and interactive environment used by millions of engineers and scientists worldwide. It lets you explore and visualize ideas and collaborate across disciplines including signal and image processing, communications, control systems, and computational finance.Key FeaturesHigh-level language for numerical computation, visualization, and application developmentInteractive environment for iterative exploration, design, and problem solvingMathematical functions for linear algebra, statistics, Fourier analysis, filtering, optimization, numerical integration, and solving ordinary differential equationsBuilt-in graphics for visualizing data and tools for creating custom plotsDevelopment tools for improving code quality and maintainability and maximizing performanceTools for building applications with custom graphical interfacesFunctions for integrating MATLAB based algorithms with external applications and languages such as C, Java, .NET, and Microsoft ExcelSee Release description for toolboxes available to installMore info:
The rupture of coal pillar can lead to spontaneous combustion or collapse of goaf, which endangers the safety of workers. To explore the relationship between the crack depth of the coal structure and the signal received by the piezoelectric ceramic sensor, the output data of coal samples were analyzed by using the piezoelectric effect, combined with the experiment and ABAQUS simulation. Based on the signal amplitude, the output signal characteristics of the coal model with different crack depths were analyzed, and the evaluation index of coal crack cracking degree (Dc) was defined. The results show that the piezoelectric fluctuation method can effectively identify the local cracks of coal. When the distance between the lead Piezoelectric Transducer (PZT) patch and crack position is constant, the amplitude of the PZT patch output signal will decay with the deepening of the crack depth, while the value of increases with the increase of crack depth. This study provides a theoretical basis for mine disaster prevention and control.
Coal spontaneous combustion is still one of the main causes of coal mine accidents, which can cause casualties and a serious waste of coal resources. Coal-seam's spontaneous combustion fire is mainly concentrated in the hidden space of the underground, such as the crushed stoop in the goaf, near the connection roadway, the stopping line, and the fall of ground and float coal accumulation of coal roadway1. Coal pillar in the mine mainly plays the role of isolation and protection support, In the process of coal cutting and tunnelling, different stress states and stress degrees will cause different forms of coal failure. When there is a crack in the coal body, it is difficult to observe by naked eye, and no abnormal occurrence. When the crack is further developed, there will be water leakage, air leakage and other phenomena, leading to the failure of isolated coal pillar, groundwater into the roadway, air into the goaf, causing floods, goaf spontaneous combustion and other accidents; The coal pillar that acts as the support protection may fracture after the crack, eventually leading to the collapse of the roadway and the ground collapse. Cracks can be detected at the early stage of cracks development, and effective prevention and control measures can be made in time to prevent further cracks development and prevent disasters. Due to the underground conditions and the particular situation of the coal pillar, it is difficult to quickly and accurately determine the location and range of the hidden fire source2. Therefore, it is necessary to develop an accurate, rapid, and real-time monitoring method for coal cracks3,4. The proposed method can improve reliability and reduce the structure's maintenance and detection costs. Previous studies focused on the evolution of the damage mechanism of as-mined coal structures from multiple perspectives, lacking the real-time monitoring of coal cracks. Owing to the defects of as-mined coal structures and the special environment underground, the safety evaluation of coal structures becomes more complicated.
During the outline of the 13th 5-year plan for national economic and social development of the People's Republic of China, the critical technology research on risk identification, monitoring, and early warning and equipment research and development of coal mine typical coal rock power disasters were focused on. It is urgent to adopt scientific and technical means and methods to intelligently identify the damage degree to coal and rock structures. The emergence of intelligent materials provides an effective way for engineering structure health monitoring technology. Among many intelligent materials, piezoelectric ceramics, as the main representative, have made significant progress in the health monitoring and damage assessment of various metal, concrete, and other structures22. Kawiecki et al. measured the damage degree of the concrete beam by pasting Piezoelectric Transducer (PZT) sheets on both ends of the measured concrete beam23. The damage degree and location of the concrete beam are analyzed through the electrical signal of the PZT sheet at the acquisition end. The test results show that the PZT sheet can measure the damage to the concrete beam very well. Subsequently, to prove that the fluctuation analysis method can identify the generation and degree of structural damage. Seth et al. used Lamb waves to monitor different defect forms, such as composite material delamination, transverse layer cracks, and through-hole. They summarized the influence of actuator sensor position on the test and the excitation methods of various signals24. Then, Sun et al. pasted a PZT patch on the surface of concrete beams to excite stress waves and obtained the relationship between the wave peak value and wave velocity with stress25. The results show that this method can monitor the generation and propagation of cracks in concrete structures in real-time. To facilitate the placement of sensors and improve their available rate, Song et al. encapsulated piezoelectric ceramic sheets in the middle of two marble aggregates to form a \"piezoelectric intelligent aggregate\" and then buried the aggregate in the monitored structure to realize the effective combination between the two.
Moreover, the feasibility and effectiveness of this encapsulation form were confirmed by experiments. Song was the first scholar to use the piezoelectric active sensing method to research concrete crack damage monitoring in the world26,27,28. By pre-embedding piezoelectric intelligent aggregate, Sun et al. conducted a detailed study on the propagation characteristics of stress wave and sound field generated by PZT patch as a sound source in concrete medium and analyzed that the monitoring data collected by sensors could effectively reflect the existing damage and the development trend of structural health29. Hughi et al. used piezo sensors embedded in reinforced concrete structures as part of an active monitoring system and used the data collected to estimate crack width to propose a method for measuring crack width and locating crack locations30. Meanwhile, Markovic et al. used the finite element software ABAQUS as a platform to establish a numerical model of smart aggregate and analyze the wave propagation process in the model. The simulation constructed a damage monitoring system based on the piezo-sensors active sensing method. The propagation characteristics of stress waves under the influence of crack depth and hole diameter of concrete beam and the difference between them were studied. However, in this model, severe reflection occurs when the wave propagates to the boundary, and the coupling effect between the piezo-sensors and the concrete is not apparent31. In addition, piezoelectric sensors have a wide range of applications. Han et al. used active sensing methods to study the damage detection of four standard timber connections32.
The monitoring method based on piezo sensors still lacks real-time monitoring and identification of coal structure damage. Based on this, combined with numerical simulation and experimental demonstration, this paper realized the excitation and reception of stress wave in coal medium through the piezoelectric effect of PZT patch33,34. The potential-time curve will be obtained and normalized processing. The voltage amplitude and propagation time of stress wave propagating under different crack depth of the sample were analyzed, so as to effectively identify the cracking degree of coal. It provides a simple, economical, and reliable way to realize the online monitoring of coal structure.
A three-dimensional finite element numerical model was constructed, and the PZT patch was mounted at a preset position on the surface of the coal structure. The model was composed of three components: coal specimen, piezoelectric actuator, and piezoelectric sensor. The model dimension is shown in Table 1. PZT1 acted as an actuator to generate stress waves based on the piezoelectric effect of piezoelectric materials, and PZT2 served as a sensor to receive stress waves. The vertical crack depth of the model was set as 0 mm, 5 mm, 10 mm, 15 mm, 20 mm, 25 mm, 30 mm, 35 mm, and 40 mm, which was in the middle of the horizontal model. After the assembly was completed, the coupling connection between the PZT patch and the coal structure was realized by creating constraints to simulate the real working state. The finite element numerical model is shown in Fig. 4. 153554b96e