Study on coal mine macro, meso and micro safety management system

SummaryIn recent years, the coal mine safety production situation in our country improved year by year, but severe accidents still occurred; the accidents caused great economic loss to the national economy. According to statistical analysis, almost all of the coal mine accidents will expose the hidden danger in before, most of the accidents caused due to safety management not reaching the designated position and the hidden danger management does not take any decision in time. Based on the coal mine safety management holes in our country, the coal mine macro, meso and micro safety management system was established in this paper, which includes meaning and conception of the theories of the macro, meso and micro safety management, and also includes the matching hardware equipment, in order to achieve the hidden danger's closed-loop control and dynamic early warning in the process of coal mine production

Zigbee-Based Positioning System For Coal Miners

AbstractChina's present communication systems in coal mine can not effectively provide the information such as dynamic distribution of coal miners in work and production environment. Hence, rescue efforts are hard to be carried out in case of coal mine accident. To deal with this problem, the paper at first introduces the characteristics, structure and network construction method of ZigBee protocol. Then, by using the ZigBee technology based on IEEE802.15.4 criteria, the wireless communication network and the structure of ZigBee communication module for coal mine are studied and designed. At last, multilateration positioning algorithm is employed to realize the positioning of coal miners. Coal miner positioning system enters into computer management system via network, laying important actual significance to the production safety and emergent resuce of coal mine

The Calculation Method of Safety Degree and Its Application in Coal Mine Enterprises

In order to evaluate the situation of safety production of coal mine enterprises effectively, quantitative analysis is necessary and very important. Safety degree of coal mine enterprises based on the concept of safety degree is defined and the method of calculating quantitatively the safety degree is put forward. The validity of this method is verified by empirical research in view of micro‐ and macroanalyses. In view of micro analysis the safety degree is derived with the calculation method based on information of one coal mine. The safety degree of this coal mine went through rapid increase period, stable period, and slow increase period. Macroresearch results show that the situation of safety production of coal mine enterprises in China has significantly been improving and the level of safety degree also has been increasing year by year since 1979, the year when the policy of reform and opening began. The reasons are the advancement of technology, strengthening of safety management and education, increasing of safety investment, and perfection of policies, laws, and regulations. These achievements can provide quantitative method for assessing the status of coal mines

Research on Theory and Technology of Floor Heave Control in Semicoal Rock Roadway: Taking Longhu Coal Mine in Qitaihe Mining Area as an Example

AbstractAs one of the most common disasters in deep mine roadway, floor heave has caused serious obstacles to mine transportation and normal production activities. The third section winch roadway in the third mining area of Qitaihe Longhu coal mine has a serious floor heave due to the large buried depths of the roadway and the semicoal rock roadway, and the maximum floor heave is 750 mm. For the problem of floor stability, this paper establishes a mechanical model to analyze the stability of roadway floor heave by analogy with the basement heave of deep foundation pit. It provides a model reference for analyzing the problem of roadway floor heave. Aiming at the problem of roadway floor heave in Longhu coal mine, the roadway model is established by using FLAC3D, and the roadway model after support is established according to the on-site support measures. Through the analysis of the distribution of roadway plastic area, stress nephogram, and displacement field simulation results, the results show that the maximum displacement of roadway roof and floor after support is reduced by 15% and 23%, but the maximum floor heave is still 770 mm, which is close to the measured floor heave of roadway. In order to solve the problem of roadway floor heave and integrate economic factors, this paper puts forward three support optimization schemes, simulates the support effect of each scheme, and finally determines that scheme 3 is the best support optimization scheme. Compared with that under the original support, the amount of floor heave is reduced by 81%, and the final amount of floor heave is 150 mm, which can meet the requirements of roadway floor deformation. The results provide a scheme and guidance for roadway support optimization

Characteristics of flame velocity of gas explosion with obstruction in pipeline

The velocity of flame propagation caused by gas explosion is very difficult to be measured in experiment. A new image processing method is applied to calculate the velocity based on correlation coefficients of images. Experiment of gas explosion with 9.5% gas is carried out. The images photographed during the experiment are processed by the new method. And the change law of velocity of flame propagation is calculated. The results show that the velocity and structure of the flame are both unstable when it propagates in the pipeline. The propagation of flame is not away in acceleration state, but acceleration and deceleration are mutual alternation. And the velocity is in shock statement till the flame extinct during the whole flame propagation. The results also show that the metal wire mesh in the pipeline can accelerate the velocity of flame propagation but reduce the damage caused by gas explosion. And this method also covers the shortage of experimental method

Positioning Algorithm of MEMS Pipeline Inertial Locator Based on Dead Reckoning and Information Multiplexing

High-precision mapping and positioning of urban underground pipelines are the basic requirements of urban digital construction. Aiming at the above problems, a dead reckoning algorithm based on the starting point and ending point correction and forward and reverse solution information reuse is proposed. This paper firstly establishes a dead reckoning system model consisting of a microelectromechanical system (MEMS) inertial measurement unit (IMU) and an odometer and analyzes the propagation mechanism of dead reckoning errors. The algorithm constructs the trajectory correction matrix by using the position information of the starting point and the ending point of the short-distance underground pipeline and then uses the trajectory correction matrix to correct the trajectory position information obtained by forward and reverse dead reckoning. Finally, the corrected forward and reverse trajectory position information is fused and averaged to achieve high-precision mapping and positioning of underground pipelines. The simulation results of the 100 m pipeline show that the maximum positioning error of the proposed algorithm for straight pipelines is within 5 cm, and the maximum positioning error for 90° curved pipelines is within 20 cm. The algorithm effectively solves the problem of a rapid accumulation of errors over time in the process of dead reckoning, which greatly improves the positioning accuracy

Positioning Algorithm of MEMS Pipeline Inertial Locator Based on Dead Reckoning and Information Multiplexing

High-precision mapping and positioning of urban underground pipelines are the basic requirements of urban digital construction. Aiming at the above problems, a dead reckoning algorithm based on the starting point and ending point correction and forward and reverse solution information reuse is proposed. This paper firstly establishes a dead reckoning system model consisting of a microelectromechanical system (MEMS) inertial measurement unit (IMU) and an odometer and analyzes the propagation mechanism of dead reckoning errors. The algorithm constructs the trajectory correction matrix by using the position information of the starting point and the ending point of the short-distance underground pipeline and then uses the trajectory correction matrix to correct the trajectory position information obtained by forward and reverse dead reckoning. Finally, the corrected forward and reverse trajectory position information is fused and averaged to achieve high-precision mapping and positioning of underground pipelines. The simulation results of the 100 m pipeline show that the maximum positioning error of the proposed algorithm for straight pipelines is within 5 cm, and the maximum positioning error for 90° curved pipelines is within 20 cm. The algorithm effectively solves the problem of a rapid accumulation of errors over time in the process of dead reckoning, which greatly improves the positioning accuracy

Using Field Spectroradiometer to Estimate the Leaf N/P Ratio of Mixed Forest in a Karst Area of Southern China: A Combined Model to Overcome Overfitting

The ratio between nitrogen and phosphorus (N/P) in plant leaves has been widely used to assess the availability of nutrients. However, it is challenging to rapidly and accurately estimate the leaf N/P ratio, especially for mixed forest. In this study, we collected 301 samples from nine typical karst areas in Guangxi Province during the growing season of 2018 to 2020. We then utilized five models (partial least squares regression (PLSR), backpropagation neural network (BPNN), general regression neural network (GRNN), PLSR+BPNN, and PLSR+GRNN) to estimate the leaf N/P ratio of plants based on these samples. We also applied the fractional differentiation to extract additional information from the original spectra of each sample. The results showed that the average leaf N/P ratio of plants was 17.97. Plant growth was primarily limited by phosphorus in these karst areas. The sensitive spectra to estimate leaf N/P ratio had wavelengths ranging from 400–730 nm. The prediction capabilities of these five models can be ranked in descending order as PLSR+GRNN, PLSR+BPNN, PLSR, GRNN, and BPNN when considering both accuracy and robustness. The PLSR+GRNN model yielded high R2 and performance to deviation (RPD), and low root mean squared error (RMSE) with values of 0.91, 3.15, and 1.98, respectively, for the training test and 0.81, 2.25, and 2.46, respectively, for validation test. Compared with the PLSR model, both PLSR+BPNN and PLSR+GRNN models had higher accuracy and were more stable. Moreover, both PLSR+BPNN and PLSR+GRNN models overcame the issue of overfitting, which occurs when a single model is used to predict leaf N/P ratio. Therefore, both PLSR+BPNN and PLSR+GRNN models can be used to predict the leaf N/P ratio of plants in karst areas. Fractional differentiation is a promising spectral preprocessing technique that can improve the accuracy of models. We conclude that the leaf N/P ratio of mixed forest can be effectively estimated using combined models based on field spectroradiometer data in karst areas