The presence of coal dust explosions in coal mining are significant safety hazards.This study mainly explores the flame propagation of coal dust combustion so as to provide a theoretical basis for the prevention and c...The presence of coal dust explosions in coal mining are significant safety hazards.This study mainly explores the flame propagation of coal dust combustion so as to provide a theoretical basis for the prevention and control of coal dust explosions.In the experiment,a dust cloud ignition device was used to experimentally explore the influence of the coal dust concentration on the flame propagation of the coal dust,and high-speed photography was used to record the coal dust flame propagation process.The results show that the flame propagates vertically along the wall of the vertical glass tube,emits a bright yellow light during the propagation process,and forms a mushroom cloud-shaped flame at the upper end of the vertical glass tube.When the concentration of coal dust is 250 g/m^(3),its burning time is much less than those of 500 g/m^(3)and 750 g/m^(3).When the concentrations are 250 g/m^(3),500 g/m^(3)and 750 g/m^(3),respectively,the corresponding maximum propagation velocities of the flame front reach 1.51 m/s,2.00 m/s and 1.61 m/s at 100 ms,353 ms and 310 ms,respectively.The time for the flame front velocity to reach the maximum and the maximum velocity of flame propagation first increase and then decrease with the rising of concentration.展开更多
Introduced the coal and rock AE propagation rule,wave guide fixing technics onAE sensors,and AE forecasting coal and rock disaster on the scene and so on,The coaland rock AE propagation rule that follows the exponent ...Introduced the coal and rock AE propagation rule,wave guide fixing technics onAE sensors,and AE forecasting coal and rock disaster on the scene and so on,The coaland rock AE propagation rule that follows the exponent attenuation function on different AEfrequencies,different quality factors and different propagation distances were analyzedand deduced by theory,numerical simulation,and by actual experiment.Consequently,itwas deduced that the coal and rock AE propagation rule follows the exponent attenuationfunction.Based on the correlative theory of wave dynamics and AE sensor,the AE waveguide propagation mechanical model on the sensor fixing manner is found,and the relationsof displacement and speed and acceleration between the AE signal source and theAE signal receiving terminal are presented.The effect of the AE sensor fixing manners oncoal and rock surfaces,coal and rock bottoms and wave guides were studied by actualexperiment.For the results,the effect of the AE sensor fixing manner on wave guides isbetter than on coal and rock surfaces,and was equivalent to the fixing manner on coal androck bottoms.Based on the above study results,actual coal and rock dynamistic disasterswere successfully forecasted.展开更多
In order to reduce the probability of fault occurrence of local ventilation system in coal mine and prevent gas from exceeding the standard limit, an approach incorporating the reliability analysis, rough set theory, ...In order to reduce the probability of fault occurrence of local ventilation system in coal mine and prevent gas from exceeding the standard limit, an approach incorporating the reliability analysis, rough set theory, genetic algorithm (GA), and intelligent decision support system (IDSS) was used to establish and develop a fault diagnosis system of local ventilation in coal mine. Fault tree model was established and its reliability analysis was performed. The algorithms and software of key fault symptom and fault diagnosis rule acquiring were also analyzed and developed. Finally, a prototype system was developed and demonstrated by a mine instance. The research results indicate that the proposed approach in this paper can accurately and quickly find the fault reason in a local ventilation system of coal mines and can reduce difficulty of the fault diagnosis of the local ventilation system, which is significant to decrease gas exploding accidents in coal mines.展开更多
A kind of feed forward neural network with three layers was applied to detect conveyor belt fire faster. And backward propagation (BP) algorithm was used to train the network parameters. The appropriate parameters and...A kind of feed forward neural network with three layers was applied to detect conveyor belt fire faster. And backward propagation (BP) algorithm was used to train the network parameters. The appropriate parameters and architecture of network were ob- tained after training with 81 pair of data. Matlab was used to simulate and the experi- ment result shows training time is least and error reduces most rapidly when ten neu- rons were in hidden layer and momentum coefficient is equal to 0.95. Temperature, rate of temperature change, dense of carbon monoxide and rate of carbon monoxide dense change were considered as four parameters to detect the PVC belt fire in this paper. It is indicated that the network can give alarm as fire takes place about 350 s. The network can effectively detect the fire at the early stage of conveyor belt fire. At the same time, the reliability of alarm can be increased and the anti-interference capability can be en- hanced when using this network.展开更多
The software system, hardware system and performance principle of the gas detector were briefly described. A new method was developed for orientating and cali- brating the instrument. The method shows excellence in au...The software system, hardware system and performance principle of the gas detector were briefly described. A new method was developed for orientating and cali- brating the instrument. The method shows excellence in automation and intelligence, and presents simpler and more reliable new method for orientating and calibrating the nominal physical quantity of the nonlinear sensor.展开更多
To resolve the conflicting requirements of measurement precision and real-time performance speed,an im-proved algorithm for pattern classification and recognition was developed. The angular distribution of diffracted ...To resolve the conflicting requirements of measurement precision and real-time performance speed,an im-proved algorithm for pattern classification and recognition was developed. The angular distribution of diffracted light varies with particle size. These patterns could be classified into groups with an innovative classification based upon ref-erence dust samples. After such classification patterns could be recognized easily and rapidly by minimizing the vari-ance between the reference pattern and dust sample eigenvectors. Simulation showed that the maximum recognition speed improves 20 fold. This enables the use of a single-chip,real-time inversion algorithm. An increased number of reference patterns reduced the errors in total and respiring coal dust measurements. Experiments in coal mine testify that the accuracy of sensor achieves 95%. Results indicate the improved algorithm enhances the precision and real-time ca-pability of the coal dust sensor effectively.展开更多
基金National Natural Science Foundation of China(No.11802272)Key Research and Development(R&D)Projects of Shanxi Province(No.201903D121028)+1 种基金Natural Science Foundation of Shanxi Province(No.201901D211228)National Defense Key Laboratory Foundation of Science and Technology on Combustion and Explosive Laboratory(Nos.6142603200509,6142603180408)。
文摘The presence of coal dust explosions in coal mining are significant safety hazards.This study mainly explores the flame propagation of coal dust combustion so as to provide a theoretical basis for the prevention and control of coal dust explosions.In the experiment,a dust cloud ignition device was used to experimentally explore the influence of the coal dust concentration on the flame propagation of the coal dust,and high-speed photography was used to record the coal dust flame propagation process.The results show that the flame propagates vertically along the wall of the vertical glass tube,emits a bright yellow light during the propagation process,and forms a mushroom cloud-shaped flame at the upper end of the vertical glass tube.When the concentration of coal dust is 250 g/m^(3),its burning time is much less than those of 500 g/m^(3)and 750 g/m^(3).When the concentrations are 250 g/m^(3),500 g/m^(3)and 750 g/m^(3),respectively,the corresponding maximum propagation velocities of the flame front reach 1.51 m/s,2.00 m/s and 1.61 m/s at 100 ms,353 ms and 310 ms,respectively.The time for the flame front velocity to reach the maximum and the maximum velocity of flame propagation first increase and then decrease with the rising of concentration.
基金Supported by the Project of National Basic Research Program of China(973 Program)(2005CB221505)the Significant Project of National Natural Science Fund(50534080/E041503)the Project of Coal Mine Gas and Fire Hazard Prevention Major Lab in Henan Province(HKLGF200508)
文摘Introduced the coal and rock AE propagation rule,wave guide fixing technics onAE sensors,and AE forecasting coal and rock disaster on the scene and so on,The coaland rock AE propagation rule that follows the exponent attenuation function on different AEfrequencies,different quality factors and different propagation distances were analyzedand deduced by theory,numerical simulation,and by actual experiment.Consequently,itwas deduced that the coal and rock AE propagation rule follows the exponent attenuationfunction.Based on the correlative theory of wave dynamics and AE sensor,the AE waveguide propagation mechanical model on the sensor fixing manner is found,and the relationsof displacement and speed and acceleration between the AE signal source and theAE signal receiving terminal are presented.The effect of the AE sensor fixing manners oncoal and rock surfaces,coal and rock bottoms and wave guides were studied by actualexperiment.For the results,the effect of the AE sensor fixing manner on wave guides isbetter than on coal and rock surfaces,and was equivalent to the fixing manner on coal androck bottoms.Based on the above study results,actual coal and rock dynamistic disasterswere successfully forecasted.
基金Projects 04JK197T supported by Shaanxi Education Bureau Science Foundation and 2005E202 by Shaanxi Science Foundation
文摘In order to reduce the probability of fault occurrence of local ventilation system in coal mine and prevent gas from exceeding the standard limit, an approach incorporating the reliability analysis, rough set theory, genetic algorithm (GA), and intelligent decision support system (IDSS) was used to establish and develop a fault diagnosis system of local ventilation in coal mine. Fault tree model was established and its reliability analysis was performed. The algorithms and software of key fault symptom and fault diagnosis rule acquiring were also analyzed and developed. Finally, a prototype system was developed and demonstrated by a mine instance. The research results indicate that the proposed approach in this paper can accurately and quickly find the fault reason in a local ventilation system of coal mines and can reduce difficulty of the fault diagnosis of the local ventilation system, which is significant to decrease gas exploding accidents in coal mines.
文摘A kind of feed forward neural network with three layers was applied to detect conveyor belt fire faster. And backward propagation (BP) algorithm was used to train the network parameters. The appropriate parameters and architecture of network were ob- tained after training with 81 pair of data. Matlab was used to simulate and the experi- ment result shows training time is least and error reduces most rapidly when ten neu- rons were in hidden layer and momentum coefficient is equal to 0.95. Temperature, rate of temperature change, dense of carbon monoxide and rate of carbon monoxide dense change were considered as four parameters to detect the PVC belt fire in this paper. It is indicated that the network can give alarm as fire takes place about 350 s. The network can effectively detect the fire at the early stage of conveyor belt fire. At the same time, the reliability of alarm can be increased and the anti-interference capability can be en- hanced when using this network.
基金Key Project Sponsored by Science and Technology Office of Hebei(01220140D)
文摘The software system, hardware system and performance principle of the gas detector were briefly described. A new method was developed for orientating and cali- brating the instrument. The method shows excellence in automation and intelligence, and presents simpler and more reliable new method for orientating and calibrating the nominal physical quantity of the nonlinear sensor.
基金Project 50674093 supported by the National Natural Science Foundation of China
文摘To resolve the conflicting requirements of measurement precision and real-time performance speed,an im-proved algorithm for pattern classification and recognition was developed. The angular distribution of diffracted light varies with particle size. These patterns could be classified into groups with an innovative classification based upon ref-erence dust samples. After such classification patterns could be recognized easily and rapidly by minimizing the vari-ance between the reference pattern and dust sample eigenvectors. Simulation showed that the maximum recognition speed improves 20 fold. This enables the use of a single-chip,real-time inversion algorithm. An increased number of reference patterns reduced the errors in total and respiring coal dust measurements. Experiments in coal mine testify that the accuracy of sensor achieves 95%. Results indicate the improved algorithm enhances the precision and real-time ca-pability of the coal dust sensor effectively.
