Shearer coal cutting dust production characteristic test platform and method based on similar simulation

Abstract

The present application relates to a kind of coal cutter coal cutting dust production characteristic test platform and method based on similarity simulation, belong to coal mining dust prevention and control technical field.The method includes: S1: build coal cutter coal cutting dust production characteristic test platform, including coal rock simulation unit, pressure loading module, cutting power system and dust monitoring system;S2: using coal rock simulation unit preparation coal rock sample, including simulating coal rock hardness and moisture content;S3: the prepared coal rock sample is placed in test platform, using pressure loading module to apply pressure to coal rock sample, according to the mathematical model of hardness, moisture content, pressure and power, the power of cutting power system is dynamically adjusted;S4: dust concentration, diffusion trajectory and granularity distribution monitored by dust monitoring system are combined, and multiple groups of working condition data are obtained by orthogonal test, and the correlation model of dust production and power is obtained by using least square method fitting, to provide quantitative basis for energy saving and consumption reduction of coal cutter.

Description

Technical Field

[0001] This invention belongs to the field of dust control technology in coal mining, and relates to a testing platform and method for testing the dust generation characteristics of coal cutting machines based on similarity simulation. Background Technology

[0002] In the field of coal mining, research on the dust generation characteristics during the drum cutting process of coal mining machines is of paramount importance. Dust not only affects the safety and health of the working environment but also poses a threat to equipment operation and production efficiency. Especially in confined spaces, dust problems can lead to serious safety hazards. Therefore, accurately predicting and controlling dust generation characteristics has become a key issue in ensuring the safety and efficiency of coal mine production.

[0003] However, current research methods largely rely on field measurements or simple theoretical calculations, which have significant limitations. Field testing is constrained by the complex environment and high-risk operating conditions in mines, resulting in high data acquisition costs and difficulties in ensuring safety; while purely theoretical models often ignore the coupling effects of multiple factors, leading to insufficient prediction accuracy and making it difficult to meet actual production needs.

[0004] The core challenge in this field lies in accurately simulating the dust generation process of coal cutting machines under constrained conditions and establishing reliable predictive models. Firstly, dust generation characteristics are influenced by a combination of factors, such as the hardness and moisture content of the coal and rock, which directly determine the amount and dispersion of dust. Because these factors vary complexly under actual working conditions, it is difficult to fully grasp their effects through a single theoretical analysis, leading to insufficient representativeness of experimental data. A deeper challenge lies in how to construct a simulation platform in a laboratory environment that can realistically reflect the actual coal cutting process, thereby safely and efficiently acquiring dust generation data under different working conditions. The difficulty in constructing such a simulation platform directly affects the accuracy of data analysis and the reliability of subsequent predictive models.

[0005] Therefore, how to accurately test and predict the dust generation characteristics during the drum cutting process of a coal mining machine by constructing a similar simulation test platform and combining a comprehensive analysis of multiple influencing factors has become a key problem that this study urgently needs to solve. Summary of the Invention

[0006] In view of this, the purpose of this invention is to provide a method for testing the dust generation characteristics of coal mining machines based on similarity simulation. A test platform is designed to realistically simulate coal mining conditions, and on this basis, the dust generation and dispersion characteristics are detected simultaneously. At the same time, a prediction model is constructed that considers the coupled influence of multiple factors such as coal and rock hardness (f), moisture content (η), roof pressure (p), and coal cutting power (P), so as to achieve accurate prediction of dust generation characteristics under complex working conditions and provide a quantitative basis for energy saving and consumption reduction of coal mining machines.

[0007] To achieve the above objectives, the present invention provides the following technical solution:

[0008] A method for testing the dust generation characteristics of coal mining machines based on similarity simulation, specifically including the following steps:

[0009] S1: Construct a coal cutting dust generation characteristic test platform for coal mining machines, including a coal and rock simulation unit, a pressure loading module, a cutting power system, and a dust monitoring system;

[0010] S2: Coal and rock samples are prepared using a coal and rock simulation unit, including simulating coal and rock hardness f and moisture content η;

[0011] S3: Simulate the dust generation process of coal cutting by a coal mining machine: Place the prepared coal and rock sample into the test platform, apply pressure p to the coal and rock sample using the pressure loading module, and dynamically adjust the power P of the cutting power system according to the mathematical model of hardness f, moisture content η, pressure p and power P to realize the dynamic correlation between cutting intensity and dust generation.

[0012] S4: Combining the dust concentration, diffusion trajectory and particle size distribution monitored by the dust monitoring system, multiple sets of working condition data were obtained through orthogonal experiments, and the correlation model between dust production M and power P was obtained by fitting with the least squares method, providing a quantitative basis for energy saving and consumption reduction of coal mining machines.

[0013] Furthermore, in step S1, the coal and rock simulation unit includes a hardness-adjustable sample box and a humidity control system; the hardness-adjustable sample box is made of gypsum-sand-coal powder composite material; the humidity control system is used to control the moisture content of the coal and rock; and an optical fiber pressure sensor is pre-embedded in the sample box.

[0014] Furthermore, in step S1, the pressure loading module includes a top pressure simulation device, which uses a hydraulic servo system to simulate the coal and rock pressure p in front of the working face, and supports sinusoidal or step load waveforms.

[0015] Furthermore, in step S1, the cutting power system includes a simulated drum, a simulated drum traction track, a variable frequency motor, and a motor power monitoring system; the variable frequency motor is used to drive the simulated drum to cut coal; the simulated drum traction track is used to pull the simulated drum forward or backward; and the motor power monitoring system is used to monitor the power of the variable frequency motor in real time.

[0016] Furthermore, in step S1, the dust monitoring system includes a laser scattering dust concentration sensor, a particle size analyzer, and a high-speed camera system; the laser scattering dust concentration sensor is used to monitor dust concentration; the particle size analyzer is used to analyze dust particle size distribution; and the high-speed camera system is used to record dust diffusion trajectory.

[0017] Furthermore, in step S1, the coal mining machine dust generation characteristic test platform also includes a dust collection system for collecting dust particles smaller than 75μm to facilitate obtaining dust output.

[0018] Furthermore, in step S3, the mathematical model expressions for hardness f, moisture content η, pressure p, and power P are as follows:

[0019] R(d) = 100·exp(-λd) N )

[0020] λ = 0.68f + 0.12η - 0.05p + 0.03P

[0021] N = 1.05 - 0.15ln(f)

[0022] Where R is the dispersion, i.e. the cumulative mass percentage of particles larger than a certain particle size d on the sieve; d is the dust particle size; λ is the degree of breakage index; and N is the breakability index.

[0023] Furthermore, in step S4, the correlation model expression between dust production M and power P is as follows:

[0024] lnM=1.32+0.32lnf-0.4lnη+0.17lnp+0.85lnP+ε M

[0025] Where, ε M This is the residual term.

[0026] Furthermore, the formula for calculating dust production M is:

[0027]

[0028] Where H(·) is the Heaviside step function, used to screen dust particles with a diameter less than 75 μm; m i Let be the mass of the i-th sample (g); n be the number of samples; t be the total sampling time (min); d be the total sampling time (min). i Let be the particle size of the dust sample taken in the i-th sampling.

[0029] The beneficial effects of this invention are as follows:

[0030] (1) Multi-dimensional working condition simulation capability

[0031] This invention integrates a coal and rock simulation unit, a hydraulic servo loading system, and a variable frequency power system, and for the first time achieves dynamic coupling control of four-dimensional parameters (coal and rock hardness, moisture content, roof pressure, and coal cutting power). The experimental conditions closely match the actual complex conditions underground, and the degree of condition matching is high.

[0032] (2) Refined monitoring of dust generation characteristics

[0033] This invention employs multimodal monitoring technology (laser scattering sensor, particle size analyzer, high-speed camera system) to achieve dust concentration (resolution 1 mg / m³). 3 The simultaneous acquisition of particle size distribution (grading accuracy 0.1-100μm) and diffusion trajectory (frame rate 1000fps) greatly improves data integrity and supports full-cycle analysis of dust generation and diffusion.

[0034] (3) Construction of accurate prediction model

[0035] Based on orthogonal experiments and least squares regression, a dust generation prediction equation considering the coupling of multiple factors is established. The model fits well and the prediction error is small, providing a quantitative basis for optimizing the power of coal mining machines and greatly improving energy efficiency.

[0036] (4) Innovative Materials and Dynamic Loading Technology

[0037] A standardized formula library for gypsum-coal powder-sand was developed (hardness error ±0.2f). Combined with a dynamic hydraulic servo system (waveform response frequency ≥10Hz), the stress fluctuations during the coal and rock crushing process were simulated, the nonlinear variation characteristics of the cutting resistance were realistically reproduced, and the reliability of experimental data was improved.

[0038] (5) Security and Standardization Upgrades

[0039] The fully enclosed negative pressure test chamber integrates an infrared dust concentration early warning and emergency stop interlocking system (response time ≤ 0.5s), meeting the explosion-proof standards of the "Coal Mine Safety Regulations"; it proposes a dust collection standard (75μm screen + Heaviside function screening) to achieve standardized measurement of dust generation quality.

[0040] (6) Significant industrial application value

[0041] By using virtual simulation to preview extreme working conditions, the optimal parameter combination can be optimized, reducing the risk of physical testing.

[0042] In summary, this invention, through multi-parameter dynamic coupling control, standardized material preparation, and intelligent monitoring technology, overcomes the bottlenecks of low working condition reproduction and data fragmentation in traditional testing methods, providing a systematic solution for energy saving and consumption reduction and precise dust control in coal mining machines, and filling the technical gap in predicting dust generation characteristics under complex working conditions.

[0043] Other advantages, objectives, and features of the invention will be set forth in part in the description which follows, and in part will be apparent to those skilled in the art from the following examination, or may be learned from practice of the invention. The objectives and other advantages of the invention can be realized and obtained through the following description. Attached Figure Description

[0044] To make the objectives, technical solutions, and advantages of the present invention clearer, the preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings, wherein:

[0045] Figure 1 This is a flowchart of the coal cutting dust generation characteristics test method of a coal mining machine based on similarity simulation according to the present invention;

[0046] Figure 2 A logical diagram of a prediction model for dust generation characteristics of a coal cutting drum in a coal mining machine.

[0047] Figure 3 A schematic diagram of the structure of a coal mining machine dust generation characteristic testing platform. Detailed Implementation

[0048] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of the present invention. Unless otherwise specified, the following embodiments and features can be combined with each other.

[0049] The accompanying drawings are for illustrative purposes only and are schematic diagrams, not actual pictures. They should not be construed as limiting the invention. To better illustrate the embodiments of the invention, some parts in the drawings may be omitted, enlarged, or reduced, and do not represent the actual product dimensions. It is understandable to those skilled in the art that some well-known structures and their descriptions may be omitted in the drawings.

[0050] In the accompanying drawings of the embodiments of the present invention, the same or similar reference numerals correspond to the same or similar components. In the description of the present invention, it should be understood that if terms such as "upper," "lower," "left," "right," "front," and "rear" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, they are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, the terms used to describe positional relationships in the drawings are only for illustrative purposes and should not be construed as limiting the present invention. For those skilled in the art, the specific meaning of the above terms can be understood according to the specific circumstances.

[0051] Please see Figures 1-3 This invention provides a method for testing the dust generation characteristics of coal mining machines based on similarity simulation, specifically including the following steps:

[0052] S1: Construct a coal cutting dust generation characteristic test platform for coal mining machines, including a coal and rock simulation unit, a pressure loading module, a cutting power system, a dust monitoring system, and a dust collection system.

[0053] S2: Prepare coal and rock samples using a coal and rock simulation unit, including simulating coal and rock hardness f and moisture content η.

[0054] S3: Simulate the dust generation process of coal cutting by a coal mining machine: Place the prepared coal and rock sample into the test platform, apply pressure p to the coal and rock sample using the pressure loading module, and dynamically adjust the power P of the cutting power system according to the mathematical model of hardness f, moisture content η, pressure p and power P, so as to realize the dynamic correlation between cutting intensity and dust generation.

[0055] S4: Combining the dust concentration, diffusion trajectory and particle size distribution monitored by the dust monitoring system, multiple sets of working condition data were obtained through orthogonal experiments, and the correlation model between dust production M and power P was obtained by fitting with the least squares method. An improved particle swarm optimization (PSO) algorithm was used for global optimization to provide a quantitative basis for energy saving and consumption reduction of coal mining machines.

[0056] Example 1:

[0057] like Figure 2 As shown, this embodiment provides a testing platform for the dust generation characteristics of a coal mining machine, wherein...

[0058] Coal and rock simulation unit: equipped with a coal and rock sample box with adjustable hardness (hardness range f = 1-6) and an integrated humidity control system (moisture content η adjustable range 0-15%).

[0059] Pressure loading module: includes a top pressure simulation device, which uses a hydraulic servo system to simulate the coal and rock pressure p (0-20MPa) in front of the working face, with an accuracy of ±0.5MPa; supports sinusoidal or step load waveforms.

[0060] Cutting power system: includes a simulated drum, a simulated drum traction rail, a variable frequency motor, and a motor power monitoring system; the variable frequency motor is used to drive the simulated drum for coal cutting. The variable frequency motor drives the simulated drum (power P = 50-500kW adjustable), with a speed of 0-100rpm. The simulated drum traction rail is used to pull the simulated drum forward or backward.

[0061] Dust monitoring system: Employs a laser scattering dust concentration sensor (range 0-1000 mg / m³) 3 ); particle size analyzer (0.1-100μm classification detection); high-speed camera system (1000fps) to record dust diffusion trajectory.

[0062] Dust collection system: It adopts a cyclone separation dust collection tray (with 75μm screen) or anti-static dust collection bag to collect dust particles smaller than 75μm, which facilitates the acquisition of dust output.

[0063] Example 2:

[0064] The experiment was conducted based on the coal cutting and dust generation characteristics test platform provided in Example 1, and specifically included the following parts:

[0065] 1. Standardized preparation of coal and rock samples

[0066] (1) Optimization of similar material ratio

[0067] A gypsum-sand-coal powder composite material was used to simulate coal and rock of different hardness (f = 1-6). The equivalence of the material's mechanical parameters needs to be verified through physical similarity simulation. Sample preparation must strictly follow the moisture content η control standard (0-15%) to ensure uniform humidity distribution.

[0068] (2) Layered Structure and Load Simulation

[0069] Pre-embedded pressure sensors are used to apply axial pressure of 0-20 MPa to simulate the actual stress state of coal and rock underground. The loading accuracy directly affects the spatial distribution characteristics of dust generation behavior.

[0070] 2. Multi-parameter coordinated regulation

[0071] (1) Dynamic operating condition matching

[0072] Based on the actual coal cutting process of the coal mining machine (oblique cutting infeed → cutting triangular coal → pushing scraper conveyor), the simulated drum speed, traction speed and power output (50-500kW) need to be adjusted synchronously to achieve a dynamic correlation between cutting intensity and dust generation.

[0073] (2) Construction of four-dimensional parameter matrix

[0074] A coupled control model based on PLC control is established, comprising f (hardness), η (moisture content), p (pressure), and P (power). The parameter combination is optimized through orthogonal experimentation to identify dust-generating sensitive factors.

[0075] R(d) = 100·exp(-λd) N )

[0076] λ = 0.68f + 0.12η - 0.05p + 0.03P

[0077] N = 1.05 - 0.15ln(f)

[0078] Where R is the dispersion, i.e. the cumulative mass percentage of particles larger than a certain particle size d on the sieve; d is the dust particle size; λ is the degree of breakage index; and N is the breakability index.

[0079] 3. Accurate capture of dust generation data

[0080] (1) Multimodal monitoring fusion

[0081] By combining laser scattering (dust concentration), high-speed imaging system (diffusion trajectory), and particle size spectrometer (particle size distribution), a quantitative analysis of the entire dust generation-diffusion cycle can be achieved.

[0082] (2) Energy efficiency correlation analysis

[0083] Based on real-time data of cutting resistance feedback value and power P, a mathematical model of dust generation rate (g / kWh) is established to provide a quantitative basis for energy saving and consumption reduction of coal mining machines.

[0084] Predictive model construction methods:

[0085] 1) Parameter Definition

[0086] Dust generation mass M = mass of dust passing through a 75μm sieve per unit time (mg / min);

[0087] Dispersion R(d) = 100·exp(-λd) N ), where λ is the degree of breakage index (0.5-2.3) and N is the breakability index (0.8-1.5).

[0088] 2) Obtain multiple sets of working condition data through orthogonal experiments;

[0089] An L9 orthogonal array was used, and the parameter range and accuracy control are shown in Table 1. The sliding window method was employed to process the granularity analysis data.

[0090] Table 1. Design parameters of L9 orthogonal array

[0091]

[0092]

[0093] 3) The correlation model expression between dust production M and power P obtained by fitting using the least squares method is as follows:

[0094] lnM=1.32+0.32lnf-0.4lnη+0.17lnp+0.85lnP+ε M

[0095] Where, ε M This is the residual term.

[0096] 4) Dynamic model of dispersion: The traction speed is obtained by combining the principle of energy conservation in crushing.

[0097] 4. Security verification closed loop

[0098] (1) Emergency Response Test

[0099] Simulated dust concentration exceeds the limit (≥500mg / m³) 3 The test was conducted to verify the reliability of the linkage between the dust suppression spraying device and the emergency stop system, and to ensure that the explosion-proof performance of the experimental platform met the standards.

[0100] (2) Virtual simulation calibration

[0101] By rehearsing extreme working conditions (such as cutting high-hardness rock layers) through a virtual experimental platform, the configuration of parameters for physical experiments can be optimized, reducing the risks of real-world testing.

[0102] 5. Verification Experiment:

[0103] Simulated coal and rock with f = 2.5 was selected, and η was adjusted to 8%.

[0104] Set p = 25 MPa, P = 300 kW;

[0105] Dust samples were collected continuously for 30 minutes.

[0106] The measured values ​​were M = 248 mg / min and d50 = 18.7 μm.

[0107] The model prediction error is <7.3%.

[0108] This invention achieves accurate prediction of dust generation characteristics under complex working conditions by integrating dynamic simulation data of coal mining machines with measured dust distribution patterns.

[0109] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for testing the dust generation characteristics of coal cutting machines based on similarity simulation, characterized in that, The method specifically includes the following steps: S1: Construct a coal cutting dust generation characteristic test platform for coal mining machines, including a coal and rock simulation unit, a pressure loading module, a cutting power system, and a dust monitoring system; S2: Prepare coal and rock samples using a coal and rock simulation unit, including simulating coal and rock hardness. f and moisture content η ; S3: Simulating the dust generation process of a coal mining machine: The prepared coal and rock sample is placed in the test platform, and pressure is applied to the coal and rock sample using the pressure loading module. p According to hardness f Moisture content η ,pressure p and power P The mathematical model dynamically adjusts the power of the cutting power system. P This enables a dynamic correlation between cutting strength and dust generation. The mathematical model expressions for hardness f, moisture content η, pressure p, and power P are: in, Dispersion; Dust particle size, As an indicator of the degree of breakage, For breakage index; S4: Combining dust concentration, diffusion trajectory, and particle size distribution monitored by the dust monitoring system, multiple sets of operating condition data were obtained through orthogonal experiments, and the dust production rate was obtained by fitting the data using the least squares method. M With power P The association model.

2. The method for testing the dust generation characteristics of coal mining machines based on similarity simulation according to claim 1, characterized in that, In step S1, the coal and rock simulation unit includes a hardness-adjustable sample box and a humidity control system; the hardness-adjustable sample box is made of gypsum-sand-coal powder composite material; the humidity control system is used to control the moisture content of the coal and rock; and an optical fiber pressure sensor is pre-embedded in the sample box.

3. The method for testing the dust generation characteristics of coal mining machines based on similarity simulation according to claim 1, characterized in that, In step S1, the pressure loading module includes a top pressure simulation device, which uses a hydraulic servo system to simulate the coal and rock pressure p in front of the working face, and supports sinusoidal or step load waveforms.

4. The method for testing the dust generation characteristics of coal mining machines based on similarity simulation according to claim 1, characterized in that, In step S1, the cutting power system includes a simulated drum, a simulated drum traction track, a variable frequency motor, and a motor power monitoring system; the variable frequency motor is used to drive the simulated drum to cut coal; the simulated drum traction track is used to pull the simulated drum forward or backward; and the motor power monitoring system is used to monitor the power of the variable frequency motor in real time.

5. The method for testing the dust generation characteristics of coal mining machines based on similarity simulation according to claim 1, characterized in that, In step S1, the dust monitoring system includes a laser scattering dust concentration sensor, a particle size analyzer, and a high-speed camera system; the laser scattering dust concentration sensor is used to monitor dust concentration; the particle size analyzer is used to analyze dust particle size distribution; and the high-speed camera system is used to record dust diffusion trajectory.

6. The method for testing the dust generation characteristics of coal mining machines based on similarity simulation according to claim 1, characterized in that, In step S1, the coal mining machine dust generation characteristic test platform also includes a dust collection system for collecting dust particles smaller than 75μm to facilitate obtaining dust output.

7. The method for testing the dust generation characteristics of coal mining machines based on similarity simulation according to claim 1, characterized in that, In step S4, dust production M With power P The association model expression is: in, This is the residual term.

8. The method for testing the dust generation characteristics of coal mining machines based on similarity simulation according to claim 6 or 7, characterized in that, Dust production M The calculation formula is: in, This is a Heaviside step function used to screen dust particles with a diameter of less than 75 μm; For the first i Sub-sampling quality; n The number of samplings; Total sampling time; For the first i The particle size of the dust sampled in the second sampling.

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