Ventilation control method for dust suppression

Abstract

The invention provides a ventilation control method for dust suppression, and relates to the technical field of intelligent control. The method comprises the steps that dust data information of a fully-mechanized excavation site is obtained, and the dust data information comprises volatile organic compound (VOC) concentration data and illumination data influenced by suspended particulate matter; determining a VOC index based on the increment change of the VOC concentration data in the dust data information; determining an optical refractive index of the particulate matter based on a characteristic index of illumination data in the dust data information; according to the VOC index and the particulate matter optical refractive index, the dust variation coefficient of the fully-mechanized excavation site is determined; the control strategy is determined based on the dust variation coefficient, and ventilation is performed according to the control strategy, so that the accumulation risk of dust concentration is reduced, possible major safety accidents such as coal dust explosion are prevented, and the safety of a mine operation environment and the health protection level of workers are comprehensively improved.

Description

Technical Field

[0001] The present application relates to the field of intelligent control technology, and in particular to a ventilation control method for dust suppression. Background Art

[0002] Intelligent ventilation optimization control for dust suppression in soft rock tunneling in coal mines is a systematic solution that combines advanced sensing technology, automated control, and intelligent algorithms. It aims to reduce dust concentration during tunneling operations, improve the working environment, and enhance mine safety. During tunneling, due to the high degree of crushing of soft rock, tunneling machinery generates large amounts of dust, which not only affects worker health but also poses safety hazards such as coal dust explosions. Intelligent ventilation optimization control effectively controls dust concentration by monitoring environmental parameters such as dust concentration, wind speed, and humidity in the tunneling working area in real time. Using intelligent algorithms, it dynamically adjusts the ventilation system, optimizing air volume distribution, precisely spraying water to suppress dust, and automatically activating dust removal equipment.

[0003] During the comprehensive excavation process, certain minerals (such as sulfide ores or rock formations containing organic matter) generate high temperatures due to mechanical action and may release gas or steam. These volatile substances are suspended in the air in the form of aerosols, steam or particles, which significantly interfere with the operation of optical dust sensors; particulate matter may also scatter light, causing the sensor to misjudge the dust concentration as too high (light scattering error), or because high-concentration steam blocks the light path, resulting in unstable measurement values. Sensor misjudgment may cause the ventilation system to underestimate the actual dust concentration, resulting in insufficient air volume or inadequate dust reduction measures. As a result, the dust concentration continues to rise, which not only threatens the health of underground workers and increases the risk of occupational diseases such as coal worker's pneumoconiosis, but may also cause greater safety hazards. Summary of the Invention

[0004] The present application aims to solve one of the technical problems in the related art at least to a certain extent.

[0005] To this end, the first purpose of this application is to propose a ventilation control method for dust suppression, so as to perform ventilation control according to an accurate and effective ventilation strategy and reduce the probability of safety hazards.

[0006] A second object of the present application is to provide a ventilation control device for dust suppression.

[0007] The third objective of this application is to provide an electronic device.

[0008] The fourth object of this application is to provide a computer-readable storage medium.

[0009] A fifth object of this application is to provide a computer program product.

[0010] To achieve the above objectives, the first embodiment of the present application provides a ventilation control method for dust suppression, comprising:

[0011] Obtain dust data information at the fully mechanized excavation site, including volatile organic compound (VOC) concentration data and illumination data affected by suspended particulate matter;

[0012] Determining a VOC index based on incremental changes in VOC concentration data in the dust data information;

[0013] Determining the optical refractive index of the particles based on characteristic indicators of the illumination data in the dust data information;

[0014] Determining the dust variation coefficient at the comprehensive excavation site according to the VOC index and the optical refractive index of the particulate matter;

[0015] A control strategy is determined based on the dust variation coefficient, and ventilation is performed according to the control strategy.

[0016] To achieve the above-mentioned objectives, a second embodiment of the present application provides a ventilation control device for dust suppression, comprising:

[0017] The first acquisition module is used to obtain dust data information at the fully mechanized excavation site, wherein the dust data information includes volatile organic compound (VOC) concentration data and illumination data affected by suspended particulate matter;

[0018] A second acquisition module is configured to determine a VOC index based on an incremental change in VOC concentration data in the dust data information;

[0019] A third acquisition module is used to determine the optical refractive index of the particles based on the characteristic index of the illumination data in the dust data information;

[0020] A fourth acquisition module is used to determine the dust variation coefficient at the comprehensive excavation site according to the VOC index and the optical refractive index of the particulate matter;

[0021] The ventilation control module is used to determine a control strategy based on the dust variation coefficient and perform ventilation according to the control strategy.

[0022] To achieve the above-mentioned objectives, a third embodiment of the present application provides an electronic device, including:

[0023] a processor, and a memory communicatively connected to the processor;

[0024] The memory stores computer-executable instructions;

[0025] The processor executes the computer-executable instructions stored in the memory to implement the method described in the embodiment of the first aspect.

[0026] To achieve the above-mentioned purpose, the fourth embodiment of the present application proposes a computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, they are used to implement the method described in the first embodiment.

[0027] To achieve the above-mentioned purpose, the fifth embodiment of the present application proposes a computer program product, which implements the method described in the first embodiment when the computer program is executed by a processor.

[0028] The ventilation control method for dust suppression provided in the present application obtains dust data information at the comprehensive excavation site, determines the VOC index based on the incremental changes in the VOC concentration data in the dust data information, and uses the VOC index to reflect the concentration of volatile organic compounds in the air; determines the optical refractive index index of the particulate matter based on the characteristic indicators of the illumination data in the dust data information, and uses the optical refractive index index of the particulate matter to reflect the current particulate matter situation; combines the VOC index and the optical refractive index index of the particulate matter to determine the dust variation coefficient at the comprehensive excavation site, and uses the dust variation coefficient to reflect the current dust environment at the comprehensive excavation site; and formulates different control strategies for ventilation control in different risk dust environments, thereby reducing the risk of dust concentration accumulation, preventing major safety accidents such as coal dust explosions that may be caused, and comprehensively improving the safety of the mine working environment and the health protection level of workers.

[0029] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0031] Figure 1 A schematic flow chart of a ventilation control method for dust suppression provided in an embodiment of the present application;

[0032] Figure 2 A schematic diagram of a process for obtaining a VOC index provided in an embodiment of the present application;

[0033] Figure 3 A schematic diagram of a process for obtaining the optical refractive index of particles provided in an embodiment of the present application;

[0034] Figure 4 A flow chart of another ventilation control method for dust suppression provided in an embodiment of the present application;

[0035] Figure 5A schematic structural diagram of a ventilation control device for dust suppression provided in an embodiment of the present application. DETAILED DESCRIPTION

[0036] The following describes in detail embodiments of the present application, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0037] The ventilation control method for dust suppression according to an embodiment of the present application will be described below with reference to the accompanying drawings.

[0038] Figure 1 This is a flow chart of a ventilation control method for dust suppression provided in an embodiment of the present application. Figure 1 As shown, the method includes the following steps:

[0039] S101, obtaining dust data information at the fully mechanized excavation site.

[0040] It is understood that a fully mechanized excavation site refers to an operation site where coal is mined using a fully mechanized tunneling machine. The high-intensity cutting operations during fully mechanized excavation can cause the coal to break and generate large amounts of dust. The friction and impact between the picks and the coal can cause the coal to undergo elastic and plastic deformation. The released elastic energy can throw coal fragments and dust into the air. Or, when the coal seam is dislocated or fractured by geological forces, the dust in the cracks is exposed and forms dust. Furthermore, dust is also generated when coal blocks collide with the machine and the ground after collapse. Dust reduces visibility at the working face, increases safety hazards, and affects the normal progress of mining operations. Furthermore, workers who work in a high-concentration dust environment for a long time are prone to inhaling large amounts of dust, which can cause various diseases.

[0041] This embodiment acquires dust data information at a fully mechanized excavation site. The dust data information includes volatile organic compound (VOC) concentration data and illumination data affected by suspended particulate matter.

[0042] It is understood that the concentration level of volatile organic compounds in the air refers to the total amount of volatile organic compounds or the content of a certain compound in a unit volume of air. The physical parameters of the refraction and scattering characteristics of suspended particulate matter on light refer to the physical manifestations of the deflection, dispersion or energy attenuation of the light path when the particles interact with light. The characteristics are determined by the size, shape, density and composition of the particles. VOCs include but are not limited to methane, ethane, benzene series and other volatile products with high volatility that can diffuse rapidly into the air.

[0043] In some embodiments, the acquisition of dust data information at the comprehensive excavation site can also be performed periodically. For example, in this embodiment, 10 minutes is used as a monitoring cycle, that is, the dust data information at the comprehensive excavation site within 10 minutes is acquired and analyzed.

[0044] S102: Determine a VOC index based on the incremental change of VOC concentration data in the dust data information.

[0045] In this embodiment, the incremental change of the VOC concentration data in the dust data information refers to the change in the VOC concentration data between the current sampling moment and the previous sampling moment. Taking methane as an example, the concentration data of methane at each sampling moment in the monitoring period is obtained to obtain the VOC concentration data. At this time, the VOC concentration data is a sequence of methane concentrations within 10 minutes; the difference between each two adjacent sampling moments of the VOC concentration data is calculated to determine the incremental change of the VOC concentration data.

[0046] In some implementations, the VOC concentration data can also be normalized to improve data processing efficiency and accuracy, and incremental changes can be obtained based on the normalized VOC concentration data. In this embodiment, the incremental change is the difference between the VOC concentration data at the current sampling moment and the VOC concentration data at the previous sampling moment.

[0047] Optionally, all incremental changes within the monitoring period can be summed up as the VOC index, or all incremental changes can be weighted and summed up to obtain the VOC index. The VOC index is used to reflect the degree and characteristics of volatile organic compound pollution in the environment. The larger the VOC index, the higher the concentration of volatile organic compounds. For example, the organic mineral layer undergoes thermal decomposition due to high temperature, friction or other mechanical effects, releasing a large amount of volatile organic compounds; conversely, if the VOC index is smaller, it can be inferred that the mineral layer has not undergone significant thermal decomposition and has not released volatile organic compounds.

[0048] S103: Determine the optical refractive index of the particles based on characteristic indicators of the illumination data in the dust data information.

[0049] In some implementations, the illumination data may be the light source illuminated by a light-emitting device into the comprehensive excavation site, and the characteristic indicators of the illumination data include but are not limited to the intensity of the incident light and the intensity of the output light after reflection by the particles; based on the characteristic indicators of the illumination data, the absorption coefficient of the particles to light and the scattering coefficient of the particles can be obtained; the absorption coefficient of the particles is a parameter that describes the ability of the particles to absorb light energy when interacting with light of a characteristic wavelength, and the scattering coefficient of the particles is a parameter that quantifies the ability of the particles to scatter light away from its original propagation direction to other directions when irradiated with light of a characteristic wavelength.

[0050] In some implementations, the specific refractive index of particles can also be calculated using Michelson interferometry and the reflectance ratio method. The specific refractive index describes the refractive power of a substance (such as particulate matter) relative to a reference medium (usually air or vacuum). It is the ratio of the two refractive indices and reflects the relative difference in optical properties between the two substances. Michelson interferometry is a precision measurement technique that uses a Michelson interferometer to detect the phase difference of light waves. Its basic principle is to split monochromatic light into two beams: one beam passes through the detection medium (such as suspended particulate matter), and the other beam serves as a reference beam. Interference fringes are formed on the interferometer screen. By analyzing the movement and changes in these fringes, the phase change, optical path difference, and refractive index of light as it propagates through the particles can be accurately calculated. The reflectance ratio method evaluates the refractive properties of particles by measuring the ratio of the reflected light intensity on the particle surface. It determines the particle's refractive power based on the proportional change in the reflected light intensity. Combining these two methods can simultaneously obtain both the real and imaginary parts of the particle's refractive index, providing a complete description of its optical properties.

[0051] Optionally, the scattering intensity of the particles to light in different directions may be obtained, and the optical refractive index of the particles may be determined based on the scattering intensity, the specific refractive index, the absorption coefficient and the scattering coefficient of the particles.

[0052] In some implementations, the particle optical refractive index is calculated as:

[0053]

[0054] Where p represents the optical refractive index of particles; represents the real part of the specific refractive index; p(θ) represents the scattering intensity; τ(λ) is the absorption coefficient of the particle to the characteristic wavelength light; S(λ) is the scattering coefficient of the particle; λ max and λ min They are the maximum wavelength and minimum wavelength extracted from the effective spectral range in the output light intensity.

[0055] S104: Determine the dust variation coefficient at the comprehensive excavation site based on the VOC index and the optical refractive index of the particulate matter.

[0056] Optionally, the VOC index and the optical refractive index index of the particulate matter can be weighted and summed to obtain the dust variation coefficient at the comprehensive excavation site; or the VOC index and the optical refractive index index of the particulate matter can be preprocessed separately, and the preprocessed results can be added together to obtain the dust variation coefficient; the VOC index and the optical refractive index index of the particulate matter can also be input into a pre-trained machine learning model, and the dust variation coefficient can be generated by the machine learning model.

[0057] It can be understood that the larger the volatile organic compound index expression value generated after analyzing the concentration level of volatile organic compounds in the air, and the larger the particle optical refractive index expression value generated after analyzing the physical parameters of the refraction and scattering characteristics of suspended particulate matter to light, the larger the dust variation coefficient expression value generated after analyzing the dust change data information obtained at the comprehensive excavation site under the detection window, indicating that the organic-containing ore layer generates high temperature due to mechanical action during the comprehensive excavation process, and undergoes significant thermal decomposition reaction, releasing a large amount of volatile organic compounds (such as methane, benzene, etc.). At the same time, these volatile substances may condense or adhere to suspended particulate matter, changing the optical properties of the particles. On the contrary, it indicates that the organic-containing ore layer is not subjected to obvious high temperature during the comprehensive excavation process, no significant thermal decomposition reaction occurs, and no obvious volatile organic compounds are released. Therefore, the dynamic characteristics of dust changes at the comprehensive excavation site can be reflected based on the dust variation coefficient.

[0058] S105: Determine a control strategy based on the dust variation coefficient, and perform ventilation according to the control strategy.

[0059] Optionally, a dust variation coefficient reference threshold can be preset, and the actually detected dust variation coefficient can be compared with the dust variation coefficient reference threshold. If the dust variation coefficient is greater than or equal to the preset dust variation coefficient reference threshold, it means that the dust environment at the current comprehensive excavation site is poor and is a high-risk dust environment; correspondingly, if the dust variation coefficient is less than the preset dust variation coefficient reference threshold, it means that the dust environment at the current comprehensive excavation site is good and is a low-risk dust environment.

[0060] In some implementations, if it is determined that the current environment is a low-risk dust environment, the current ventilation strategy can be continued, that is, ventilation control can be continued according to the current control strategy without making too many changes or restrictions to the current ventilation.

[0061] In some implementations, if the current environment is determined to be high-risk dust, the control strategy may be to issue a high-risk warning and increase ventilation to reduce the dust concentration in the air and dilute the concentration of harmful gases until the dust concentration returns to a safe range.

[0062] In this embodiment, dust data information is obtained from the fully mechanized excavation site. Based on the incremental changes in VOC concentration data in the dust data, a VOC index is determined, and the VOC index is used to reflect the concentration of volatile organic compounds in the air. Based on the characteristic indicators of the illumination data in the dust data, the optical refractive index index of the particles is determined, and the optical refractive index index of the particles is used to reflect the current particulate matter situation. The VOC index and the optical refractive index of the particles are combined to determine the dust variation coefficient at the fully mechanized excavation site, and the dust variation coefficient is used to reflect the current dust environment at the fully mechanized excavation site. Thus, whether it is a low-risk dust environment or a high-risk dust environment is determined. Different control strategies are formulated for different risk dust environments, and ventilation control is performed according to the corresponding control strategies. Through this intelligent and dynamic control method, the risk of dust concentration accumulation is greatly reduced, and the probability of workers suffering from occupational diseases due to long-term exposure to high-concentration dust environments is significantly reduced. At the same time, major safety accidents such as coal dust explosions that may be caused are effectively prevented, and the safety of the mine working environment and the level of health protection for workers are comprehensively improved.

[0063] Based on the above embodiment, the process of obtaining the VOC index is described. Figure 2 This is a flow chart of obtaining VOC index provided by the embodiment of the present application. Figure 2 As shown, the method includes the following steps:

[0064] S201 , preprocessing the VOC concentration data to obtain target concentration data.

[0065] Optionally, the VOC concentration data may be subjected to multi-scale decomposition to obtain decomposed VOC data; and the decomposed VOC data may be normalized based on the molecular mass corresponding to the decomposed VOC data to obtain target concentration data.

[0066] Optionally, the Discrete Wavelet Transform (DWT) can be used to perform multi-scale decomposition on the VOC concentration data, decomposing the data into components in different frequency ranges, thereby effectively extracting key features from the signal and removing noise. Specifically, DWT captures the main trends and overall changes in the data through low-frequency components (approximate signals), and reflects rapid changes or emergencies through high-frequency components (detail signals). Multi-scale decomposition can identify and isolate useful information in sensor data while suppressing high-frequency noise such as mechanical vibration, environmental interference, or instantaneous outliers, thereby improving signal stability and analysis accuracy. This process provides refined characteristic signals for subsequent analysis, which helps to optimize the generation of indicators such as the volatile organic compound index.

[0067] In some implementations, the computational expression for performing multi-scale decomposition of the acquired raw data using DWT is as follows:

[0068] C′ i (t) = DWT low (C i (t))

[0069] Among them, C i (t) is the VOC concentration data, t is the sampling time, i is the type index of volatile organic compounds; DWT low It is the low-frequency component in DTW, used to extract the main features; C′ i (t) is the decomposed VOC data obtained after processing, which reflects the low-frequency characteristic concentration sequence of the i-th volatile organic compound.

[0070] Furthermore, the decomposed VOC data is normalized. The contribution of different volatile organic compounds to the volatile organic compound index is related to their molecular weight. In this embodiment, normalization is performed based on the molecular weight of the volatile organic compounds. The calculation expression for the normalization is as follows:

[0071]

[0072] Among them, C i (t) is the normalized target concentration data; M i is the molecular mass of the i-th volatile organic compound.

[0073] It can be understood that the purpose of molecular mass normalization of the raw data of volatile organic compound concentration in this embodiment is to eliminate the impact caused by differences in molecular mass of different compounds, thereby making their contribution to the overall volatile organic compound index more scientific and reasonable; due to the wide variety of volatile organic compounds, the molecular masses of different compounds (such as methane 16g / mol, benzene 78g / mol) may vary greatly. Direct use of concentration data will cause the contribution of compounds with larger molecular mass to the index to be amplified, while ignoring the relative amount of their actual release in the environment. Therefore, through normalization, the concentration of each compound is standardized to the same dimension according to its molecular mass. This can not only reflect its actual release ratio, but also avoid the bias caused by differences in chemical composition characteristics, thereby more accurately evaluating the environmental impact and dynamic change trend of different volatile organic compounds.

[0074] S202 , determining dynamic incremental data according to the difference between the target concentration data and the target concentration data at the previous sampling moment.

[0075] Optionally, the method for obtaining dynamic incremental data may be:

[0076]

[0077] Where, ΔC″ i(t) is the dynamic incremental data; C″ i (t) is the target concentration data at the current sampling time t; C″ i (t-Δt) is the target concentration data at the previous sampling time t-Δt; ∈ is a small constant used to prevent calculation errors caused by the denominator being zero.

[0078] S203: Determine the VOC index based on the dynamic incremental data.

[0079] Optionally, the dynamic incremental data can be exponentially adjusted to obtain target incremental data; the target incremental data can be expressed as |ΔC″ i (t)| α , α is an exponential adjustment parameter, which is a power exponent used to nonlinearly amplify the influence of a certain variable. Its function is to enhance the response to high change rates or extreme values through nonlinear adjustment, while reducing the sensitivity to small changes. The application of the adjustment parameter in this embodiment makes the index more prominent in the significant volatile organic compound release behavior in the environment by enhancing the contribution of highly volatile compounds. For example, when α>1, compounds with large concentration changes will have a greater weight on the index, which is especially important for quickly identifying abnormal release events. Therefore, the setting of α can ensure a balance between system sensitivity and robustness. The larger its value, the more sensitive the model is to sudden changes in VOC concentration. It is often used in safety warning scenarios. The typical value range is 1.0-3.0, and it can be flexibly set according to the fitting accuracy of historical monitoring data, system fault tolerance requirements and application scenario characteristics.

[0080] Furthermore, the environmental weight of the VOC data is determined; the environmental weight is used to measure the potential hazards of different volatile organic compounds to the environment and human health. The value is based on the toxicity level of the substance (such as acute toxicity, carcinogenicity), environmental residual characteristics, national and international limit standards (such as GB 3095, WHO reference concentration) and the frequency and concentration ratio of the substance in actual monitoring. The weight is usually set between 0 and 1 in a normalized manner and determined by expert experience or multi-indicator comprehensive evaluation methods (such as hierarchical analysis).

[0081] Furthermore, the target incremental data is weighted and summed based on the environmental weight to obtain the VOC index. Optionally, the calculation of the VOC index can be expressed as:

[0082]

[0083] Wherein, V represents the VOC index; w i is the environmental weight of the i-th volatile organic compound; |ΔC″ i (t)| α Incremental data for the target.

[0084] It's understandable that a higher VOC index value indicates a higher concentration of volatile organic compounds per unit volume of air. This generally indicates that the organic-bearing ore layer has undergone thermal decomposition due to high temperatures, friction, or other mechanical effects, releasing large amounts of volatile organic compounds. Conversely, a low VOC index value or no significant fluctuations indicates that the ore layer has not undergone significant thermal decomposition and has not released volatile organic compounds.

[0085] In some implementations, a neural network model may be trained based on the above-mentioned VOC index acquisition process, and the trained neural network model may be used to calculate the VOC index, thereby improving the acquisition efficiency and calculation accuracy of the VOC index.

[0086] In this embodiment, when acquiring VOC data, the VOC concentration data is first preprocessed to obtain target concentration data, thereby avoiding bias caused by differences in chemical composition characteristics, thereby more accurately evaluating the environmental impact and dynamic change trend of different volatile organic compounds. According to the difference between the current target concentration data and the target concentration data at the previous sampling moment, the dynamic incremental data is determined, and the VOC index is determined based on the dynamic incremental data, which more intuitively reflects whether there is a large-scale release of volatile organic compounds, and obtains a more accurate VOC index for subsequent evaluation of the dust variation coefficient.

[0087] Based on the above embodiment, the process of obtaining the optical refractive index of particles is described. Figure 3 This is a flow chart of obtaining the optical refractive index of particles provided in the embodiment of the present application. Figure 3 As shown, the method includes the following steps:

[0088] S301 , irradiating a fully mechanized excavation site with a characteristic light source and determining an absorption coefficient of particulate matter at the fully mechanized excavation site to the characteristic light source and a scattering coefficient of the particulate matter based on the wavelength of the characteristic light source.

[0089] Optionally, the suspended particulate matter can be irradiated by a multi-wavelength light source (such as visible light, near-infrared light), and the scattered light and transmitted light intensity after passing through the particulate matter are recorded at the same time, that is, the incident light intensity and output light intensity when the current light source is irradiating are recorded; for example, a light source emitting unit (such as visible light, near-infrared) can be deployed, and the light source beam irradiates the suspended particulate matter passing through the target area; during the light beam penetration process, the particulate matter produces wavelength-dependent absorption and scattering effects on light of different wavelengths; the output intensity and incident intensity after penetration are collected for comparative analysis, and the absorption coefficient and scattering coefficient of the particulate matter are inferred based on the intensity changes in multiple spectral bands.

[0090] It can be understood that the output intensity refers to the intensity value of the light received by the detector after passing through the suspended particles in the optical monitoring system. It is the comprehensive performance of the transmitted light and scattered light generated by the interaction between light and particles. That is, after irradiating the comprehensive excavation site, the particles will absorb, scatter and refract the light, causing the original light intensity to change. The intensity of the light source absorbed and scattered by the particles at the comprehensive excavation site reflects the optical properties of the particles, including the absorption capacity and scattering behavior of light of different wavelengths. It is usually captured by multi-wavelength or multi-angle optical detection equipment and recorded in the form of a spectrum or intensity distribution; the absorption coefficient of the particles at the comprehensive excavation site to the characteristic light source and the scattering coefficient of the particles are determined based on the incident light intensity and the output light intensity.

[0091] Optionally, the absorption coefficient and scattering coefficient may be obtained as follows:

[0092] I out (λ)=I in (λ)·e -τ(λ) S(λ)

[0093] Among them, I out (λ) is the output intensity of the characteristic light source with wavelength λ; I in (λ) is the incident intensity of the characteristic light source with a wavelength of λ; τ(λ) is the absorption coefficient of the particle to the characteristic wavelength light; S(λ) is the scattering coefficient of the particle; and e is a natural constant.

[0094] It is understandable that the absorption coefficient and scattering coefficient of particles for light of different wavelengths can be inferred under multi-wavelength conditions to evaluate them. A nonlinear equation set can be constructed through multi-spectral measurements, and inversion estimation can be performed in combination with particle size distribution, scattering theory or trained regression models to quantify the physical response characteristics of particles to light.

[0095] The absorption coefficient of particulate matter for light of a characteristic wavelength is a parameter that describes the ability of particulate matter to absorb light energy when interacting with light of a characteristic wavelength. It reflects the efficiency of particulate matter in converting light energy into heat or other forms of energy, and is usually closely related to the composition, size, surface characteristics and wavelength of the particulate matter. The magnitude of the absorption coefficient determines the degree of attenuation of light intensity passing through the particulate matter and is an important indicator for evaluating the optical properties of particulate matter. In mineral layer monitoring, when volatile organic compounds (such as those released from organic mineral layers) are adsorbed on the surface of particulate matter, the absorption coefficient will change significantly due to the new chemical or physical properties. Therefore, by monitoring the dynamic changes in the absorption coefficient, the concentration and properties of volatile substances released from the mineral layer can be indirectly reflected, providing a basis for environmental control and mineral layer dynamic analysis.

[0096] The scattering coefficient of particulate matter is a parameter that quantifies the ability of particles to scatter light away from its original propagation direction to other directions when irradiated with light of a characteristic wavelength. The scattering coefficient depends on the size, shape, internal structure and composition of the particles, as well as the wavelength of light. The size of the scattering coefficient affects the distribution characteristics of light in the detection window, and thus affects the measurement accuracy of the optical dust sensor. In a comprehensive excavation environment, volatile organic compounds released at high temperatures may condense into fine aerosol particles. These particles will significantly enhance the scattering effect, resulting in an increase in the scattering coefficient. By analyzing the scattering coefficient, abnormal particle behavior caused by mineral pyrolysis can be identified, providing technical support for the dynamic adjustment of dust control and ventilation optimization strategies.

[0097] S302: Obtain refractive index parameters of the particles, and determine the specific refractive index of the particles according to the refractive index parameters.

[0098] The refractive index parameters include the real refractive index, the imaginary refractive index and the medium refractive index.

[0099] In some implementations, the medium refractive index can be approximated by looking up the ambient medium in a table, representing the ratio of the refractive index of the particle to the surrounding medium, and representing the comparison of optical properties between the particle and the medium.

[0100] In some implementations, the real and imaginary refractive indices can be obtained by inversion calculation based on multi-band light intensity measurement results combined with Mie scattering or interference models. This inversion process usually uses nonlinear fitting, least squares method, or pre-trained models to extract the optical refraction and absorption coefficients that can best explain the measured spectral changes. This is a key indirect derivation link in the analysis of particle optical properties. The real refractive index represents the particle's ability to refract light and is an inherent optical property of the particle. It is related to the particle's material composition, density, and wavelength of light. The imaginary refractive index represents the particle's ability to absorb light energy, also known as the absorption coefficient, and is a non-negligible part of the particle's optical behavior.

[0101] Optionally, a first difference may be determined based on the real refractive index and the imaginary refractive index; and a ratio of the first difference to the refractive index of the medium is calculated as the relative refractive index. In this embodiment, the relative refractive index may be calculated as follows:

[0102]

[0103] Among them, m r is the specific refractive index; n p is the real refractive index; n m is the refractive index of the medium; k p is the imaginary refractive index; j is the imaginary unit.

[0104] The specific refractive index is a parameter that describes the refracting ability of a substance (such as particulate matter) relative to another reference medium (usually air or vacuum). It is the ratio of the two refractive indices and reflects the relative difference in optical properties between the two substances. The real and imaginary refractive indices of particulate matter describe two core characteristics of the interaction between particulate matter and light, respectively, and are part of the complex form of the particulate refractive index. The real refractive index indicates the influence of particulate matter on the propagation speed of light, that is, the refractive power of light when propagating through particulate matter, and mainly reflects the density and chemical composition of the particulate matter. The higher the value, the slower the propagation speed of light in the particulate matter. The imaginary refractive index describes the ability of particulate matter to absorb light energy and represents the attenuation characteristics of light when propagating through particulate matter. The larger the imaginary refractive index, the stronger the particulate matter's ability to absorb light. Together, the two determine the refraction, absorption, and scattering behavior of particulate matter and are important parameters for quantifying the optical properties of particulate matter and analyzing its composition, surface characteristics, and environmental changes.

[0105] The Michelson interferometer method is a precision measurement technique that uses a Michelson interferometer to detect the phase difference of light waves. Its basic principle is to split monochromatic light into two beams, one of which passes through the detection medium (such as suspended particulate matter) and the other serves as a reference beam, ultimately forming interference fringes on the interferometer screen. By analyzing the movement and changes of the fringes, the phase change, optical path difference, and refractive index of light as it propagates through the particles can be accurately calculated. The reflectance ratio method evaluates the refractive properties of particles by measuring the ratio of the reflected light intensity on the particle surface. It determines the particle's ability to refract light by measuring the proportional change in the reflected light intensity. Combining these two methods can simultaneously obtain the real and imaginary parts of the particle's refractive index, fully describing its optical properties.

[0106] Combining Michelson interferometry and the reflectance ratio method allows for precise measurement of the specific refractive index of particles in specific media, a crucial parameter for evaluating their physical properties. The specific refractive index not only reflects the particles' ability to refract and absorb light, but also indirectly reveals their composition and surface properties. During comprehensive excavation operations, when volatile organic compounds (VOCs) are released from the ore layer, these substances may adsorb on the surface of particles or form new particles, causing their specific refractive index to change significantly. By calculating the specific refractive index, these dynamic changes can be identified, providing a scientific basis for monitoring the thermal release behavior of the ore layer, optimizing environmental control strategies, and improving the accuracy of dust detection.

[0107] S303: Obtain the scattering intensity of particles to light in different directions.

[0108] In some implementations, the scattering amplitude function of parallel polarized light and the scattering amplitude function of vertically polarized light can be obtained. The scattering amplitude function is the core physical quantity that describes the interaction between light and particulate matter under different polarization states. Based on the Mie scattering theory, by inputting parameters such as particle size distribution, complex refractive index and wavelength, the function value can be numerically solved using a mathematical model. Alternatively, through actual measurement, a laser multi-angle polarization scattering device can be used to obtain the intensity of parallel and vertically polarized light at multiple scattering angles, and then the corresponding amplitude distribution function can be calculated. In this embodiment, the scattering amplitude function of parallel polarized light can be expressed as S1, and the scattering amplitude function of vertically polarized light can be expressed as S2.

[0109] Based on the scattering angle and the scattering amplitude function of parallel polarized light, a first scattering value is determined. In this embodiment, the scattering angle is substituted into the scattering amplitude function of parallel polarized light to obtain the first scattering value S1(θ); based on the scattering angle and the scattering amplitude function of vertically polarized light, a second scattering value is determined. In this embodiment, the scattering angle is substituted into the scattering amplitude function of vertically polarized light to obtain the second scattering value S2(θ).

[0110] Furthermore, the scattering intensity of the particles to the light at the current scattering angle is obtained based on the first scattering value and the second scattering value. The scattering intensity can be expressed as:

[0111]

[0112] Where P(θ) represents the scattering intensity, which is the normalized quantitative value of the scattered light intensity at the scattering angle when the particles interact with light.

[0113] The scattering amplitude function S1(θ) of parallel-polarized light describes the scattering amplitude distribution function of polarized light whose electric field direction is parallel to the scattering plane when light is scattered by particles. The scattering plane is the plane formed by the directions of the incident light and the scattered light. S1(θ) reflects the scattering intensity of parallel-polarized light by particles at specific angles and is an important indicator of the optical properties of particles (such as refractive index, absorptivity, and particle size distribution). Analyzing S1(θ) can reveal the shape and optical symmetry of particles and is particularly suitable for detecting the presence of special substances (such as adsorption layers of volatile organic compounds) on the particle surface. By measuring the distribution of S1(θ), the scattering behavior of particles and their potential impact on environmental optical sensors can be evaluated.

[0114] The scattering amplitude function S2(θ) of vertically polarized light describes the scattering amplitude distribution function of polarized light with the electric field direction perpendicular to the scattering plane when light is scattered on particles. S2(θ) mainly reflects the influence of the optical asymmetry and internal structure of particles on light scattering. Unlike S1(θ), S2(θ) is more sensitive to the non-spherical structure and changes in the complex refractive index of particles. Analysis of S2(θ) can detect the surface roughness of particles and their internal complexity, such as whether they contain a non-uniform condensation layer of volatile substances. Through the analysis of S2(θ), the light scattering pattern of particles can be more finely evaluated, providing more in-depth data support for environmental monitoring and dynamic particle behavior analysis.

[0115] S304: Determine the optical refractive index of the particles according to the absorption coefficient, the scattering coefficient, the specific refractive index, and the scattering intensity.

[0116] Optionally, the real part value of the specific refractive index can be obtained, and the product of the real part value, the scattering intensity and the scattering coefficient can be calculated; the ratio of the product result to the absorption coefficient is used as the integrand, and the integrand is integrated to obtain the optical refractive index of the particle.

[0117] Alternatively, the calculation of the optical refractive index of the particle can be expressed as:

[0118]

[0119] Wherein, P represents the optical refractive index of particles; represents the real part of the specific refractive index; is the integrand; max and λ min are the maximum and minimum wavelengths extracted from the effective spectral range of the output light intensity; they define the spectral analysis range when calculating the optical refractive index of particles, ensuring that only spectral data with sufficient intensity and signal-to-noise ratio are used for integration and modeling. Specifically, the output light intensity in the detection window will show different characteristic distributions as the wavelength changes, and λ max and λ min The wavelength boundary corresponds to the light intensity significantly above background noise and can stably capture changes in the refractive and scattering characteristics of particles. Selecting a reasonable wavelength range can reduce the impact of useless or interfering data, improve the accuracy and robustness of the calculation results, and avoid error propagation caused by external light source characteristics or insufficient sensor sensitivity.

[0120] In some implementations, neural network training can be performed based on the above process of obtaining the optical refractive index of particulate matter, and the optical refractive index of particulate matter in subsequent monitoring cycles can be obtained based on the trained neural network model to improve calculation efficiency and accuracy.

[0121] In this embodiment, a characteristic light source is used to illuminate the comprehensive excavation site, and based on the input intensity and output intensity of the characteristic light source, the absorption coefficient and scattering coefficient of the particulate matter for the characteristic light source are determined, and the specific refractive index of the particulate matter is further obtained to reflect the relative difference in optical properties between the two substances. The scattering intensity of the particulate matter for light in different scattering angle directions is obtained, and then the optical refractive index of the particulate matter is obtained based on multiple parameters such as the scattering intensity, scattering coefficient, absorption coefficient and specific refractive index. In the calculation process, a reasonable wavelength range is selected to reduce the influence of useless or interfering data, improve the accuracy and robustness of the calculation results, and avoid error diffusion caused by external light source characteristics or insufficient sensor sensitivity, thereby ensuring the calculation accuracy of the optical refractive index of the particulate matter.

[0122] Based on the above embodiments, Figure 4 This is a flow chart of another ventilation control method for dust suppression provided in an embodiment of the present application. Figure 4 As shown, the method includes the following steps:

[0123] S401, obtaining dust data information at the fully mechanized excavation site.

[0124] In the embodiment of the present application, the implementation method of step S401 can be implemented by any of the methods in the embodiments of the present disclosure, which is not limited here and will not be described in detail.

[0125] S402: Preprocess the VOC concentration data to obtain target concentration data.

[0126] In the embodiment of the present application, the implementation method of step S402 can be implemented by any of the methods in the embodiments of the present disclosure, which is not limited here and will not be repeated.

[0127] S403: Determine dynamic incremental data based on the difference between the target concentration data and the target concentration data at the previous sampling moment.

[0128] In the embodiment of the present application, the implementation method of step S403 can be implemented by any of the methods in the embodiments of the present disclosure, which is not limited here and will not be described in detail.

[0129] S404: Determine the VOC index based on the dynamic incremental data.

[0130] In the embodiment of the present application, the implementation method of step S404 can be implemented by any of the methods in the embodiments of the present disclosure, which is not limited here and will not be described in detail.

[0131] S405 , irradiating the fully mechanized excavation site with a characteristic light source and determining an absorption coefficient of particulate matter at the fully mechanized excavation site to the characteristic light source and a scattering coefficient of the particulate matter based on the wavelength of the characteristic light source.

[0132] In the embodiment of the present application, the implementation method of step S405 can be implemented by any of the methods in the embodiments of the present disclosure, which is not limited here and will not be described in detail.

[0133] S406: Obtain refractive index parameters of the particles, and determine the specific refractive index of the particles according to the refractive index parameters.

[0134] In the embodiment of the present application, the implementation method of step S406 can be implemented by any of the methods in the embodiments of the present disclosure, which is not limited here and will not be repeated.

[0135] S407: Obtain the scattering intensity of the particles to light in different directions.

[0136] In the embodiment of the present application, the implementation method of step S407 can be implemented by any of the methods in the various embodiments of the present disclosure, which is not limited here and will not be repeated.

[0137] S408 , determining the optical refractive index of the particles according to the absorption coefficient, the scattering coefficient, the specific refractive index, and the scattering intensity.

[0138] In the embodiment of the present application, the implementation method of step S408 can be implemented by any of the methods in the embodiments of the present disclosure, which is not limited here and will not be repeated.

[0139] S409: Determine the dust variation coefficient at the comprehensive excavation site based on the VOC index and the optical refractive index of the particulate matter.

[0140] It can be understood that during the monitoring period, the larger the optical refractive index performance value of the particles generated after analyzing the physical parameters of the refraction and scattering characteristics of suspended particles to light, the more significant the change in the refraction and scattering characteristics of the suspended particles, which is usually closely related to the release of volatile organic compounds. After being released from the mineral layer at high temperature, volatile organic compounds may condense to form aerosols or be adsorbed on the surface of dust particles, thereby changing the physical properties of the particles, especially the performance value of their optical refractive index. Therefore, the higher the index performance value, the more it can reflect the increase in the concentration of volatile organic compounds and their impact on the optical properties of the particles. On the contrary, if the index performance value is low, it indicates that no significant release of organic compounds or changes in the characteristics of the particles occurred during the monitoring period.

[0141] In some implementations, the dust variation coefficient is calculated as:

[0142]

[0143] Wherein, D is the dust variation coefficient; V is the VOC index; p is the optical refractive index index of the particulate matter; f1 is the preset proportional coefficient of the VOC index; f2 is the preset proportional coefficient of the optical refractive index of the particulate matter.

[0144] Based on the above calculation formula, it can be seen that the larger the volatile organic compound index expression value generated after analyzing the concentration level of volatile organic compounds in the air, and the larger the particle optical refractive index expression value generated after analyzing the physical parameters of the refraction and scattering characteristics of suspended particulate matter to light, the larger the dust variation coefficient expression value generated after analyzing the dust change data information obtained at the comprehensive excavation site under the detection window, indicating that the organic-containing ore layer generates high temperature due to mechanical action during the comprehensive excavation process, and undergoes significant thermal decomposition reaction, releasing a large amount of volatile organic compounds (such as methane, benzene, etc.). At the same time, these volatile substances may condense or adhere to suspended particulate matter, changing the optical properties of the particles. Conversely, it indicates that the organic-containing ore layer is not subjected to obvious high temperature during the comprehensive excavation process, no significant thermal decomposition reaction occurs, and no obvious volatile organic compounds are released.

[0145] In this embodiment, f1 and f2 are weight parameters used to balance the influence of the volatile organic compound index and the particle optical refractive index index on the dust variation coefficient; adjustments are made based on the relative importance of these two indices to dust changes in actual application scenarios. For example, if in some cases the change of volatile organic compounds has a greater impact on the abnormal dust concentration, f1 can be set to a higher value to enhance the contribution of the volatile organic compound index to the dust variation coefficient; on the contrary, if the change of the particle optical refractive index index is more important, the value of f2 is increased; the preset proportional coefficient is usually obtained through historical data analysis or empirical model to ensure that the dust variation coefficient can accurately reflect the dynamic characteristics of dust changes at the comprehensive excavation site.

[0146] S410: Determine a control strategy based on the dust variation coefficient, and perform ventilation according to the control strategy.

[0147] In some implementations, a preset dust variation coefficient reference threshold can be obtained, and based on the dust variation coefficient reference threshold, whether the current dust environment is a high-risk environment is determined. For example, if the dust variation coefficient is less than the preset dust variation coefficient reference threshold, the current dust environment is determined to be a low-risk environment; correspondingly, if the dust variation coefficient is greater than or equal to the preset dust variation coefficient reference threshold, the current dust environment is determined to be a high-risk environment.

[0148] Optionally, in response to the dust variation coefficient being less than a preset dust variation coefficient reference threshold, the control strategy is determined to be a low-risk dust ventilation strategy; that is, when the current dust environment is a low-risk environment, the control strategy is determined to be a low-risk dust ventilation strategy, for example, maintaining the current ventilation conditions and not taking special measures when the risk is low.

[0149] Optionally, in response to the dust variation coefficient being greater than or equal to a preset dust variation coefficient reference threshold, the dust variation coefficients of multiple consecutive detection cycles are obtained to obtain the average value and standard deviation of the dust variation coefficients of multiple detection cycles; that is, the dust variation coefficients of multiple detection cycles are continuously obtained from the current detection cycle to obtain a coefficient set, which includes the dust variation coefficients of at least two detection cycles; further, the average value and standard deviation of multiple detection cycles in the coefficient set are calculated, and the average value and standard deviation are continued to be compared with the corresponding average value reference threshold and standard deviation reference threshold to obtain the corresponding control strategy.

[0150] In some implementations, in response to the average value being greater than or equal to the average value reference threshold, the control strategy is determined to be a high-risk emergency warning ventilation strategy; in this embodiment, when the average value is greater than or equal to the average value reference threshold, it is determined that the current environment is a persistent high-risk dust environment, and the high-risk emergency warning ventilation strategy can be to issue an emergency red warning, increase the air volume to dilute the concentration of harmful gases and dust, reduce suspended particulate matter in the air, suspend comprehensive excavation operations and evacuate personnel until the dust concentration returns to a safe range.

[0151] In some implementations, in response to the average value being less than the average value reference threshold and the standard deviation being greater than or equal to the standard deviation reference threshold, the control strategy is determined to be a high-risk general warning ventilation strategy; in this embodiment, when the average value is less than the average value reference threshold and the standard deviation is greater than or equal to the standard deviation reference threshold, it is determined that the current environment is an unstable high-risk dust environment, and the high-risk general warning ventilation strategy can be to issue a general orange warning, while increasing the air volume to dilute the concentration of harmful gases and dust, reduce suspended particulate matter in the air, suspend comprehensive excavation operations and evacuate personnel until the dust concentration returns to a safe range.

[0152] In some implementations, in response to the average value being less than the average value reference threshold and the standard deviation being less than the standard deviation reference threshold, the control strategy is determined to be a high-risk continuous monitoring ventilation strategy; in this embodiment, when the average value is less than the average value reference threshold and the standard deviation is less than the standard deviation reference threshold, it is determined that the current environment is a sudden high-risk dust environment, and the high-risk continuous monitoring ventilation strategy is to continuously record relevant information such as the dust variation coefficient. The dust may be discharged by the ventilation system in a short time and will not cause dust accumulation, so no early warning prompt is issued.

[0153] In this embodiment, dust data information of the comprehensive excavation site is obtained, and the VOC concentration data is preprocessed to obtain target concentration data, thereby avoiding bias caused by differences in chemical composition characteristics, thereby more accurately evaluating the environmental impact and dynamic change trend of different volatile organic compounds, and determining the dynamic incremental data based on the difference between the current target concentration data and the target concentration data at the previous sampling moment, and determining the VOC index based on the dynamic incremental data, which more intuitively reflects whether there is a large-scale release of volatile organic compounds; the comprehensive excavation site is illuminated by a characteristic light source, and based on the input intensity and output intensity of the characteristic light source, the absorption coefficient and scattering coefficient of the particulate matter to the characteristic light source are determined, and the specific refractive index of the particulate matter is further obtained to reflect the relative difference in optical properties between the two substances, and the scattering intensity of the particulate matter to light in different scattering angles is obtained, and then according to the scattering intensity The optical refractive index of particles is obtained by combining the VOC index and the optical refractive index of particles to determine the dust variation coefficient of the comprehensive excavation site. The dust variation coefficient is used to reflect the current dust environment of the comprehensive excavation site, so as to determine whether it is a low-risk dust environment or a high-risk dust environment, and distinguish between continuous high-risk, unstable high-risk or sudden high-risk situations. Different control strategies are formulated for different risk dust environments, and ventilation control is carried out with the corresponding control strategies. Through this intelligent and dynamic control method, the accumulation risk of dust concentration is greatly reduced, and the probability of workers suffering from occupational diseases due to long-term exposure to high-concentration dust environment is significantly reduced. At the same time, major safety accidents such as coal dust explosions that may be caused are effectively prevented, and the safety of the mine working environment and the health protection level of workers are comprehensively improved.

[0154] In order to implement the above embodiment, the present application also proposes a ventilation control device for dust suppression.

[0155] Figure 5 This is a schematic diagram of the structure of a ventilation control device for dust suppression provided in an embodiment of the present application. Figure 5 As shown, the ventilation control device 500 for dust suppression includes:

[0156] The first acquisition module 501 is used to acquire dust data information at the fully mechanized excavation site, the dust data information including volatile organic compound (VOC) concentration data and illumination data affected by suspended particulate matter;

[0157] A second acquisition module 502 is configured to determine a VOC index based on an incremental change in VOC concentration data in the dust data information;

[0158] The third acquisition module 503 is used to determine the optical refractive index of the particles based on the characteristic index of the illumination data in the dust data information;

[0159] The fourth acquisition module 504 is used to determine the dust variation coefficient at the comprehensive excavation site based on the VOC index and the optical refractive index of the particulate matter;

[0160] The ventilation control module 505 is used to determine a control strategy based on the dust variation coefficient and perform ventilation according to the control strategy.

[0161] Furthermore, in a possible implementation of the embodiment of the present application, the second obtaining module 502 includes:

[0162] Preprocess the VOC concentration data to obtain target concentration data;

[0163] Determine dynamic incremental data based on the difference between the target concentration data and the target concentration data at the previous sampling moment;

[0164] Determine the VOC index based on dynamic incremental data.

[0165] Furthermore, in a possible implementation of the embodiment of the present application, the second obtaining module 502 includes:

[0166] Perform multi-scale decomposition on VOC concentration data to obtain decomposed VOC data;

[0167] Based on the molecular mass corresponding to the decomposed VOC data, the decomposed VOC data is normalized to obtain the target concentration data.

[0168] Furthermore, in a possible implementation of the embodiment of the present application, the second obtaining module 502 includes:

[0169] Perform exponential adjustment on dynamic incremental data to obtain target incremental data;

[0170] Determine the environmental weight of VOC data;

[0171] The target incremental data is weighted and summed based on the environmental weight to obtain the VOC index.

[0172] Furthermore, in a possible implementation of the embodiment of the present application, the third obtaining module 503 includes:

[0173] Based on the characteristic light source irradiating the fully mechanized excavation site and the wavelength of the characteristic light source, the absorption coefficient of the particulate matter at the fully mechanized excavation site to the characteristic light source and the scattering coefficient of the particulate matter are determined;

[0174] Obtaining refractive index parameters of the particles and determining the specific refractive index of the particles based on the refractive index parameters, wherein the refractive index parameters include a real refractive index, an imaginary refractive index, and a medium refractive index;

[0175] Obtain the scattering intensity of particles on light in different directions;

[0176] The optical refractive index of the particles is determined based on the absorption coefficient, scattering coefficient, specific refractive index and scattering intensity.

[0177] Furthermore, in a possible implementation of the embodiment of the present application, the third obtaining module 503 includes:

[0178] determining a first difference based on the real refractive index and the imaginary refractive index;

[0179] The ratio of the first difference to the refractive index of the medium is calculated as the relative refractive index.

[0180] Furthermore, in a possible implementation of the embodiment of the present application, the third obtaining module 503 includes:

[0181] Obtaining a scattering amplitude function of parallel polarized light and a scattering amplitude function of perpendicular polarized light;

[0182] determining a first scattering value based on the scattering angle and the scattering amplitude function of the parallel polarized light;

[0183] determining a second scattering value based on the scattering angle and the scattering amplitude function of the vertically polarized light;

[0184] The scattering intensity of the particles to the light at the current scattering angle is obtained according to the first scattering value and the second scattering value.

[0185] Furthermore, in a possible implementation of the embodiment of the present application, the third obtaining module 503 includes:

[0186] Obtaining the real part value of the specific refractive index and calculating the product of the real part value, the scattering intensity and the scattering coefficient;

[0187] The ratio of the product result and the absorption coefficient is used as the integrand, and the integrand is integrated to obtain the optical refractive index of the particles.

[0188] Furthermore, in a possible implementation of the embodiment of the present application, the fourth obtaining module 504 includes:

[0189] The calculation of dust variation coefficient is:

[0190]

[0191] Wherein, D is the dust variation coefficient; V is the VOC index; P is the optical refractive index index of the particulate matter; f1 is the preset proportional coefficient of the VOC index; f2 is the preset proportional coefficient of the optical refractive index of the particulate matter.

[0192] Furthermore, in a possible implementation of the embodiment of the present application, the ventilation control module 505 includes:

[0193] In response to the dust variation coefficient being less than a preset dust variation coefficient reference threshold, determining the control strategy to be a low-risk dust ventilation strategy;

[0194] In response to the dust variation coefficient being greater than or equal to a preset dust variation coefficient reference threshold, obtaining the dust variation coefficients of a plurality of consecutive detection cycles to obtain an average value and a standard deviation of the dust variation coefficients of the plurality of detection cycles;

[0195] In response to the average value being greater than or equal to the average value reference threshold, determining the control strategy as a high-risk emergency warning ventilation strategy;

[0196] In response to the average being less than the average reference threshold and the standard deviation being greater than or equal to the standard deviation reference threshold, determining the control strategy to be a high-risk ordinary warning ventilation strategy;

[0197] In response to the average being less than a average reference threshold and the standard deviation being less than a standard deviation reference threshold, determining that the control strategy is a high-risk continuous monitoring ventilation strategy.

[0198] It should be noted that the above explanation of the embodiment of the ventilation control method for dust suppression is also applicable to the ventilation control device for dust suppression in this embodiment, and will not be repeated here.

[0199] In an embodiment of the present application, dust data information of a comprehensive excavation site is obtained, and a VOC index is determined based on incremental changes in VOC concentration data in the dust data information, and the VOC index is used to reflect the concentration of volatile organic compounds in the air; based on characteristic indicators of illumination data in the dust data information, an optical refractive index index of particles is determined, and the optical refractive index index of particles is used to reflect the current particle situation; the VOC index and the optical refractive index of particles are combined to determine a dust variation coefficient of the comprehensive excavation site, and the dust variation coefficient is used to reflect the current dust environment of the comprehensive excavation site, thereby determining whether it is a low-risk dust environment or a high-risk dust environment, and formulating different control strategies for different risk dust environments, and performing ventilation control with the corresponding control strategies. Through this intelligent and dynamic control method, the risk of dust concentration accumulation is greatly reduced, and the probability of workers suffering from occupational diseases due to long-term exposure to high-concentration dust environments is significantly reduced. At the same time, major safety accidents such as coal dust explosions that may be caused are effectively prevented, and the safety of the mine working environment and the health protection level of workers are comprehensively improved.

[0200] In order to implement the above embodiments, the present application also proposes an electronic device, comprising: a processor, and a memory communicatively connected to the processor; the memory stores computer-executable instructions; the processor executes the computer-executable instructions stored in the memory to implement the method provided by the above embodiments.

[0201] In order to implement the above embodiments, the present application also proposes a computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, they are used to implement the methods provided by the above embodiments.

[0202] In order to implement the above embodiments, the present application also proposes a computer program product, including a computer program, which implements the methods provided by the above embodiments when executed by a processor.

[0203] The collection, storage, use, processing, transmission, provision and disclosure of user personal information involved in this application are in compliance with relevant laws and regulations and do not violate public order and good morals.

[0204] It is important to note that personal information collected from users should be used for legitimate and reasonable purposes and should not be shared or sold beyond these legitimate uses. Furthermore, such collection / sharing should be conducted only after receiving the user's informed consent, including but not limited to notifying the user to read the user agreement / user notice and sign an agreement / authorization that includes the relevant user information before using the feature. Furthermore, any necessary steps must be taken to safeguard and secure access to such personal data and ensure that others with access to personal data comply with its privacy policies and procedures.

[0205] This application contemplates providing implementations that allow users to selectively block the use or access of personal information data. Specifically, this disclosure contemplates providing hardware and / or software to prevent or block access to such personal information data. Risks can be minimized by limiting data collection and deleting data once it is no longer needed. Furthermore, where applicable, such personal information can be de-identified to protect user privacy.

[0206] In the descriptions of the foregoing embodiments, the reference terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" mean that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, unless they are mutually inconsistent.

[0207] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of the technical features being referred to. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of such features. Throughout the description of this application, "plurality" means at least two, for example, two, three, etc., unless otherwise specifically defined.

[0208] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code comprising one or more executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may be performed out of the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by those skilled in the art to which the embodiments of the present application belong.

[0209] The logic and / or steps represented in the flowcharts or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing the logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (e.g., a computer-based system, a system including a processor, or other system that can fetch and execute instructions from an instruction execution system, apparatus, or device). For purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include the following: an electrical connection with one or more wires (electronic devices), a portable computer disk cartridge (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and programmable read-only memory (EPROM or flash memory), fiber optic devices, and a portable compact disc read-only memory (CDROM). Furthermore, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or processing it in another suitable manner if necessary, and then storing it in a computer memory.

[0210] It should be understood that various parts of the present application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented using hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof can be used to implement: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application-specific integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0211] Those skilled in the art will understand that all or part of the steps in the method of the above embodiment can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable storage medium. When the program is executed, it includes one or a combination of the steps of the method embodiment.

[0212] In addition, the functional units in the various embodiments of the present application may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into a module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0213] The storage medium mentioned above may be a read-only memory, a magnetic disk, or an optical disk, etc. Although the embodiments of the present application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present application. Persons skilled in the art may make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present application.

Claims

1. A ventilation control method for dust suppression, characterized in that: The method comprises: Obtain dust data information at the fully mechanized excavation site, including volatile organic compound (VOC) concentration data and illumination data affected by suspended particulate matter; Determining a VOC index based on incremental changes in VOC concentration data in the dust data information; Determining the optical refractive index of the particles based on characteristic indicators of the illumination data in the dust data information; Determining the dust variation coefficient at the comprehensive excavation site according to the VOC index and the optical refractive index of the particulate matter; A control strategy is determined based on the dust variation coefficient, and ventilation is performed according to the control strategy.

2. The method according to claim 1, characterized in that The determining of the VOC index based on the incremental change of the VOC concentration data in the dust data information includes: Preprocessing the VOC concentration data to obtain target concentration data; determining dynamic incremental data based on a difference between the target concentration data and the target concentration data at a previous sampling moment; The VOC index is determined based on the dynamic incremental data.

3. The method according to claim 2, characterized in that The preprocessing of the VOC concentration data to obtain target concentration data includes: Performing multi-scale decomposition on the VOC concentration data to obtain decomposed VOC data; The decomposed VOC data is normalized based on the molecular mass corresponding to the decomposed VOC data to obtain target concentration data.

4. The method according to claim 2, characterized in that Determining the VOC index based on the dynamic incremental data includes: Performing exponential adjustment on the dynamic incremental data to obtain target incremental data; Determine the environmental weight of VOC data; The target incremental data is weightedly summed based on the environmental weight to obtain the VOC index.

5. The method according to claim 1, wherein The determining of the optical refractive index of the particles based on the characteristic index of the illumination data in the dust data information includes: Illuminating the fully mechanized excavation site with a characteristic light source and determining, based on the wavelength of the characteristic light source, an absorption coefficient of particulate matter at the fully mechanized excavation site to the characteristic light source and a scattering coefficient of the particulate matter; Obtaining refractive index parameters of the particles, and determining the specific refractive index of the particles according to the refractive index parameters, wherein the refractive index parameters include a real refractive index, an imaginary refractive index, and a medium refractive index; Obtain the scattering intensity of particles on light in different directions; The optical refractive index of the particle is determined according to the absorption coefficient, the scattering coefficient, the specific refractive index and the scattering intensity.

6. The method according to claim 5, characterized in that Determining the specific refractive index of the particles according to the refractive index parameter includes: determining a first difference based on the real refractive index and the imaginary refractive index; The ratio of the first difference to the refractive index of the medium is calculated as the relative refractive index.

7. The method according to claim 5, characterized in that The obtaining of the scattering intensity of particles to light in different directions includes: Obtaining a scattering amplitude function of parallel polarized light and a scattering amplitude function of perpendicular polarized light; determining a first scattering value based on a scattering angle and a scattering amplitude function of the parallel polarized light; determining a second scattering value based on a scattering angle and a scattering amplitude function of the vertically polarized light; The scattering intensity of the particles to the light at the current scattering angle is obtained according to the first scattering value and the second scattering value.

8. The method according to claim 5, characterized in that Determining the optical refractive index of the particle according to the absorption coefficient, the scattering coefficient, the specific refractive index, and the scattering intensity includes: Obtaining a real part value of the specific refractive index, and calculating a product of the real part value, the scattering intensity, and the scattering coefficient; The ratio of the product result to the absorption coefficient is used as an integrand, and an integration operation is performed on the integrand to obtain the optical refractive index of the particle.

9. The method according to any one of claims 1 to 8, characterized in that Determining the dust variation coefficient at the comprehensive excavation site according to the VOC index and the particulate matter optical refractive index index includes: The calculation of the dust variation coefficient is: Wherein, D is the dust variation coefficient; V is the VOC index; p is the optical refractive index index of the particulate matter; f1 is the preset proportional coefficient of the VOC index; and f2 is the preset proportional coefficient of the optical refractive index of the particulate matter.

10. The method according to claim 9, characterized in that The determining of the control strategy based on the dust variation coefficient includes: In response to the dust variation coefficient being less than a preset dust variation coefficient reference threshold, determining that the control strategy is a low-risk dust ventilation strategy; In response to the dust variation coefficient being greater than or equal to a preset dust variation coefficient reference threshold, obtaining the dust variation coefficient for a plurality of consecutive detection cycles to obtain an average value and a standard deviation of the dust variation coefficient for the plurality of detection cycles; In response to the average value being greater than or equal to an average value reference threshold, determining that the control strategy is a high-risk emergency warning ventilation strategy; In response to the average being less than an average reference threshold and the standard deviation being greater than or equal to a standard deviation reference threshold, determining that the control strategy is a high-risk general warning ventilation strategy; In response to the average being less than an average reference threshold and the standard deviation being less than a standard deviation reference threshold, the control strategy is determined to be a high-risk continuous monitoring ventilation strategy.

Images