Coal gangue solid waste treatment system and control method thereof

Abstract

The present application provides a kind of coal gangue solid waste treatment system and control method thereof, it is related to coal gangue processing technical field.The coal gangue solid waste treatment system and control method thereof, including raw material detection and grading module: be equipped with on-line X-ray fluorescence spectrometer, laser particle size analyzer and grading bin, for the fast component detection (detection data includes SiO2, Al2O3, Fe2O3 And sulfide content) and according to " high sulfur (> 5%), high clay (> 30%), normal " grading storage, and detection data is transmitted to intelligent monitoring module;Intelligent component pretreatment module is equipped with clay separation unit and sulfide removal unit, wherein clay separation unit uses " selective flocculation-hydraulic cyclone " technology.Advantages such as intelligent target removal, parameter self-adaptive control, improve product pass rate to more than 98%, reduce energy consumption by 15-20%, reduce manual intervention by more than 60%, realize efficient and stable resource utilization.

Description

Technical Field

[0001] This invention relates to the field of coal gangue treatment technology, specifically to a coal gangue solid waste treatment system and its control method. Background Technology

[0002] Coal gangue is a major solid waste generated during coal mining and washing, and its emissions are enormous.

[0003] Currently, there are numerous technologies for the comprehensive utilization of coal gangue, such as mine backfilling, land reclamation, combustion power generation, and the preparation of building materials. However, these technologies generally have significant drawbacks. Faced with the continuous and rapid growth of the total amount of coal gangue, it is urgent to develop efficient, adaptable, and environmentally friendly coal gangue solid waste treatment systems and control methods. Summary of the Invention

[0004] Technical problems to be solved To address the shortcomings of existing technologies, this invention provides a coal gangue solid waste treatment system and its control method, which solves the problems of difficult separation of complex impurities such as high clay and high sulfides in coal gangue, unstable product quality, high energy consumption, and the need for frequent manual adjustments in traditional systems.

[0005] Technical solution

[0006] To achieve the above objectives, the present invention provides the following technical solution: a coal gangue solid waste treatment system, characterized in that it comprises: Raw material testing and grading module: Equipped with an online X-ray fluorescence spectrometer, a laser particle size analyzer, and a grading silo, it is used to perform rapid component testing on coal gangue (test data includes SiO2, Al2O3, Fe2O3, and sulfide content) and to grade and store it according to "high sulfur (>5%), high clay (>30%), and conventional", and transmit the test data to the intelligent monitoring module; The intelligent component pretreatment module is equipped with a clay separation unit and a sulfide removal unit. The clay separation unit adopts the "selective flocculation-hydraulic cyclone" technology, and the critical value of the separation particle size of its hydrocyclone is calculated according to formula (1): d 50 =k×(D 2 ×Δρ×P) n (1) In the formula, d 50 For the critical particle size to be separated (mm), k is the equipment coefficient (0.8-1.2), D is the hydrocyclone diameter (m), Δρ is the solid-liquid density difference (g / cm³), P is the inlet pressure (MPa), and n is the exponent (-0.25 to -0.3). The sulfide removal unit adopts a combination of magnetic separation and flotation. The amount of flotation reagent is dynamically adjusted according to formula (2): Q=α×S×β (2) where Q is the amount of xanthate collector (g / t), α is the coefficient (5-8), S is the sulfide content in coal gangue (%), and β is the flotation concentration correction coefficient (0.8-1.2). The processed purified gangue (clay <10%, sulfide <2%) is transported to the deep crushing and sorting module. The separated clay and sulfide are collected separately, and this module receives control commands from the intelligent monitoring module to adjust the process parameters. The deep crushing and sorting module automatically adjusts the crushing particle size according to formula (3) based on the characteristics of the purified gangue from the intelligent component pretreatment module: D p =k1×(C s ) k2 (3) In the formula, D p The target particle size after crushing (mm) is given by k1, which is the basic coefficient (5-8), and C is the target particle size after crushing. s The SiO2 content (%) in the purified gangue is given, and k2 is the correction index (-0.1 to -0.2). Combustible materials and inorganic minerals are separated by heavy medium separators and wind separators. Combustible materials are transported to the energy recovery module, while inorganic minerals are transported to the resource utilization module. The resource utilization module includes a brick production line and a roadbed filler processing line. The material self-adjustment unit of the brick production line calculates the amount of auxiliary material added according to formula (4): M=k3×(A / S-γ)×M0 (4) where M is the amount of lime auxiliary material added (kg), k3 is the proportional coefficient (0.3-0.5), A / S is the mass ratio of Al2O3 to SiO2 in the pretreated gangue, γ is the target A / S value (0.2-0.3), and M0 is the total mass of gangue (kg). This module returns defective products to the deep crushing and sorting module, and its operating parameters are controlled by the intelligent monitoring module. The energy recovery module uses the sorted combustibles to generate electricity or heat. The amount of boiler desulfurizing agent (limestone) used is calculated according to formula (5): G=k4×Q×S a In the formula ×η(5), G is the amount of limestone used (kg / h), k4 is the calcium-sulfur ratio coefficient (1.1-1.3), Q is the amount of combustible material burned (t / h), and S a η represents the sulfur content of combustibles (%), and η represents the target value for desulfurization efficiency (90%-95%). This module provides power and waste heat to other modules in the system, and its operating parameters are controlled by the intelligent monitoring module.

[0007] Preferably, the AI ​​algorithm of the intelligent monitoring module is based on the BP neural network model. It obtains the mapping relationship between the coefficients (k, k1, k2, k3, k4) and the coal gangue components in formulas (1)-(5) through training with historical data, and outputs the optimized coefficient values ​​in real time. The formula is as follows: k=f(X) (6) where X is the multidimensional feature vector output by the raw material detection module (including SiO2, Al2O3, and sulfide content), and f(·) is the trained BP neural network function.

[0008] Preferably, the density parameter of the heavy medium separator in the deep crushing and sorting module is dynamically calibrated according to formula (7): ρ=ρ0+Δρ×(C p / 100)(7) In the formula, ρ is the actual sorting density (g / cm³), ρ0 is the basic density (1.8-2.0g / cm³), Δρ is the correction coefficient (0.1-0.3), C p The predicted content of combustibles (%).

[0009] A method for controlling the treatment of coal gangue solid waste includes the following steps: The raw material detection and grading module performs component detection on coal gangue, obtains feature vector X, and transmits it to the intelligent monitoring module; The intelligent monitoring module calculates the coefficients of each process parameter formula using formula (6), sends instructions to the intelligent component pretreatment module, adjusts the hydrocyclone parameters according to formula (1), and adjusts the flotation reagent dosage according to formula (2). The deep crushing and sorting module receives the purified gangue, adjusts the crushing particle size according to formula (3), and calibrates the heavy medium sorting density according to formula (7); The resource utilization module adjusts the amount of auxiliary materials added according to formula (4), and the energy recovery module controls the amount of desulfurizing agent added according to formula (5); The intelligent monitoring module collects the operating data of each module in real time and optimizes the coefficients in formulas (1)-(7) through AI algorithm iteration to achieve adaptive control of the whole system.

[0010] Beneficial effects

[0011] This invention provides a coal gangue solid waste treatment system and its control method. It has the following beneficial effects: 1. This invention provides a coal gangue solid waste treatment system and its control method. By adding an intelligent component pretreatment module, it can target and separate different types of impurities, effectively removing harmful impurities such as clay and sulfides. Actual testing shows that it can handle complex coal gangue with a clay content exceeding 30% and a sulfide content >5%, significantly increasing the product qualification rate from 85% to 98% compared to traditional systems. In the resource utilization module, such as a brick-making production line, auxiliary materials can be automatically added according to the SiO2 / Al2O3 ratio of the pretreated gangue, ensuring that the compressive strength of the bricks is ≥15MPa, greatly improving the stability and reliability of product quality.

[0012] 2. This invention provides a coal gangue solid waste treatment system and its control method. Based on an AI algorithm introduced through an intelligent monitoring module, the system achieves self-optimization of parameters across the entire "raw material-process-product" chain. According to the component data from the raw material detection module, the system automatically generates optimal process parameters for each module, such as precisely controlling crushing speed and flotation reagent dosage, thus avoiding unnecessary energy consumption. Simultaneously, the system's adaptive control reduces manual intervention; statistics show that manual intervention is reduced by more than 60%, significantly lowering labor costs. The system's overall energy consumption is reduced by 15-20%, achieving a dual breakthrough in high-efficiency energy saving and intelligent production. Attached Figure Description

[0013] Figure 1 This is a schematic diagram of the system flow of the present invention. Detailed Implementation

[0014] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0015] This invention provides a coal gangue solid waste treatment system and its control method. Taking a coal gangue treatment example from a certain mining area (the coal gangue in this mining area has an average sulfur content of 6.2% and a clay content of 35%, belonging to the high-sulfur and high-clay type), the system operation process and parameters are described in detail.

[0016] This embodiment uses, as follows: Figure 1 The core equipment and initial parameters of each module of the coal gangue solid waste treatment system shown in Table 1 are as follows:

[0017] The system operation process and parameter adjustment procedure are as follows: Step 1: Raw material testing and grading Coal gangue enters the raw material testing module via a conveyor belt. Online XRF spectrometer analysis yielded the following composition data: SiO2=52%, Al2O3=28%, sulfur content 6.2%, clay content 35%; laser particle size analyzer measured d... 50 =25mm.

[0018] The intelligent monitoring module determines that the material is classified as "high sulfur + high clay" and instructs the grading silo to transport it to the intelligent component pretreatment module.

[0019] Step 2: Intelligent component pretreatment Clay separation: The intelligent monitoring module calculates the hydrocyclone coefficient k=1.0 using formula (6) (based on BP neural network learning of features of 6.2% sulfur and 35% clay), and substitutes it into formula (1): d 50 =1.0×(0.5 2 ×(2.6-1.0)×0.3) -0.28 ≈0.075mm (ensure that clay particles <0.075mm are separated).

[0020] After actual operation, the clay content decreased from 35% to 9.8%.

[0021] Sulfide removal: The amount of xanthate used is calculated according to formula (2) Q=6×6.2×1.1 (β is taken as 1.1 due to slightly higher concentration)≈41g / t. After flotation, the sulfur content is reduced to 1.8% (meeting the requirement of <2%).

[0022] Step 3: Deep crushing and sorting Crushing particle size adjustment: The intelligent monitoring module calculates the particle size using formula (3) based on the purified gangue SiO2=52%. D p =6×(52) -0.15 ≈4.8mm (the actual output particle size is 4.7mm, as the crusher speed is automatically adjusted to 1200r / min).

[0023] Heavy media sorting: predicted combustible content C p =12%, calibrate the density according to formula (7): ρ = 1.9 + 0.2 × (12 / 100) = 1.924 g / cm³, and the purity of combustibles after sorting is increased to 85% (calorific value 2200 kcal / kg).

[0024] Step 4: Resource utilization (brick production) After pretreatment, the ratio of gangue A / S is approximately 28% / 52% ≈ 0.54, which is higher than the target value of 0.25. The amount of lime to be added is calculated according to formula (4): M = 0.4 × (0.54 - 0.25) × 1000 kg (assuming a total mass of gangue of 1000 kg) ≈ 116 kg, which means the addition ratio is 11.6%.

[0025] The compressive strength of the masonry after curing was tested to be 16.8 MPa (meeting the requirement of ≥15 MPa).

[0026] Step 5: Energy Recovery and Pollution Control The combustible material has a combustion rate of 0.8 t / h and a sulfur content of 1.8%. The amount of limestone required is calculated according to formula (5): G = 1.2 × 0.8 × 1.8 × 92% ≈ 1.6 t / h (actual dosage is 1.6 t / h, and the SO2 concentration in the flue gas after desulfurization is 35 mg / m³, which meets the standard).

[0027] Wastewater is treated by MBR and then reused in the crushing process, with a reuse rate of 90%; dust emission concentration is <10mg / m³.

[0028] Finally, compared with conventional systems that do not employ this invention, the key performance indicators of this embodiment are shown in Table 2 below:

[0029] Thus, this embodiment achieves efficient processing of high-sulfur, high-clay coal gangue through the formulaic parameter control of the intelligent module (such as formulas 1-7) and AI algorithm optimization, significantly improving processing efficiency and product quality.

[0030] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their likenesses.

Claims

1. A coal gangue solid waste treatment system, characterized in that, include: Raw material testing and grading module: Equipped with an online X-ray fluorescence spectrometer, laser particle size analyzer, and grading bins, it is used for rapid component testing of coal gangue. The test data includes the content of SiO2, Al2O3, Fe2O3, and sulfides, and is stored according to the classification of "high sulfur, high clay, and conventional". The test data is transmitted to the intelligent monitoring module, where high sulfur is defined as sulfide content >5% and high clay is defined as clay content >30%. The intelligent component pretreatment module is provided with a clay separation unit and a sulfide removal unit, wherein the clay separation unit adopts a "selective flocculation-hydraulic cyclone" technology, and a cyclone separation particle size critical value is calculated according to formula (1): d 50 =k×(D 2 ×Δρ×P) n (1) wherein d 50 is a separation critical particle size, in mm, k is an equipment coefficient of 0.8-1.2, D is a cyclone diameter, in m, Δρ is a solid-liquid density difference, in g / cm³, P is an inlet pressure, in MPa, and n is an index of-0.25 to-0.3; The sulfide removal unit adopts a combination of magnetic separation and flotation. The amount of flotation reagent is dynamically adjusted according to formula (2): Q = α × S × β (2) where Q is the amount of xanthate collector in g / t, α is a coefficient of 5-8, S is the sulfide content in coal gangue and is expressed as a percentage, and β is the flotation concentration correction coefficient of 0.8-1.

2. The processed purified gangue is transported to the deep crushing and sorting module, where the separated clay and sulfides are collected separately. This module receives control commands from the intelligent monitoring module to adjust process parameters. The purified gangue has a clay content of <10% and a sulfide content of <2%. The deep crushing and sorting module automatically adjusts the crushing particle size according to formula (3) based on the characteristics of the purified gangue from the intelligent component pretreatment module: (3) In the formula, D p The target particle size after crushing is in mm, k1 is the basic coefficient of 5-8, and C s The SiO2 content in the purified gangue is expressed as a percentage, with k2 being a correction index of -0.1 to -0.

2. Combustible materials and inorganic minerals are separated by heavy medium separators and wind separators. Combustible materials are transported to the energy recovery module, while inorganic minerals are transported to the resource utilization module. The resource utilization module includes a brick production line and a roadbed filler processing line. The material self-adaptive adjustment unit of the brick production line calculates the amount of auxiliary material added according to formula (4): M=k3×(A / S-γ)×M0 (4) where M is the amount of lime auxiliary material added, in kg, k3 is the proportional coefficient 0.3-0.5, A / S is the mass ratio of Al2O3 to SiO2 in the pretreated gangue, γ is the target A / S value 0.2-0.3, and M0 is the total mass of gangue, in kg. This module returns defective products to the deep crushing and sorting module, and its operating parameters are controlled by the intelligent monitoring module. The energy recovery module uses the sorted combustibles to generate electricity or heat. The amount of desulfurizing agent used in its boiler is calculated according to formula (5): G=k4×Q×S a In the formula ×η(5), G is the amount of limestone used, in kg / h; k4 is the calcium-sulfur ratio coefficient, 1.1-1.3; Q is the amount of combustible material burned, in t / h; S a The sulfur content of the combustible material is expressed as a percentage, and η is the target value for desulfurization efficiency of 90%-95%, where the boiler desulfurizing agent is limestone. This module provides power and waste heat to other modules in the system, and its operating parameters are controlled by the intelligent monitoring module.

2. The coal gangue solid waste treatment system according to claim 1, characterized in that: The AI ​​algorithm of the intelligent monitoring module is based on the BP neural network model. It obtains the mapping relationship between the coefficients k, k1, k2, k3, k4 and the coal gangue components in formulas (1)-(5) through training with historical data, and outputs the optimized coefficient values ​​in real time. The formula is as follows: k=f(X) (6) where X is the multi-dimensional feature vector output by the raw material detection module, which includes the content of SiO2, Al2O3 and sulfides, and f(·) is the trained BP neural network function.

3. The coal gangue solid waste treatment system according to claim 2, characterized in that: The density parameter of the heavy medium separator in the deep crushing and sorting module is dynamically calibrated according to formula (7): ρ=ρ0+Δρ×(C p / 100)(7) In the formula, ρ is the actual sorting density, in g / cm³, ρ0 is the basic density of 1.8-2.0 g / cm³, Δρ is the correction coefficient of 0.1-0.3, C p This represents the predicted content of combustibles, expressed as a percentage.

4. A method for controlling the treatment of coal gangue solid waste, applied to the coal gangue solid waste treatment system described in claim 3, characterized in that, Includes the following steps: S1. The raw material detection and grading module performs component detection on coal gangue, obtains feature vector X, and transmits it to the intelligent monitoring module; S2. The intelligent monitoring module calculates the coefficients of each process parameter formula using formula (6), sends instructions to the intelligent component pretreatment module, adjusts the hydrocyclone parameters according to formula (1), and adjusts the flotation reagent dosage according to formula (2). S3. The deep crushing and sorting module receives the purified gangue, adjusts the crushing particle size according to formula (3), and calibrates the heavy medium sorting density according to formula (7). S4. The resource utilization module adjusts the amount of auxiliary materials added according to formula (4), and the energy recovery module controls the amount of desulfurizing agent added according to formula (5); S5. The intelligent monitoring module collects the operating data of each module in real time and optimizes the coefficients in formulas (1)-(7) through AI algorithm iteration to achieve adaptive control of the whole system.

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