Coal gangue solid waste treatment system and control method thereof

Abstract

The invention provides a coal gangue solid waste treatment system and a control method thereof, and relates to the technical field of coal gangue treatment. The coal gangue solid waste treatment system comprises a raw material detection and grading module which is provided with an online X-ray fluorescence spectrophotometer, a laser particle size analyzer and a grading stock bin and is used for carrying out rapid component detection (detection data comprises SiO2, Al2O3, Fe2O3 and sulfide content) on coal gangue and carrying out grading storage according to high sulfur (more than 5%), high clay (more than 30%) and conventional conditions; the detection data is transmitted to the intelligent monitoring module; the intelligent component pretreatment module is provided with a clay separation unit and a sulfide removal unit, and the clay separation unit adopts a selective flocculation-hydraulic cyclone technology. The method has the advantages of intelligent targeted impurity removal and parameter self-adaptive regulation and control, the product qualification rate is increased to 98% or above, energy consumption is reduced by 15-20%, manual intervention is reduced by 60% or above, and efficient and stable resource utilization is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of coal gangue treatment, and in particular to a coal gangue solid waste treatment system and a control method thereof. Background Art

[0002] Gangue, the primary solid waste generated during coal mining and washing, produces significant amounts of waste. According to the China Coal Industry Association, as of 2022, my country's gangue stockpile reached approximately 7.5 billion tons, with an annual increase of 500 to 800 million tons. Gangue production accounts for approximately 8% of coal production. The long-term accumulation of gangue not only occupies valuable land resources but also, due to its sulfur content, is prone to spontaneous combustion, releasing harmful gases such as sulfur dioxide and nitrogen oxides, severely polluting the atmosphere. Heavy metals and other harmful substances contained in gangue can also seep into the soil and groundwater through rainwater leaching, causing soil pollution and deteriorating water quality, posing a serious threat to the surrounding ecological environment.

[0003] Currently, numerous technologies exist for the comprehensive utilization of gangue, such as mine backfill, land reclamation, combustion for power generation, and the production of building materials. However, these technologies generally suffer from significant drawbacks: Mine backfill and land reclamation require significant manpower and material resources for site planning and construction, and improper handling during the backfill process can lead to geological problems such as ground collapse. While combustion for power generation can partially recover energy, it is inefficient, and the large amount of waste gas generated by gangue combustion requires complex and costly exhaust gas treatment equipment to meet environmental standards. Regarding the production of building materials, the complex and diverse composition of gangue, which varies significantly from mining area to mining area, makes it difficult for existing processing technologies to accurately adapt to its variability, resulting in unstable product quality. For example, in the production of building materials such as bricks, problems such as insufficient strength and poor durability often occur. In particular, when complex impurities such as clay and sulfides are mixed into the gangue, existing crushing and sorting modules struggle to accurately separate them, severely impacting the quality of subsequent resource-based products and the stable operation of the energy recovery module. Frequent manual adjustments to process parameters are also required, significantly reducing production efficiency and system stability. Faced with the continued rapid growth of the total amount of coal gangue, it is urgent to develop an efficient, adaptable and environmentally friendly coal gangue solid waste treatment system and its control method. Summary of the Invention

[0004] Technical problems solved

[0005] In response to the shortcomings of the existing technology, the present invention provides a coal gangue solid waste treatment system and a control method thereof, which solves the problems of difficulty in separating complex impurities such as high clay and high sulfide in coal gangue, and the unstable product quality, high energy consumption and frequent manual adjustment of traditional systems.

[0006] Technical Solution

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions: A coal gangue solid waste treatment system, comprising:

[0008] Raw material detection and grading module: equipped with an online X-ray fluorescence spectrometer, a laser particle size analyzer, and a grading silo, it is used to quickly detect the components of coal gangue (test data includes SiO2, Al2O3, Fe2O3 and sulfide content) and classify and store them according to "high sulfur (>5%), high clay (>30%), and conventional" categories, and transmit the test data to the intelligent monitoring module;

[0009] 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-hydrocyclone" technology, and the critical value of the cyclone separation particle size is calculated according to formula (1): d 50 =k×(D 2 ×Δρ×P) n (1) In the formula, d 50 is the critical particle size for separation (mm), k is the equipment coefficient (0.8-1.2), D is the diameter of the cyclone (m), Δρ is the density difference between solid and liquid (g / cm 3 ), P is the inlet pressure (MPa), and n is the exponent (-0.25 to -0.3);

[0010] The sulfide removal unit adopts a "magnetic separation + flotation" combined process, and the flotation agent dosage is dynamically adjusted according to formula (2): Q = α × S × β (2) where Q is the dosage of xanthate collector (g / t), α is the coefficient (5-8), S is the sulfide content in the gangue (%), and β is the flotation concentration correction coefficient (0.8-1.2);

[0011] The treated purified gangue (clay <10%, sulfide <2%) is transported to the deep crushing and sorting module, where the separated clay and sulfide are collected separately. The module also receives control instructions from the intelligent monitoring module to adjust process parameters.

[0012] The deep crushing and sorting module automatically adjusts the crushing particle size according to the characteristics of the gangue after purification by the intelligent component pretreatment module according to formula (3): D p =k1×(C s ) k2 (3) In the formula, D p is the target particle size after crushing (mm), k1 is the basic coefficient (5-8), C s is the SiO2 content (%) in the purified gangue, k2 is the correction index (-0.1 to -0.2);

[0013] The combustibles and inorganic minerals are separated by heavy medium separators and wind separators. The combustibles are transported to the energy recovery module, and the inorganic minerals are transported to the resource utilization module.

[0014] The resource utilization module includes a brick production line and a roadbed filler processing line. The 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 (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 the gangue (kg);

[0015] This module returns unqualified products to the deep crushing and sorting module, and the operating parameters are controlled by the intelligent monitoring module;

[0016] The energy recovery module uses the combustibles obtained from the sorting to generate electricity or provide heat. The amount of desulfurizer (limestone) used in the boiler is calculated according to formula (5): G = k4 × Q × S a ×η(5) where 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 combustibles burned (t / h), and S a is the sulfur content of the combustible material (%), and η is the target value of desulfurization efficiency (90%-95%);

[0017] This module provides electricity and waste heat to other modules in the system, and its operating parameters are regulated by the intelligent monitoring module.

[0018] Preferably, the AI ​​algorithm of the intelligent monitoring module is based on the BP neural network model, and the mapping relationship between the coefficients (k, k1, k3, k4) in formulas (1)-(5) and the coal gangue components is obtained through historical data training, and the optimized coefficient values ​​are output in real time. The formula is as follows: k=f(X)(6) where X is the multidimensional feature vector (including SiO2, Al2O3, and sulfide content) output by the raw material detection module, and f(·) is the trained BP neural network function.

[0019] Preferably, the density parameter of the heavy medium separator of the deep crushing and sorting module is dynamically calibrated according to formula (7): ρ=ρ0+Δρ×(C p / 100)(7)where ρ is the actual sorting density (g / cm 3 ), ρ0 is the basic density (1.8-2.0g / cm 3 ), Δρ is the correction coefficient (0.1-0.3), C p is the predicted combustible content (%).

[0020] A method for controlling the treatment of coal gangue solid waste comprises the following steps:

[0021] The raw material detection and classification module detects the components of the gangue, obtains the feature vector X and transmits it to the intelligent monitoring module;

[0022] The intelligent monitoring module calculates the coefficients of each process parameter formula through formula (6), sends instructions to the intelligent component pretreatment module, adjusts the cyclone parameters according to formula (1), and adjusts the flotation agent dosage according to formula (2);

[0023] The deep crushing and sorting module receives the purified gangue, adjusts the crushing particle size according to formula (3), and calibrates the heavy medium separation density according to formula (7);

[0024] The resource utilization module adjusts the amount of auxiliary materials added according to formula (4), and the energy recovery module controls the amount of desulfurizer added according to formula (5);

[0025] The intelligent monitoring module collects the operating data of each module in real time, and iteratively optimizes the coefficients in formulas (1)-(7) through AI algorithms to achieve adaptive control of the entire system.

[0026] Beneficial effects

[0027] The present invention provides a gangue solid waste treatment system and a control method thereof, which has the following beneficial effects:

[0028] 1. The present invention provides a coal gangue solid waste treatment system and its control method. By adding an intelligent component pretreatment module, it can perform targeted separation of different impurity types and effectively remove harmful impurities such as clay and sulfide. After actual testing, it can process complex coal gangue with a clay content exceeding 30% and a sulfide content greater than 5%. Compared with traditional systems, the product qualification rate has been significantly improved from 85% to 98%. In resource utilization modules, such as brick production lines, auxiliary materials can be automatically replenished based on the SiO2 / Al2O3 ratio of the pretreated gangue to ensure that the compressive strength of the brick body is ≥15MPa, greatly improving the stability and reliability of product quality.

[0029] 2. The present invention provides a coal gangue solid waste treatment system and control method thereof. Based on the AI ​​algorithm introduced by the intelligent monitoring module, the system realizes self-optimization of parameters in the entire chain of "raw materials-process-product". Based on the component data of the raw material detection module, the optimal process parameters of each module are automatically generated, such as precise control of crushing speed and flotation agent dosage, thus avoiding unnecessary energy consumption. At the same time, the system's adaptive control reduces manual intervention. According to statistics, manual intervention has been reduced by more than 60%, significantly reducing labor costs and reducing the overall energy consumption of the system by 15-20%, achieving a dual breakthrough in efficient energy saving and intelligent production. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 Schematic diagram of the system flow of the present invention. DETAILED DESCRIPTION

[0031] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0032] An embodiment of the present invention provides a coal gangue solid waste treatment system and a control method thereof. Based on an example of coal gangue treatment in 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.

[0033] This embodiment adopts Figure 1 The core equipment and initial parameters of each module of the gangue solid waste treatment system shown in Table 1 are as follows:

[0034]

[0035]

[0036] The system operation process and parameter adjustment process are as follows:

[0037] Step 1: Raw material testing and grading

[0038] The gangue enters the raw material detection module via a conveyor belt, and the online XRF spectrometer detects the composition data: SiO2 = 52%, Al2O3 = 28%, sulfur content 6.2%, clay content 35%; the laser particle size analyzer measures d50 = 25mm.

[0039] The intelligent monitoring module determines that it is a "high sulfur + high clay" grade and instructs the grading silo to transport it to the intelligent component pretreatment module.

[0040] Step 2: Smart component preprocessing

[0041] Clay separation: The intelligent monitoring module calculates the cyclone coefficient k = 1.0 through formula (6) (based on the BP neural network's feature learning of sulfur 6.2% and clay 35%), and substitutes it into formula (1):

[0042] 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).

[0043] After actual operation, the clay content dropped from 35% to 9.8%.

[0044] Sulfide removal: The dosage of xanthate is calculated according to formula (2): Q = 6 × 6.2 × 1.1 (β is taken as 1.1 due to slightly higher concentration) ≈ 41 g / t. After flotation, the sulfur content is reduced to 1.8% (meeting the requirement of <2%).

[0045] Step 3: Deep Crushing and Sorting

[0046] Crushing particle size adjustment: The intelligent monitoring module calculates the crushing particle size according to the SiO2 of the purified gangue = 52% through formula (3):

[0047] D p =6×(52) -0 · 15 ≈4.8mm (the crusher speed is automatically adjusted to 1200r / min, and the actual discharge particle size is 4.7mm).

[0048] Heavy medium separation: predicted combustible content C p =12%, calibrated density according to formula (7): ρ = 1.9 + 0.2 × (12 / 100) = 1.924 g / cm 3 After sorting, the purity of combustible materials is increased to 85% (calorific value 2200kcal / kg).

[0049] Step 4: Resource Utilization (Brick Production)

[0050] After pretreatment, the gangue A / S is 28% / 52%≈0.54, which is 0.25 higher than the target value. The amount of lime added is calculated according to formula (4):

[0051] M = 0.4 × (0.54-0.25) × 1000 kg (assuming the total mass of the gangue is 1000 kg) ≈ 116 kg, that is, the addition ratio is 11.6%.

[0052] The compressive strength of the masonry after curing was tested to be 16.8MPa (meeting the requirement of ≥15MPa).

[0053] Step 5: Energy Recovery and Pollution Control

[0054] The combustion rate of combustible materials is 0.8t / h, the sulfur content is 1.8%, and the limestone dosage is calculated according to formula (5): G = 1.2 × 0.8 × 1.8 × 92% ≈ 1.6t / h (the actual dosage is 1.6t / h, and the SO2 concentration of the flue gas after desulfurization is 35mg / m 3 , meet the standards).

[0055] Wastewater is treated by MBR and then reused in the crushing process, with a reuse rate of 90%; dust emission concentration is less than 10mg / m 3 .

[0056] Finally, compared with the traditional system that does not adopt the present invention, the key indicators of this embodiment are shown in Table 2 below:

[0057]

[0058] Therefore, this embodiment achieves efficient processing of high-sulfur and 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.

[0059] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A coal gangue solid waste treatment system, characterized in that: include: Raw material detection and grading module: Equipped with an online X-ray fluorescence spectrometer, a laser particle size analyzer, and a grading silo, it is used to quickly detect the composition of coal gangue (test data includes SiO2, Al2O3, Fe2O3, and sulfide content), and store it according to "high sulfur (>5%), high clay (>30%), and conventional" classifications. The test data is then transmitted 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-hydrocyclone" technology, and the critical value of the cyclone separation particle size is calculated according to formula (1): d 50 =k×(D 2 ×Δρ×P) n (1) In the formula, d 50 is the critical particle size for separation (mm), k is the equipment coefficient (0.8-1.2), D is the diameter of the cyclone (m), Δρ is the density difference between solid and liquid (g / cm 3 ), P is the inlet pressure (MPa), and n is the exponent (-0.25 to -0.3); The sulfide removal unit adopts a "magnetic separation + flotation" combined process, and the flotation agent dosage is dynamically adjusted according to formula (2): Q = α × S × β (2) where Q is the xanthate collector dosage (g / t), α is the coefficient (5-8), S is the sulfide content in the gangue (%), and β is the flotation concentration correction coefficient (0.8-1.2); The treated purified gangue (clay <10%, sulfide <2%) is transported to the deep crushing and sorting module, where the separated clay and sulfide are collected separately. The module also receives control instructions from the intelligent monitoring module to adjust process parameters. The deep crushing and sorting module automatically adjusts the crushing particle size according to the characteristics of the gangue after purification by the intelligent component pretreatment module according to formula (3): Where D p is the target particle size after crushing (mm), k1 is the basic coefficient (5-8), C s is the SiO2 content (%) in the purified gangue, k2 is the correction index (-0.1 to -0.2); The combustibles and inorganic minerals are separated by heavy medium separators and wind separators. The combustibles are transported to the energy recovery module, and the 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 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 (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 the gangue (kg); This module returns unqualified products to the deep crushing and sorting module, and the operating parameters are controlled by the intelligent monitoring module; The energy recovery module uses the combustibles obtained from the sorting to generate electricity or provide heat. The amount of desulfurizer (limestone) used in the boiler is calculated according to formula (5): G = k4 × Q × S a ×η(5) where 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 combustibles burned (t / h), and S a is the sulfur content of the combustible material (%), and η is the target value of desulfurization efficiency (90%-95%); This module provides electricity and waste heat to other modules in the system, and its operating parameters are regulated 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. The mapping relationship between the coefficients (k, k1, k3, k4) in formulas (1)-(5) and the coal gangue components is obtained through historical data training, and the optimized coefficient values ​​are output in real time. The formula is as follows: k = f(X)(6) where X is the multidimensional feature vector (including SiO2, Al2O3, and sulfide content) output by the raw material detection module, and f(·) is the trained BP neural network function.

3. The coal gangue solid waste treatment system according to claim 1, characterized in that: The density parameter of the heavy medium separator of the deep crushing and sorting module is dynamically calibrated according to formula (7): ρ = ρ0 + Δρ × (C p / 100)(7)where ρ is the actual sorting density (g / cm 3 ), ρ0 is the basic density (1.8-2.0g / cm 3 ), Δρ is the correction coefficient (0.1-0.3), C p is the predicted combustible content (%).

4. A method for controlling the treatment of coal gangue solid waste, characterized in that: The following steps are involved: S1. The raw material detection and classification module detects the components of the gangue, obtains the 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 cyclone parameters according to formula (1), and adjusts the flotation agent 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 separation 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 desulfurizer added according to formula (5); S5. The intelligent monitoring module collects the operating data of each module in real time, and iteratively optimizes the coefficients in formulas (1)-(7) through AI algorithms to achieve adaptive control of the entire system.

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