Self-adaptive regulation and control system and method for coal quality improvement

Abstract

The invention relates to the technical field of coal upgrading, and discloses a self-adaptive regulation and control system and method for coal upgrading, and the system comprises a coal sorting module which is used for sorting raw coal; the coal-oil slurry generation module is used for preparing coal-oil slurry from pulverized coal and circulating solvent oil; the reactant mixing module is used for adding hot high-pressure gas into the heating tank for heat exchange and temperature rise with the coal-oil slurry, and adding hot high-pressure oil into the heating tank for mixing with the coal-oil slurry; the upgrading reaction module is mixed and reacted with the heated hydrogen to generate a reaction product; the product separation module is used for separating new hot high-pressure separated gas and new hot high-pressure separated oil from reaction products; separating the new hot high-pressure separated oil to obtain a solid-state clean coal product; and the dehydration module is used for removing residual moisture of the clean coal product through the synergistic effect of centrifugal force and hot air drying, and the dried clean coal product is obtained. According to the method, multiple parameters in the coal upgrading process are optimized, and the coal upgrading effect is improved.

Description

Technical Field

[0001] This invention relates to the field of coal upgrading technology, and more specifically, to an adaptive control system and method for coal upgrading. Background Technology

[0002] With the increasing demand for energy and the rising requirements for environmental protection, the clean and efficient utilization of coal, as an important fossil energy source, has received widespread attention. Traditional coal combustion and chemical processing suffer from problems such as low calorific value, high ash content, numerous impurities, high moisture content, and incomplete combustion, directly affecting coal utilization efficiency and the quality of downstream products. Furthermore, traditional coal upgrading methods often rely on fixed process conditions, making them difficult to adapt to the actual production environment with significant differences in coal quality and complex and variable reaction conditions. This can easily lead to increased energy consumption, fluctuations in equipment load, and unstable product quality.

[0003] For example, CN116218560B discloses a method for coal hydrogenation and upgrading, which involves mixing pulverized coal with circulating solvent oil to prepare an oil-coal slurry, pressurizing it with a pressure pump, and then feeding it into a heating tank. The slurry is heated by heat exchange with hot high-temperature gas, then mixed with hot high-temperature oil, and fed into a fluidized bed reactor for hydrogenation. Finally, clean coal and coal-based oil products are obtained through high-pressure separation, a pressure-reducing tower, and solid-liquid separation. However, this type of upgrading method still has some shortcomings: the heating process of the oil-coal slurry in the heating tank mainly relies on the natural heat transfer of the hot high-temperature gas, lacking real-time monitoring of the local temperature distribution of the oil-coal slurry. The heating efficiency is difficult to accurately determine, easily leading to local overheating or uneven heating, affecting the efficiency of coal liquefaction and hydrogenation reactions; the parameters of temperature, pressure, and gas-liquid mixing uniformity in the fluidized bed reactor lack real-time feedback control, and traditional methods mainly rely on experience-based settings or manual adjustments, making it difficult to achieve long-term stable operation; and it cannot achieve real-time analysis and optimization of temperature, pressure, gas flow rate, bed state, and equipment operating status, affecting product quality stability.

[0004] Therefore, it is necessary to design an adaptive control system and method for coal upgrading to solve the problems existing in the current technology. Summary of the Invention

[0005] In view of this, the present invention proposes an adaptive control system and method for coal upgrading, aiming to solve the problems of the inability to judge, analyze and optimize various parameters in the current upgrading process, resulting in low product quality stability and high moisture content.

[0006] In one aspect, the present invention proposes an adaptive control system for coal upgrading, comprising: The coal sorting module is used to sort raw coal, remove gangue and impurities based on differences in particle size and density, and grade it to obtain high-purity sorted coal. The oil-coal slurry generation module is used to mix the coal powder and circulating solvent oil of the sorted coal in a set ratio to prepare oil-coal slurry, and to initially pressurize the oil-coal slurry. After the initial pressurization, the oil-coal slurry is added to the heating tank. The reactant mixing module is used to add hot high-density gas to the heating tank at an initial addition rate to exchange heat with the oil-coal slurry and raise its temperature; it collects the temperature value of the oil-coal slurry based on distributed optical fiber temperature monitoring, and determines whether the heating efficiency is normal based on the oil-coal slurry temperature value. When the heating efficiency is determined to be abnormal, PID control adjusts the initial addition rate of the hot high-density gas; after the heat exchange and heating are completed, hot high-density oil is added to the heating tank to mix with the oil-coal slurry; The quality improvement reaction module is used to perform secondary pressurization after mixing and to add heated hydrogen into the fluidized bed reactor for mixing and reaction. It collects the reaction temperature and pressure values ​​within the fluidized bed reactor for data preprocessing, compares the preprocessed values ​​with preset reaction conditions to determine if the operating parameters of the fluidized bed reactor need adjustment. If adjustment is required, the fluidized bed reactor is operated with the adjusted parameters. After the mixing reaction is completed, reaction products are generated. The product separation module is used to separate the reaction products into new hot high-pressure gas and new hot high-pressure oil in a hot high-pressure separator; part of the new hot high-pressure oil is sent back into the heating tank to mix with the oil-coal slurry, and the other part is sent to a pressure reducing tower for pressure separation to form mid-section oil and bottom section oil; and the bottom section oil is separated into solid clean coal products based on a solid-liquid separator. The dehydration module is used to feed the clean coal product into the dehydration equipment, and remove residual moisture through the combined action of centrifugal force and hot air drying, reducing the moisture content to a preset threshold to obtain a dry clean coal product.

[0007] Furthermore, when the coal sorting module sorts raw coal, it includes: The coal sorting module uses gravity sorting equipment, which, based on the density difference between raw coal and impurities, separates raw coal into coarse-grained coal, fine-grained coal and gangue under the action of vibrating screen. The coarse-grained coal and the fine-grained coal are respectively subjected to flotation treatment. By adding flotation reagents to adjust the surface hydrophobicity, high-calorific-value coal and low-calorific-value coal are separated. The coal sorting module monitors the ash content and particle size distribution of the sorted coal in real time. When the ash content exceeds the preset threshold or the particle size distribution is abnormal, it automatically adjusts the amplitude, frequency and reagent flow of the sorting equipment.

[0008] Furthermore, when the reactant mixing module acquires the temperature value of the oil-coal slurry based on distributed fiber optic temperature monitoring, it includes: The heating tank is equipped with the distributed optical fiber. The reactant mixing module obtains the temperature distribution of the oil-coal slurry at different locations in real time through the distributed optical fiber and converts the analog signal output by the distributed optical fiber into a digital signal through an analog-to-digital converter. The reactant mixing module sets a sampling period, and takes several temperature sampling points before and after each sampling period to form a sliding window. The average value of the digital signal within the sliding window is calculated as the current oil-coal slurry temperature value. The reactant mixing module connects the oil-coal slurry temperature values ​​obtained from each time point through the sliding window processing into a curve in chronological order to obtain the actual temperature curve.

[0009] Furthermore, when the reactant mixing module determines whether the heating efficiency is within the normal range based on the oil-coal slurry temperature value, it includes: The reactant mixing module compares and analyzes the actual temperature curve with the theoretical heating curve, aligns the two curves on the same time axis, and compares the actual oil-coal slurry temperature value on the actual temperature curve at each time point with the theoretical temperature value corresponding to the theoretical heating curve to obtain a residual value sequence; the residual value sequence is statistically processed to quantify the degree of deviation and obtain the final residual value. The reactant mixing module compares the final residual value with the residual value threshold. When the final residual value is less than or equal to the residual value threshold, the heating efficiency is determined to be in a normal state; when the final residual value is greater than the residual value threshold, the heating efficiency is determined to be in a non-normal state.

[0010] Furthermore, when the reactant mixing module PID controls the initial addition rate of the hot high-density gas, it includes: The final residual value is amplified by a certain proportion to obtain the initial correction amount; Integral regulation generates a flow correction amount based on the deviation of the accumulated temperature from the theoretical curve. Differential adjustment: The differential correction is calculated based on the rate of change of the temperature deviation. The reactant mixing module obtains a final correction value by superimposing the initial correction amount, flow rate correction amount, and differential correction amount obtained through the proportional adjustment, integral adjustment, and differential adjustment. The initial addition rate is corrected by the correction value, and the hot high-density gas is added at the corrected initial addition rate.

[0011] Furthermore, when the upgrading reaction module collects the reaction temperature and reaction pressure values ​​within the fluidized bed reactor for data preprocessing, it includes: The data preprocessing includes outlier identification and removal, signal smoothing, signal normalization, and data fusion.

[0012] Furthermore, when the quality improvement reaction module compares the pretreated reaction temperature and reaction pressure values ​​with preset reaction conditions to determine whether the operating parameters of the fluidized bed reactor need to be adjusted, it includes: The preset reaction conditions include a preset temperature range and a preset pressure range; when the reaction temperature value is within the preset temperature range and the reaction pressure value is within the preset pressure range, it is determined that the operating parameters of the fluidized bed reactor do not need to be adjusted; when the reaction temperature value is not within the preset temperature range or the reaction pressure value is not within the preset pressure range, it is determined that the operating parameters of the fluidized bed reactor need to be adjusted.

[0013] Furthermore, when it is determined that the operating parameters need to be adjusted, the upgrading reaction module operates the fluidized bed reactor with the adjusted operating parameters, including: The upgrading reaction module collects temperature data at different locations in the fluidized bed reactor to obtain the temperature distribution of the oil-coal slurry and the bed; it also collects pressure data at different locations in the fluidized bed reactor to obtain the pressure distribution of the bed; it detects the flow rates of hydrogen and hot high-density gas entering the reactor, obtains gas flow information in real time, and determines whether the set values ​​have been reached; it assesses the mixing uniformity of the oil-coal slurry and gas; it detects the movement, vibration, and height distribution of bed particles to determine whether there is sedimentation, blockage, or uneven gas passage; it detects the temperature of the auxiliary equipment heating tank, pump pressure, and valve opening to determine whether the equipment is operating normally; and it constructs multivariate detection data from the various detection results.

[0014] Furthermore, when it is determined that the operating parameters need to be adjusted, the upgrading reaction module operates the fluidized bed reactor with the adjusted operating parameters, including: The upgrading reaction module collects temperature data at different locations in the fluidized bed reactor to obtain the temperature distribution of the oil-coal slurry and the bed; it also collects pressure data at different locations in the fluidized bed reactor to obtain the pressure distribution of the bed; it detects the flow rates of hydrogen and hot high-density gas entering the reactor, obtains gas flow information in real time, and determines whether the set values ​​have been reached; it assesses the mixing uniformity of the oil-coal slurry and gas; it detects the movement, vibration, and height distribution of bed particles to determine whether there is sedimentation, blockage, or uneven gas passage; it detects the temperature of the auxiliary equipment heating tank, pump pressure, and valve opening to determine whether the equipment is operating normally; and it constructs multivariate detection data from the various detection results.

[0015] Furthermore, the dewatering module feeds the clean coal product into the dewatering equipment, and when removing residual moisture through the combined action of centrifugal force and hot air drying, it includes: The dehydration module feeds the clean coal product into a centrifugal dehydrator, where centrifugal force generated by high-speed rotation separates free water, initially reducing the moisture content. The pre-dehydrated clean coal product is then fed into a multi-stage filtration unit, where a vibrating screen and filter cloth are used for fine filtration to remove microporous moisture. The filtered clean coal product is then fed into a hot air drying tower for drying under a controllable temperature gradient. The moisture content of the product is monitored in real time, and drying is stopped when the moisture content reaches a preset threshold, at which point the dried clean coal product is output.

[0016] Compared with existing technologies, the advantages of this invention are as follows: By deploying distributed optical fibers within the heating tank, real-time temperature monitoring of the oil-coal slurry at different locations is achieved, and a precise actual temperature curve is obtained by combining this with a sliding window algorithm. By comparing the actual temperature curve with the theoretical heating curve, the heating deviation is quantified, and the hot high-temperature gas addition rate is automatically adjusted through PID control, achieving precise control of the heating process, improving heating efficiency, and avoiding overheating or underheating. Real-time monitoring of temperature, pressure, gas flow rate, and bed state within the fluidized bed reactor generates multi-dimensional detection data. A combined model of convolutional neural networks and long short-term memory networks is used to predict and analyze the deviations of various operating parameters, automatically generating optimized adjustment schemes. This achieves dynamic control of parameters such as reaction temperature, pressure, gas flow rate, and bed stirring, improving the stability and uniformity of the upgrading reaction. A temperature gradient and pressure difference are formed in the high-temperature oil within the vacuum tower, achieving effective separation of the middle and bottom sections of the oil. The bottom section oil undergoes mechanical centrifugation, filtration, and cyclone separation through a solid-liquid separator to remove residual oil, resulting in a solid clean coal product, reducing pollutant and impurity content, and improving the coal upgrading effect. In the product separation stage, the combination of a pressure reducing tower and a solid-liquid separator effectively removes residual liquid components from the oil-coal slurry, reducing the moisture and oil content in the solid coal product, thus achieving efficient coal dehydration. Through multi-stage separation and cyclone filtration, the moisture content in the solid coal can be further reduced, achieving deep drying of the coal.

[0017] On the other hand, this application also provides an adaptive control method for coal upgrading, used in applying the aforementioned adaptive control system for coal upgrading, comprising: The raw coal is sorted to remove gangue and impurities based on differences in particle size and density, and then graded to obtain high-purity sorted coal. The coal powder from the sorted coal and the circulating solvent oil are mixed in a set ratio to prepare an oil-coal slurry, and the oil-coal slurry is initially pressurized. The oil-coal slurry after the initial pressurization is then added to a heating tank. Hot high-density gas is added to the heating tank at an initial addition rate to exchange heat with the oil-coal slurry and raise its temperature; the temperature value of the oil-coal slurry is collected based on distributed optical fiber temperature monitoring, and the heating efficiency is determined to be normal based on the oil-coal slurry temperature value. When the heating efficiency is determined to be abnormal, PID control adjusts the initial addition rate of the hot high-density gas; after the heat exchange and heating are completed, hot high-density oil is added to the heating tank to mix with the oil-coal slurry; After mixing, the mixture is pressurized again and added to a fluidized bed reactor with heated hydrogen for further mixing and reaction. The reaction temperature and pressure values ​​within the fluidized bed reactor are collected for data preprocessing. These preprocessed values ​​are then compared with preset reaction conditions to determine if adjustments to the reactor's operating parameters are necessary. If adjustments are required, the fluidized bed reactor is operated with the adjusted parameters. After the mixing reaction is complete, reaction products are generated. The reaction products are separated into new hot high-pressure gas and new hot high-pressure oil in a hot high-pressure separator. Part of the new hot high-pressure oil is sent back into the heating tank to mix with the oil-coal slurry, and the other part is sent to a vacuum tower for depressurization and separation to form mid-section oil and bottom section oil. The bottom section oil is then separated by a solid-liquid separator to obtain solid clean coal products. The clean coal product is fed into a dehydration device, where residual moisture is removed through the combined action of centrifugal force and hot air drying, reducing the moisture content to a preset threshold, thereby obtaining a dry clean coal product.

[0018] It is understandable that the aforementioned adaptive control system and method for coal upgrading have the same beneficial effects, and will not be elaborated further here. Attached Figure Description

[0019] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings: Figure 1 This is a structural block diagram of an adaptive control system for coal upgrading provided in an embodiment of the present invention; Figure 2 A flowchart of an adaptive control method for coal upgrading provided in an embodiment of the present invention. Detailed Implementation

[0020] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the disclosure to those skilled in the art. It should be noted that, unless otherwise specified, embodiments and features in the embodiments of the present invention can be combined with each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0021] Currently, coal upgrading processes commonly suffer from low upgrading efficiency, inaccurate control of process parameters, poor coal mixing uniformity, and low energy utilization. Traditional methods struggle to achieve precise heat exchange and temperature control between the coal-oil slurry and the hot high-efficiency gas and oil fractions, resulting in significant temperature and pressure fluctuations during the reaction process. This leads to unstable upgrading reactions and substantial differences in the quality of the resulting clean coal products. Furthermore, the separation and solid-liquid purification processes have limited efficiency, leaving some oil and impurities, thus restricting the level of clean coal utilization.

[0022] For example, in a coal chemical plant, when using conventional washing and heating to treat low-ash coal powder, uneven mixing of oil and coal slurry and uncontrollable heating rate lead to localized low temperatures or large pressure fluctuations in the fluidized bed reactor, resulting in incomplete upgrading reaction and the generated solid clean coal still containing high moisture and ash content.

[0023] Without improvements to coal upgrading processes, low-quality coal will undergo incomplete combustion during combustion or chemical utilization, resulting in low energy efficiency, increased production costs, and excessive emissions of particulate matter, sulfur dioxide, and nitrogen oxides, causing serious environmental pollution. Uneven reactions and low solid-liquid separation efficiency may also lead to insufficient clean coal production and unstable product quality, hindering the achievement of clean and modern coal utilization and industrial energy conservation and emission reduction goals.

[0024] In this regard, see some embodiments of this application. Figure 1 As shown, an adaptive control system for coal upgrading includes: The coal sorting module is used to sort raw coal, remove gangue and impurities based on differences in particle size and density, and grade it to obtain high-purity sorted coal. The oil-coal slurry generation module is used to mix coal powder from coal sorting and circulating solvent oil in a set ratio to prepare oil-coal slurry, and to initially pressurize the oil-coal slurry. After the initial pressurization, the oil-coal slurry is added to the heating tank. The reactant mixing module is used to add hot high-density gas and oil-coal slurry to the heating tank at an initial addition rate for heat exchange and temperature rise; it collects the oil-coal slurry temperature value based on distributed fiber optic temperature monitoring and determines whether the heating efficiency is normal based on the oil-coal slurry temperature value. When the heating efficiency is determined to be abnormal, PID control adjusts the initial addition rate of hot high-density gas; after the heat exchange and temperature rise are completed, hot high-density oil is added to the heating tank to mix with the oil-coal slurry. The quality improvement reaction module is used to perform secondary pressurization after mixing and add heated hydrogen to the fluidized bed reactor for mixing and reaction. It collects the reaction temperature and pressure values ​​in the fluidized bed reactor for data preprocessing, and compares the preprocessed reaction temperature and pressure values ​​with the preset reaction conditions to determine whether the operating parameters of the fluidized bed reactor need to be adjusted. When it is determined that the operating parameters need to be adjusted, the fluidized bed reactor is operated with the adjusted operating parameters. After the mixing reaction is completed, the reaction products are generated. The product separation module is used to separate the reaction products into new hot high-pressure gas and new hot high-pressure oil in a hot high-pressure separator. Part of the new hot high-pressure oil is sent back into the heating tank to mix with the oil-coal slurry, and the other part is sent to the pressure reducing tower for pressure separation to form mid-section oil and bottom section oil. The bottom section oil is then separated into solid clean coal products by a solid-liquid separator. The dehydration module is used to feed clean coal products into the dehydration equipment, where residual moisture is removed through the combined action of centrifugal force and hot air drying, reducing the moisture content to a preset threshold to obtain dry and clean coal products.

[0025] This coal upgrading adaptive control system achieves intelligent processing of the entire process from raw coal to high-quality clean coal through the coordinated operation of six functional modules. The system first pre-treats the raw coal through a coal sorting module, precisely removing gangue and impurities by utilizing particle size and density differences (coal density 1.2-1.5 g / cm³, gangue density 1.8-2.5 g / cm³). A jig and flotation process are used to separate the raw coal into different particle sizes. Ash content is monitored in real time, and the amplitude and reagent flow rate are automatically adjusted to ensure the output of high-purity sorted coal (ash content 6-8%). Subsequently, the oil-coal slurry generation module mixes the sorted coal powder with circulating solvent oil at a ratio of 60-65%:35-40%. Under initial pressure of 2-3 MPa, air bubbles are eliminated and the slurry homogeneity is improved, while some free solvents are replaced. Moisture is removed, reducing the water content of the oil-coal slurry from 10-12% to 8-10%, laying the foundation for subsequent reactions. The reactant mixing module introduces hot high-temperature gas into the heating tank at a rate of 0.5-1.0 m³ / min for heat exchange and heating. A distributed fiber optic temperature monitoring system collects the temperature distribution at various locations in the oil-coal slurry in real time. When the actual temperature curve deviates from the theoretical heating curve (target 250℃) by more than ±2℃, the PID controller automatically adjusts the hot high-temperature gas flow rate to ensure precise and controllable heating. After heating, hot high-temperature oil is added to further optimize the slurry properties. The upgrading reaction module applies a secondary pressure of 5-6 MPa to the mixture. The gas is pressurized and heated to 200-250℃ with hydrogen gas, which then enters a fluidized bed reactor for a catalytic reaction at 230-260℃. Temperature and pressure data are collected by multiple sensors and pre-processed. When parameters deviate from the set range, a CNN-LSTM neural network model analyzes the multivariate detection data and intelligently generates adjustment schemes to optimize reaction parameters, promoting efficient vaporization of moisture in the coal particles. The product separation module separates the reaction products into new hot high-pressure gas and new hot high-pressure oil in a hot high-pressure separator. 20% of the new hot high-pressure oil is recycled back to the heating tank, while 80% enters a vacuum tower where it is separated into mid-section oil and bottom oil at a pressure of 0.2-0.5 MPa. The bottom oil is separated by centrifugation at 3000 rpm, multi-stage filtration, and cyclone separation to obtain solid clean coal product (8-10% moisture content). Finally, the dehydration module uses a three-stage process to deeply dehydrate the clean coal. First, the moisture content is reduced to 6-7% by centrifugation at 3000-3500 rpm. Then, the microporous moisture is removed to 5-6% by multi-stage filtration. Finally, the temperature gradient is precisely controlled in the hot air drying tower, and the moisture content is monitored in real time. When the preset threshold (4.5-5.0%) is reached, the drying is stopped. The final product is a dry clean coal product with less than 5% moisture content, less than 9% ash content, and a 22% increase in calorific value.

[0026] Specifically, the coal sorting module, as the system's pretreatment unit, uses gravity sorting equipment to precisely remove gangue and impurities from raw coal based on particle size and density differences, achieving the classification of coarse-grained coal, fine-grained coal, and low-calorific-value coal. This ensures that the coal powder input to the oil-coal slurry generation module has an ash content of less than 8% and uniform particle size. The oil-coal slurry generation module mixes the sorted coal powder with circulating solvent oil at a ratio of 60%:40%, and uses initial pressurization (2–3 MPa) to remove air bubbles and improve slurry homogeneity, providing a stable material basis for subsequent reactions. The reactant mixing module uses distributed optical fibers to monitor the oil-coal slurry temperature distribution in real time and dynamically adjusts the hot high-temperature gas flow rate (0.5–1.0) through PID control. The heating rate is m³ / min to ensure the heating efficiency meets the standard, and hot high-precision oil is added to optimize the thermal properties of the slurry. The upgrading reaction module drives the oil-coal slurry and hydrogen to complete catalytic upgrading in the fluidized bed reactor under secondary pressure (5–6 MPa), and intelligently controls the reaction parameters by combining convolutional neural network and LSTM model. The product separation module realizes the graded recovery of oil components through hot high-pressure separator and pressure reducing tower, and the solid-liquid separator extracts solid clean coal. The dehydration module adopts centrifugal-hot air synergistic process to accurately control the moisture of clean coal to below 5%, and finally outputs high-calorific-value dried product.

[0027] The working principle and process of this application are as follows: The coal sorting module first separates gangue (density > 1.8 g / cm³) and high-calorific-value coal (density < 1.4 g / cm³) based on density differences through vibrating screening and flotation reagent adjustment, while real-time monitoring of ash content and feedback adjustment of amplitude. In the oil-coal slurry generation module, coal powder and solvent oil are fully impregnated in a stirred tank. Initial pressurization causes pore water to be replaced by the solvent, improving slurry fluidity. In the reactant mixing stage, distributed optical fibers collect temperature signals at a frequency of 5 seconds / time, and a sliding window algorithm calculates the average temperature value. When the actual heating curve (target 250℃) deviates from the theoretical curve by more than ±2℃, the PID controller amplifies the residual value through the proportional term and the integral term. Accumulated historical deviations and differential term trend predictions are used to dynamically correct the hot high-temperature gas flow rate. In the upgrading reaction, the multi-element sensor data of the fluidized bed reactor, after outlier removal and normalization, is input into the CNN-LSTM model to analyze the spatial temperature distribution and time series dynamics, automatically generating adjustment schemes for parameters such as hydrogen flow rate and stirring intensity, promoting the vaporization of coal particle moisture at a high temperature of 230–260℃. During product separation, the pressure reducing tower uses a pressure difference of 0.2–0.5MPa to drive the separation of light and heavy components. The bottom oil is centrifuged at 3000rpm and then enters the dehydration module. The moisture sensor feeds back signals to the PLC system in real time, dynamically controlling the centrifuge speed and hot air temperature to achieve gradient moisture removal.

[0028] As a preferred embodiment, the specific implementation of this application's solution is as follows: Taking lignite with a moisture content of 18% as an example: the coal sorting module uses a jig to separate the raw coal into +50mm coarse coal (calorific value 4500kcal / kg) and -50mm fine coal (calorific value 4800kcal / kg), reducing the ash content from 22% to 7.5%; the oil-coal slurry generation module mixes coal powder at a ratio of 58%:solvent oil of 42%, pressurizes it at 2.5MPa, and reduces the slurry moisture content from 18% to 12%; in the reactant mixing module, distributed fiber optic monitoring found that the heating rate of the middle layer of the oil-coal slurry was only 4.2℃ / min (target 6℃ / min), and the PID controller reduced the hot high-pressure gas flow rate from 0.7m³ / min to 4.2℃ / min. The flow rate was increased from 3 m³ / min to 0.9 m³ / min, and the temperature reached a uniform 250℃ after 10 minutes. During the upgrading reaction stage, the CNN-LSTM model detected that the temperature at the bottom of the reactor was too low (225℃), so it automatically increased the hydrogen flow rate to 1.1 m³ / min and increased the stirring intensity, which improved the water vaporization efficiency by 35%. After product separation, the bottom oil was centrifuged to obtain the initial clean coal (8% moisture). The dehydration module processed the coal in three stages: centrifugal dehydration (3200 rpm, moisture reduced to 6.5%), multi-stage filtration (removing microporous water to 5.2%), and hot air drying (80℃ gradient heating, final moisture 4.7%), producing dry clean coal with a calorific value of 5800 kcal / kg.

[0029] Through the above technical solution, the reactant mixing module of this application adopts distributed fiber optic temperature monitoring to achieve real-time temperature acquisition of the oil-coal slurry at different locations. PID control is used to adjust the flow rate of the high-temperature gas separator, ensuring stable heating efficiency and avoiding localized overheating or underheating. The reaction temperature and pressure within the fluidized bed reactor are monitored in real-time and pre-processed. After comparison with preset reaction conditions, the operating parameters are automatically adjusted to ensure thorough mixing and uniform reaction of the oil-coal slurry and hydrogen, thereby generating high-quality, stable reaction products. Multi-stage dehydration is achieved, including initial pressurization, heat exchange heating, deep vaporization in the fluidized bed, and solid-liquid separation, reducing the coal moisture content from a high-moisture state to a low-moisture state; improving the calorific value and combustion efficiency of the coal; and ensuring dehydration uniformity and process stability through real-time monitoring and automatic control, thus improving the overall coal upgrading effect; resulting in solid clean coal products with low moisture content and high calorific value.

[0030] This application further proposes that when a coal sorting module performs sorting processing on raw coal, it includes: The coal sorting module uses gravity sorting equipment, which, based on the density difference between raw coal and impurities, separates raw coal into coarse-grained coal, fine-grained coal and gangue under the action of vibrating screen. Coarse-grained coal and fine-grained coal are subjected to flotation treatment separately. By adding flotation reagents to adjust the surface hydrophobicity, high-calorific-value coal and low-calorific-value coal are separated. The coal sorting module monitors the ash content and particle size distribution of the sorted coal in real time. When the ash content exceeds the preset threshold or the particle size distribution is abnormal, it automatically adjusts the amplitude, frequency and reagent flow of the sorting equipment.

[0031] Specifically, the coal sorting module employs advanced gravity separation technology. Based on the density difference between raw coal and impurities (coal density 1.2-1.5 g / cm³, gangue density >1.8 g / cm³), a combination of jigs and heavy media hydrocyclones, under the action of an optimized vibrating screen (amplitude 2-5 mm, frequency 10-30 Hz), precisely separates the raw coal into coarse-grained coal (+50 mm), medium-fine-grained coal (6-50 mm), and fine-grained coal (-6 mm), as well as gangue. For different particle size characteristics, the system implements differentiated flotation processes: coarse-grained coal uses shallow-tank flotation (bubble diameter 0.5-1.5 mm, stirring speed 80-120 rpm), while fine-grained coal uses mechanical stirring flotation or flotation column treatment, through precise addition of collectors (…). The hydrophobicity of coal particles is adjusted by adding 0.5-2.0 kg / t coal and frother (0.2-0.8 kg / t coal). Combined with surface potential monitoring (ζ potential > 40 mV is preferred), the effective separation of high-calorific-value coal and low-calorific-value coal is achieved. The module is equipped with a dual-energy gamma-ray ash analyzer and a laser particle size analyzer to monitor the ash content (accuracy ±0.5%) and particle size distribution of the separated coal in real time. When the ash content exceeds the preset threshold of 8% or the target particle size ratio is less than 85%, the intelligent control system automatically adjusts the vibration amplitude (±1 mm), frequency (10-30 Hz), and reagent flow rate (±30%) of the vibrating screen to ensure the output of high-purity separated coal (ash content stable at 6-8%, moisture 10-12%, clean coal recovery rate 85-90%), providing high-quality raw materials for subsequent oil-coal slurry preparation.

[0032] As a preferred embodiment, the specific implementation of this application is as follows: After the raw coal enters the system, the gravity separation equipment immediately identifies the significant density difference between the coal and the gangue. Under the synergistic effect of the vibrating screen, the raw coal is effectively separated into three parts: coarse-grained, fine-grained, and gangue. The system detects that the coarse-grained coal contains a large amount of medium-density impurities and automatically enhances the water flow pulsation intensity of the jig, making the stratification clearer. At the same time, for the fine-grained coal slime, the flotation system dynamically adjusts the reagent formula according to the surface characteristics of the coal particles, increasing the proportion of specific collectors and significantly improving the hydrophobic properties of the coal particles. During the processing, the monitoring system detects a slight increase in the ash content of the coal after separation and immediately triggers the adaptive control mechanism, fine-tuning the amplitude and frequency of the vibrating screen and optimizing the reagent addition amount, so that the separation effect quickly returns to the ideal state. After this series of intelligent adjustments, the final produced separated coal has a uniform texture and extremely low impurity content, fully meeting the requirements of subsequent upgrading processes and providing a high-quality raw material foundation for the entire coal upgrading system.

[0033] Through the above technical solution, the separation quality of this application is significantly improved, and the high-purity separated coal produced ensures the stability and efficiency of subsequent oil-coal slurry preparation and upgrading reaction.

[0034] In some of the solutions described above in this application, the temperature signal acquired by distributed optical fiber may be affected by instantaneous disturbances, resulting in noise or fluctuations, which makes the real-time temperature value unstable.

[0035] This application further proposes a reactant mixing module that, when acquiring the temperature value of oil-coal slurry based on distributed optical fiber temperature monitoring, includes: The heating tank is equipped with distributed optical fibers. The reactant mixing module obtains the temperature distribution of the oil-coal slurry at different locations in real time through the distributed optical fibers and converts the analog signal output by the distributed optical fibers into a digital signal through an analog-to-digital converter. The reactant mixing module sets a sampling period, and takes several temperature sampling points before and after each sampling period to form a sliding window. The average value of the digital signal within the sliding window is calculated as the current oil-coal slurry temperature value. The reactant mixing module connects the oil-coal slurry temperature values ​​obtained from each time point in the sliding window processing into a curve in chronological order to obtain the actual temperature curve.

[0036] Specifically, in the reactant mixing module, distributed optical fibers are first strategically deployed inside the heating tank to cover different flow areas of the oil-coal slurry, enabling real-time temperature monitoring at multiple points. The temperature signals acquired by the optical fibers are analog signals, which are converted into digital signals by a high-precision analog-to-digital converter (ADC) for subsequent calculations and control. A reasonable sampling period is set, for example, collecting temperature data 10 times per second. Within each sampling period, several temperature sampling points are taken to form a sliding window. The current temperature value of the oil-coal slurry is obtained by calculating the average value within the sliding window. The temperature values ​​at each time point are connected in chronological order to form an actual temperature curve, providing basic data for judging heating efficiency and PID control. This process effectively reflects the temperature distribution and dynamic changes of the oil-coal slurry within the heating tank.

[0037] As a preferred embodiment, the specific implementation of this application is as follows: In a coal upgrading device, the heating tank has a volume of 5 cubic meters and is equipped with 20 distributed optical fibers, covering different heights and positions within the tank. When the oil-coal slurry begins to heat up after initial pressurization, the system collects temperature signals 10 times per second, and calculates the average value using a sliding window formed by five sampling points. At a certain time point, the actual temperature curve shows that the tank bottom temperature is 320℃, the tank interior temperature is 315℃, and the tank top temperature is 318℃.

[0038] Through the above technical solution, this application reduces the noise impact of temperature measurement, improves the stability and accuracy of temperature data, and can promptly detect local overheating or insufficient temperature rise. The actual temperature curve generated using the sliding window average and time series data can provide accurate feedback for PID control.

[0039] In some of the solutions described above in this application, the oil-coal slurry exhibits uneven flow, localized temperature fluctuations, and sensor noise in the heating tank, which can cause the temperature data at a single point to deviate from the actual overall heating trend, thus leading to a misjudgment of the heating efficiency.

[0040] This application further proposes a method for the reactant mixing module to determine whether the heating efficiency is within a normal range based on the oil-coal slurry temperature value, including: The reactant mixing module compares and analyzes the actual temperature curve with the theoretical heating curve, aligns the two curves on the same time axis, and compares the actual oil-coal slurry temperature value on the actual temperature curve at each time point with the theoretical temperature value corresponding to the theoretical heating curve to obtain the residual value sequence; the residual value sequence is statistically processed to quantify the degree of deviation and obtain the final residual value. The reactant mixing module compares the final residual value with the residual value threshold. When the final residual value is less than or equal to the residual value threshold, the heating efficiency is determined to be in a normal state; when the final residual value is greater than the residual value threshold, the heating efficiency is determined to be in an abnormal state.

[0041] Specifically, the reactant mixing module determines whether the heating efficiency is normal by precisely comparing the actual oil-coal slurry temperature curve with the theoretical heating curve. The two curves are aligned on the time axis, comparing the actual temperature at each sampling time point with the corresponding theoretical temperature to obtain a residual value sequence. Statistical processing is performed on the residual value sequence, such as calculating the average residual or standard deviation, to quantify the degree of deviation in the oil-coal slurry heating rate, resulting in the final residual value. Finally, the final residual value is compared with a preset residual value threshold. If it is less than or equal to the threshold, the heating efficiency is determined to be normal; if it is greater than the threshold, the heating efficiency is determined to be abnormal, triggering further control adjustments. This method can eliminate the influence of instantaneous temperature fluctuations and local anomalies on the heating efficiency judgment, making the judgment more accurate and reliable.

[0042] As a preferred embodiment, the specific implementation of this application is as follows: The theoretical temperature rise curve of the oil-coal slurry in a heating tank is 8°C per minute, with a target temperature increase from 300°C to 360°C. The actual temperature curve is obtained through distributed fiber optic monitoring. The data shows that the temperature is slightly lower than the theoretical value by 4°C in the 2nd and 3rd minutes, and the deviation at other times is within the range of 1~2°C. After statistical analysis of the residual value sequence, the final residual value is 2.5°C, and the set residual value threshold is 5°C. Therefore, the heating efficiency is determined to be normal, and there is no need to adjust the flow rate of the hot high-temperature gas. If the final residual value exceeds 5°C, the system will immediately adjust the hot high-temperature gas addition rate through a PID algorithm to quickly bring the oil-coal slurry temperature back to near the theoretical temperature rise curve, ensuring the stable progress of the upgrading reaction.

[0043] Through the above technical solution, this application achieves refined control of the oil-coal slurry heating process, improving the uniformity and stability of the entire heating system. Through residual value analysis, the system can quickly identify abnormal temperature rises and automatically adjust the addition rate of hot high-temperature gas when necessary, preventing uneven oil-coal slurry quality caused by localized overheating or insufficient temperature rise.

[0044] In some of the schemes described above in this application, an excessively large proportional coefficient may lead to drastic flow fluctuations and cause overshoot in the temperature of the oil-coal slurry.

[0045] This application further proposes a method for adjusting the initial addition rate of hot high-density gas using PID control in the reactant mixing module, including: The proportional adjustment amplifies the final residual value by a certain proportion to obtain the initial correction amount; Integral regulation generates a flow correction amount based on the deviation of the accumulated temperature from the theoretical curve. Differential adjustment: The differential correction is calculated based on the rate of change of the temperature deviation. The reactant mixing module obtains the initial correction amount, flow rate correction amount, and differential correction amount through proportional adjustment, integral adjustment, and differential adjustment, and then adds the final correction value. The initial addition rate is corrected by the correction value, and the hot high-density gas is added at the corrected initial addition rate.

[0046] Specifically, PID control generates a correction value for the initial addition rate of hot high-temperature gas through the coordinated action of proportional, integral, and derivative control. Proportional control amplifies the deviation between the current actual temperature of the oil-coal slurry and the theoretical temperature target (this amplification is continuously adjusted based on historical deviations) to generate an initial correction. This is primarily used for rapid response to instantaneous temperature deviations, enabling the system to immediately adjust to temperature anomalies. Integral control accumulates temperature deviations from past sampling periods to generate a flow correction, thereby eliminating long-term steady-state errors and ensuring the oil-coal slurry gradually approaches the theoretical temperature curve throughout the heating process. Derivative control predicts the temperature trend based on the rate of temperature deviation change over time and calculates the derivative correction. This is mainly used to suppress temperature overshoot or oscillations, resulting in a smoother temperature rise. Finally, the three corrections are superimposed to obtain a total correction value. The system dynamically adjusts the initial addition rate of hot high-temperature gas based on this correction value, achieving refined control of the oil-coal slurry heating process and ensuring the heating curve closely approximates the expected target.

[0047] As a preferred embodiment, the specific implementation of this application is as follows: In actual production, assuming the target temperature rise curve of the oil-coal slurry requires a temperature increase of 7°C per minute, and sampling at the 5th minute reveals that the actual temperature is 2°C lower than the theoretical temperature. The proportional control increases the flow rate of the hot high-temperature gas by 2.4 L / min based on the deviation calculation; the integral control accumulates past deviations to generate a correction of 0.9 L / min; and the derivative control generates a correction of 0.6 L / min based on the temperature rise trend. The three are superimposed to obtain the final correction value of 3.9 L / min. After the system applies this correction value to the addition rate of the hot high-temperature gas, the oil-coal slurry temperature rapidly returns to near the theoretical curve at the 6th minute, with a stable temperature rise and no oscillations, thus ensuring that the upgrading reaction proceeds within the optimal temperature range.

[0048] Through the above technical solution, this application uses PID control to improve the uniformity and stability of the oil-coal slurry temperature rise. Proportional control enables the system to respond quickly to temperature deviations, integral control eliminates long-term deviations, and derivative control suppresses overshoot and oscillations, thereby ensuring that the temperature rise efficiency is close to the theoretical setting, improving the utilization efficiency of the hot gas fractionation and reducing energy waste.

[0049] In some of the solutions described above in this application, the sensor may be affected by vibration, bubbles, particle impact, or electrical noise, which may cause abnormal points or sudden changes in the collected data; the signals collected by sensors at different locations may differ, which may lead to inconsistent data or local deviations; the original signal fluctuates greatly, which may affect subsequent control judgment and response adjustment.

[0050] This application further proposes that when the upgrading reaction module collects the reaction temperature and reaction pressure values ​​in the fluidized bed reactor for data preprocessing, it includes: Data preprocessing includes outlier identification and removal, signal smoothing, signal normalization, and data fusion.

[0051] Specifically, in the quality improvement reaction module, data preprocessing first identifies and removes outliers from the collected temperature and pressure values ​​of the fluidized bed reactor. This involves setting reasonable threshold ranges and continuous detection to eliminate abnormal data that significantly deviates from the normal range, preventing them from interfering with subsequent analysis and control. Next, the remaining signals are smoothed using filtering algorithms to reduce sensor noise and instantaneous fluctuations, making the data curves more continuous and stable. Then, the signals are normalized to unify the dimensions, ranges, or unit differences of different sensors to the same standard range, facilitating comprehensive analysis. Finally, data fusion combines temperature and pressure data from multiple sensors to form a unified comprehensive signal.

[0052] As a preferred embodiment, the solution of this application is implemented as follows: A temperature sensor occasionally generates instantaneous jump data due to particle impact. If used directly, it will cause the system to misjudge that the reaction temperature is too high and reduce the flow rate of hydrogen or hot high-temperature gas. After outlier removal and smoothing, these instantaneous jumps are removed. After normalization and data fusion, the system can accurately reflect the true temperature distribution of the entire reactor.

[0053] Through the above technical solutions, this application can effectively eliminate abnormalities and noise interference, making the collected data more stable and reliable, and improving the accuracy and safety of reactor operation control; normalization and data fusion enable the overall analysis of multi-point and multi-type sensor data.

[0054] This application further proposes that when the quality improvement reaction module compares the pretreated reaction temperature and reaction pressure values ​​with preset reaction conditions to determine whether the operating parameters of the fluidized bed reactor need to be adjusted, the following steps are included: The preset reaction conditions include a preset temperature range and a preset pressure range; When the reaction temperature and reaction pressure are within the preset temperature and pressure ranges, it is determined that no adjustment of the operating parameters of the fluidized bed reactor is required. When the reaction temperature or reaction pressure is not within the preset temperature or pressure range, it is determined that the operating parameters of the fluidized bed reactor need to be adjusted.

[0055] Specifically, in the quality improvement reaction module, the system first acquires the pre-processed reaction temperature and pressure values, and then compares and analyzes these values ​​with the preset reaction conditions. The preset reaction conditions include temperature and pressure ranges, for example, a temperature set to 200℃ to 210℃ and a pressure set to 1.5MPa to 1.7MPa. The system determines whether the currently acquired temperature and pressure values ​​are within their respective safe ranges. If both temperature and pressure meet the preset conditions, the system determines that the reactor does not require adjustment and maintains its current operating state; if either temperature or pressure exceeds the preset range, the system determines that the reactor needs adjustment. As a preferred embodiment, the solution of this application is implemented as follows: The system collects the temperature of the fluidized bed reactor as 215°C and the pressure as 1.6 MPa. The temperature exceeds the preset upper limit of 210°C. Although the pressure is still within the safe range, the system still determines that adjustment is needed. Subsequently, the system reduces the hot high-pressure gas addition rate and fine-tunes the hydrogen supply, causing the temperature to slowly decrease to 208°C while maintaining the pressure at 1.6 MPa.

[0056] Through the above technical solution, this application can effectively ensure that the fluidized bed reactor always operates in a safe and efficient reaction range by comparing the temperature and pressure with the preset conditions in real time, and prevent incomplete reaction, uneven thermal decomposition or equipment damage caused by excessively high or low temperature and pressure.

[0057] In some of the solutions described above in this application, there may be a variety of factors that cause problems in the operation of the fluidized bed reactor. If the operating parameters are adjusted only based on the reaction temperature and reaction pressure values, problems may still occur in the operation of the fluidized bed reactor after the adjustment.

[0058] This application further proposes that when it is determined that the operating parameters need to be adjusted, the upgrading reaction module operates the fluidized bed reactor with the adjusted operating parameters, including: The upgrading reaction module collects temperature data at different locations in the fluidized bed reactor to obtain the temperature distribution of the oil-coal slurry and the bed; it also collects pressure data at different locations in the fluidized bed reactor to obtain the pressure distribution of the bed; it detects the flow rate of hydrogen and hot high-density gas entering the reactor, obtains gas flow information in real time, and determines whether the set value has been reached; it assesses the mixing uniformity of the oil-coal slurry and gas; it detects the movement, vibration, and height distribution of bed particles to determine whether there is sedimentation, blockage, or uneven gas passage; it detects the temperature of the auxiliary equipment heating tank, pump pressure, and valve opening to determine whether the equipment is operating normally; and it constructs multivariate detection data from the various detection results.

[0059] Specifically, when the upgrading reaction module operates the fluidized bed reactor with adjusted operating parameters, the system needs to comprehensively monitor all key locations within the reactor. Multiple sensors are deployed to collect temperature data from different locations, thereby obtaining the temperature distribution of the oil-coal slurry and the bed, ensuring uniform heating of the entire bed. Pressure data is collected at different locations within the bed to analyze pressure gradients and distribution, preventing uneven gas flow or bed settling caused by excessively high or low local pressures. The system also monitors the flow rates of hydrogen and hot high-density gas entering the reactor in real time to determine if the gas supply meets the set requirements and assess the mixing uniformity of the oil-coal slurry and gas, avoiding incomplete or excessive local reactions. The system detects the movement, vibration, and height distribution of bed particles, promptly identifying settling, blockage, or uneven gas flow; simultaneously, it monitors the status of auxiliary equipment, including heater temperature, pump pressure, and valve opening, ensuring normal equipment operation. All collected temperature, pressure, flow rate, and bed particle status data are integrated to generate multi-dimensional monitoring data, providing a comprehensive basis for reactor control.

[0060] The upgrading reaction module collects temperature data at different locations within the fluidized bed reactor to obtain the temperature distribution of the coal-oil slurry and the bed. By analyzing temperature changes at each location, it can determine whether the moisture vaporization in the coal is uniform. Locally low temperatures may lead to moisture residue, while locally high temperatures may cause localized coking or heat loss. Based on the temperature distribution data, the system can adjust parameters such as the flow rate of the hot high-temperature gas and the bed stirring intensity to ensure temperature uniformity during coal dehydration and improve overall dehydration efficiency. By collecting pressure data at different locations within the fluidized bed, the system obtains the bed pressure distribution, reflecting the gas permeation and resistance distribution within the bed. Excessively high bed pressure or abnormal local pressure may lead to localized coal slurry settling, moisture retention, or uneven gas flow. The opening of the distribution valve or the pumping rate can be adjusted based on the pressure distribution to optimize the contact between the gas and the coal-oil slurry, increase the moisture evaporation rate, and thus enhance the coal dehydration effect. The system also detects the flow rates of hydrogen and hot high-temperature gas entering the reactor, obtaining real-time gas flow information to determine whether the set values ​​have been reached. Insufficient gas flow may hinder the rapid vaporization of coal moisture, affecting dewatering efficiency; excessive flow may cause coal powder dispersion or increase energy consumption. By adjusting the gas flow in real time, the system ensures that the moisture evaporation rate matches the bed heat supply, achieving efficient dewatering. The system assesses the mixing uniformity of the oil-coal slurry and gas, and detects bed particle movement, vibration, and height distribution to determine if there is sedimentation, blockage, or uneven gas flow. Uneven mixing can lead to insufficient dewatering in some areas of the coal, while other areas become over-dryed. The system adjusts the bed stirring intensity, pumping rate, and distribution valve opening to ensure uniform suspension and heating of coal within the reactor, improving dewatering uniformity. The system monitors the temperature of the auxiliary equipment heating tank, pumping pressure, and valve opening to determine if the equipment is operating normally. Abnormalities in auxiliary equipment may lead to insufficient heat, delayed moisture evaporation, or poor oil-coal slurry transport. Through real-time monitoring and feedback adjustments, the system ensures the stability and reliability of the entire dewatering process.

[0061] As a preferred embodiment, the solution of this application is implemented as follows: System data collection shows that the temperature at the bottom of the fluidized bed is higher than the theoretical value, while the temperature at the top is lower, and the hydrogen flow rate is slightly lower than the set value. Analysis of multivariate detection data reveals that particle settling at the bottom of the bed has led to uneven gas distribution, while the pumping pressure is slightly low and the valve opening is insufficient. The system automatically adjusts the pumping pressure, increases the hydrogen flow rate, and fine-tunes the temperature of the heating tank, ultimately achieving a gradually uniform bed temperature, normal gas distribution, and uniform mixing of the oil-coal slurry and gas, ensuring the stable reaction under preset conditions.

[0062] Through the above technical solution, this application achieves comprehensive control over the operating status of the fluidized bed reactor. Real-time monitoring and analysis can quickly identify and locate anomalies, preventing decreased reaction efficiency or equipment damage caused by uneven temperature or pressure distribution, bed blockage, or insufficient gas supply.

[0063] This application further proposes a dewatering module that feeds clean coal products into a dewatering device to remove residual moisture through the combined action of centrifugal force and hot air drying, including: The dehydration module feeds the clean coal product into a centrifugal dehydrator, where centrifugal force generated by high-speed rotation separates free water, initially reducing the moisture content. The pre-dehydrated clean coal product is then fed into a multi-stage filtration unit, where vibrating screens and filter cloths are used for fine filtration to remove microporous moisture. The filtered clean coal product is then fed into a hot air drying tower, where it is dried under a controllable temperature gradient. The moisture content of the product is monitored in real time, and drying is stopped when the moisture content reaches a preset threshold, at which point the dried clean coal product is output.

[0064] Specifically, the dewatering module achieves deep coal dewatering through a three-stage synergistic dewatering process, with each stage having a clearly defined function and complementing each other. The centrifugal dewatering stage, as the first process, utilizes the powerful centrifugal force field generated by high-speed rotation to effectively separate free water from the clean coal product, rapidly reducing surface moisture content and laying the foundation for subsequent fine dewatering. The multi-stage filtration stage, as an intermediate treatment step, employs a combination of vibrating screens and multi-layer filter cloths. Through the synergistic effect of mechanical vibration and fine filtration, it deeply removes bound moisture from the micropores of coal particles, solving the problem of micropore moisture that is difficult to handle with traditional dewatering methods. The hot air drying stage, as the final fine treatment stage, utilizes the full contact between hot air and coal particles under a precisely controlled temperature gradient environment to promote the evaporation of residual moisture. Simultaneously, a highly sensitive moisture monitoring system is equipped to achieve precise control of the drying process, ensuring that the final product reaches an ideal dry state.

[0065] The dehydration process begins with the clean coal product entering a centrifugal dehydrator. Once started, the high-speed rotation creates a strong centrifugal force field, causing coal particles to aggregate towards the cylinder wall, while moisture, due to density differences, is thrown to the outside and collected, achieving rapid separation of free water. Next, the material enters a multi-stage filtration unit. The periodic vibration of the vibrating screen loosens the coal particles, and the filter cloths of different pore sizes intercept the moisture in the micropores step by step. The vibration also prevents the filter cloths from clogging, maintaining filtration efficiency. Finally, the material enters a hot air drying tower. Multiple distributors inside the tower ensure uniform hot air circulation. The temperature control system automatically adjusts the hot air temperature gradient according to the material's condition, ensuring a smooth drying process from the surface inwards, avoiding surface overheating and internal moisture residue. Throughout the process, a moisture sensor continuously monitors the product's condition, automatically terminating drying when the preset drying standard is reached, ensuring stable product quality.

[0066] As a preferred embodiment, the solution of this application is implemented as follows: When clean coal products containing a large amount of moisture enter the system, the centrifugal dewatering machine first identifies the moisture state of the material and automatically adjusts its speed to adapt to different moisture contents, quickly removing surface free moisture; then the material enters a multi-stage filtration unit, where the system automatically optimizes the vibration frequency and filter cloth combination according to the material characteristics, specifically treating the unique microporous structure of lignite to effectively remove microporous moisture that is difficult to separate; finally, in the hot air drying stage, the control system dynamically adjusts the temperature distribution based on real-time monitoring data to prevent the lignite from undergoing pyrolysis at high temperatures, ensuring a gentle and efficient drying process. Throughout the process, when a batch of coal is detected to be particularly viscous, the system automatically extends the vibrating screening time and fine-tunes the hot air temperature curve, successfully overcoming the challenges posed by the material characteristics, and ultimately producing dry, clean coal with a uniform texture and no agglomeration.

[0067] Through the above technical solutions, the synergistic effect of the three-stage dehydration process in this application improves the dehydration efficiency and uniformity, ensuring that the moisture content of the final product reaches an ideal level, thereby enhancing the calorific value and combustion performance of coal. The pretreatment of centrifugation and filtration reduces the load on hot air drying, lowers energy consumption, and achieves the production goal of energy conservation and environmental protection.

[0068] In another preferred embodiment based on the above embodiments, see [reference] Figure 2 As shown, this embodiment provides an adaptive control method for coal upgrading, which applies the aforementioned adaptive control system for coal upgrading, including: S100: The raw coal is sorted and processed to remove gangue and impurities based on differences in particle size and density, and then graded to obtain high-purity sorted coal. S200: Coal powder from coal sorting and circulating solvent oil are mixed in a set ratio to prepare coal-oil slurry, and the coal-oil slurry is initially pressurized. After the initial pressurization, the coal-oil slurry is added to the heating tank. S300: Heat high-temperature gas is added to the heating tank at the initial addition rate to exchange heat with the oil-coal slurry and raise the temperature; the temperature value of the oil-coal slurry is collected based on distributed optical fiber temperature monitoring, and the temperature value of the oil-coal slurry is used to determine whether the heating efficiency is in a normal state. When the heating efficiency is determined to be abnormal, the PID control adjusts the initial addition rate of the heat high-temperature gas; after the heat exchange and heating are completed, heat high-temperature oil is added to the heating tank to mix with the oil-coal slurry. S400: After mixing, the mixture is pressurized again and added to the fluidized bed reactor for mixing and reaction with heated hydrogen. The reaction temperature and pressure values ​​in the fluidized bed reactor are collected for data preprocessing. The preprocessed reaction temperature and pressure values ​​are compared with the preset reaction conditions to determine whether the operating parameters of the fluidized bed reactor need to be adjusted. If it is determined that the operating parameters need to be adjusted, the fluidized bed reactor is operated with the adjusted operating parameters. After the mixing reaction is completed, the reaction products are generated. S500: The reaction products are separated into new hot high-pressure gas and new hot high-pressure oil in a hot high-pressure separator; part of the new hot high-pressure oil is sent back into the heating tank to mix with the oil-coal slurry, and the other part is sent to the pressure reducing tower for pressure separation to form mid-section oil and bottom section oil; and the bottom section oil is separated by a solid-liquid separator to obtain solid clean coal products. S600: The clean coal product is fed into the dewatering equipment, where residual moisture is removed through the combined action of centrifugal force and hot air drying, reducing the moisture content to a preset threshold to obtain a dry clean coal product.

[0069] In summary, by deploying distributed optical fibers within the heating tank, real-time temperature monitoring of the oil-coal slurry at different locations is achieved, and a precise actual temperature curve is obtained using a sliding window algorithm. By comparing the actual temperature curve with the theoretical heating curve, the heating deviation is quantified, and the hot high-temperature gas addition rate is automatically adjusted via PID control, achieving precise control of the heating process, improving heating efficiency, and avoiding overheating or underheating. Real-time monitoring of temperature, pressure, gas flow rate, and bed state within the fluidized bed reactor generates multivariate detection data. A combined model of convolutional neural networks and long short-term memory networks is used to predict and analyze deviations in various operating parameters, automatically generating optimized adjustment schemes. This enables dynamic control of parameters such as reaction temperature, pressure, gas flow rate, and bed stirring, improving the stability and uniformity of the upgrading reaction. A temperature gradient and pressure difference are formed in the high-temperature oil within the vacuum distillation tower, achieving effective separation of the middle and bottom sections of the oil. The bottom section oil undergoes mechanical centrifugation, filtration, and cyclone separation through a solid-liquid separator to remove residual oil, yielding a solid clean coal product, reducing pollutant and impurity content, and improving coal upgrading efficiency.

[0070] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program goods. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program goods embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0071] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program goods according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0072] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0073] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0074] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. An adaptive control system for coal upgrading, characterized by, The application relates to a coal upgrading system and method. The coal upgrading system comprises: a coal sorting module for sorting raw coal, removing gangue and impurities based on particle size and density differences, and grading to obtain high-purity sorted coal; an oil coal slurry generating module for mixing coal powder of the sorted coal and circulating solvent oil according to a set proportion to prepare oil coal slurry, and performing primary pressurization on the oil coal slurry, and adding the oil coal slurry after the primary pressurization into a heating tank; a reactant mixing module for adding hot high-pressure gas into the heating tank at an initial adding rate to exchange heat with the oil coal slurry to increase the temperature of the oil coal slurry; collecting the temperature value of the oil coal slurry based on distributed optical fiber temperature monitoring, and determining whether the temperature increasing efficiency is normal based on the temperature value of the oil coal slurry; when it is determined that the temperature increasing efficiency is abnormal, adjusting the initial adding rate of the hot high-pressure gas through PID control; after the heat exchange and temperature increasing are completed, hot high-pressure oil is added into the heating tank to mix with the oil coal slurry; a quality upgrading reaction module for performing secondary pressurization on the mixed oil coal slurry, adding heated hydrogen into a boiling bed reactor to mix and react, collecting the reaction temperature value and reaction pressure value in the boiling bed reactor for data preprocessing, comparing the preprocessed reaction temperature value and reaction pressure value with preset reaction conditions, and determining whether the operating parameters of the boiling bed reactor need to be adjusted; when it is determined that the operating parameters need to be adjusted, operating the boiling bed reactor with the adjusted operating parameters; and generating reaction products after the mixing and reaction are completed; a product separation module for separating new hot high-pressure gas and new hot high-pressure oil from the reaction products through a hot high-pressure separation tank; part of the new hot high-pressure oil is sent back into the heating tank to mix with the oil coal slurry, and the other part of the new hot high-pressure oil is sent into a pressure reduction tower to form middle section oil and bottom section oil; and the bottom section oil is separated into solid clean coal products based on a solid-liquid separator; 2. An adaptive control system for coal upgrading according to claim 1, wherein, a dehydration module for sending the clean coal products into a dehydration device to remove residual moisture through the synergistic effect of centrifugal force and hot air drying, to reduce the moisture content to a preset threshold, and to obtain dry clean coal products. When the coal sorting module sorts raw coal, the coal sorting module comprises: The coal sorting module adopts a gravity sorting device, and raw coal is divided into coarse grain coal, fine grain coal and gangue under the action of a vibrating screen based on the density difference between the raw coal and impurities; The coarse grain coal and the fine grain coal are respectively subjected to flotation treatment, high-calorific-value coal and low-calorific-value coal are separated out by adding a flotation reagent to adjust the surface hydrophobicity; 3. An adaptive control system for coal upgrading as claimed in claim 1, wherein, The coal sorting module monitors the ash content and particle size distribution of the sorted coal in real time, and automatically adjusts the amplitude, frequency and reagent flow of the sorting device when the ash content exceeds a preset threshold or the particle size distribution is abnormal. When the reactant mixing module collects the temperature value of the oil coal slurry based on distributed optical fiber temperature monitoring, the heating tank is provided with the distributed optical fiber, the reactant mixing module obtains the temperature distribution of the oil coal slurry at different positions in real time through the distributed optical fiber, and an analog signal output by the distributed optical fiber is converted into a digital signal through an analog-to-digital converter. The reactant mixing module sets a sampling period, takes a plurality of temperature sampling points before and after each sampling period to form a sliding window, and calculates the average value of the digital signal in the sliding window as the current oil coal slurry temperature value; The reactant mixing module connects the oil coal slurry temperature values at each time point obtained by processing the sliding window in time sequence to obtain an actual temperature curve.

4. An adaptive control system for coal upgrading as claimed in claim 3, wherein, When the reactant mixing module determines whether the heating efficiency is in a normal state through the oil coal slurry temperature value, the method comprises: The reactant mixing module compares and analyzes the actual temperature curve with a theoretical heating curve, aligns the two curves at the same time coordinate, compares the actual oil coal slurry temperature value on the actual temperature curve at each time point with the theoretical temperature value corresponding to the theoretical heating curve, and obtains a residual sequence; the residual sequence is statistically processed to quantify the deviation degree to obtain a final residual value; The reactant mixing module compares the final residual value with a residual threshold value, and when the final residual value is less than or equal to the residual threshold value, it is determined that the heating efficiency is in a normal state; when the final residual value is greater than the residual threshold value, it is determined that the heating efficiency is not in a normal state.

5. An adaptive control system for coal upgrading as claimed in claim 4, wherein, When the reactant mixing module adjusts the initial addition rate of the hot high fraction gas through PID control, the method comprises: Proportional adjustment, which amplifies the final residual value by a certain proportion to obtain a preliminary correction amount; Integral adjustment, which accumulates the deviation of the temperature from the theoretical curve to generate a flow correction amount; The differential adjustment calculates a differential correction amount according to the rate of change of the temperature deviation; The reactant mixing module superimposes the preliminary correction amount, the flow correction amount and the differential correction amount obtained through the proportional adjustment, the integral adjustment and the differential adjustment to obtain a final correction value, and adjusts the initial addition rate through the correction value, and adds the hot high fraction gas at the adjusted initial addition rate.

6. An adaptive control system for coal upgrading according to claim 5, wherein, When the upgrading reaction module collects the reaction temperature value and the reaction pressure value in the ebullated bed reactor for data preprocessing, the method comprises: The data preprocessing includes outlier identification and elimination, signal smoothing processing, signal normalization and data fusion.

7. An adaptive control system for coal upgrading according to claim 6, wherein, When the upgrading reaction module compares the preprocessed reaction temperature value and reaction pressure value with the preset reaction conditions to determine whether the operating parameters of the ebullated bed reactor need to be adjusted, the method comprises: The preset reaction conditions include a preset temperature range and a preset pressure range; when the reaction temperature value is within the preset temperature range and the reaction pressure value is within the preset pressure range, it is determined that the operating parameters of the ebullated bed reactor do not need to be adjusted; when the reaction temperature value is not within the preset temperature range or the reaction pressure value is not within the preset pressure range, it is determined that the operating parameters of the ebullated bed reactor need to be adjusted.

8. An adaptive control system for coal upgrading according to claim 7, wherein, When it is determined that the operating parameters need to be adjusted, the upgrading reaction module operates the ebullated bed reactor with the adjusted operating parameters, and the method comprises: The upgrading reaction module collects temperature data at different positions of the fluidized bed reactor to obtain the temperature distribution of the oil coal slurry and the bed; collects pressure data at different positions of the fluidized bed reactor to obtain the pressure distribution of the bed; detects the flow of hydrogen and hot high-pressure gas entering the reactor to obtain real-time gas flow information and determine whether the set value is reached; evaluates the mixing uniformity of the oil coal slurry and the gas; detects the movement, vibration and height distribution of the bed particles to determine whether there are phenomena such as settling, blocking or uneven gas passage; detects the temperature of the heating tank, the pumping pressure and the valve opening of the auxiliary equipment to determine whether the equipment is operating normally; and constructs multiple detection data from the detection results.

9. An adaptive control system for coal upgrading according to claim 8, wherein, The dewatering module sends the clean coal product to a dewatering device to remove residual moisture through the synergistic effect of centrifugal force and hot air drying, including: The dewatering module sends the clean coal product to a centrifugal dewatering machine to separate free moisture through centrifugal force generated by high-speed rotation, thereby preliminarily reducing the moisture content; sends the preliminarily dewatered clean coal product to a multi-stage filtration unit for fine filtration using a vibrating screen and filter cloth to remove micropore moisture; and sends the filtered clean coal product to a hot air drying tower for drying under a controllable temperature gradient, real-time monitoring of the moisture content of the product, stopping the drying when the moisture content reaches a preset threshold, and outputting the dried clean coal product.

10. An adaptive control method for coal upgrading for use with an adaptive control system for coal upgrading according to any one of claims 1 to 9, characterized in that, including: The raw coal is sorted and treated to remove gangue and impurities based on differences in particle size and density, and high-purity sorted coal is obtained by classification; The coal powder and recycled solvent oil of the sorted coal are mixed in a set proportion to prepare an oil coal slurry, and the oil coal slurry is subjected to primary pressurization, and the oil coal slurry after the primary pressurization is added to a heating tank; Hot high-pressure gas is added to the heating tank at an initial addition rate to exchange heat with the oil coal slurry to raise the temperature; the temperature value of the oil coal slurry is collected based on distributed optical fiber temperature monitoring, and whether the temperature raising efficiency is normal is determined based on the temperature value of the oil coal slurry; when it is determined that the temperature raising efficiency is not normal, the initial addition rate of the hot high-pressure gas is adjusted by PID control; after the heat exchange and temperature raising are completed, hot high-pressure oil is added to the heating tank to mix with the oil coal slurry; After the mixing is completed, secondary pressurization is performed, and heated hydrogen is added to the fluidized bed reactor for mixing and reaction; the reaction temperature value and the reaction pressure value in the fluidized bed reactor are collected for data preprocessing, and the preprocessed reaction temperature value and reaction pressure value are compared with preset reaction conditions to determine whether the operating parameters of the fluidized bed reactor need to be adjusted; when it is determined that the operating parameters need to be adjusted, the fluidized bed reactor is operated with the adjusted operating parameters; and a reaction product is generated after the mixing and reaction are completed; The reaction product is separated into new hot high-pressure gas and new hot high-pressure oil in a hot high-pressure separation tank; part of the new hot high-pressure oil is sent back to the heating tank to mix with the oil coal slurry, and the other part is sent to a pressure reduction tower to form middle oil and bottom oil by pressure reduction separation; and the bottom oil is separated by a solid-liquid separator to obtain a solid clean coal product; The clean coal product is sent into a dehydration device, residual moisture is removed through the synergistic effect of centrifugal force and hot air drying, the moisture content is reduced to a preset threshold, and a dry clean coal product is obtained.

Images