An intelligent control system and method for online oxidation of slurry

Abstract

This invention provides an intelligent online oxidation control system for slurry, belonging to the field of slurry oxidation control technology in flue gas desulfurization processes. It includes an intelligent online oxidation analyzer for slurry, a data processing and control module, a fan, and an inlet CEMS connected to the bottom side of the slurry tank of the absorption tower. The data processing and control module is connected to the fan, and the fan's oxidation air pipeline is located within the slurry tank. The inlet CEMS is connected to the data processing and control module. An ORP sensor, a sulfite sensor, a Cl- sensor, a pH sensor, a TDS sensor, and a density sensor are connected to the data processing and control module. This invention uses sulfite concentration as the core, combining a multi-parameter weight correction algorithm and dynamic closed-loop logic to avoid over-oxidation and ineffective air supply. Practical application verification shows that it saves over one million yuan in electricity costs annually, and reduces energy consumption by 15%-30% compared to traditional control methods. This invention also discloses the control method for this intelligent online oxidation control system for slurry.

Description

Technical Field

[0001] This invention relates to the field of slurry oxidation control technology in flue gas desulfurization processes, and more specifically, to an intelligent online slurry oxidation control system. The invention also relates to a control method for this intelligent online slurry oxidation control system. Background Technology

[0002] In wet desulfurization processes, the slurry oxidation stage is a crucial step in ensuring desulfurization efficiency and improving gypsum quality. Its core involves introducing sufficient air into the slurry of the absorption tower using an oxidation blower, thus reducing the sulfite (SO32-) generated during the desulfurization reaction. 2- ) is oxidized to sulfate (SO4) 2- This process ultimately produces qualified gypsum products. The current industry-wide methods for controlling oxidation airflow have the following prominent problems:

[0003] 1) The control mode is crude and lacks precision: Traditional control methods mostly determine the oxidation air volume based on theoretical calculations of the SO2 concentration at the inlet of the absorption tower, without considering the real-time feedback of the sulfite concentration in the absorption tower slurry, nor combining it with TDS and Cl. - The influence of key parameters such as concentration and pH value can lead to either an excess of oxidation air volume, resulting in wasted fan energy, or an insufficient volume, leading to the accumulation of sulfite ions, which affects desulfurization efficiency and gypsum quality.

[0004] 2) Weak ability to adapt to peak-shaving conditions: As the demand for "economic peak shaving" in the power industry becomes increasingly urgent, the unit load fluctuates frequently, usually in the range of 30%-100%. The traditional control logic is slow to respond and maintains high air volume supply under low load conditions, resulting in a large amount of ineffective energy consumption; under high load conditions, insufficient air volume may lead to incomplete oxidation.

[0005] 3) Inadequate safety redundancy mechanism: There is a lack of emergency control schemes for extreme operating conditions such as sensor failure and sudden increase in inlet SO2 concentration, which may easily lead to risks such as desulfurization efficiency exceeding the standard and equipment damage.

[0006] 4) Lack of multi-parameter monitoring and low level of intelligence: Existing systems mostly only monitor inlet SO2 concentration and fan operating status, and do not monitor sulfite, Cl-, etc. -Integrated online monitoring of core indicators such as ORP is required. Traditional monitoring methods use multiple independent sensors installed separately and sampling separately. Due to differences in sampling points and sampling times, the data of various parameters lack correlation and consistency (for example, the pH value and sulfite concentration at different sampling points at the same time may not match), which cannot provide an accurate data foundation for intelligent control. At the same time, independent sensors need to be installed, calibrated and cleaned separately, which not only occupies a lot of space and has high installation costs, but also has a cumbersome maintenance process. There is a lack of real-time monitoring of the operating status, and faults such as reagent shortages, sensor leaks and calibration abnormalities cannot be warned in time, which can easily lead to data distortion or system shutdown, increase operating costs and safety risks, and make it difficult to meet the needs of enterprises for carbon emission reduction accounting and refined energy consumption management.

[0007] Therefore, developing an online slurry oxidation system that can achieve precise control, adapt to peak-shaving conditions, has multiple safety guarantees, and supports intelligent management has become an urgent need for the green and low-carbon transformation of the desulfurization industry. Summary of the Invention

[0008] The primary objective of this invention is to overcome the shortcomings of the aforementioned background technology and provide an intelligent online oxidation control system for slurry. This invention addresses the problems of high energy consumption, slow response, unstable oxidation effect, and weak adaptability to peak-shaving conditions inherent in traditional coarse-grained desulfurization oxidation airflow control. It constructs a technical system of "online monitoring - multi-parameter coordination - dynamic closed loop - safety redundancy"; by integrating sulfite concentration, inlet SO2 concentration, TDS, and Cl... - This invention features an integrated online monitoring module that combines core indicators such as concentration, pH value, ORP, and oxidation burial depth. It incorporates a triple-core control logic and a multi-parameter weight correction algorithm to achieve precise, on-demand supply of oxidation air volume. Simultaneously, it incorporates multiple safety redundancy mechanisms and a rapid response strategy for peak-shaving conditions, balancing desulfurization efficiency, gypsum quality, and energy conservation goals. It also supports seamless integration with DCS systems. This invention can reduce desulfurization system energy consumption by 15%-30%, maintain a stable desulfurization efficiency of ≥99%, and adapt to unit load fluctuations of ±60%, providing technical support for the desulfurization industry's dual core objectives of "high-efficiency desulfurization + economical peak shaving."

[0009] The second objective of this invention is to provide a control method for such an intelligent control system for online oxidation of slurry.

[0010] To achieve the aforementioned first objective, the technical solution of the present invention is as follows: an intelligent control system for online oxidation of slurry, characterized in that it includes an intelligent online oxidation analyzer for slurry connected to the bottom side of the slurry tank of the absorption tower, a data processing and control module connected to the intelligent online oxidation analyzer for slurry, a fan connected to the slurry tank, and an inlet CEMS installed at the flue gas inlet of the absorption tower; the data processing and control module is connected to the fan, the oxidation air pipeline of the fan is installed in the slurry tank, and the inlet CEMS is connected to the data processing and control module;

[0011] The online oxidation intelligent analyzer for slurry includes a sampling inlet, an analytical water tank, and a sedimentation tank; both the analytical water tank and the sedimentation tank are connected to the sampling inlet; the analytical water tank is equipped with an ORP sensor, a sulfite sensor, a Cl- sensor, a TDS sensor, and a density sensor; the sedimentation tank is equipped with a pH sensor.

[0012] The ORP sensor, sulfite sensor, Cl- sensor, pH sensor, TDS sensor, and density sensor are connected to the data processing and control module.

[0013] The data processing and control module incorporates a multi-parameter weight correction algorithm. This algorithm is based on a gradient boosting tree machine learning model, which obtains the weight coefficients of each monitoring parameter through training with historical operating data. It then optimizes the model accuracy using synchronous data from the online slurry oxidation intelligent analyzer and establishes an oxidation air volume calculation model.

[0014] Q oxidation air volume = w1 × C(SO3) 2- )+w2×TDS+w3×C(Cl - )+w4×pH+w5×ORP+w6×ρ(density)+w7×H(burial depth)+ε;

[0015] Where: w1 is the weighting coefficient of sulfite concentration, w2 is the weighting coefficient of TDS, and w3 is the weighting coefficient of Cl. - The weighting coefficients are: concentration (w4), pH (w5), ORP (w6), slurry density in slurry tank (110), and burial depth of the oxidation air pipeline. ε is the correction coefficient. 2- ) represents the sulfite concentration, in mmol / L; C(Cl) - ) for Cl - Concentration, in mmol / L; ρ (density), the density of the slurry in the slurry pool, in g / cm³; H (burial depth), the burial depth of the oxidation air pipeline, in m.

[0016] In the above technical solution, the bottom of the analytical water tank is connected to the switch valve; the switch valve is connected to the drain port of the analytical water tank through the first drain valve; the bottom of the sedimentation tank is connected to the second drain valve; and the second drain valve is connected to the drain port of the sedimentation tank through the third drain valve.

[0017] In the above technical solution, the online slurry oxidation intelligent analyzer further includes a process water flushing inlet and a compressed air flushing inlet; the process water flushing inlet is connected to the switch valve in sequence through a process water flushing valve and a flushing valve; the compressed air flushing inlet is connected to the switch valve in sequence through a compressed air flushing valve and a flushing valve.

[0018] In the above technical solution, the bottom side of the slurry tank is connected to the sampling inlet via a sampling valve;

[0019] The sampling inlet is connected to the bottom side of the analysis water tank in sequence through the first sampling valve, the second sampling valve, the filter valve, and the filter pump; the sampling inlet is connected to the side of the sedimentation tank in sequence through the first sampling valve and the second sampling valve.

[0020] In the above technical solution, the top side of the analysis water tank is connected to the analysis water tank drain outlet through a first overflow pipe; the top side of the sedimentation tank is connected to the sedimentation tank drain outlet through a second overflow pipe.

[0021] In the above technical solution, the fan is a magnetic levitation oxidation fan.

[0022] To achieve the second objective mentioned above, the technical solution of the present invention is: a control method for an online intelligent control system for slurry oxidation, characterized in that: the data processing and control module incorporates a triple core control logic, which determines the final oxidation air volume through dynamic calculation and maximum value selection.

[0023] Q_final = max(Q_sulfite, Q_inlet SO2 catch-up, Q_oxygen-sulfur ratio correction);

[0024] Logic 1, Q Sulfite: The sulfite graded adjustment logic dynamically adjusts the oxidation fan load in real time based on the sulfite concentration measured by the sulfite sensor (222).

[0025] When C(SO3) 2- When ) < 0.15 mmol / L, Q sulfite ion = 60% Q oxidizing air volume;

[0026] When 0.15 mmol / L ≤ C(SO3) 2- When ) < 5 mmol / L, Q sulfite = 60% - 100% Q oxidizing air volume, increasing linearly;

[0027] When C(SO3) 2-When ≥5mmol / L, Q(sulfite) = 100%Q(oxidation air volume);

[0028] Logic 2, Q entry point SO2 fallback: The calculation formula is as follows:

[0029] QentrySO2 catch-all = [m(SO2) / 64] × SR' × 22.4 / 0.21;

[0030] Where: m(SO2) is the SO2 mass flow rate in the inlet flue gas, in kg / h; SR' is the forced oxidation oxygen demand per mole of S, in kmol O / kmol S, SR' = 0.7 + 405 / SD; SD is the burial depth of the oxidation air pipeline, in feet; 0.21 is the volume fraction of O2 in the air; 22.4 is the molar volume of the gas under standard conditions, in Nm³ / kmol;

[0031] Simultaneously introduce TDS and Cl - Concentration correction: If TDS > 20% or C(Cl) - When the concentration is >20000 mg / L, the SO2 at the inlet of Q increases by 10%-15%;

[0032] Logic 3, Q Oxygen-Sulfur Ratio Correction: The oxygen-sulfur ratio is defined as the ratio of the molar amount of O in the oxidation air to the molar amount of SO2 in the inlet flue gas. Theoretically, the oxygen-sulfur ratio is required to be ≥2.2. If the final oxygen-sulfur ratio corresponding to Q calculated according to Logic 1 and 2 is <1, then the minimum air volume is calculated by back-calculating based on an oxygen-sulfur ratio of 1.

[0033] QO-sulfur ratio correction = m(SO2) / 64×2.2 / 2 / 0.21×22.4 = 1.834×m(SO2);

[0034] Where: 64 is the molar mass of SO2, in g / mol; 2 is the number of O atoms in the O2 molecule; 0.21 is the volume fraction of O2 in the air; and 22.4 is the molar volume of the gas under standard conditions, in Nm³ / kmol.

[0035] In the above technical solution, the data processing and control module also incorporates pH co-correction logic; the pH co-correction logic is as follows:

[0036] When 5.0 > pH ≥ 4.5, the fan load increases linearly by 10%-15% based on the calculation results of the triple core control logic;

[0037] When pH < 4.5, an "emergency ventilation increase" command is triggered, the fan load is directly increased to 100% of the design capacity, and an "abnormal slurry pH" alarm signal is sent to the DCS system.

[0038] In the above technical solution, the data processing and control module also has built-in ORP and Cl -Cooperative correction logic; ORP and Cl - Collaborative correction logic:

[0039] When ORP < 200mV, the fan load increases by 5%-10%;

[0040] When C(Cl) - When C(Cl) > 20000 mg / L, the fan load increases by 8%-15%; when C(Cl) > 20000 mg / L, the fan load increases by 8%-15%; - When the concentration of Cl is greater than 30000 mg / L, it is synchronously triggered. - Alarm triggered if concentration exceeds limit.

[0041] Compared with the prior art, the present invention has the following advantages.

[0042] 1) Precise control, energy saving and consumption reduction: This invention takes sulfite concentration as the core, combines multi-parameter weight correction algorithm and dynamic closed-loop logic to avoid excessive oxidation and ineffective air supply. Practical application has verified that it saves more than one million yuan in electricity costs per year, and reduces energy consumption by 15%-30% compared with traditional control methods.

[0043] 2) Adaptable to peak shaving and rapid response: This invention can quickly respond to fluctuations in unit load of ±30%, with a response time of ≤10 seconds. It automatically reduces the fan load under low load conditions and accurately matches the air volume under high load conditions, thereby improving the system's operational flexibility.

[0044] 3) Stable and efficient, quality assurance: This invention ensures stable desulfurization efficiency ≥95% and residual sulfite content ≤0.1% in gypsum through triple safety redundancy and multi-parameter collaborative correction. - The concentration should be controlled within a reasonable range to avoid gypsum deterioration;

[0045] 4) Safe and reliable with strong fault tolerance: This invention sets up multiple safety mechanisms for extreme conditions such as sensor failure and sudden rise in inlet SO2, reducing the system failure rate by 80% and ensuring the continuous and stable operation of the desulfurization system;

[0046] 5) Intelligent management and control, data empowerment: This invention is seamlessly integrated with DCS, providing comprehensive data support for process optimization, carbon emission reduction accounting, and energy consumption management, and promoting the green and low-carbon transformation of the desulfurization industry;

[0047] 6) High versatility and easy to promote: Parameters such as grading threshold and weight coefficient support project customization, adapt to wet desulfurization systems of different scales and working conditions, and are easy to install and debug. They can be widely used in industries such as thermal power generation, steel, and chemical industry.

[0048] 7) Revolutionary improvement in data quality: The online intelligent slurry oxidation analyzer achieves "sampling from the same source and measurement simultaneously", completely solving the data inconsistency problem caused by traditional decentralized sampling. Data consistency is improved by 80%, providing a high-quality data foundation for intelligent control, and the accuracy of oxidation air volume adjustment is improved to ±5%.

[0049] 8) Significantly reduced operation and maintenance costs: The automatic cleaning, calibration, and maintenance functions of this invention, along with the pre-diagnosis system, reduce the equipment maintenance frequency from once a week to once a month, reducing maintenance time by 75%; the fault early warning accuracy rate is ≥98%, avoiding process fluctuations caused by data distortion and reducing operating costs;

[0050] 9) High integration and easy installation: A single online slurry oxidation intelligent analyzer replaces 6 independent sensors, reducing installation space by 80%, eliminating the need for complex pipeline layout, and shortening the installation and commissioning cycle by 50%. Attached Figure Description

[0051] Figure 1 This is a schematic diagram of the structure of the present invention.

[0052] Figure 2 This is a schematic diagram of the intelligent online oxidation analyzer for slurry.

[0053] Figure 3 This is a flowchart of the present invention.

[0054] Among them, 100-absorption tower, 110-slurry tank, 111-sampling valve, 200-slurry online oxidation intelligent analyzer, 210-sampling inlet, 211-first sampling valve, 212-second sampling valve, 213-filter valve, 214-filter pump, 220-analytical water tank, 221-ORP sensor, 222-sulfite sensor, 223-Cl-sensor, 224-on / off valve, 225-TDS sensor, 226-density sensor, 230-settling tank, 231-pH sensor, 24-... 1-First vent valve, 242-Second vent valve, 243-Third vent valve, 251-Analytical water tank vent, 252-Sedimentation tank vent, 260-Process water flushing inlet, 261-Process water flushing valve, 270-Compressed air flushing inlet, 271-Compressed air flushing valve, 280-Flushing valve, 291-First overflow pipe, 292-Second overflow pipe, 300-Data processing and control module, 400-Fan, 410-Oxidation air pipeline, 500-Inlet CEMS, 600-Calibration chamber. Detailed Implementation

[0055] The embodiments of the present invention will be described in detail below with reference to the accompanying drawings, but these descriptions are not intended to limit the invention and are merely illustrative. The advantages of the present invention will become clearer and easier to understand through this description.

[0056] Referring to the accompanying drawings, a slurry online oxidation intelligent control system is characterized by comprising: an online slurry oxidation intelligent analyzer 200 connected to the bottom side of the slurry tank 110 of the absorption tower 100; a data processing and control module 300 connected to the online slurry oxidation intelligent analyzer 200; a blower 400 connected to the slurry tank 110; and an inlet CEMS 500 installed at the flue gas inlet of the absorption tower 100; the data processing and control module 300 is connected to the blower 400, the oxidation air pipeline 410 of the blower 400 is installed inside the slurry tank 110, and the inlet CEMS 500 is connected to the data processing and control module 300;

[0057] The online slurry oxidation intelligent analyzer 200 includes a sampling inlet 210, an analysis water tank 220, and a sedimentation tank 230; both the analysis water tank 220 and the sedimentation tank 230 are connected to the sampling inlet 210; the analysis water tank 220 is equipped with an ORP sensor 221, a sulfite sensor 222, a Cl- sensor 223, a TDS sensor 225, and a density sensor 226; the sedimentation tank 230 is equipped with a pH sensor 231;

[0058] The ORP sensor 221, sulfite sensor 222, Cl- sensor 223, pH sensor 231, TDS sensor 225 and density sensor 226 are connected to the data processing and control module 300.

[0059] The data processing and control module 300 incorporates a multi-parameter weight correction algorithm. This algorithm is based on a gradient boosting tree machine learning model. It is trained using historical operating data (covering different loads, SO2 concentrations, and slurry physicochemical parameters) to obtain the weight coefficients of each monitoring parameter. The model accuracy is optimized using synchronous data from the same source provided by the online slurry oxidation intelligent analyzer 200, and an oxidation air volume calculation model is established.

[0060] Q oxidation air volume = w1 × C(SO3) 2- )+w2×TDS+w3×C(Cl - )+w4×pH+w5×ORP+w6×ρ(density)+w7×H(burial depth)+ε;

[0061] Where: w1 is the weighting coefficient of sulfite concentration, w2 is the weighting coefficient of TDS, and w3 is the weighting coefficient of Cl. - The weighting coefficients are: concentration (w4), pH (w5), ORP (w6), slurry density in slurry tank 110 (w7), and burial depth of oxidation air pipeline 410 (w7); ε is a correction coefficient; C(SO3) 2- ) represents the sulfite concentration, in mmol / L; C(Cl) -) for Cl - Concentration, in mmol / L; ρ (density), the density of the slurry in slurry tank 110, in g / cm³; H (burial depth), the burial depth of the oxidation air pipeline 410, in m; Q (oxidation air volume), in Nm³. 3 / h.

[0062] The bottom of the analysis water tank 220 is connected to the switch valve 224; the switch valve 224 is connected to the analysis water tank drain port 251 through the first drain valve 241; the bottom of the sedimentation tank 230 is connected to the second drain valve 242; the second drain valve 242 is connected to the sedimentation tank drain port 252 through the third drain valve 243.

[0063] The online slurry oxidation intelligent analyzer 200 also includes a process water flushing inlet 260 and a compressed air flushing inlet 270; the process water flushing inlet 260 is connected to the switch valve 224 in sequence through a process water flushing valve 261 and a flushing valve 280; the compressed air flushing inlet 270 is connected to the switch valve 224 in sequence through a compressed air flushing valve 271 and a flushing valve 280.

[0064] The bottom side of the slurry tank 110 is connected to the sampling inlet 210 via a sampling valve 111;

[0065] The sampling inlet 210 is connected to the bottom side of the analysis water tank 220 in sequence through the first sampling valve 211, the second sampling valve 212, the filter valve 213, and the filter pump 214; the sampling inlet 210 is connected to the side of the sedimentation tank 230 in sequence through the first sampling valve 211 and the second sampling valve 212.

[0066] The top side of the analysis water tank 220 is connected to the analysis water tank drain port 251 via a first overflow pipe 291; the top side of the sedimentation tank 230 is connected to the sedimentation tank drain port 252 via a second overflow pipe 292.

[0067] The fan 400 is a magnetic levitation oxidation fan with a frequency conversion range of 30Hz-60Hz and an adjustment accuracy of ±0.5Hz. It communicates with the data processing and control module 300 via the Modbus TCP protocol and adjusts the operating frequency of the fan 400 in real time according to the final Q command to achieve stepless adjustment of the oxidation air volume. The fan 400 is equipped with an operating status monitoring unit to monitor vibration, temperature, and current, and the data is fed back to the control module in real time.

[0068] A control method for an online intelligent control system for slurry oxidation, characterized in that: the data processing and control module 300 incorporates a triple core control logic, which determines the final oxidation air volume through dynamic calculation and maximum value selection.

[0069] Q_final = max(Q_sulfite, Q_inlet SO2 catch-up, Q_oxygen-sulfur ratio correction);

[0070] Q final, Q sulfite, Q inlet SO2 catch-up, and Q oxygen-sulfur ratio correction are all in Nm. 3 / h;

[0071] The three air volumes were calculated using three different methods. Q ultimately selected the maximum value from these three calculations and sent it to the 400 frequency-controlled fan.

[0072] Logic 1, Q Sulfite: The sulfite grading adjustment logic dynamically adjusts the oxidation fan load in real time based on the sulfite concentration measured by the sulfite sensor (222). The grading threshold supports project customization and on-site calibration.

[0073] When C(SO3) 2- When sulfite concentration is <0.15 mmol / L, Qsulfite = 60% of Qoxidation airflow, maintaining the basic oxidation airflow; the fan load at 400 rpm is approximately 60% of the design capacity.

[0074] When 0.15 mmol / L ≤ C(SO3) 2- When ) < 5 mmol / L (corresponding to 12-400 mg / L), Q sulfite = 60%-100% Q oxidation air volume, increasing linearly; the fan load of 400 is approximately 60%-100% of the design rating, increasing linearly.

[0075] When C(SO3) 2- When ≥5mmol / L, Q sulfite = 100%Q oxidation air volume, forced full-load oxidation; the fan load of 400 is approximately 100% of the design capacity;

[0076] Logic 1 is the main logic.

[0077] Logic 2, Q entry point SO2 fallback: The calculation formula is as follows:

[0078] QentrySO2 catch-all = [m(SO2) / 64] × SR' × 22.4 / 0.21;

[0079] Where: m(SO2) is the SO2 mass flow rate in the inlet flue gas, in kg / h; SR' is the forced oxidation oxygen demand per mole of S, in kmol O / kmol S, SR' = 0.7 + 405 / SD; SD is the burial depth of the oxidation air pipeline 410, in feet; 0.21 is the volume fraction of O2 in the air; 22.4 is the molar volume of the gas under standard conditions, in Nm³ / kmol;

[0080] Simultaneously introduce TDS and Cl - Concentration correction: If TDS > 20% or C(Cl) -When the concentration is >20000 mg / L, the SO2 at the inlet of Q increases by 10%-15%;

[0081] Logic 2 is the safety lower limit, which serves as a "safety net" when the sulfite sensor 222 malfunctions or the inlet SO2 concentration suddenly increases.

[0082] Logic 3, Q Oxygen-Sulfur Ratio Correction: The oxygen-sulfur ratio is defined as the ratio of the molar amount of O in the oxidation air to the molar amount of SO2 in the inlet flue gas. Theoretically, the oxygen-sulfur ratio is required to be ≥2.2. If the final oxygen-sulfur ratio corresponding to Q calculated according to Logic 1 and 2 is <1, then the minimum air volume is calculated by back-calculating based on an oxygen-sulfur ratio of 1.

[0083] QO-sulfur ratio correction = m(SO2) / 64×2.2 / 2 / 0.21×22.4 = 1.834×m(SO2);

[0084] Where: m(SO2) is the mass flow rate of SO2 in the inlet flue gas, 64 is the molar mass of SO2 in g / mol; 2 is the number of O atoms in the O2 molecule; 0.21 is the volume fraction of O2 in the air; 22.4 is the molar volume of the gas under standard conditions in Nm³ / kmol;

[0085] Logic 3 provides measurement assurance.

[0086] The data processing and control module 300 also has a built-in pH co-correction logic; the pH co-correction logic is as follows:

[0087] When pH 5.0 > pH ≥ 4.5, the load of the 400 kW fan increases linearly by 10%-15% based on the calculation results of the triple core control logic; it increases by 12% when pH = 4.8 and by 15% when pH = 4.5.

[0088] When pH < 4.5, the "emergency ventilation" command is triggered, the fan load of 400 is directly increased to 100% of the design capacity, and an "abnormal pH of slurry" alarm signal is sent to the DCS system.

[0089] pH-coordinated correction logic serves as a supplementary correction mechanism to further optimize oxidation effects.

[0090] The data processing and control module 300 also has built-in ORP and Cl - Cooperative correction logic; ORP and Cl - Collaborative correction logic:

[0091] When ORP < 200mV, the load on the fan (400) increases by 5%-10%;

[0092] When C(Cl) - When C(Cl) > 20000 mg / L, the fan load increases by 8%-15%; when C(Cl) > 20000 mg / L, the fan load increases by 8%-15%; -When the concentration of Cl is greater than 30000 mg / L, it is synchronously triggered. - Alarm triggered if concentration exceeds limit.

[0093] In practical use, the 200 online slurry oxidation intelligent analyzer innovatively integrates the sulfite sensor 222, TDS sensor 225, Cl- sensor 223, pH sensor 231, ORP sensor 221, and density sensor 226 into the same sampling flow path, achieving "sampling from the same source and synchronous measurement." The specific design is as follows:

[0094] 1) Core Structure:

[0095] Sampling flow path: The integrated flow path design is made of corrosion-resistant material, with only one sampling inlet 210, which is installed at a key node of the gypsum discharge pump accessory of the absorption tower. The flow path has a built-in constant temperature control unit with a temperature control accuracy of ±0.5℃, ensuring that the measurement environment of each sensor is consistent.

[0096] Integrated sensors: All sensor probes are embedded in the same flow path cavity, with a probe spacing of ≤5cm and a measurement delay of ≤300ms, ensuring data synchronization; performance parameters of each sensor:

[0097] Sulfite sensor 222: Measurement range 0-10 mmol / L, accuracy ±5%;

[0098] pH sensor 231: Measurement range 0-14, accuracy 0.1, resolution 0.01;

[0099] ORP sensor 221: Measurement range -1999~+1999mV, accuracy 0.1mV, resolution 0.01mV;

[0100] TDS sensor 225: Measurement range 0-30%, accuracy ±0.1%;

[0101] Cl-sensor 223: Measurement range 0-50000 mg / L, accuracy ±5%;

[0102] Density sensor 226: Measurement range 1.0-1.5 g / cm³, accuracy ±0.001 g / cm³;

[0103] Auxiliary unit: built-in cleaning chamber, calibration chamber 600, and reagent storage chamber, integrating a micro metering pump and ultrasonic cleaning components.

[0104] 2) Automated operation and maintenance function:

[0105] Automatic cleaning: Set timed cleaning (default 24 hours / time) and triggered cleaning (when sensor response time > 1s). Use ultrasonic cleaning (50W power, 30s duration) + neutral cleaning solution to remove scale and slurry residue from the probe surface and ensure measurement accuracy.

[0106] Automatic calibration: Supports single-point / multi-point automatic calibration; the calibration chamber 600 contains built-in standard solutions (sulfite 0.1mmol / L, 5mmol / L; pH 4.01, 7.00, 10.01; Cl). - The calibration process is automatically initiated when the concentration is 1000 mg / L or 10000 mg / L, triggered at regular intervals (default 48 hours / time) or when the data fluctuation exceeds the threshold (±5%). The standard solution is selected to perform the calibration operation, the new calibration coefficient is calculated, and the calibration result is stored in real time.

[0107] Automatic maintenance: The calibration chamber 600 has a built-in reagent balance monitoring sensor 610. When the balance of cleaning fluid and calibration fluid is lower than 10%, a reagent replenishment warning is automatically triggered. The probe activation and maintenance program is started periodically (default 720 hours / time) to extend the service life of the sensor. The calibration chamber 600 is connected to the analysis water tank 220 through the data processing and control module 300.

[0108] 3) Pre-diagnostic system: Equipped with a built-in microprocessor, it monitors the instruments, valves, and reagent levels of the entire equipment in real-time, dynamically monitoring the equipment's operating status to achieve:

[0109] Fault warning: The system provides graded warnings for faults such as reagent shortage, calibration abnormality (calibration deviation > 3%), flow path leakage (pressure sensor monitoring), sensor probe contamination (abnormal response time), and temperature runaway (Level 1 alarm: immediate handling; Level 2 alarm: planned handling), and automatically records the fault time, type, and data change trend;

[0110] Status assessment: The stability coefficient of each sensor is calculated in real time. When the stability coefficient is <0.9 (indicating sensor aging), the probe is prompted to be replaced to avoid data distortion.

[0111] 4) Data transmission: All sensor data are synchronously uploaded to the data processing and control module 300 via the same data interface (supporting Modbus TCP / OPCUA protocol), with a sampling frequency ≥1Hz and a data transmission delay ≤500ms;

[0112] The inlet CEMS500 includes an inlet SO2 concentration sensor (measurement range 0-10000 mg / Nm³). 3 The system includes a flue gas flow sensor (measurement accuracy ±2%), an inlet flue gas O2 concentration sensor, and equipment and structural parameters: burial depth of the oxidation air pipeline, and the absorption tower slurry level gauge 112 (measurement range 0-20m, accuracy ±0.01m). The absorption tower slurry level gauge 112 is installed on the side of the slurry pool 110 to measure the liquid level height. The burial depth of the oxidation air pipeline is determined during the design phase, and the burial depth of the oxidation air pipeline is equal to the liquid level height minus the oxidation air pipeline height.

[0113] The data processing and control module 300 is the core computing unit of the system, which adopts a PLC controller and supports Modbus TCP / OPCUA protocol;

[0114] This invention incorporates a security redundancy module:

[0115] Sensor fault diagnosis: When any core sensor (sulfite, pH, inlet SO2) data is abnormal (outside the measurement range or fluctuation > 5% / s), the system automatically switches to "backup mode", using Q inlet SO2 as the dominant airflow, and sends a sensor fault alarm; New emergency mechanism for the slurry online oxidation intelligent analyzer 200: When the slurry online oxidation intelligent analyzer 200 malfunctions (such as flow path leakage, calibration abnormality, reagent depletion and failure to replenish in time), the system automatically determines that multiple parameter data are invalid, immediately switches to inlet SO2 backup logic, and sends a "detector fault" level one alarm to the DCS system, prompting operators to handle it in time.

[0116] Emergency response to fan failure: When the fan 400 operation status monitoring unit detects an abnormality (vibration > 4.5 mm / s or temperature > 85℃), it will automatically start the backup fan 40, or reduce the unit load and issue an alarm.

[0117] Over-temperature and over-pressure protection: When the slurry temperature in the absorption tower 100 exceeds 60°C, the load on the fan 400 increases by 10%, and the cooling system is activated simultaneously; when the pressure in the oxidation air pipeline 410 exceeds 0.6MPa, the pressure is automatically released and an alarm is triggered.

[0118] This invention includes a data integration module:

[0119] It supports seamless integration with desulfurization system DCS and enterprise energy management platforms, and uploads the following data in real time: the operating status of the slurry online oxidation intelligent analyzer 200 (including data from each sensor, calibration results, cleaning records, and fault warning information), the operating parameters of the fan 400 (frequency, current, load), the oxidation air volume calculation results, alarm information, etc.; it has data storage function (storage period ≥ 1 year), providing reliable data support for process optimization, carbon emission reduction accounting, and refined energy consumption management.

[0120] Example

[0121] Taking a limestone-gypsum desulfurization system of a 300MW coal-fired unit as an example, the system composition and installation are as follows:

[0122] The slurry online oxidation intelligent analyzer 200 is installed near the gypsum discharge pump of absorption tower 100 for sampling; inlet SO2 is obtained from CEMS data of the inlet flue of absorption tower 100; sulfite sensor 222; pH sensor 231, model: PH-800, measurement range 2-12; Cl- sensor 223, model: CL-600, measurement range 0-50000mg / L; TDS sensor 225, model: TDS-500, measurement range 0-30%; ORP sensor 221, model: ORP-700, measurement range -500~+500mV; oxidation depth data is obtained from the height difference between the liquid level of the absorption tower and the installation position of the oxidation air pipeline 410;

[0123] Logic debugging phase:

[0124] Basic air volume control: Calculate Q inlet SO2 based on inlet SO2 concentration and flue gas volume, adjust the fan frequency to 400 to the corresponding load, run continuously for 72 hours, and collect data such as sulfite concentration, pH, and TDS.

[0125] Data-driven optimization: Based on the collected data, a gradient boosting tree model was trained, and the weight coefficients of each parameter were optimized. Finally, w1=0.45, w2=0.15, w3=0.12, w4=0.18, w5=0.05, w6=0.03, w7=0.02; a correspondence between "sulfite concentration and oxidation air volume" was established and embedded into the PLC control logic.

[0126] Trial operation phase: Simulate unit load fluctuations (30%-100%), sudden changes in inlet SO2 concentration (from 1000mg / Nm³ to 5000mg / Nm³), and other operating conditions to verify the system's response speed, air volume regulation accuracy, and alarm function, and continuously optimize parameters until they meet the design requirements.

[0127] Operation process:

[0128] Daily operation: The system defaults to starting the sulfite graded regulation logic (main logic). The data processing and control module 300 receives data from each sensor in real time, calculates the Q oxidation air volume through a multi-parameter weight correction algorithm, and determines the final Q by combining the inlet SO2 back-off logic and the oxygen-sulfur ratio correction logic, and instructs the fan to adjust the frequency; at the same time, the data is uploaded to the DCS system.

[0129] Peak-shaving operation: When the unit load drops from 100% to 30%, the inlet SO2 concentration decreases synchronously, and the sulfite concentration drops to below 0.1 mmol / L. The system automatically adjusts the fan load to 60% of the design quota to avoid ineffective air supply. When the load increases from 30% to 100%, the sulfite concentration rises to 3 mmol / L, and the fan load increases linearly to 85% of the design quota to precisely match the oxidation demand.

[0130] Handling Abnormal Operating Conditions:

[0131] pH abnormality: When the pH drops to 4.4, the system triggers "emergency ventilation", the fan load increases to 100%, and an alarm is sent to the DCS. Operators adjust the pH of the slurry in time.

[0132] Sensor Failure: When the sulfite sensor data is abnormal, the system automatically switches to the Q inlet SO2 fallback logic, sends a sensor fault alarm, and the operator arranges for maintenance.

[0133] Cl - Exceeding the standard: When Cl - When the concentration rises to 25,000 mg / L, the fan load increases by 12%, and an alarm is triggered, which in turn triggers the gypsum dewatering system to increase the discharge volume.

[0134] Implementation effect verification:

[0135] After the system in this embodiment has been running for 6 months, the following indicators have been verified:

[0136] Energy consumption: The average operating load of the oxidation blower has been reduced from 85% under traditional control to 62%, saving approximately 1.2 million yuan in electricity costs annually and reducing energy consumption by 27%.

[0137] Desulfurization efficiency: Stably maintained at 96.5%-98%, meeting the national ultra-low emission requirements;

[0138] Gypsum quality: The residual sulfite content in gypsum is ≤0.08%, Cl... - The content is ≤1500mg / kg, which meets the GB / T9776-2021 standard for building gypsum;

[0139] Response performance: When the unit load fluctuates by ±30%, the system response time is ≤8 seconds, with no signs of insufficient or excessive oxidation;

[0140] Reliability: The system can operate continuously without failure for ≥5000 hours, and the alarm accuracy rate is 100%.

[0141] Data consistency: The deviation of synchronous measurement data from the online slurry oxidation intelligent analyzer 200 is ≤3%, which is far better than the 15% deviation of traditional decentralized measurement;

[0142] Operation and maintenance costs: Equipment maintenance frequency has been reduced from once a week to once a month, resulting in an annual maintenance cost reduction of 800,000 yuan.

[0143] All other unspecified parts belong to the prior art.

Claims

1. An online oxidation intelligent regulation system for slurry, characterized in that: The system includes an online slurry oxidation intelligent analyzer (200) connected to the bottom side of the slurry tank (110) of the absorption tower (100), a data processing and control module (300) connected to the online slurry oxidation intelligent analyzer (200), a fan (400) connected to the slurry tank (110), and an inlet CEMS (500) installed at the flue gas inlet of the absorption tower (100); the data processing and control module (300) is connected to the fan (400), the oxidation air pipeline (410) of the fan (400) is installed in the slurry tank (110), and the inlet CEMS (500) is connected to the data processing and control module (300); The online slurry oxidation intelligent analyzer (200) includes a sampling inlet (210), an analysis water tank (220), and a sedimentation tank (230); both the analysis water tank (220) and the sedimentation tank (230) are connected to the sampling inlet (210); the analysis water tank (220) is equipped with an ORP sensor (221), a sulfite sensor (222), a Cl- sensor (223), a TDS sensor (225), and a density sensor (226); the sedimentation tank (230) is equipped with a pH sensor (231). The ORP sensor (221), sulfite sensor (222), Cl- sensor (223), pH sensor (231), TDS sensor (225), and density sensor (226) are connected to the data processing and control module (300); The data processing and control module (300) incorporates a multi-parameter weight correction algorithm. This algorithm is based on a gradient boosting tree machine learning model, which obtains the weight coefficients of each monitoring parameter through training with historical operating data. It then optimizes the model accuracy using synchronous data from the online slurry oxidation intelligent analyzer (200) and establishes an oxidation air volume calculation model. Q oxidizing air volume = w1 x C(SO3 2- ) + w2 x TDS + w3 x C(Cl - ) + w4 x pH + w5 x ORP + w6 x p(density) + w7 x H(burial depth) + ε; wherein: w1 is the weight coefficient of sulfite concentration, w2 is the weight coefficient of TDS, w3 is the weight coefficient of Cl - concentration, w4 is the weight coefficient of pH value, w5 is the weight coefficient of ORP, w6 is the weight coefficient of slurry density in the slurry tank (110), w7 is the weight coefficient of the buried height of the oxidation air pipe network (410); ε is the correction coefficient; C(SO3 2- ) is the sulfite concentration, with the unit of mmol / L; C(Cl - ) is the Cl - concentration, with the unit of mmol / L; ρ(density) is the slurry density in the slurry tank (110), with the unit of g / cm³; H(buried depth) is the buried height of the oxidation air pipe network (410), with the unit of m.

2. The slurry online oxidation intelligent control system according to claim 1, characterized in that: The bottom of the analytical water tank (220) is connected to the switch valve (224); the switch valve (224) is connected to the drain port (251) of the analytical water tank through the first drain valve (241); the bottom of the sedimentation tank (230) is connected to the second drain valve (242); the second drain valve (242) is connected to the drain port (252) of the sedimentation tank through the third drain valve (243).

3. The slurry online oxidation intelligent control system according to claim 2, characterized in that: The online slurry oxidation intelligent analyzer (200) also includes a process water flushing inlet (260) and a compressed air flushing inlet (270); the process water flushing inlet (260) is connected to the switch valve (224) in sequence through a process water flushing valve (261) and a flushing valve (280); the compressed air flushing inlet (270) is connected to the switch valve (224) in sequence through a compressed air flushing valve (271) and a flushing valve (280).

4. The intelligent control system for online oxidation of slurry according to claim 1, characterized in that: The bottom side of the slurry tank (110) is connected to the sampling inlet (210) via a sampling valve (111); The sampling inlet (210) is connected to the bottom side of the analysis water tank (220) in sequence through the first sampling valve (211), the second sampling valve (212), the filter valve (213), and the filter pump (214); the sampling inlet (210) is connected to the side of the sedimentation tank (230) in sequence through the first sampling valve (211) and the second sampling valve (212).

5. The intelligent control system for online oxidation of slurry according to claim 2, characterized in that: The top side of the analytical water tank (220) is connected to the analytical water tank drain port (251) via a first overflow pipe (291); the top side of the sedimentation tank (230) is connected to the sedimentation tank drain port (252) via a second overflow pipe (292).

6. The intelligent control system for online oxidation of slurry according to claim 1, characterized in that: The fan (400) is a magnetic levitation oxidation fan.

7. A control method for an online intelligent control system for slurry oxidation, characterized in that: The data processing and control module (300) has a built-in triple core control logic, which determines the final oxidation air volume through dynamic calculation and maximum value selection. Q_final = max(Q_sulfite, Q_inlet SO2 catch-up, Q_oxygen-sulfur ratio correction); Logic 1, Q Sulfite: The sulfite graded adjustment logic dynamically adjusts the oxidation fan load in real time based on the sulfite concentration measured by the sulfite sensor (222). When C(SO3 2- ) < 0.15 mmol / L, Q sulfite = 60% Q oxidant When 0.15 mmol / L ≤ C(SO3 2- ) < 5 mmol / L, Q sulfite = 60-100% Q oxidant, linearly increasing; When C(SO3 2- ) ≥ 5 mmol / L, Q sulfite = 100% Q oxidant Logic 2, Q entry point SO2 fallback: The calculation formula is as follows: QentrySO2 catch-all = [m(SO2) / 64] × SR' × 22.4 / 0.21; Where: m(SO2) is the SO2 mass flow rate in the inlet flue gas, in kg / h; SR' is the forced oxidation oxygen demand per mole of S, in kmol O / kmol S, SR'=0.7+405 / SD; SD is the burial depth of the oxidation air pipeline (410), in feet; 0.21 is the volume fraction of O2 in the air; 22.4 is the molar volume of the gas under standard conditions, in Nm³ / kmol; Simultaneously introduce TDS and Cl - Concentration correction: if TDS > 20% or C(Cl - Concentration) > 20000 mg / L, QinletSO2 bottom increase 10%-15%; Logic 3, Q Oxygen-Sulfur Ratio Correction: The oxygen-sulfur ratio is defined as the ratio of the molar amount of O in the oxidation air to the molar amount of SO2 in the inlet flue gas. Theoretically, the oxygen-sulfur ratio is required to be ≥2.

2. If the final oxygen-sulfur ratio corresponding to Q calculated according to Logic 1 and 2 is <1, then the minimum air volume is calculated by back-calculating based on an oxygen-sulfur ratio of 1. QO-sulfur ratio correction = m(SO2) / 64×2.2 / 2 / 0.21×22.4 = 1.834×m(SO2); Where: 64 is the molar mass of SO2, in g / mol; 2 is the number of O atoms in the O2 molecule; 0.21 is the volume fraction of O2 in the air; and 22.4 is the molar volume of the gas under standard conditions, in Nm³ / kmol.

8. The control method of the intelligent control system for online oxidation of slurry according to claim 7, characterized in that: The data processing and control module (300) also has built-in pH synergistic correction logic; The pH co-correction logic is as follows: When 5.0 > pH ≥ 4.5, the load of the fan (400) increases linearly by 10%-15% based on the calculation results of the triple core control logic; When pH < 4.5, the "emergency ventilation" command is triggered, the load of the fan (400) is directly increased to 100% of the design capacity, and an "abnormal pH of slurry" alarm signal is sent to the DCS system.

9. The control method of the intelligent control system for online oxidation of slurry according to claim 8, characterized in that: The data processing and control module (300) also incorporates ORP and Cl - Cooperative correction logic; ORP and Cl - Cooperative correction logic: When ORP < 200mV, the load on the fan (400) increases by 5%-10%; When C(Cl - ) > 20000 mg / L, the fan load increases by 8%-15%; when C(Cl - ) > 30000 mg / L, the alarm of exceeding the standard of Cl⁻ concentration is triggered simultaneously.

Images