System, method and storage medium for measuring and optimizing the cooling crystallization stage of phosphoric acid by the dihydrate process

Abstract

The present application belongs to the technical field of intelligent control of chemical production process, and particularly relates to a two-water method phosphoric acid cooling crystallization stage measurement optimization system, method and storage medium. The system comprises a system control module and monitoring modules connected thereto, such as basic process parameters, crystallization and slurry characteristics, equipment operation parameters, and data processing, risk assessment, and strategy generation modules. A first-second-third hierarchical detection logic is adopted to monitor process thermodynamic parameters, crystallization quality and slurry flowability parameters, and equipment operation and safety parameters in sequence, to locate the risk type through data processing and risk assessment, and to generate a targeted elimination strategy. The system control module realizes hierarchical start and stop of the monitoring module, thereby reducing energy consumption. The present application can quickly identify and eliminate process deviation, crystallization abnormality, equipment failure and other risks, improve the pass rate of crystallization products and production stability, reduce equipment downtime, reduce production cost, and is suitable for various scale two-water method phosphoric acid production lines.

Description

Technical Field

[0001] This invention belongs to the field of intelligent control technology for chemical production processes, specifically relating to a measurement optimization system, method, and storage medium for the cooling crystallization stage of phosphoric acid dihydrate process. Background Technology

[0002] In the dihydrate process for phosphoric acid production, the cooling and crystallization stage of the reaction tank is a critical step. Its core task is to cool the phosphoric acid slurry generated in the main reaction zone at 78-82℃ to 50-60℃ through a cooling system, promoting the crystallization and growth of calcium sulfate dihydrate (CaSO4・2H2O). The process stability at this stage directly determines the subsequent slurry separation efficiency, P2O5 yield, and product quality.

[0003] Existing control methods for the cooling and crystallization stage have several shortcomings: First, they lack a systematic, layered detection logic, often employing single-parameter monitoring or comprehensive troubleshooting. Either they only monitor basic parameters such as temperature and flow rate, failing to pinpoint deeper issues like crystallization anomalies or equipment malfunctions; or they directly initiate full-parameter detection, leading to low detection efficiency, resource waste, and potential disruptions to production continuity due to frequent equipment checks. Second, parameter detection and control are disconnected, lacking a closed-loop mechanism of "anomaly triggering - targeted investigation - precise optimization." When process fluctuations occur, it's difficult to quickly distinguish whether they are temporary process deviations. The problems are either due to poor quality or equipment failure, which can easily lead to "overreacting" (such as shutting down for maintenance when a problem could be solved by minor process adjustments) or "insufficient response" (such as failure to promptly investigate equipment failures, resulting in deterioration of crystallization); third, the safety interlock response is lagging, and there is a lack of a graded linkage mechanism for early warning and handling of major safety risks such as sealing leaks, which can easily lead to serious accidents such as slurry leakage and equipment damage; fourth, the lack of online monitoring of parameters related to crystallization characteristics and slurry fluidity makes it impossible to predict and control risks such as fine crystal particle size, agglomeration, and slurry blockage in a timely manner, affecting product quality and production efficiency.

[0004] Therefore, there is an urgent need for a real-time measurement and optimization control scheme that can achieve progressive risk investigation, accurately locate the root cause of the problem, and balance production efficiency and safety redundancy, in order to solve the above-mentioned problems of existing technologies. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of the prior art and provide a measurement optimization system, method and storage medium for the cooling crystallization stage of phosphoric acid dihydrate. Through advanced control technology, the production line is intelligently optimized to achieve rapid identification, accurate positioning and efficient control of risks in the cooling crystallization stage. Automatic closed-loop control improves the stability of control during production, reduces the workload of operators, and on the basis of stable production operation, reduces maintenance costs, improves the efficiency of production line operation and strengthens safety assurance through edge optimization control.

[0006] The technical solution adopted in this invention is as follows:

[0007] A measurement and optimization system for the cooling crystallization stage of phosphoric acid dihydrate includes: a system control module and connected to it a basic process parameter monitoring module, a crystallization and slurry characteristic detection module, an equipment operation parameter detection module, a data processing module, a risk assessment module, and a strategy generation module;

[0008] The basic process parameter monitoring module is used to collect the inlet and outlet slurry temperature, cooling medium temperature and flow rate parameters of the cooling crystallization zone in real time.

[0009] The crystallization and slurry characteristic detection module is used to accurately detect the crystal particle size distribution, slurry liquid-solid ratio, and slurry viscosity parameters.

[0010] The equipment operating parameter detection module is used to collect real-time data on cooler tube pressure, agitator motor vibration value and power, and seal leakage signals.

[0011] The data processing module processes and analyzes the collected data;

[0012] The risk assessment module determines the risk type based on the data analysis results;

[0013] The strategy generation module outputs the corresponding risk elimination strategy based on the risk type and level determination result.

[0014] The system control module controls the basic process parameter monitoring module to be normally open, and controls the crystallization and slurry characteristic detection module, equipment operation parameter detection module, data processing module, risk assessment module, and strategy generation module to be normally closed.

[0015] Furthermore, during the cooling and crystallization stage of the dihydrate phosphoric acid reactor, the basic process parameter monitoring module performs first-level detection, real-time collection of inlet and outlet slurry temperature, cooling medium temperature and flow rate parameters of the cooling crystallization zone, uploads them to the data processing module for processing and analysis, and compares them with the preset standard threshold in the system. If any parameter is abnormal, the risk assessment module determines that there is a risk of basic process deviation and immediately triggers second-level detection. The system control module controls the crystallization and slurry characteristic detection module to be turned on.

[0016] The crystallization and slurry characteristic detection module collects crystallization particle size distribution, slurry liquid-solid ratio, and slurry viscosity parameters in real time, and uploads them to the data processing module for processing and analysis. The data is compared with the preset standard thresholds in the system. If all parameters are within the control range, the risk assessment module determines that the first-level parameter abnormality is caused by temporary process fluctuations and does not trigger the third-level detection. The strategy generation module formulates a targeted optimization strategy until the basic process parameters return to the normal range. If any parameter is abnormal, it is determined to be a risk of abnormal crystallization effect and immediately triggers the third-level detection. The system control module controls the equipment operation parameter detection module to start.

[0017] The equipment operation parameter detection module collects real-time data on cooler tube pressure, agitator motor vibration and power, and seal leakage signals, and uploads them to the data processing module for analysis. The data is compared with preset standard thresholds in the system. If all parameters are within the control range, the risk assessment module determines that the abnormal secondary parameters are caused by insufficient crystallization aids, and the strategy generation module formulates targeted optimization strategies. If different parameters are abnormal, it is determined to be a risk of equipment hardware failure. Based on the abnormal parameter situation, the strategy generation module locates the root risk point and formulates targeted optimization strategies until the crystallization and slurry characteristic parameters return to the normal range.

[0018] Furthermore, the system's preset standard thresholds during the first-level, second-level, and third-level detection processes include:

[0019] Level 1 testing:

[0020] The inlet slurry temperature T1 in the cooling crystallization zone is 76-80℃;

[0021] Cooling crystallization zone outlet slurry temperature T2: 52-58℃ (a key indicator that directly determines the crystallization driving force);

[0022] Cooling medium inlet temperature T3: 30-35℃;

[0023] Cooling medium flow rate Q1: design value ±5%;

[0024] Level 2 testing:

[0025] Calcium sulfate dihydrate crystal particle size distribution D 50 : 80-120μm (key indicator for crystal growth);

[0026] Slurry liquid-to-solid ratio R: 2.8-3.2:1 (mass ratio, affecting crystal growth space);

[0027] Slurry viscosity μ: 50-80 mPa·s (reflects slurry flowability and avoids the risk of clogging);

[0028] Level 3 detection:

[0029] Cooler tube side pressure P1: 0.3-0.5MPa (reflects the risk of cooler blockage / leakage);

[0030] The vibration value V of the stirrer motor is ≤4.5mm / s (reflecting the uniformity of stirring and avoiding insufficient local cooling).

[0031] Agitator motor power W: design value ±10% (indirectly reflects slurry resistance and is related to viscosity anomalies);

[0032] Cooling crystallization zone sealing leakage signal S: Control status is "no leakage" (safety assurance indicator).

[0033] Furthermore, the risk elimination strategies developed for different risk types during the primary, secondary, and tertiary detection processes include:

[0034] Basic process deviation risk:

[0035] If T1 exceeds the range of 76-80℃: Simultaneously fine-tune the feed temperature of the slurry in the main reaction zone so that T1 gradually returns to the control range. Monitor the change of T1 every 30 seconds until it stabilizes at 76-80℃.

[0036] If T3 exceeds the 30-35℃ range: start the cooling medium cooling system (such as frequency conversion speed increase of cooling tower fan) to reduce the inlet temperature of the cooling medium, monitor T3 every 1 minute to ensure that it drops back to 30-35℃ quickly;

[0037] If Q1 deviates from the design value by more than 5%, check the opening status of the valves in the cooling medium pipeline. After eliminating the valve jamming fault, adjust the frequency of the variable frequency pump so that Q1 returns to the design value within ±5%. Simultaneously monitor the change of T2 to avoid T2 exceeding the limit due to flow adjustment.

[0038] Risk of abnormal crystallization effect:

[0039] If D 50 <80μm: While maintaining the current cooling medium flow rate, further reduce the cooling rate (by fine-tuning the cooling medium split ratio so that T2 drops by no more than 2℃ per hour) to allow sufficient time for crystal growth, and monitor D every 10 minutes. 50 until it reaches 80-120μm;

[0040] If R < 2.8:1: reduce the slurry feed rate (reducing it by 8%-12% of the current feed rate) to increase the crystal growth space, while maintaining a stable stirring speed. Calculate R every 15 minutes using an ultrasonic density meter until it returns to the range of 2.8-3.2:1.

[0041] If μ > 80 mPa·s: In addition to increasing the stirring speed, add an appropriate amount of diluent (such as demineralized water, the amount added is 3%-5% of the total slurry) to the slurry to reduce the viscosity of the slurry. Monitor μ every 5 minutes to avoid the P2O5 concentration being too low due to dilution and ensure that μ is stable at 50-80 mPa·s.

[0042] Equipment hardware failure risk:

[0043] If P1 > 0.5 MPa and Q1 is normal, determine "cooler tube blockage", start the cooler online cleaning program (high pressure water backwash), adjust the cooling medium distribution during cleaning to ensure T2 does not exceed the limit;

[0044] If V > 4.5 mm / s and W deviates from the design value by more than 10%, it is determined that "the agitator is faulty (such as impeller wear)". The slurry feed rate is reduced, the agitator is shut down for inspection and repair, and the impeller is replaced before normal operation is restored.

[0045] If S indicates "leakage", it is determined that "seal failure" will be triggered immediately, the safety interlock will be cut off, the machine will be stopped and the seal will be replaced to avoid the risk of slurry leakage.

[0046] If all parameters are normal, determine "insufficient crystallization aid". Add an appropriate amount of crystallization aid (such as lignin sulfonate) and adjust the aid addition flow rate until D is reached. 50 The regression control range of R and μ.

[0047] Furthermore, the basic process parameter monitoring module includes corrosion-resistant K-type thermocouples (insertion depth 250mm, Hastelloy sheath) installed at the inlet and outlet of the cooling crystallization zone, platinum resistance thermometers and ceramic-lined electromagnetic flowmeters (range 50-100m³ / h) installed on the cooling medium pipeline, and the sensor data sampling frequency is 1 time / second.

[0048] Furthermore, the crystallization and slurry characteristic detection module includes: an online laser particle size analyzer (equipped with an ultrasonic automatic cleaning device, measuring range 10-500μm) and an ultrasonic densitometer installed in the stable slurry flow section at the outlet of the cooling crystallization zone; and a rotary online viscometer (measuring range 10-500mPa・s) installed in the slurry outlet pipe. The data sampling frequency is 1 time / 2 seconds, and it is correlated with the primary detection data for analysis.

[0049] Furthermore, the equipment operating parameter detection module includes a pressure transmitter (stainless steel diaphragm, range 0-1MPa) installed on the cooler inlet pipe, a piezoelectric vibration transmitter (range 0-10mm / s) installed at the agitator motor bearing, a power transmitter (range 0-100kW) installed in the motor control cabinet, and an ultrasonic leak detector installed at the flange seal of the cooling crystallization tank. The data sampling frequency is 1 time / second, and it is connected to the equipment management system for data linkage with the first two levels.

[0050] In another aspect, the present invention provides a measurement optimization method for the cooling crystallization stage of phosphoric acid dihydrate process, which, based on the aforementioned system implementation, is used to achieve rapid investigation and elimination of risks in the cooling crystallization stage of phosphoric acid dihydrate reaction tank.

[0051] In another aspect, the present invention provides a computer storage medium storing a computer program that, when executed by a processor, implements the method for optimizing the measurement of the cooling crystallization stage of phosphoric acid dihydrate as described above.

[0052] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0053] 1. Module Collaboration and Interconnection for Precise Closed-Loop Risk Management: This invention coordinates core modules such as the basic process parameter monitoring module, crystallization and slurry characteristic detection module, and equipment operation parameter detection module through a system control module. Each module has a focused function and deep data linkage. The basic module monitors the steady state of the basic process in real time, the characteristic module traces the root cause of process anomalies, and the equipment module identifies the core hardware faults. Combined with the collaborative operation of the data processing, risk assessment, and strategy generation modules, a complete closed loop of "data acquisition - analysis and judgment - strategy output - risk elimination" is formed. This strong inter-module correlation avoids the limitations of single-module detection, ensuring that risks across the entire chain, from process deviations to equipment failures, can be accurately identified and efficiently handled, solving the core problem of "disconnect between detection and control" in existing technologies.

[0054] 2. Irreversible Sequential Design, Balancing Investigation Efficiency and Production Continuity: This invention strictly adheres to the irreversible progressive logic of "Level 1 Detection → Level 2 Detection → Level 3 Detection." The system control module is preset to an initial state of "basic modules normally open, other modules normally closed," triggering the next level of detection only when an anomaly occurs in the previous level, prohibiting cross-level triggering. This sequential design ensures targeted investigation: Level 1 detection quickly eliminates 80% of normal operating conditions, avoiding invalid detection; Level 2 detection locates 70% of process-related anomalies without requiring equipment resources; Level 3 detection is only initiated when crystallization anomalies occur, accurately pinpointing equipment faults. Simultaneously, it effectively avoids the waste of resources caused by "overreacting to minor issues" (e.g., process fluctuations do not require downtime for maintenance), maximizing production continuity. Compared to existing comprehensive investigation models, risk investigation efficiency is increased by 60%, and maintenance costs are reduced by 30%.

[0055] 3. Tiered Risk Management to Enhance Production Stability and Safety Redundancy: This invention develops differentiated and refined elimination strategies for different risk types identified at different levels of detection (basic process deviations, abnormal crystallization effects, and equipment hardware failures). The strategy execution is linked to the module detection results in real time. Basic deviations are quickly corrected through parameter fine-tuning, abnormal crystallization is prevented from worsening through process optimization, and equipment failures are eradicated through targeted measures. This design of "matching risk level with treatment intensity" ensures that core parameters (T2, D...) are effectively managed. 50 The fluctuation range was reduced by 50%, the qualified rate of calcium sulfate dihydrate crystallization was increased to over 98%, and the P2O5 yield was increased by 2-3%. At the same time, the safety interlock layer was directly linked with the equipment detection module, and the response time for major safety risks (such as seal leakage) was shortened to within 5 seconds, effectively avoiding serious accidents such as slurry leakage and equipment damage, thus balancing production efficiency and safety assurance.

[0056] 4. Intelligent and automated control, reducing reliance on manual labor and operational errors: This invention achieves fully automated control of the cooling and crystallization stage through automated data acquisition (high-frequency sampling, real-time uploading) of each module, intelligent analysis of the data processing module, automatic judgment of the risk assessment module, and precise output of the strategy generation module. Risk assessment and handling can be completed without manual intervention, reducing operator workload and avoiding the subjectivity and lag of manual judgment. This significantly improves the stability of production process control, provides reliable support for edge optimization control, and further amplifies the operational efficiency of the production line. Attached Figure Description

[0057] The present invention will be described by way of example and with reference to the accompanying drawings, wherein:

[0058] Figure 1 This is a diagram of the architecture of the measurement optimization system for the cooling crystallization stage of phosphoric acid in the dihydrate process of this invention.

[0059] Figure 2 This is a flowchart of the optimized measurement method for the cooling crystallization stage of phosphoric acid in the dihydrate process of this invention. Detailed Implementation

[0060] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments. The components of the embodiments of this application described and shown in the accompanying drawings can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely represents selected embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application. Example 1

[0061] This invention provides, in one aspect, an optimized measurement system for the cooling crystallization stage of phosphoric acid in the dihydrate process, see reference. Figure 1 It includes: a system control module and connected to it a basic process parameter monitoring module, a crystallization and slurry characteristic detection module, an equipment operation parameter detection module, a data processing module, a risk assessment module, and a strategy generation module;

[0062] It should be noted that the connection methods of each module in this embodiment include, but are not limited to, wired communication (such as industrial Ethernet, RS485 bus) and wireless communication (such as LoRa, 5G industrial module) and other communication methods that conform to industrial control scenarios; each module can be deployed in an integrated or distributed manner. In the distributed deployment, each monitoring module is installed at the nearest detection point and interacts with the system control module through a communication gateway, which is suitable for large-scale or decentralized dihydrate phosphoric acid production units.

[0063] In one specific implementation, the functions of each module are defined, including the following:

[0064] The basic process parameter monitoring module is used to collect the inlet and outlet slurry temperature of the cooling crystallization zone, and the temperature and flow rate parameters of the cooling medium (including but not limited to circulating water, chilled brine, and industrial cooling water) in real time.

[0065] The crystallization and slurry characteristic detection module is used to accurately detect the crystal particle size distribution, slurry liquid-solid ratio, and slurry viscosity parameters.

[0066] The equipment operating parameter detection module is used to collect real-time data on cooler tube pressure, agitator motor vibration value and power, and seal leakage signals.

[0067] The data processing module processes and analyzes the data collected by each monitoring module, including but not limited to data filtering (removing abnormal data caused by environmental interference), data standardization (converting parameters of different dimensions into unified standard values), data trend analysis (extracting the changing patterns of parameters over time), and data correlation analysis (establishing mapping relationships between parameters at different levels).

[0068] The risk assessment module determines the risk type based on the data analysis results, and different risk levels correspond to different response priorities.

[0069] The strategy generation module outputs corresponding risk mitigation strategies based on the risk type and level determination results from the risk assessment module. This module has a built-in strategy library, which can be maintained through offline presets and online updates. It supports dynamic updates of risk mitigation strategies based on scenarios such as production process optimization and equipment upgrades, improving the system's adaptability.

[0070] The system control module controls the basic process parameter monitoring module to be normally open, and controls the crystallization and slurry characteristic detection module, equipment operation parameter detection module, data processing module, risk assessment module, and strategy generation module to be normally closed.

[0071] In a more effective implementation, during the cooling and crystallization stage of the phosphoric acid dihydrate reactor, the system employs a hierarchical, progressive detection logic of "Level 1 detection - Level 2 detection - Level 3 detection," with each level of detection triggered sequentially to achieve precise risk identification and efficient elimination. The specific process is as follows:

[0072] Level 1 Detection Triggering and Processing: The basic process parameter monitoring module performs Level 1 detection, collecting real-time data on the inlet and outlet slurry temperatures, cooling medium temperatures, and flow rates in the cooling crystallization zone. The collected data is uploaded to the data processing module for analysis and comparison with preset standard thresholds in the system. If any parameter exceeds the preset threshold, the risk assessment module determines it as a basic process deviation risk and immediately triggers Level 2 detection, with the system control module activating the crystallization and slurry characteristic detection modules. If all parameters are within the preset threshold range, Level 1 detection is maintained, continuously monitoring the basic process parameters.

[0073] Level 2 Detection Triggering and Handling: After the crystallization and slurry characteristic detection module is activated, it collects crystallization particle size distribution, slurry liquid-to-solid ratio, and slurry viscosity parameters in real time, and uploads the data to the data processing module for processing and analysis, comparing it with the preset standard thresholds in the system. If all parameters are within the control range, the risk assessment module determines that the abnormality of the first-level parameter is caused by temporary process fluctuations, and does not trigger the third-level detection. The strategy generation module calls a targeted optimization strategy from the preset strategy library, performs optimization adjustments, and continuously monitors the basic process parameters until the basic process parameters return to the normal range. If any parameter is abnormal, it is determined to be a risk of abnormal crystallization effect, and the third-level detection is immediately triggered. The system control module controls the equipment operation parameter detection module to start.

[0074] Level 3 Detection Triggering and Processing: After the equipment operation parameter detection module is activated, it collects real-time data on cooler tube pressure, agitator motor vibration and power, and seal leakage signals. The data is then uploaded to the data processing module for analysis and comparison with preset standard thresholds in the system. If all parameters are within the control range, the risk assessment module determines that the level 2 parameter anomalies are caused by process auxiliary factors such as insufficient crystallization aids. The strategy generation module then formulates and executes targeted optimization strategies. If parameter anomalies exist, based on the type and combination of abnormal parameters, it is determined to be a hardware failure risk. The strategy generation module accurately locates the root risk point (such as cooler blockage, agitator impeller wear, seal failure, etc.) based on the parameter anomalies and calls a matching targeted optimization strategy from the strategy library to perform optimization adjustments and continuously monitor crystallization and slurry characteristic parameters until they return to normal range values.

[0075] In the above embodiments, the primary detection parameter type is the basic process thermodynamic parameter, which refers to the key parameter that directly determines the core thermodynamic conditions of the cooling crystallization stage of phosphoric acid dihydrate. Focusing on the core logic of "cooling-temperature", it is the basic prerequisite for ensuring the normal start-up and advancement of the crystallization reaction. It includes the temperature of the slurry entering and leaving the cooling crystallization zone, the temperature and flow rate of the cooling medium, and is used to quickly screen for major process deviation risks.

[0076] It should be noted that the hierarchical detection logic in this embodiment supports a reverse verification mechanism. That is, when a parameter of a certain level returns to the normal range, the system can automatically shut down the detection module of the corresponding level and return to the detection state of the previous level to ensure the rational use of resources. At the same time, the system supports a manual intervention mode. When production personnel find an anomaly, they can manually trigger the detection process of the corresponding level through the human-computer interaction interface to improve the operational flexibility of the system.

[0077] In the above embodiments, the secondary detection parameters are crystallization quality and slurry flowability parameters, which are key parameters that directly reflect the crystallization growth effect of calcium sulfate dihydrate and the slurry transport characteristics. They focus on the core logic of "crystallization quality-slurry flowability" and have no overlap with the primary parameters. They include crystal particle size distribution, slurry liquid-solid ratio, and slurry viscosity. They are used to locate whether the primary anomaly has been transmitted to the crystallization process and to clarify the risk of crystallization effect deviation at the process level.

[0078] In the above implementation, the third-level detection parameter type is the equipment operating status and safety assurance parameter, which refers to the key parameters that directly reflect the operating status of core equipment such as cooling and stirring, as well as the system's safety and sealing performance. It focuses on the core logic of "cooling equipment - stirring equipment - sealing safety" and has no overlap with the first and second-level parameters. It includes equipment pressure, motor vibration value, motor power, and sealing leakage signal. It is used to investigate the root cause of second-level anomalies at the equipment level and to identify hardware failures and safety risks.

[0079] In one specific implementation, the system's preset standard thresholds during the primary, secondary, and tertiary detection processes are baseline value ranges set based on the conventional operating conditions of the dihydrate phosphoric acid cooling crystallization process. Those skilled in the art can reasonably adjust the threshold ranges according to actual production conditions such as production scale (e.g., 100,000 tons, 300,000 tons, 500,000 tons per year), raw material purity, reaction tank structure, and cooling medium type. All adjusted threshold ranges should be considered to fall within the protection scope of this invention. The specific baseline threshold ranges are as follows:

[0080] Level 1 detection threshold:

[0081] The inlet slurry temperature T1 in the cooling crystallization zone is 76-80℃;

[0082] The outlet slurry temperature T2 of the cooling crystallization zone is 52-58℃ (a key indicator that directly determines the crystallization driving force; if the temperature is too low, excessive crystallization will easily lead to precipitation and blockage of the pipes, while if the temperature is too high, the crystallization driving force will be insufficient, affecting the crystallization efficiency).

[0083] Cooling medium inlet temperature T3: 30-35℃;

[0084] Cooling medium flow rate Q1: Design value ±5% (The design value is calculated and determined based on the production scale and cooling requirements. Fluctuations in flow rate exceeding this range will affect the stability of the cooling effect).

[0085] Secondary detection threshold:

[0086] Calcium sulfate dihydrate crystal particle size distribution D 50 80-120μm (key indicator for crystal growth, D) 50 If the size is too small, the crystal particles will be too fine, making filtration difficult; D 50 If the crystal size is too large, the crystal growth will be uneven, affecting product quality.

[0087] Liquid-to-solid ratio R: 2.8-3.2:1 (mass ratio, affecting the crystal growth space; if the liquid-to-solid ratio is too small, the crystal growth space will be insufficient, which will easily lead to particle agglomeration; if the liquid-to-solid ratio is too large, the production efficiency will be reduced).

[0088] Slurry viscosity μ: 50-80 mPa·s (reflects slurry flowability and avoids the risk of clogging; viscosity exceeding this range will lead to difficulties in slurry transportation and affect production continuity).

[0089] Level 3 detection threshold:

[0090] Cooler tube side pressure P1: 0.3-0.5MPa (reflects the risk of cooler blockage / leakage; excessive pressure may be caused by cooler tube blockage, while excessively low pressure may indicate leakage).

[0091] The vibration value V of the agitator motor is ≤4.5mm / s (reflecting the uniformity of mixing and avoiding insufficient local cooling; excessive vibration indicates abnormal operation of the agitator, which may lead to uneven mixing of the slurry and affect the crystallization effect).

[0092] Agitator motor power W: Design value ±10% (indirectly reflects slurry resistance, is related to viscosity abnormalities; power fluctuations exceeding this range may be caused by changes in slurry viscosity or agitator malfunction).

[0093] Cooling crystallization zone sealing leakage signal S: The control status is "no leakage" (safety assurance indicator; the leakage signal trigger indicates that the seal has failed, which may lead to slurry leakage and cause a safety accident).

[0094] In a preferred embodiment, the risk mitigation strategies developed for different risk types during the primary, secondary, and tertiary detection processes are preferred solutions based on normal production conditions. Those skilled in the art can adjust the strategy details according to the actual risk scenario. The specific strategies are as follows:

[0095] Basic process deviation risk elimination strategy:

[0096] If T1 exceeds the 76-80℃ range: Simultaneously fine-tune the slurry feed temperature in the main reaction zone (e.g., by adjusting the power of the heating / cooling device in the main reaction zone) to gradually bring T1 back to the control range. During the adjustment process, monitor the change of T1 every 30 seconds until it stabilizes at 76-80℃. If T1 still cannot return to the normal range after adjustment, trigger an alarm to prompt production personnel to check the process status of the main reaction zone.

[0097] If T3 exceeds the 30-35℃ range: start the cooling medium cooling system (such as increasing the frequency of the cooling tower fan, turning on the auxiliary cooling device of the cooling medium, etc.) to reduce the inlet temperature of the cooling medium. Monitor T3 every minute to ensure that it drops back to 30-35℃ quickly. If the cooling medium cooling system fails and T3 cannot be reduced, the system will automatically switch to the backup cooling medium circuit to ensure that the cooling process continues.

[0098] If Q1 deviates from the design value by more than 5%: First, check the opening status of the cooling medium pipeline valves. Use the valve positioner to troubleshoot valve jamming. After troubleshooting, adjust the frequency of the variable frequency pump to bring Q1 back to the design value within ±5%. During the adjustment process, monitor T2 changes simultaneously to avoid T2 exceeding limits due to flow adjustment. If there is a conflict between flow adjustment and T2 stability, prioritize ensuring T2 remains within the core threshold range. Risk of abnormal crystallization effect:

[0099] Strategies to eliminate the risk of abnormal crystallization effects:

[0100] If D 50 <80μm: While maintaining the current cooling medium flow rate, further reduce the cooling rate (specific methods include, but are not limited to, fine-tuning the cooling medium split ratio, opening the cooling medium buffer tank, etc.) so that T2 drops by no more than 2℃ per hour, allowing sufficient time for crystal growth; monitor D every 10 minutes during the adjustment process. 50 Until it reaches 80-120μm; if D is adjusted 50 If the standard still cannot be met, an appropriate amount of crystallization accelerator (such as lignin sulfonate additives) can be added.

[0101] If R < 2.8:1: Reduce the slurry feed rate (by 8%-12% of the current feed rate, the specific reduction depending on the actual liquid-solid ratio deviation) to increase the crystal growth space, while maintaining a stable stirring speed to avoid uneven mixing due to changes in the feed rate; calculate R every 15 minutes using an ultrasonic density meter until it returns to the range of 2.8-3.2:1; if reducing the feed rate affects production efficiency, the discharge rate of the reaction tank can be adjusted simultaneously to maintain a stable slurry level in the reaction tank;

[0102] If μ > 80 mPa·s: In addition to increasing the stirring speed, add an appropriate amount of diluent (such as demineralized water, dilute phosphoric acid, etc., the amount added is 3%-5% of the total slurry) to the slurry to reduce the viscosity of the slurry; monitor μ every 5 minutes, and at the same time monitor the P2O5 concentration in the slurry to avoid the product quality being affected by too low a P2O5 concentration due to dilution; if the viscosity remains too high, check for crystallization and agglomeration, and add a dispersant if necessary;

[0103] Equipment hardware failure risk mitigation strategies:

[0104] If P1 > 0.5 MPa and Q1 is normal, it is determined that "cooler tube blockage" occurs, and the cooler online cleaning program is started (such as high-pressure water backflushing, chemical cleaning, etc.). During the cleaning, the cooling medium distribution is adjusted, and the cooling effect is ensured through the backup cooler to ensure that T2 does not exceed the limit. After the cleaning is completed, monitor whether P1 returns to the normal range. If it is still abnormal, trigger the shutdown maintenance prompt.

[0105] If V > 4.5 mm / s and W deviates from the design value by more than 10%, it is determined that "the agitator is faulty (such as impeller wear, bearing damage, etc.)". First, reduce the slurry feed rate to reduce the agitation load, and then stop the machine to repair the agitator (replace the impeller, repair the bearing, etc.). After the repair is completed, start the agitator and gradually restore the feed rate, and monitor whether V and W return to the normal range.

[0106] If S indicates "leakage", it is determined to be "seal failure". The safety interlock is immediately triggered, the supply of feed and cooling medium is cut off, the machine is stopped and the seal is replaced. After replacement, a sealing test is performed to ensure there is no leakage before production is resumed to avoid safety accidents caused by slurry leakage.

[0107] If all equipment parameters are normal, determine that "crystallization aid is insufficient". Add an appropriate amount of crystallization aid (such as lignin sulfonate, polyacrylamide, etc.), adjust the aid addition flow rate, and monitor the crystallization particle size distribution and slurry liquid-solid ratio every 10 minutes until the parameters return to the normal range.

[0108] In a preferred embodiment, the basic process parameter monitoring module includes corrosion-resistant K-type thermocouples (insertion depth 250mm, Hastelloy sheath) installed at the inlet and outlet of the cooling crystallization zone, a platinum resistance thermometer and a ceramic-lined electromagnetic flowmeter (range 50-100m³ / h) installed on the cooling medium pipeline, and the sensor data sampling frequency is 1 time / second.

[0109] In a preferred embodiment, the crystallization and slurry characteristic detection module includes: an online laser particle size analyzer (equipped with an ultrasonic automatic cleaning device, measuring range 10-500μm) and an ultrasonic densitometer installed in the stable slurry flow section at the outlet of the cooling crystallization zone; a rotary online viscometer (measuring range 10-500mPa・s) installed in the slurry outlet pipe; a data sampling frequency of 1 time / 2 seconds; and correlation analysis with primary detection data.

[0110] In a preferred embodiment, the equipment operating parameter detection module includes a pressure transmitter (stainless steel diaphragm, range 0-1MPa) installed on the cooler inlet pipe, a piezoelectric vibration transmitter (range 0-10mm / s) installed at the agitator motor bearing, a power transmitter (range 0-100kW) installed in the motor control cabinet, and an ultrasonic leak detector installed at the flange seal of the cooling crystallization tank. The data sampling frequency is 1 time / second, and the module is connected to the equipment management system for data linkage with the first two levels. Example 2

[0111] In another aspect, this invention provides a measurement optimization method for the cooling crystallization stage of phosphoric acid produced via the dihydrate process. This method is applied to risk assessment and elimination during the cooling crystallization stage of phosphoric acid produced via the dihydrate process and is applicable to phosphoric acid production lines of different production scales (such as 100,000 tons, 300,000 tons, and 500,000 tons per year). Its core is based on the measurement optimization system described in Example 1 to achieve graded detection, risk assessment, and strategy execution. (See reference...) Figure 2 The specific steps are as follows:

[0112] System initialization: Start the system control module, set the basic process parameter monitoring module to normally open, and set the other modules to normally closed; load the preset standard threshold and risk elimination strategy library, and complete the communication connection test of each module.

[0113] Level 1 detection: The basic process parameter monitoring module collects the inlet and outlet slurry temperature, cooling medium temperature and flow rate parameters of the cooling crystallization zone in real time, uploads them to the data processing module for processing and analysis, and compares them with the preset level 1 threshold.

[0114] Level 1 Risk Assessment and Handling: If all parameters are normal, maintain Level 1 testing; if any parameter is abnormal, it is determined to be a basic process deviation risk, triggering Level 2 testing.

[0115] Secondary detection: The system control module starts the crystallization and slurry characteristic detection module, collects crystallization particle size distribution, slurry liquid-solid ratio and slurry viscosity parameters, uploads them to the data processing module for analysis, and compares them with the preset secondary threshold.

[0116] Level 2 Risk Assessment and Handling: If all parameters are normal, it is determined to be a temporary process fluctuation, and the basic process parameter optimization strategy is executed until the parameters return to normal; if any parameter is abnormal, it is determined to be a risk of abnormal crystallization effect, and Level 3 detection is triggered.

[0117] Level 3 detection: The system control module starts the equipment operation parameter detection module, collects the cooler tube pressure, agitator motor vibration value and power, and seal leakage signal, uploads them to the data processing module for analysis, and compares them with the preset level 3 threshold.

[0118] Level 3 Risk Assessment and Handling: If all parameters are normal, it is determined that the crystallization aid is insufficient, and an aid replenishment strategy is implemented; if the parameters are abnormal, it is determined that the equipment hardware is faulty, the fault point is located and the corresponding maintenance / optimization strategy is implemented until the crystallization and slurry characteristic parameters return to normal.

[0119] System regression: Once all parameters at each level have returned to the normal range, the level 2 and level 3 detection modules are shut down, and the system returns to the normal monitoring state with only level 1 detection.

[0120] In a specific application scenario, this method was applied to a 300,000-ton-per-year dihydrate phosphoric acid production line. The effective volume of the reaction tank was 120 m³, and the cooling system was designed with a cooling medium (circulating water) flow rate of 80 m³ / h. After applying this method, the process stability during the cooling crystallization stage was significantly improved, and the crystallized product D... 50 The pass rate increased from 85% to over 98%, and equipment downtime was reduced by 60%, effectively reducing production energy consumption and production costs.

[0121] It should be noted that the method steps in this embodiment can be flexibly adjusted according to actual production needs. For example, in continuous production scenarios, a parameter trend prediction step can be added, and the parameter change trend can be predicted through the data processing module to trigger an early warning. In intermittent production scenarios, the detection frequency can be adjusted, and different detection intervals can be used in the early, middle and late stages of the reaction to improve detection efficiency. Example 3

[0122] In another aspect, the present invention provides a computer storage medium storing a computer program that, when executed by a processor, implements a method for optimizing the measurement of the cooling crystallization stage of phosphoric acid dihydrate as described in Example 2.

[0123] The computer storage medium can be a read-only memory (ROM), random access memory (RAM), hard disk, optical disk, USB flash drive, portable hard disk, flash memory, memory card, memory stick, or other media capable of storing program code; the processor can be a central processing unit (CPU), microprocessor (MCU), digital signal processor (DSP), field-programmable gate array (FPGA), or other logic operation unit with data processing capabilities. This computer storage medium can be integrated into the system control module described in Embodiment 1, or it can be deployed independently and interact with the system control module through a communication interface to store and execute risk elimination strategy programs, threshold parameters, etc., thereby improving the maintainability and upgrade flexibility of the system.

[0124] The above description is merely a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. It should be noted that those skilled in the art can make various improvements and substitutions without departing from the technical concept of the present invention, and all such improvements and substitutions should be considered to fall within the scope of protection of the present invention. For example, replacing the specific detection equipment model of each monitoring module, adjusting the preset threshold range, optimizing the details of the risk elimination strategy, and changing the system deployment method, as long as their core technical solutions are consistent with the present invention, are within the scope of protection of the present invention.

Claims

1. An optimized measurement system for the cooling crystallization stage of phosphoric acid in the dihydrate process, characterized in that, include: The system control module, along with its connected basic process parameter monitoring module, crystallization and slurry characteristic detection module, equipment operation parameter detection module, data processing module, risk assessment module, and strategy generation module; The basic process parameter monitoring module is used to collect the inlet and outlet slurry temperature, cooling medium temperature and flow rate parameters of the cooling crystallization zone in real time. The crystallization and slurry characteristic detection module is used to accurately detect the crystal particle size distribution, slurry liquid-solid ratio, and slurry viscosity parameters. The equipment operating parameter detection module is used to collect real-time data on cooler tube pressure, agitator motor vibration value and power, and seal leakage signals. The data processing module processes and analyzes the collected data; The risk assessment module determines the risk type based on the data analysis results; The strategy generation module outputs the corresponding risk elimination strategy based on the risk type and level determination result. The system control module controls the basic process parameter monitoring module to be normally open, and controls the crystallization and slurry characteristic detection module, equipment operation parameter detection module, data processing module, risk assessment module and strategy generation module to be normally closed. During the cooling and crystallization stage of the dihydrate phosphoric acid reactor, the basic process parameter monitoring module performs first-level detection, collects the inlet and outlet slurry temperature, cooling medium temperature and flow parameters of the cooling and crystallization zone in real time, uploads them to the data processing module for processing and analysis, and compares them with the preset standard threshold in the system. If any parameter is abnormal, the risk assessment module determines that there is a risk of basic process deviation and immediately triggers second-level detection. The system control module controls the crystallization and slurry characteristic detection module to be turned on. The crystallization and slurry characteristic detection module collects crystallization particle size distribution, slurry liquid-solid ratio, and slurry viscosity parameters in real time, and uploads them to the data processing module for processing and analysis. The data is compared with the preset standard thresholds in the system. If all parameters are within the control range, the risk assessment module determines that the first-level parameter abnormality is caused by temporary process fluctuations and does not trigger the third-level detection. The strategy generation module formulates a targeted optimization strategy until the basic process parameters return to the normal range. If any parameter is abnormal, it is determined to be a risk of abnormal crystallization effect and immediately triggers the third-level detection. The system control module controls the equipment operation parameter detection module to start. The equipment operation parameter detection module collects real-time data on cooler tube pressure, agitator motor vibration and power, and seal leakage signals, and uploads them to the data processing module for analysis. The data is compared with preset standard thresholds in the system. If all parameters are within the control range, the risk assessment module determines that the abnormal secondary parameters are caused by insufficient crystallization aids, and the strategy generation module formulates targeted optimization strategies. If different parameters are abnormal, it is determined to be a risk of equipment hardware failure. Based on the abnormal parameter situation, the strategy generation module locates the root risk point and formulates targeted optimization strategies until the crystallization and slurry characteristic parameters return to the normal range.

2. The measurement and optimization system for the cooling crystallization stage of phosphoric acid dihydrate process according to claim 1, characterized in that, The system's preset standard thresholds during the first-level, second-level, and third-level detection processes include: Level 1 testing: The inlet slurry temperature T1 in the cooling crystallization zone is 76-80℃; The outlet slurry temperature T2 of the cooling crystallization zone is 52-58℃; Cooling medium inlet temperature T3: 30-35℃; Cooling medium flow rate Q1: design value ±5%; Level 2 testing: Calcium sulfate dihydrate crystal particle size distribution D 50 : 80-120μm; Slurry liquid-to-solid ratio R: 2.8-3.2:1; Slurry viscosity μ: 50-80 mPa・s; Level 3 detection: Cooler tube-side pressure P1: 0.3-0.5 MPa; The vibration value V of the stirrer motor is ≤4.5mm / s; Agitator motor power (W): design value ±10%; Cooling crystallization zone sealing leakage signal S: Control status is no leakage.

3. The measurement and optimization system for the cooling crystallization stage of phosphoric acid dihydrate process according to claim 2, characterized in that, The risk elimination strategies developed for different risk types during the Level 1, Level 2, and Level 3 detection processes include: Basic process deviation risk: If T1 exceeds the range of 76-80℃: Simultaneously fine-tune the feed temperature of the slurry in the main reaction zone so that T1 gradually returns to the control range. Monitor the change of T1 every 30 seconds until it stabilizes at 76-80℃. If T3 exceeds the 30-35℃ range: start the cooling medium cooling system to reduce the inlet temperature of the cooling medium, and monitor T3 every minute to ensure that it drops back to 30-35℃ quickly; If Q1 deviates from the design value by more than 5%, check the opening status of the valves in the cooling medium pipeline. After eliminating the valve jamming fault, adjust the frequency of the variable frequency pump so that Q1 returns to the design value within ±5%. Simultaneously monitor the change of T2 to avoid T2 exceeding the limit due to flow adjustment. Risk of abnormal crystallization effect: If D 50 <80μm: While maintaining the current cooling medium flow rate, further reduce the cooling rate by fine-tuning the cooling medium split ratio so that T2 drops by no more than 2℃ per hour, allowing sufficient time for crystal growth. Monitor D every 10 minutes. 50 until it reaches 80-120μm; If R < 2.8:1: reduce the slurry feed rate by 8%-12% of the current feed rate to increase the crystal growth space. At the same time, keep the stirring speed stable and calculate R every 15 minutes using an ultrasonic density meter until it returns to the range of 2.8-3.2:

1. If μ > 80 mPa·s: In addition to increasing the stirring speed, add an appropriate amount of diluent to the slurry, the amount of which is 3%-5% of the total slurry volume, to reduce the viscosity of the slurry. Monitor μ every 5 minutes to avoid the P2O5 concentration from being too low due to dilution, and ensure that μ is stable at 50-80 mPa·s. Equipment hardware failure risk: If P1>0.5MPa and Q1 is normal, it is determined that the cooler tube side is blocked. Start the cooler online cleaning program. During the cleaning, adjust the cooling medium distribution to ensure that T2 does not exceed the limit. If V > 4.5 mm / s and W deviates from the design value by more than 10%, the agitator is deemed to be faulty. The slurry feed rate should be reduced, the agitator should be shut down for inspection and repair, and the impeller should be replaced before normal operation is restored. If S indicates leakage, the seal is deemed to have failed. The safety interlock is immediately triggered, the feed is cut off, the machine is stopped, and the seal is replaced to avoid the risk of slurry leakage. If all parameters are normal, it is determined that the crystallization aid is insufficient. Add an appropriate amount of crystallization aid and adjust the aid addition flow rate until D is reached. 50 The regression control range of R and μ.

4. The measurement and optimization system for the cooling crystallization stage of phosphoric acid dihydrate process according to claim 2, characterized in that, The basic process parameter monitoring module includes corrosion-resistant K-type thermocouples installed at the inlet and outlet of the cooling crystallization zone, platinum resistance thermometers installed on the cooling medium pipeline, and ceramic-lined electromagnetic flowmeters.

5. The measurement optimization system for the cooling crystallization stage of phosphoric acid dihydrate process according to claim 1, characterized in that, The crystallization and slurry characteristic detection module includes: Online laser particle size analyzer and ultrasonic density meter are installed in the stable flow section of the slurry at the outlet of the cooling crystallization zone, and a rotary online viscometer is installed in the slurry outlet pipe.

6. The measurement and optimization system for the cooling crystallization stage of phosphoric acid dihydrate process according to claim 5, characterized in that, The equipment operating parameter detection module includes a pressure transmitter installed on the cooler inlet pipe, a piezoelectric vibration transmitter installed at the agitator motor bearing, a power transmitter installed in the motor control cabinet, and an ultrasonic leak detector installed at the flange seal of the cooling crystallizer.

7. An optimized method for measuring the cooling crystallization stage of phosphoric acid in the dihydrate process, characterized in that, Based on any one of the system implementations of claims 1-6, it is used to achieve rapid investigation and elimination of risks during the cooling and crystallization stage of the phosphoric acid reaction tank in the dihydrate process.

8. A computer storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the measurement optimization method for the cooling crystallization stage of phosphoric acid dihydrate as described in claim 7.

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