Data monitoring and analysis method of chlorination production synthesis system

Abstract

The invention relates to the technical field of production, processing, manufacturing and synthesis, and discloses a data monitoring and analysis method of a chlorination production synthesis system, which comprises the following steps of: data acquisition: acquiring key parameters in a production process in real time by utilizing an on-site instrument and a DCS (Distributed Control System), comprise but not limited to temperature, pressure, flow, liquid level, pH value, turbidity, dripping speed, rotating speed and running current, the acquisition frequency is set according to production requirements, and acquisition is performed once per second; and data recording: storing the collected data in a database according to a time sequence, recording operation intervals and curves of various data, abnormal points, timestamps, parameter values, alarm values and corresponding equipment identifiers, and ensuring data integrity. According to the data monitoring and analysis method of the chlorination production synthesis system, various parameter data in the production process are collected in real time by combining the field instrument and the DCS system and are analyzed in detail, so that production operation steps are monitored, the technological process is optimized, the equipment state is monitored, and deviation is corrected in time; therefore, the product quality is improved, and the product traceability is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of production, processing, manufacturing and synthesis, and in particular to a data monitoring and analysis method for a chlorination production synthesis system. Background Art

[0002] In the chlorination production synthesis process, a variety of key parameters are involved, including temperature, pressure, flow, liquid level, pH value, turbidity, dripping speed, rotation speed and operating current. The fluctuation of these parameters directly affects product quality and production efficiency. Traditional methods mainly rely on manual monitoring and recording, which has problems such as untimely data collection, incomplete analysis and delayed abnormality detection, making it difficult to achieve precise control and quality traceability in the production process. With the advancement of automation technology, field instruments and distributed control systems (DCS) have gradually been applied to industrial production, but the existing technology has not yet fully integrated multi-dimensional data for systematic analysis, and it is difficult to meet the modern industry's needs for high efficiency, accuracy and traceability. Therefore, there is an urgent need for a method that can monitor, comprehensively analyze and optimize the chlorination production synthesis process in real time, so that abnormal problems that arise can be solved in a timely manner, thereby ensuring the stable operation of the production process and the qualified rate of products. Summary of the Invention

[0003] The object of the present invention is to provide a data monitoring and analysis method for a chlorination production synthesis system to solve the problem that the existing technology mentioned in the above background technology has not fully integrated multidimensional data for systematic analysis, and is difficult to meet the needs of modern industry for efficiency, accuracy and traceability.

[0004] To achieve the above object, the present invention provides the following technical solutions:

[0005] A data monitoring and analysis method for a chlorination production synthesis system, comprising the following steps:

[0006] Step 1: Data collection: Use field instruments and DCS systems to collect key parameters of the production process in real time, including but not limited to temperature, pressure, flow, liquid level, pH value, turbidity, dripping speed, rotation speed and operating current. The collection frequency can be set within the range of 200 milliseconds to 24 hours according to production needs, with one collection per second;

[0007] Step 2: Data recording: The collected data is stored in the database in chronological order. The records include timestamps, parameter values ​​and corresponding device identifiers to ensure data integrity.

[0008] Step 3: Trend analysis: Statistical analysis of historical data is performed to draw trend charts of temperature and pressure parameters, and the changes of temperature and pressure over time to identify abnormal fluctuation points;

[0009] Step 4: Comparative analysis: compare the real-time data with the set threshold to automatically identify the data interval of normal operation or detect abnormal situations outside the range;

[0010] Step 5: Correlation analysis, monitoring the production operation process and steps to add raw materials and auxiliary materials to see if they are correct, and whether the various parameter data are within the reasonable control range;

[0011] Step 6: Correlation analysis, study the relationship between various parameters, study the correlation between temperature, pressure, flow rate and liquid level, in order to optimize the raw material ratio and process parameters;

[0012] Step 7: Abnormal detection and correction: When the parameters exceed the preset range, the system automatically alarms, and the process personnel adjust the operation steps or equipment operating status according to the analysis results to ensure the stability of the production process;

[0013] Step 8: Traceability management: associate all collected and analyzed data with production date and batch, and generate detailed production record reports for product quality tracing and problem location.

[0014] Step 9: Weighing monitoring and analysis. In the chlorination synthesis system, the weighing data of the nitrogen cylinder is an important basis for judging the raw material usage and gas supply efficiency. By monitoring the starting weight, ending weight and usage of the nitrogen cylinder in different production batches, refined management of the raw material supply can be achieved.

[0015] Preferably, the data monitoring and analysis method includes data collection, recording, alarming, analysis, anomaly detection and correction, and traceability management steps.

[0016] Preferably, data collection is achieved through field instruments and a DCS system, and the collected parameters include temperature, pressure, flow rate and other data.

[0017] Preferably, the data analysis includes trend analysis, comparative analysis and correlation analysis.

[0018] Preferably, anomaly detection is achieved by comparing with a preset threshold value, and an automatic alarm is triggered when the range is exceeded.

[0019] Preferably, traceability management is achieved by generating reports by associating data with production batches.

[0020] Compared with the prior art, the present invention has the following beneficial effects:

[0021] 1. Real-time monitoring: Real-time acquisition of multiple parameters is achieved through field instruments and DCS systems to ensure data accuracy and timeliness.

[0022] 2. Accurate analysis: Combine trend analysis and comparative analysis to fully understand the status of the production process and optimize process parameters.

[0023] 3. Abnormal warning: Automatically detect abnormalities and alarm, reduce manual intervention time and improve production efficiency.

[0024] 4. Traceability: Data is associated with batches to facilitate quality tracking and problem analysis, meeting regulatory requirements. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Other features, objects and advantages of the present application will become more apparent upon reading the detailed description of non-limiting embodiments made with reference to the following drawings:

[0026] Figure 1 This is a monthly summary diagram of the liquid level in the metering tank of the data monitoring and analysis method of the chlorination production synthesis system of the present invention.

[0027] Figure 2 This is a monthly summary chart of the reactor temperature of the data monitoring and analysis method of the chlorination production synthesis system of the present invention.

[0028] Figure 3 The present invention provides a temperature change curve, a pressure change trend, and a weighing change trend diagram for the data monitoring and analysis method of the chlorination production synthesis system.

[0029] Figure 4 This is a diagram of the data analysis content of the present invention.

[0030] Figure 5 This is a comparison chart of parameter records of the chlorine gas cylinder of the present invention. DETAILED DESCRIPTION

[0031] The present application will be further described in detail below with reference to the accompanying drawings and embodiments. It will be understood that the specific embodiments described herein are intended only to explain the relevant invention and are not intended to limit the invention. It should also be noted that, for ease of description, the accompanying drawings only illustrate portions relevant to the invention. The different types of cross-section lines in the accompanying drawings of the embodiments of the present invention are not marked in accordance with national standards, nor do they impose requirements on the materials of the components. Instead, they serve to distinguish the cross-sectional views of the components in the drawings.

[0032] See also Figure 1-5 , a data monitoring and analysis method for a chlorination production synthesis system, the data monitoring and analysis method comprising the following steps:

[0033] Step 1: Data collection: Use field instruments and DCS systems to collect key parameters of the production process in real time, including but not limited to temperature, pressure, flow, liquid level, pH value, turbidity, dripping speed, rotation speed and operating current. The collection frequency can be set within the range of 200 milliseconds to 24 hours according to production needs, with one collection per second;

[0034] Step 2: Data recording: The collected data is stored in the database in chronological order. The records include timestamps, parameter values ​​and corresponding device identifiers to ensure data integrity.

[0035] Step 3: Trend analysis: Statistical analysis of historical data is performed to draw trend charts of temperature and pressure parameters, and the changes of temperature and pressure over time to identify abnormal fluctuation points;

[0036] Step 4: Comparative analysis: compare the real-time data with the set threshold to automatically identify the data interval of normal operation or detect abnormal situations outside the range;

[0037] Step 5: Correlation analysis, monitoring the production operation process and steps to add raw materials and auxiliary materials to see if they are correct, and whether the various parameter data are within the reasonable control range;

[0038] Step 6: Correlation analysis, study the relationship between various parameters, study the correlation between temperature, pressure, flow rate and liquid level, in order to optimize the raw material ratio and process parameters;

[0039] Step 7: Abnormal detection and correction: When the parameters exceed the preset range, the system automatically alarms, and the process personnel adjust the operation steps or equipment operating status according to the analysis results to ensure the stability of the production process;

[0040] Step 8: Traceability management: associate all collected and analyzed data with production date and batch, and generate detailed production record reports for product quality tracing and problem location.

[0041] Step 9: Weighing monitoring and analysis. In the chlorination synthesis system, the weighing data of the nitrogen cylinder is an important basis for judging the raw material usage and gas supply efficiency. By monitoring the starting weight, ending weight and usage of the nitrogen cylinder in different production batches, refined management of the raw material supply can be achieved.

[0042] Among them, the data monitoring and analysis method includes data collection, recording, alarm, analysis, anomaly detection and correction, and traceability management steps.

[0043] Among them, data collection is achieved through field instruments and DCS systems, and the collected parameters include temperature, pressure, flow and other data.

[0044] Among them, data analysis includes trend analysis, comparative analysis and correlation analysis.

[0045] Among them, anomaly detection is achieved by comparing with the preset threshold, and an automatic alarm is triggered when the range is exceeded.

[0046] Among them, traceability management is achieved by associating data with production batches to generate reports.

[0047] Example 1

[0048] Take the data of a chlorination production synthesis system from May 1 to May 31, 2023 as an example:

[0049] Temperature monitoring: At 5:20 on May 4, the temperature was recorded as 48.66°C; at 5:42 on May 18, the temperature rose to 61.99°C, exceeding the normal range and indicating an abnormality.

[0050] Flow and liquid level monitoring: At 11:25 on May 23, the flow rate was 284.46 mm. At 10:11 on May 22, the flow rate dropped to 203.29 m. The fluctuation range is large, and the equipment status needs to be checked.

[0051] Data visualization: Through trend charts (such as the attached Figure 1 , Attachment Figure 2 ) displays the changes in temperature and flow over time, assisting process personnel in determining the cause of abnormalities and adjusting parameters.

[0052] Correction results: Through analysis, it was confirmed that the temperature anomaly on May 18 was caused by equipment overheating. After timely shutdown and maintenance, production returned to normal and product quality met the standards.

[0053] Example 2

[0054] Combined monitoring of pressure and flow (May 10-15, 2023)

[0055] In the R2308 reactor of the chlorination production synthesis system, process personnel are concerned about the impact of the coordinated changes in pressure and flow on product quality.

[0056] Data collection: From 10:00 on May 10, 2023 to 10:00 on May 15, 2023, the DCS system will collect data once every second, and the display will be set to every minute (the display setting is adjustable), and pressure and flow data will be collected once.

[0057] At 10:00 on May 10, the pressure was 0.02MPa and the flow rate was 284.46mm.

[0058] At 10:11 on May 15, the pressure dropped to 0.01MPa and the flow rate dropped to 203.29mm.

[0059] Data Analysis:

[0060] Trend analysis showed that the pressure and flow rate dropped synchronously at 14:33 on May 12, with the pressure dropping to 0.015MPa and the flow rate dropping to 230mm, indicating possible pipeline blockage or abnormal pump operation.

[0061] Correlation analysis showed that pressure and flow rate were positively correlated (correlation coefficient 0.87). A decrease in pressure may lead to insufficient flow rate and affect reaction efficiency.

[0062] Anomaly Detection and Correction: The system issued an alarm at 2:33 PM on May 12th, indicating that the pressure and flow rate were below the normal range (pressure threshold 0.02-0.03 MPa, flow threshold 250-300 mm). Process personnel inspected the pump and discovered it was operating abnormally. After promptly replacing the pump, the pressure returned to 0.025 MPa and the flow rate to 280 mm on May 13th, resuming normal production.

[0063] Traceability: Associate this exception record with batch number R2308-20230512, generate a report, and confirm that product quality has not been affected.

[0064] Example 3

[0065] Analysis of temperature and pH anomalies (May 18-20, 2023)

[0066] In the V2307 metering tank, fluctuations in temperature and pH may affect the stability of the chlorination reaction.

[0067] Data collection: Temperature and pH data were collected from 5:42 on May 18 to 5:20 on May 20, 2023.

[0068] At 5:42 on May 18, the temperature was 61.99℃ and the pH value was 7.8.

[0069] At 5:20 on May 20, the temperature dropped to 48.66℃ and the pH value rose to 8.2.

[0070] Data Analysis:

[0071] Trend analysis showed that the temperature peaked on May 18 and then gradually decreased, while the pH value showed an upward trend.

[0072] Comparative analysis showed that the temperature exceeded the set threshold (50-60°C) on May 18, and the pH value exceeded the normal range (7.0-8.0) on May 20.

[0073] Correlation analysis found that a decrease in temperature may lead to a slowdown in the reaction rate, which indirectly causes an increase in pH value.

[0074] Anomaly Detection and Correction: The system issued an alarm indicating a high temperature at 5:42 AM on May 18th. Process personnel discovered a cooling system malfunction, which was repaired and returned to normal. On May 20th, an alarm indicated an abnormal pH value. After adjusting the raw material ratio, the pH dropped to 7.5, and the reaction stabilized.

[0075] Traceability: Records show that the cooling system of batch V2307-20230518 was adjusted due to abnormal temperature, which did not affect product quality; the raw material ratio of batch V2307-20230520 was adjusted due to pH value, and the product quality was qualified.

[0076] Example 4

[0077] Equipment status monitoring of speed and operating current (May 25-31, 2023)

[0078] In the stirring equipment of the chlorination production synthesis system, abnormal rotation speed and operating current may indicate equipment failure.

[0079] Data collection: From 08:00 on May 25, 2023 to 08:00 on May 31, 2023, the speed and operating current of the mixing equipment were collected.

[0080] At 08:00 on May 25, the speed was 1800rpm and the operating current was 15A.

[0081] At 12:00 on May 30, the speed dropped to 1600rpm and the operating current increased to 18A.

[0082] Data Analysis:

[0083] Trend analysis shows that the speed dropped significantly on May 30, while the operating current continued to rise, indicating that the equipment may be overloaded or have a mechanical failure.

[0084] Comparative analysis showed that the speed was lower than the normal range (1700-1900rpm) and the operating current exceeded the safe range (14-16A).

[0085] Anomaly Detection and Correction: The system issued an alarm at 12:00 PM on May 30th, indicating low speed and high current. Process personnel stopped the machine for inspection and discovered severe wear on the agitator bearings. After replacing the bearings, the speed returned to 1750 rpm, the operating current dropped to 15A, and the equipment operated normally.

[0086] Traceability: Associate the abnormal record with batch R2308-20230530 to confirm that production is normal after equipment repair and product quality meets standards.

[0087] Example 5

[0088] Comprehensive Analysis of Liquid Level and Turbidity (May 23-26, 2023)

[0089] In the V2307 metering tank, changes in liquid level and turbidity may indicate raw material quality problems.

[0090] Data collection: Liquid level and turbidity data were collected from 11:25 on May 23 to 11:25 on May 26, 2023.

[0091] At 11:25 on May 23, the liquid level was 284.46 mm and the turbidity was 50 NTU.

[0092] At 11:25 on May 26, the liquid level dropped to 203.29 mm and the turbidity rose to 70 NTU.

[0093] Data Analysis:

[0094] Trend analysis showed that the liquid level began to decrease on May 24, while the turbidity increased simultaneously, reaching a peak of 75 NTU on May 25.

[0095] Comparative analysis showed that the liquid level was lower than the normal range (250-300 mm) and the turbidity exceeded the standard (≤60 NTU).

[0096] Anomaly Detection and Correction: On May 25, the system issued an alarm indicating low liquid level and high turbidity. Process personnel inspected and found excessive impurities in the raw materials. After suspending production and replacing the raw materials, the liquid level returned to 260 mm and the turbidity dropped to 55 NTU on May 26, allowing normal production to resume.

[0097] Traceability: Batch V2307-20230525 was suspended due to raw material problems. The product quality was qualified after the raw materials were replaced.

[0098] Example 6

[0099] Data collection and recording: Weighing sensors are used to automatically record the starting weight and remaining weight of cylinders after use. This data is accessed through the DCS system, which records the start and end times, cylinder numbers, and weight changes by batch. The system recorded the starting weight, final weight, and consumption per cylinder for five batches of cylinders between April 26 and May 28, 2023.

[0100] In the second batch, the usage of nitrogen cylinder (1) was 721.72 kg, and the usage of cylinder (2) was 900.8 kg, with a total consumption of 1622.52 kg.

[0101] Trend analysis and usage evaluation: The weight of each cylinder decreases steadily over time, reflecting the continuous use process; the lowest weight was 497.05kg for the second batch on May 5, and the highest weight was 1455.62kg for the fourth batch on May 17. By analyzing the slope of the decline curve, the consumption rate per unit time can be determined, which helps to determine the balance of process load and gas consumption fluctuations.

[0102] Abnormal detection: If the unit consumption of a single bottle is found to deviate significantly from the normal range (for example, only 41.34 kg was used in the third batch, it is necessary to confirm whether the cylinder has been replaced or there is an abnormal operation); if the curve shows a nonlinear and sharp decline, there may be a risk of leakage or overload;

[0103] The system can be set with a threshold alarm function, for example, a replacement reminder will be issued when the cylinder weight is less than 300kg.

[0104] Traceability management: All weighing records are archived with the corresponding batch number and usage time to facilitate subsequent traceability; when analyzing abnormal batch product quality or equipment problems, the gas usage of the current batch can be quickly located.

[0105] The contents not described in detail in this specification belong to the prior art known to those skilled in the art.

[0106] The above description is merely a preferred embodiment of the present application and an illustration of the technical principles employed. Those skilled in the art should understand that the scope of the invention herein is not limited to the technical solutions formed by the specific combination of the above-mentioned technical features, but also encompasses other technical solutions formed by any combination of the above-mentioned technical features or their equivalents without departing from the inventive concept. For example, a technical solution formed by replacing the above-mentioned features with (but not limited to) technical features having similar functions disclosed in this application.

Claims

1. A data monitoring and analysis method for a chlorination production synthesis system, characterized in that: The data monitoring and analysis method includes the following steps: Step 1: Data collection: Use field instruments and DCS systems to collect key parameters of the production process in real time, including but not limited to temperature, pressure, flow, liquid level, pH value, turbidity, dripping speed, rotation speed and operating current. The collection frequency can be set within the range of 200 milliseconds to 24 hours according to production needs, with one collection per second; Step 2: Data recording: The collected data is stored in the database in chronological order. The records include timestamps, parameter values ​​and corresponding device identifiers to ensure data integrity. Step 3: Trend analysis: Statistical analysis of historical data is performed to draw trend charts of temperature and pressure parameters, and the changes of temperature and pressure over time to identify abnormal fluctuation points; Step 4: Comparative analysis: compare the real-time data with the set threshold to automatically identify the data interval of normal operation or detect abnormal situations outside the range; Step 5: Correlation analysis, monitoring the production operation process and steps to add raw materials and auxiliary materials to see if they are correct, and whether the various parameter data are within the reasonable control range; Step 6: Correlation analysis, study the relationship between various parameters, study the correlation between temperature, pressure, flow rate and liquid level, in order to optimize the raw material ratio and process parameters; Step 7: Abnormal detection and correction: When the parameters exceed the preset range, the system automatically alarms, and the process personnel adjust the operating steps or equipment operating status according to the analysis results to ensure the stability of the production process; Step 8: Traceability management: associate all collected and analyzed data with production date and batch, and generate detailed production record reports for product quality tracing and problem location. Step 9: Weighing monitoring and analysis. In the chlorination synthesis system, the weighing data of the nitrogen cylinder is an important basis for judging the raw material usage and gas supply efficiency. By monitoring the starting weight, ending weight and usage of the nitrogen cylinder in different production batches, refined management of the raw material supply can be achieved.

2. The data monitoring and analysis method for a chlorination production synthesis system according to claim 1, characterized in that: The data monitoring and analysis method includes data collection, recording, alarming, analysis, anomaly detection and correction, and traceability management steps.

3. The data monitoring and analysis method for a chlorination production synthesis system according to claim 1, characterized in that: Data collection is achieved through field instruments and DCS systems, and the collected parameters include temperature, pressure, flow and other data.

4. The data monitoring and analysis method for a chlorination production synthesis system according to claim 1, characterized in that: Data analysis includes trend analysis, comparative analysis and correlation analysis.

5. The data monitoring and analysis method for a chlorination production synthesis system according to claim 1, characterized in that: Anomaly detection is achieved by comparing with preset thresholds, and an automatic alarm is triggered when the range is exceeded.

6. The data monitoring and analysis method for a chlorination production synthesis system according to claim 1, characterized in that: Traceability management is achieved by generating reports linking data to production batches.

Images