Intelligent control system for monitoring and controlling industrial refrigeration systems

Abstract

This invention provides an intelligent control system for monitoring and controlling industrial refrigeration systems, comprising a data acquisition module, a calculation module, a trend recording module, and an alarm module. The data acquisition module is configured to acquire refrigerant flow parameters of each refrigerant user and operating parameters of the refrigeration compressor in real time. The calculation module is configured to dynamically calculate the heat load of the heat exchanger at the compressor outlet based on the real-time acquired compressor operating parameters. The trend recording module is configured to store the refrigerant flow parameters of each refrigerant user and the heat load parameters of the heat exchanger at the compressor outlet generated by the calculation module at sampling periods, and perform time-series analysis on these parameters to form trend characteristics. The alarm module is configured to generate an alarm signal based on the trend characteristics when the fluctuation amplitude of any parameter in the trend exceeds an alarm threshold.

Description

Technical Field

[0001] This invention relates to intelligent monitoring and early warning of industrial refrigeration systems, and more specifically to an intelligent control system and method for monitoring and controlling industrial refrigeration systems. Background Technology

[0002] Industrial refrigeration systems, as core infrastructure in process industries such as petrochemicals and pharmaceuticals, bear the critical task of providing stable cooling capacity to multiple user process units. With the increasing scale and integration of industrial plants, refrigeration systems need to simultaneously serve dozens or even hundreds of cooling users, such as fractionation towers, reactors, and storage tanks, forming a highly coupled cooling supply and demand network. As a typical example, the propylene refrigeration system plays a crucial role in the operation of an ethylene plant. It is a closed-loop system using propylene as refrigerant, providing cooling capacity at different temperature levels to many users. In actual operation, user loads may dynamically change due to fluctuations in raw materials, ambient temperature, changes in material composition, and abnormal situations (such as false instrument readings or valve malfunctions). These changes in user load directly affect the compressor's operating status, thus impacting the stability of the entire refrigeration system.

[0003] Based on long-term practical production experience, the following situations frequently occur in continuous production processes of chemical plants: a sudden and significant adjustment by a refrigerant user, due to time differences in communication and adjustments between different positions, or due to false instrument readings, valve malfunctions, etc., causes significant fluctuations in the entire refrigeration system. More seriously, once the refrigeration system fluctuates, the resulting coupling effect will affect the stability of all refrigerant users, thereby causing fluctuations in the entire product separation system, including C2 / C3 separation, C3 / C4 separation, C1 / C2 separation, and IB units.

[0004] Due to the multi-user and complex nature of refrigeration systems, when fluctuations occur in the refrigeration compressor, it is difficult for operators to find the starting point of the problem in the first instance. This requires different positions and different operators to check the changes in their respective refrigerant user parameters. This process will cause a delay in valuable adjustment time. As time goes by, the coupling effect caused by the fluctuations of each user will cause serious production fluctuations in the unit.

[0005] Traditional monitoring may rely on fixed threshold alarms or single parameter monitoring, which cannot effectively capture abnormal situations involving multiple variables. Although existing DCS systems have achieved basic data acquisition and logic control, their built-in alarm management modules usually only support static rule configuration and cannot analyze multi-parameter trends in real time, resulting in delayed fault warnings.

[0006] Therefore, the present invention aims to provide an intelligent control system and method for monitoring and controlling industrial refrigeration systems. Through the intelligent control system and method of the present invention, risks existing in the refrigeration system can be accurately and quickly identified, such as abnormal adjustments by a user or sudden changes in compressor load, and an alarm can be issued to alert operators to intervene in advance to make relevant adjustments, thereby improving the efficiency of fault diagnosis and avoiding excessive fluctuations in the refrigeration system and the resulting coupling effects. Summary of the Invention

[0007] On one hand, this invention provides an intelligent control system for monitoring and controlling industrial refrigeration systems, comprising a data acquisition module, a calculation module, a trend recording module, and an alarm module, wherein...

[0008] The data acquisition module is configured to acquire refrigerant flow parameters and refrigeration compressor operating parameters of each refrigerant user in real time; the calculation module is configured to dynamically calculate the heat load of the heat exchanger at the compressor outlet based on the real-time acquired compressor operating parameters; the trend recording module is configured to store the refrigerant flow parameters of each refrigerant user and the heat load parameters of the heat exchanger at the compressor outlet generated by the calculation module at a certain sampling period, and perform efficient time-series analysis on these parameters to form trend characteristics; the alarm module is configured to generate an alarm signal based on the trend characteristics when the fluctuation amplitude of any parameter in the trend exceeds the alarm threshold.

[0009] On the other hand, the present invention provides a method for monitoring and controlling an industrial refrigeration system, the method comprising the following steps:

[0010] Real-time acquisition of compressor operating parameters and refrigerant flow parameters for each refrigerant user in the refrigeration system;

[0011] Based on real-time collected compressor operating parameters, the heat load of the heat exchanger at the compressor outlet is dynamically calculated.

[0012] The refrigerant flow parameters of each refrigerant user and the heat load parameters of the heat exchanger at the compressor outlet are stored at a preset sampling period, and time-series data analysis is performed to form the trend of each parameter;

[0013] An alarm signal is generated based on the aforementioned trend characteristics.

[0014] In one implementation, the operating parameters of the compressor include the circulating water flow rate and the circulating water outlet / inlet temperature of the heat exchanger at the compressor outlet.

[0015] In one implementation, the refrigerant flow parameters for each refrigerant user include the opening degree of the regulating valve.

[0016] The intelligent control system and method of this invention integrates the key influencing factors of all refrigerant users, continuously monitors their changes, sets certain alarm thresholds, and issues an early warning as soon as the threshold is exceeded. This allows operators to identify potential risks in advance, accurately pinpoint the starting point of the problem, intervene early, and make relevant adjustments to the problematic user. This avoids excessive fluctuations in the refrigerant system and prevents the resulting coupling effects. Detailed Implementation

[0017] The intelligent control system for industrial refrigeration systems of the present invention includes a data acquisition module, a calculation module, a trend recording module, and an alarm module. The intelligent control system is preferably a distributed control system (DCS).

[0018] In the intelligent control system of the present invention, preferably a distributed control system, the data acquisition module is configured to acquire the refrigerant flow parameters of each refrigerant user and the operating parameters of the refrigeration compressor in real time. In one specific embodiment, the refrigerant flow parameters of each refrigerant user include the opening degree of the regulating valve. In another embodiment, the operating parameters of the refrigeration compressor include the circulating water flow rate and circulating water inlet / outlet temperature of the heat exchanger at the compressor outlet, etc. The heat exchanger is preferably a water cooler.

[0019] The calculation module is configured to dynamically calculate the heat load of the heat exchanger at the compressor outlet based on real-time collected compressor operating parameters. This heat load is typically calculated using the following formula: Q = m × c p ×ΔT, where m is the mass flow rate of the circulating water, and c p Let ΔT be the specific heat capacity of water, and ΔT be the temperature difference between the outlet and inlet temperatures of the circulating water (T). 出口 -T 入口 ).

[0020] The trend recording module is configured to store refrigerant flow parameters for each refrigerant user and heat load parameters of the heat exchanger at the compressor outlet generated by the calculation module at a certain sampling period, and perform time-series analysis on these parameters to form trend characteristics. Specifically, a trend graph with time as the horizontal axis and the relevant parameters such as flow rate, regulating valve opening, and heat load as the vertical axis is displayed in real time on the display screen of the intelligent control system, such as DCS, to achieve real-time and dynamic monitoring of the changes in these parameters. This trend characteristic can also reflect the changing patterns of these parameters by looking up historical data. In a specific implementation, for the refrigerant flow parameters of each refrigerant user, the preferred sampling period is the regulating valve opening, with a preset value of 5-10 seconds, for example, 5 seconds; for the heat load at the compressor outlet, the preset sampling period is 5-10 seconds, for example, 5 seconds. The sampling period can be optimized and adjusted according to the actual production situation.

[0021] The alarm module is configured to generate an alarm signal based on the trend characteristics, when the fluctuation range of any of the above parameters exceeds an alarm threshold. The preset value of the alarm threshold is a change of 5%-10% (e.g., 5%) relative to the most recently sampled parameter. Based on historical trends and actual production conditions, those skilled in the art can dynamically adjust the alarm threshold. The alarm signal indicates to the operator which user's regulating valve opening is experiencing abnormal fluctuations or which compressor outlet heat load is experiencing abnormal fluctuations.

[0022] Based on alarm signals, operators can accurately identify the source of the problem and intervene promptly for adjustments. If a user's valve position changes significantly, the root cause can be quickly located. If the heat load fluctuates abnormally, but the valve positions of all users remain unchanged, the problem may lie in a malfunction of the compressor's anti-surge system, such as unplanned activation, or significant changes in ambient temperature, such as sudden weather events like heavy rain. For example, the compressor's anti-surge system provides a circulation loop from the compressor outlet to the inlet when the total refrigerant usage by all users is low, allowing some of the compressed refrigerant to return to the compressor inlet to ensure the compressor's minimum design flow rate, thereby preventing compressor surge. In one implementation, if the compressor heat load changes by more than the alarm threshold compared to the previous sampling period, but the valve positions of all users remain unchanged (indicating that the total refrigerant usage by all users has not decreased significantly, and the anti-surge system's circulation loop should not need to be activated), this may indicate an anti-surge system malfunction. The alarm module can then generate an anti-surge system fault message, reminding operators to check the surge system. In a preferred embodiment, the alarm module is further configured to, when the fluctuation range of the regulating valve opening exceeds an alarm threshold, instruct the data acquisition module to read the change in the liquid level of the corresponding refrigerant user within a specified time period, and generate a false liquid level indication related to the corresponding refrigerant user when the change in the liquid level of the corresponding refrigerant user within the specified time period is non-smooth. For example, the specified time period is typically 1-5 minutes before the alarm occurs. If the liquid level of the refrigerant user changes by more than the alarm threshold compared to the value of the previous sampling period, it is considered a non-smooth change. This configuration can quickly locate the false liquid level indication fault of the refrigerant user, allowing operators to switch the corresponding refrigerant user's level gauge in a timely manner and eliminate the root cause of the problem. At the same time, under normal circumstances, it is not necessary to continuously track or display the liquid level of each refrigerant user in parameter tracking, thereby reducing the amount of data that operators need to pay attention to.

[0023] In another preferred embodiment, the data acquisition module is further configured to acquire weather parameters in real time, and the trend recording module is further configured to, when the weather parameters indicate a sudden weather warning, adjust the sampling period to 1 / m of the original preset value of the sampling period, and instruct the alarm module to adjust the alarm threshold to 1 / n of the original preset value of the alarm threshold; and when the weather parameters indicate that the sudden weather warning has been lifted, adjust the sampling period back to the original preset value of the sampling period, and instruct the alarm module to adjust the alarm threshold back to the original preset value of the alarm threshold, where m and n can be positive integers of 2-10, preferably 2-5, and m is less than or equal to n. The values ​​of m and n can be determined and adjusted according to actual conditions. Taking a preset sampling period of 10 seconds and a preset alarm threshold of 10% relative to the most recently sampled parameter as an example, when m=2 and n=2, the sampling period is shortened to 5 seconds and the preset alarm threshold is reduced to 5% relative to the most recently sampled parameter, that is, the sensitivity to the relative speed of parameter changes remains unchanged, but each parameter is tracked more frequently. As another example, with the same preset values ​​as above, when m=4 and n=5, the sampling period is shortened to 2.5 seconds and the preset alarm threshold is reduced to a 2% change relative to the most recently sampled parameter. In this case, not only are the parameters tracked more frequently, but the sensitivity to the relative rate of parameter change is also improved. This configuration allows the shortening of the monitoring interval and / or the reduction of the alarm threshold to be triggered before sudden weather events occur, thereby making the monitoring more sensitive to weather changes and ensuring more stable operation of the cooling system during sudden weather anomalies.

[0024] The intelligent control system of the present invention is applicable to single-stage and multi-stage compression cycle systems, and is particularly suitable for propylene refrigeration systems in ethylene plants.

[0025] The method for monitoring and controlling industrial refrigeration systems according to the present invention can be implemented through the intelligent control system described in the present invention. The intelligent control system and method of the present invention will be described in detail below using a propylene refrigeration system as an example.

[0026] The refrigerant users in a propylene refrigeration system typically include ethylene distillation columns, de-ethaners, and propane de-condensers. In a propylene refrigeration system, compressors are usually divided into single-stage, double-stage, and triple-stage (or more) compression, each handling different pressure and temperature ranges to provide different temperature levels for different refrigerant users. For example, based on different temperature requirements, propylene refrigerants are classified as low-pressure propylene refrigerant (-38°C), medium-pressure propylene refrigerant (-21°C), and high-pressure propylene refrigerant (+10°C), with their suction pressures corresponding to the first, second, and third inlet stages of the propylene refrigeration compressor, respectively. In the method of this invention, firstly, the data acquisition module of the intelligent control system acquires the refrigerant flow parameters of each refrigerant user in real time, including all high, medium, and low-pressure propylene refrigerant users, optimizing the valve opening, and compressor operating parameters, optimizing the circulating water flow rate and circulating water outlet / inlet temperature of the compressor outlet water cooler.

[0027] Then, using the calculation module, based on the real-time collected compressor operating parameters, the above formula Q=m×c is applied. p ×ΔT dynamically calculates the heat load of the heat exchanger at the compressor outlet.

[0028] The intelligent control system's trend recording module automatically reads changes in refrigerant flow parameters for each refrigerant user every 5 seconds, prioritizing changes in the opening of regulating valves and the heat load of the heat exchanger at the compressor outlet, and generates trends. Monitoring these parameters within these trends, an alarm signal is generated when any parameter's change relative to the most recent sample exceeds an alarm threshold of 5%-10%, for example, 5%. This alarm signal prompts operators to intervene early to mitigate the negative impact of load fluctuations and prevent significant fluctuations in the entire refrigeration system. In some implementations, early warning of parameter trends is based solely on the parameter's change relative to the most recent sample, without considering earlier trends. The impact of parameter changes (e.g., refrigerant user regulating valve opening, heat load of the heat exchanger at the compressor outlet) on the compressor's operating status is highly instantaneous. Therefore, focusing only on the change relative to the most recent sample while selectively ignoring earlier trends can assist operators in improving their prediction of instantaneous impacts through alarms, thus reducing the impact of earlier trends on the instantaneous sensitivity of early warnings.

[0029] In existing propylene refrigeration systems, for example, if the level gauge of a propylene refrigerant user in compressor stage one shows a false reading (e.g., the indicated value is lower than the actual value), the regulating valve for that user will automatically open wider, increasing the amount of gaseous propylene entering the compressor stage inlet. This will cause the compressor inlet pressure to rise. According to the existing control logic, when the increased suction pressure in compressor stage one is detected, the system will automatically increase the compressor speed. The increased compressor speed will affect the suction pressure of compressor stages two and three, decreasing it, while increasing the outlet pressure of stage three. Only after observing the abnormal rise in the outlet pressure of compressor stage three will operators consider whether the unit load or the ambient temperature has changed. If no changes have occurred, each station needs to be notified to check their respective refrigerant users to identify which user's load has changed significantly and what caused it. This process often takes time, and operators may find it difficult to identify the false level reading immediately. As time goes on, each user is affected by pressure fluctuations and needs to adjust their refrigerant valve openings, causing changes in the operating load of each stage of the compressor, ultimately leading to large fluctuations in the entire system.

[0030] Using the intelligent control system and method of this invention, the abnormal opening of the refrigerant regulating valve of the faulty user can be detected in the early stage, that is, an alarm signal is issued at the beginning of the load change. The operator can locate the abnormal user at the first time, intervene quickly, switch the user's refrigerant regulating valve to manual control, and adjust it to the normal valve opening, thereby avoiding subsequent system fluctuations.

[0031] The intelligent control system for monitoring and controlling industrial refrigeration systems, as described in this invention, enables staff to quickly identify which system's refrigerant user load has experienced a significant change based on system prompts. By communicating with relevant personnel and making adjustments in advance, larger fluctuations and coupling effects can be avoided, thereby improving the overall operational stability and anti-fluctuation capability of the propylene refrigeration system.

Claims

1. An intelligent control system for monitoring and controlling an industrial refrigeration system, comprising a data acquisition module, a calculation module, a trend recording module, and an alarm module, wherein the industrial refrigeration system is a propylene refrigeration system of an ethylene plant, wherein... The data acquisition module is configured to acquire refrigerant flow parameters and refrigeration compressor operating parameters for each refrigerant user in real time. The calculation module is configured to dynamically calculate the heat load of the heat exchanger at the compressor outlet based on real-time collected compressor operating parameters. The trend recording module is configured to store the refrigerant flow parameters of each refrigerant user and the heat load parameters of the heat exchanger at the compressor outlet generated by the calculation module at a sampling period, and to perform time-series analysis on these parameters to form trend characteristics; The alarm module is configured to generate an alarm signal based on the trend characteristics when any of the parameters fluctuates beyond the alarm threshold.

2. The intelligent control system according to claim 1 is a distributed control system (DCS).

3. The intelligent control system according to claim 1 or 2, wherein the compressor operating parameters include the circulating water flow rate and the circulating water outlet / inlet temperature of the heat exchanger at the compressor outlet.

4. The intelligent control system according to claim 1 or 2, wherein the refrigerant flow parameters of each refrigerant user include the opening degree of the regulating valve.

5. The intelligent control system according to claim 4, wherein the alarm module is further configured to, when the opening of the regulating valve fluctuates beyond an alarm threshold, instruct the data acquisition module to read the change in the liquid level of the corresponding refrigerant user within a specified time period, and generate a false liquid level indication prompt related to the corresponding refrigerant user when the change in the liquid level of the corresponding refrigerant user within the specified time period is a non-smooth change.

6. The intelligent control system according to claim 1 or 2, wherein the heat load of the heat exchanger at the compressor outlet is calculated by the following formula: Q = m × c p ×ΔT, where m is the mass flow rate of the circulating water, and c p Let be the specific heat capacity of water, and ΔT be the temperature difference between the inlet and outlet of the circulating water.

7. The intelligent control system according to claim 1 or 2, wherein the preset value of the sampling period is 5-10s.

8. The intelligent control system according to claim 7, wherein the preset value of the alarm threshold is a change of 5%-10% relative to the parameter of the most recent sampling.

9. The intelligent control system according to claim 8, wherein the data acquisition module is further configured to acquire weather parameters in real time, and the trend recording module is further configured to, when the weather parameters indicate a sudden weather warning, adjust the sampling period to one-m of a preset value of the sampling period, and instruct the alarm module to adjust the alarm threshold to one-n of a preset value of the alarm threshold; and when the weather parameters indicate the sudden weather warning is lifted, adjust the sampling period back to the preset value of the sampling period, and instruct the alarm module to adjust the alarm threshold back to the preset value of the alarm threshold, wherein m and n are positive integers from 2 to 10, and m is less than or equal to n.