Compressor cooling adaptive control method based on thermal load prediction

Abstract

The present application belongs to the technical field of compressor cooling control, and particularly relates to a compressor cooling adaptive control method based on thermal load prediction, which comprises the following steps: collecting operation data of the compressor; calculating a cumulative heat production load index and an actual thermal resistance value of the compressor according to the operation data; fusing the cumulative heat production load index, the actual thermal resistance value and a discrete change rate of the body surface temperature to obtain a target cooling flow rate; smoothing and correcting the target cooling flow rate according to an adaptive response factor to obtain a final control flow rate; controlling the rotating speed of a cooling water pump according to the final control flow rate, and determining the state of the cooling water circuit according to the relationship between the actual thermal resistance value and a fouling alarm threshold value. The present application improves the long-term precision degradation of compressor cooling resource allocation, and improves the operation stability and cooling control precision of the compressor.

Description

Technical Field

[0001] This invention relates to the field of compressor cooling control technology. More specifically, this invention relates to an adaptive control method for compressor cooling based on heat load prediction. Background Technology

[0002] In the field of industrial gas compression, compressors are the core power equipment. During compressor operation, the gas compression process and the high-frequency movement of moving parts inside the compressor generate a large amount of compression heat and mechanical heat. To ensure the safe operation of the compressor, cooling water channels or water jackets are usually installed on the compressor body to cool the internal parts through a cooling water system. Proper cooling control can maintain the compressor operating within the allowable thermal equilibrium temperature range, thereby ensuring the service life of key components and the working efficiency of the equipment.

[0003] To maintain the operating temperature of the compressor, current methods typically employ cooling water regulation mechanisms based on thermal theory calculations or real-time temperature feedback. For example, Chinese patent application CN107191359A discloses an air compressor cooling method and system. This system obtains the theoretical value of the heat released by the air compressor within a set period, calculates the required cooling water volume for cooling based on meteorological conditions, determines the optimal speed of the cooling water pump accordingly, and adjusts the cooling water flow rate based on actual temperature collected by sensors during operation.

[0004] However, in actual cooling control during long-term operation, as scale forms in the cooling water pipes, the machine temperature often gradually increases under the same cooling water flow rate. Simultaneously, during sudden load changes, temperature feedback regulation typically lags behind by 1-3 control cycles. Specifically, this application ignores the thermal resistance degradation caused by long-term scaling in the cooling water pipes and fails to thoroughly assess the dynamic accumulation and decay of heat sources within the machine, resulting in static cooling commands failing to match actual nonlinear heat exchange demands. Furthermore, in the face of sudden high-load conditions, single temperature feedback regulation lacks a proactive intervention mechanism for the instantaneous temperature rise rate, leading to temperature regulation lag under high loads, which can easily trigger thermal runaway risks and high-frequency oscillations in the actuators. Summary of the Invention

[0005] To address the aforementioned technical problem of declining cooling control accuracy, this invention provides a compressor cooling adaptive control method based on heat load prediction, comprising: The system collects compressor operating data, including discharge pressure, suction pressure, compressor speed, compressor surface temperature, cooling water inlet temperature, cooling water outlet temperature, and cooling water flow rate. A window is set up, and the cumulative heat load index of the compressor is obtained by combining the ratio of discharge pressure to suction pressure and the load proportion of compressor speed within the window, and weighting the data according to the residual heat over time. An evaluation window is set up, and the actual thermal resistance value of the compressor is obtained based on the time-series cumulative change characteristics of the compressor surface temperature, cooling water inlet temperature, and cooling water flow rate collected within the evaluation window. The target cooling flow rate of the compressor is obtained by combining the cumulative heat load index and the actual thermal resistance value with the discrete change rate of the compressor surface temperature. The target cooling flow rate is smoothed and corrected according to a preset adaptive response factor to obtain the final control flow rate. The speed of the cooling water pump is controlled according to the final control flow rate. The cooling water circuit status is determined based on the relationship between the actual thermal resistance value and a preset scaling alarm threshold.

[0006] This invention assesses the degree of heat accumulation inside the machine by acquiring the cumulative heat load index and the actual thermal resistance value to perceive the heat transfer degradation caused by long-term service of the cooling water system. It then integrates these two values ​​with the discrete rate of change of the machine surface temperature to obtain the target cooling flow rate. Through adaptive response factor smoothing correction, the final control flow rate is output to control the speed of the cooling water pump. This allows the cooling command to dynamically match the actual cooling demand caused by the superposition of historical heat source residue and heat exchange efficiency decline. This reduces the risk of machine overheating and thermal runaway caused by static command disconnection or sudden change in transient operating conditions. At the same time, it alleviates the mechanical wear and adjustment oscillation caused by high-frequency jump water flow commands to the frequency converter and water circuit execution unit, and improves the overall adjustment accuracy of the compressor cooling adaptive control method and the safety of equipment operation under long-term service.

[0007] Preferably, the acquisition of compressor operating data includes: Piezoresistive pressure sensors are installed on the compressor's intake and exhaust pipes to continuously collect exhaust and intake pressures; Hall effect speed sensors are installed on the compressor's main shaft to continuously collect compressor speeds; platinum resistance temperature sensors are installed on the compressor's cylinder surface to continuously collect surface temperatures; temperature sensors are installed at the cooling water inlet and outlet to continuously collect cooling water inlet and outlet temperatures; electromagnetic flow meters are installed on the cooling water pipeline to continuously collect cooling water flow rates; all sensors and electromagnetic flow meters collect data at preset sampling time intervals.

[0008] Preferably, the cumulative heat load index of the compressor satisfies the following relationship: ; In the formula, Indicates that the compressor is in The cumulative heat load index at any given time; Indicates the total number of sampling points within the window; Indicates the first in the window The pressure ratio of the compressor at each sampling point; Indicates the first in the window Compressor speed at each sampling point; This indicates the compressor's rated maximum speed; Indicates the first in the window The timestamp corresponding to each sampling point; This indicates the preset maximum residual heat duration.

[0009] This invention integrates the compressor pressure ratio at sampling points within a fusion window with the square of the compressor speed as a percentage of the compressor's rated maximum speed. It also utilizes the linear time residual ratio combined with the timestamps and heat dissipation delay time corresponding to the sampling points to obtain attenuation weights. The cumulative heat load index of the compressor is then obtained by weighted summation within the window. This approach takes into account the coupling relationship between gas compression load, mechanical friction heating, and the thermal inertia of the metal body, ensuring that the obtained cumulative heat load index closely reflects the actual dynamic heat source retention state of the machine body. This reduces the delay in heat dissipation control caused by insufficient estimation of historical heat accumulation.

[0010] Preferably, the actual thermal resistance value of the compressor satisfies the following relationship: ; In the formula, Indicates that the compressor is in The actual thermal resistance value at that moment; This represents the reference thermal resistance under initial clean conditions. Indicates the scaling effect coefficient; This indicates the total number of preset sampling points included in the evaluation window; Indicates the first evaluation window Body surface temperature at each sampling point; Indicates the first evaluation window Cooling water inlet temperature at each sampling point; Indicates the first evaluation window The effective cooling heat power of the cooling water at each sampling point; This represents the first preset minute value.

[0011] This invention obtains the instantaneous degree of heat conduction obstruction by integrating the difference between the surface temperature of the compressor body and the inlet temperature of the cooling water, as well as the effective cooling heat power. It also obtains the actual thermal resistance value of the compressor by combining the scaling influence coefficient and the reference thermal resistance under the initial clean state. This enables the control system to continuously perceive the degree of latent aging such as scaling and corrosion inside the cooling water system, reducing the situation where the predetermined cooling water flow cannot meet the cooling requirements of the compressor body due to the slow deterioration of the water circuit condition, and reducing the risk of control deviation caused by relying on a single static parameter during long-term operation.

[0012] Preferably, the target cooling flow rate of the compressor satisfies the following relationship: ; In the formula, Indicates that the compressor is in The target cooling flow rate at any given time; This indicates the minimum cooling water flow rate required to maintain basic heat exchange. Indicates the heat compensation coefficient; express The theoretical heat transfer demand intensity of the constant cooling system; Indicates the temperature rise compensation coefficient; express The surface temperature of the organism at any given time; express The surface temperature of the organism at any given time; Indicates the sampling time interval; This represents the maximum value function.

[0013] This invention combines the minimum cooling water flow rate required to maintain basic heat exchange with the theoretical heat exchange demand intensity, and introduces the rising trend of the machine body surface temperature to obtain the target cooling flow rate of the compressor. This allows for a comprehensive assessment of the objective heat dissipation burden faced by the machine body and the potential overheating risk. As a result, the cooling control command has both the ability to match the current heat load in real time and the ability to intervene in sudden temperature rises. This alleviates the temperature regulation lag caused by relying solely on feedback control under high load conditions and reduces the risk of component thermal damage caused by the equipment operating in the critical temperature range.

[0014] Preferably, the acquisition of the final control flow includes: The adaptive response factor is set, and the product of the adaptive response factor and the target cooling flow rate at the current sampling time is added to the product of the complement of the adaptive response factor and the target cooling flow rate at the previous sampling time to obtain the final control flow rate of the compressor.

[0015] This invention multiplies the adaptive response factor by the target cooling flow rate at the current sampling time and introduces a smoothing correction mechanism based on the adaptive response factor. This utilizes the system's own control inertia to filter the high-frequency fluctuating flow demand. While ensuring that the system tracks sudden changes in heat generation, it reduces the negative impact of drastic fluctuations in the target command, reduces the adjustment oscillations and mechanical fatigue of the actuator caused by the direct drive of the cooling water pump frequency converter, improves the stability of the cooling water system's water flow output, and extends the overall service life of the corresponding hardware.

[0016] Preferably, controlling the speed of the cooling water pump based on the final controlled flow rate includes: The final control flow rate is output to the variable frequency drive of the cooling water pump corresponding to the compressor cooling water system. The variable frequency drive of the cooling water pump adjusts the speed of the water pump motor according to the command corresponding to the final control flow rate, so as to perform closed-loop adjustment control of the compressor cooling water flow rate.

[0017] Preferably, determining the cooling water circuit status based on the relationship between the actual thermal resistance value and the preset scaling alarm threshold includes: The actual thermal resistance value of the compressor is compared with a preset scaling alarm threshold. When the actual thermal resistance value is less than the scaling alarm threshold, the current cooling water circuit is determined to be in normal condition. When the actual thermal resistance value is greater than or equal to the scaling alarm threshold, the scaling or corrosion inside the cooling water circuit is determined to be severe, and the system hardware outputs a cleaning and maintenance alarm signal to the external central control room terminal.

[0018] Preferably, obtaining the effective cooling heat power of the cooling water includes: Subtract the cooling water inlet temperature from the current cooling water outlet temperature to obtain the actual temperature rise of the cooling water at the current moment. Calculate the product of the specific heat capacity of the cooling water, the density of the cooling water, the current cooling water flow rate, and the current actual temperature rise of the cooling water to obtain the effective cooling heat power of the cooling water at the current moment.

[0019] Preferably, obtaining the theoretical heat transfer demand intensity of the cooling system includes: Calculate the difference between the preset upper limit of the compressor's safe temperature and the current surface temperature of the compressor body, and truncate the difference of the surface temperature of the compressor body to a value no less than a preset second minimum value using a maximum value function; divide the product of the compressor's cumulative heat load index and the actual thermal resistance value at the current moment by the truncated difference of the surface temperature of the compressor body to obtain the theoretical heat exchange demand intensity of the cooling system at the current moment.

[0020] The beneficial effects of this invention are as follows: Addressing the technical problem of long-term inaccurate cooling control, this invention integrates the compressor's cumulative heat load index and actual thermal resistance value, and combines this with the discrete rate of change of the machine surface temperature to obtain the final control flow rate. This enables dynamic adjustment of the cooling water pump speed, overcoming the objective perception limitations of existing static allocation mechanisms. It allows cooling control commands to adaptively match the nonlinear real cooling demand, compensating for the shortcomings of existing technologies in sensing hidden hardware aging and insufficient assessment of thermodynamic hysteresis. This reduces the disconnect between control strategies and actual heat exchange requirements during long-term service, alleviates the bottom-level heat dissipation bottleneck caused by increased scaling resistance inside the pipes, and improves the responsiveness of temperature regulation under high-load conditions. This reduces the probability of the machine temperature exceeding the set upper limit and lowers the adjustment frequency of drastic fluctuations in water pump speed caused by high-frequency jump commands. Attached Figure Description

[0021] Figure 1 This is a flowchart of a compressor cooling adaptive control method based on heat load prediction; Figure 2 This is a schematic diagram showing how the cumulative heat load index of the compressor changes with the sampling points; Figure 3 This is a schematic diagram illustrating how the final control flow rate changes with the sampling point. Detailed Implementation

[0022] This invention discloses an adaptive control method for compressor cooling based on heat load prediction, referring to... Figure 1 This includes steps S100-S500: S100, compressor multi-dimensional operation data acquisition.

[0023] It should be noted that, due to the presence of high-frequency electromagnetic interference and mechanical vibration noise in the compressor's operating environment, the pressure, speed, and temperature signals directly acquired by the sensors often contain random fluctuations. Considering that the moving average algorithm can effectively smooth signal spikes and extract the steady-state characteristics of physical quantities, reflecting the true operating conditions of the compressor, this invention introduces noise reduction processing in the data acquisition stage to reduce the interference of environmental noise on the accuracy of thermal balance calculation and improve the reliability of the control input signal.

[0024] Specifically, piezoresistive pressure sensors are installed on the compressor's intake and exhaust pipes to continuously collect exhaust and intake pressures; a Hall effect speed sensor is installed on the compressor's main shaft to continuously collect compressor speed; a platinum resistance temperature sensor is installed on the compressor cylinder surface to continuously collect surface temperature; temperature sensors are installed at the cooling water inlet and outlet to continuously collect cooling water inlet and outlet temperatures; and an electromagnetic flow meter is installed on the cooling water pipeline to continuously collect cooling water flow. All sensors and electromagnetic flow meters collect data at preset sampling time intervals. For example, the sampling time interval is 1 second to meet the real-time acquisition requirements of the compressor's thermal balance response.

[0025] Furthermore, a moving average filtering algorithm is used to denoise the collected time-series data, including exhaust pressure, intake pressure, compressor speed, engine surface temperature, cooling water inlet temperature, cooling water outlet temperature, and cooling water flow rate, to obtain a smooth, true physical signal. It should be noted that the moving average filtering algorithm is existing technology and will not be elaborated upon here.

[0026] The pressure ratio of the compressor is obtained by calculating the ratio of the exhaust pressure to the intake pressure.

[0027] Thus, the compressor's pressure ratio, compressor speed, compressor body surface temperature, cooling water inlet temperature, cooling water outlet temperature, and cooling water flow rate were obtained.

[0028] S200, calculates the cumulative heat load index of the compressor based on heat decay.

[0029] It should be noted that, considering that the heat generated by gas compression work and mechanical friction will gradually dissipate to the environment with the heat dissipation delay time, the longer the time away from the current moment, the lower the proportion of heat remaining inside the body; therefore, this invention suppresses the assessment lag caused by heat dissipation delay and improves the dynamic accuracy of heat load prediction by weighted summing of the heat generation intensity at each sampling point within the window and using a linear decay model to correct the proportion of heat residue at different time points.

[0030] It should be further explained that by multiplying the pressure ratio, representing the work done by gas compression, by the square of the speed-load ratio, representing high-frequency mechanical friction, the instantaneous heat generation intensity at a certain historical moment is calculated. Multiplying this by the time residual ratio allows us to extract the actual amount of historical heat remaining at present after deducting natural losses. By summing the heat retained at all sampling points within the window, the final result is... The cumulative heat load index at any given time measures the actual heat source accumulation of the compressor under continuous operation, reflecting the inherent thermal inertia and thermodynamic hysteresis of the metal body due to heat dissipation delay.

[0031] Specifically, based on the temporal distribution of the compressor's heat production intensity and its heat decay characteristics, the cumulative heat load index of the compressor is calculated, including: by A window containing a preset number of sampling points is set with the time as the endpoint. For example, the preset number of sampling points is 300. If the preset number of sampling points is too large, such as reaching 1000, it will lead to the introduction of too much historical data and reduce the real-time sensitivity of cooling control commands. If the preset number of sampling points is too small, such as only 10, it will not be able to effectively cover the heat dissipation delay cycle of the machine body, resulting in the distortion of the evaluation of the cumulative heat load index of the compressor.

[0032] The compressor is The cumulative heat load index at any given time satisfies the following relationship: ; In the formula, Indicates that the compressor is in The cumulative heat load index at any given time; Indicates the total number of sampling points within the window; Indicates the first in the window The pressure ratio of the compressor at each sampling point; Indicates the first in the window Compressor speed at each sampling point; This indicates the compressor's rated maximum speed, which is obtained based on the compressor's factory calibration parameters and is set to 500 r / min in this embodiment; Indicates the first in the window The timestamp corresponding to each sampling point; This represents the preset maximum residual heat duration, which is obtained based on the heat conduction limit of the compressor's metal body. In this embodiment, it is set as the total window duration.

[0033] In this relation, It represents the instantaneous relative heat generation intensity driven by the combined effects of gas compression load and internal mechanical friction; This represents the total initial accumulated heat generation intensity within the entire window. The larger the initial accumulated heat generation intensity, the more the compressor operates under high load within the window and the more initial heat sources are accumulated; conversely, the smaller the initial accumulated heat generation intensity, the more the compressor operates under low load within the window and the less initial heat sources are accumulated. This indicates the relative proportion of time span to the maximum residual heat duration. The larger the value, the more likely it is to be the first. The timestamp distance corresponding to each sampling point The longer the time elapsed, the more heat generated has been dissipated into the environment, and the lower the proportion remaining inside the body; conversely, this indicates that the... The timestamp distance corresponding to each sampling point As the moment approaches, a significant amount of heat generated remains inside the body and has not yet dissipated.

[0034] For example, Figure 2 This is a schematic diagram showing the change of the cumulative heat load index of the compressor with the sampling point. The curve in the figure shows a trend of rapid rise followed by stable fluctuation. This reflects the thermodynamic hysteresis physical process in which heat is continuously accumulated inside the compressor in the early stage of startup, and then a dynamic balance is reached between the newly generated heat and the heat lost to the outside.

[0035] Thus, the cumulative heat load index of the compressor was obtained.

[0036] S300: Calculate the actual thermal resistance of the compressor based on the temperature difference and water flow accumulation.

[0037] It should be noted that, considering that the ratio of the temperature difference between the machine body surface and the cooling water to the actual heat power removed can characterize the heat transfer resistance, and that the evolution of this heat transfer resistance has a slow change characteristic across cycles, this invention introduces a dynamic thermal resistance assessment mechanism based on a long-term assessment window. By calculating the temperature difference requirement per unit power, the aging degree of the pipeline is characterized, thereby reducing the interference of short-term operating condition fluctuations on the scaling status assessment.

[0038] It should be further explained that the instantaneous degree of heat conduction obstruction is obtained by dividing the difference between the machine surface temperature and the cooling water inlet temperature by the effective cooling heat power. By accumulating this degree of obstruction within the evaluation window and multiplying it by the scaling influence coefficient, transient fluctuations under short-term operating conditions can be effectively filtered out, and the overall degradation trend of the cooling water system due to long-term operation can be extracted. Finally, this overall degradation trend is superimposed on the reference thermal resistance to calculate the... The actual thermal resistance value of the compressor is measured at all times. This actual thermal resistance value reflects the degree of objective heat exchange efficiency reduction caused by latent aging phenomena such as scaling and corrosion inside the cooling pipes.

[0039] Preferably, the actual thermal resistance of the compressor is calculated based on the continuously collected surface temperature of the compressor body, the cooling water inlet temperature, and the cooling water flow rate over a long evaluation period, including: by An evaluation window containing a preset number of sampling points is set with the time point as the endpoint. For example, the number of sampling points in the evaluation window is set to 86,400, i.e., one day. If the number of sampling points in the evaluation window is too large, for example, reaching 2,592,000, i.e., 30 days, it will introduce too much early cleaning status data, thereby reducing the diagnostic sensitivity to recent scale surges. If the number of sampling points in the evaluation window is too small, for example, only 3,600, i.e., one hour, it will be dominated by short-term operating condition fluctuations and will be difficult to reflect the aging trend of the cooling system.

[0040] Will Subtracting the cooling water inlet temperature from the cooling water outlet temperature at any given time gives the result. Calculate the actual temperature rise of the cooling water at any given time, and determine the specific heat capacity and density of the cooling water. Cooling water flow rate at any time and The product of the actual temperature rise of the cooling water at each moment is obtained. The effective cooling heat power of the cooling water at all times.

[0041] The compressor is The actual thermal resistance at any given time satisfies the following relationship: ; In the formula, Indicates that the compressor is in The actual thermal resistance value at that moment; The reference thermal resistance, representing the initial clean state, is the value specified by the compressor at the factory. The scaling influence coefficient is obtained by least squares fitting of historical data on scaling and thermal resistance deterioration of pipelines in the long-term operation of the same type of compressor. In this embodiment, it is set to 0.002. This indicates the total number of preset sampling points included in the evaluation window; Indicates the first evaluation window Body surface temperature at each sampling point; Indicates the first evaluation window Cooling water inlet temperature at each sampling point; Indicates the first evaluation window The effective cooling heat power of the cooling water at each sampling point; This represents the first preset microvalue, used to prevent calculation divergence caused by a denominator of 0 under shutdown or short-term flow interruption conditions. It is set to 0.001W in this embodiment based on the combined minimum detection resolution limit of the temperature sensor and flow meter. It should be further noted that the least squares method is used for fitting when obtaining the scaling influence coefficient because it can effectively filter out high-frequency random noise during historical data acquisition. By minimizing the sum of squared errors, the globally optimal degradation slope that best conforms to the actual scaling evolution law is found.

[0042] In this relation, Indicates the degree of instantaneous obstruction of heat conduction; This indicates the overall degradation trend of the cooling system over time. The larger the value, the more frequently the cooling system operates under high resistance and low efficiency heat exchange conditions within the evaluation window, indicating that scaling, corrosion, or deposits inside the cooling pipes have reached a high level; conversely, the smaller the value, the more stable the heat exchange performance of the system remains within the evaluation period, and the cleaner the pipes are.

[0043] Thus, the actual thermal resistance value of the compressor was obtained.

[0044] S400: Calculate the target cooling flow rate and smooth it to obtain the final control flow rate.

[0045] It should be noted that, considering that the closer the surface temperature of the machine body is to the upper limit of the safe temperature, the smaller the heat dissipation redundancy of the system, and the higher the sensitivity requirement for cooling flow rate adjustment, while the instantaneous heating rate can reflect the risk of thermal runaway in advance. Therefore, this invention integrates the theoretical heat transfer demand intensity and the temperature rise compensation coefficient to suppress the regulation lag caused by single feedback control.

[0046] It should be further explained that by using the minimum cooling water flow rate required to maintain basic heat exchange as the underlying benchmark for system heat dissipation, the theoretical heat exchange demand intensity is multiplied by the heat compensation coefficient to obtain the basic compensation flow rate that balances the current heat generation of the machine body and the aging resistance of the pipeline. Simultaneously, the discrete rate of temperature rise on the machine body surface is extracted, and a maximum value function is applied to filter the cooling state, combined with the temperature rise compensation coefficient, to convert the excessively rapid temperature rise trend into an advanced compensation flow rate. The final result is obtained by superimposing the above three parameters. The target cooling flow rate of the compressor is determined by comprehensively assessing the objective heat dissipation burden and potential thermal runaway risk faced by the compressor, so that the flow command has both the ability to match the current heat load and the ability to suppress sudden temperature rise.

[0047] Specifically, this invention integrates the cumulative heat load index, actual thermal resistance value, and the discrete rate of change of the machine body surface temperature to calculate the target cooling flow rate of the compressor, including: Calculate the preset upper limit threshold of the compressor's safe temperature and The temperature difference of the machine body surface at any given time is used, and the temperature difference is truncated to a second minimum value not less than a preset value using a maximum value function; the compressor is then... The product of the cumulative heat load index at any given time and the actual thermal resistance value, divided by the difference in surface temperature of the machine body after the cutoff, yields the following result: The theoretical heat exchange demand intensity of the cooling system is constantly monitored. For example, the upper limit threshold of the compressor's safe temperature is set to 368.15K, which is obtained by comprehensively calibrating based on the initial coking critical temperature of conventional industrial compressor lubricating oil and the high-temperature thermal tolerance decay limit of commonly used nitrile rubber (NBR) sealing materials to ensure the long-term physical safety of the core friction pair and sealing system; the preset second minute value is set to 0.1K, which is set based on the lower limit of the effective resolution accuracy and reliable signal-to-noise ratio of industrial-grade temperature sensors in complex electromagnetic interference environments, to prevent the control system from over-responding to invalid temperature noise below the sensor's physical resolution, thereby causing calculation divergence.

[0048] The compressor is The target cooling flow rate at any given time satisfies the following relationship: ; In the formula, Indicates that the compressor is in The target cooling flow rate at any given time; This indicates the minimum cooling water flow rate required to maintain basic heat exchange; this information can be obtained from the compressor's instruction manual. This represents the heat compensation coefficient, calculated based on the rated heat dissipation power of the compressor cooling system and the frequency regulation characteristic curve of the cooling pump. In this embodiment, it is set to... ; express The theoretical heat transfer demand intensity of the constant cooling system; This represents the temperature rise compensation coefficient, obtained based on the thermal inertia calibration of the compressor's metal body. It is used to convert the instantaneous temperature rise rate into the advance compensation flow rate, and in this embodiment, it is set to... ; express The surface temperature of the organism at any given time; express The surface temperature of the organism at any given time; Indicates the sampling time interval; This represents the maximum value function.

[0049] In this relation, This indicates the basic compensation flow rate that the system must provide within a given safe temperature boundary in order to balance the actual heat generation of the compressor and the resistance caused by the aging of the cooling pipes. The larger the basic compensation flow rate, the more it indicates that the compressor is currently operating under extremely high load and the heat exchange capacity of the pipes has been severely degraded, or that the body temperature is extremely close to the upper limit of safety, and the cooling water flow rate must be increased to maintain thermal balance. Conversely, it indicates that the system is in a state of low heat generation, high heat exchange efficiency and sufficient safety buffer space, and no excessive additional flow rate is required. This indicates the rate of instantaneous change in the surface temperature of an organism over time, i.e., the manifestation of thermal inertia. A larger and positive value indicates that the current cooling system, due to a lag in response or a sudden increase in load, has failed to suppress the temperature rise in time, and the machine is rapidly overheating; conversely, if... A value that is negative or close to zero indicates that the body temperature is decreasing or stabilizing, and the trend of heat accumulation has been controlled.

[0050] Thus, the target cooling flow rate of the compressor was obtained.

[0051] It should be noted that since the calculated target flow command changes in real time with the sampled data, if the actuator is directly driven, frequent load increases and decreases will occur. Therefore, this invention introduces an adaptive response factor to smoothly correct the target cooling flow, thereby reducing the adjustment oscillation of the frequency converter and improving the service life of the water pump motor.

[0052] Preferably, an adaptive response factor is set, and the final control flow rate of the compressor is obtained by multiplying the adaptive response factor and the target cooling flow rate at the current sampling time, plus the complement of the adaptive response factor and the target cooling flow rate at the previous sampling time. For example, when the compressor is in a commissioning phase with fluctuating operating conditions or when there is a risk of high-frequency overheating, the adaptive response factor is set to 0.5 to improve the system's tracking sensitivity to the target cooling flow rate and ensure that the cooling water flow rate can quickly respond to sudden changes in heat generation. When the compressor is in an energy-saving phase of long-term stable operation or when the sensor sampling noise is high, the adaptive response factor is set to 0.1. By increasing the weight of the target cooling flow rate at the sampling time, the system's control inertia is used to smooth the final control flow rate, thereby reducing the adjustment frequency of the variable frequency water pump and extending the service life of the actuator.

[0053] For example, Figure 3 This is a schematic diagram of the final control flow rate changing with the sampling point. The curve in the figure shows a sharp peak in the initial stage, then quickly falls back and tends to the stable baseline. This demonstrates the control logic that the system can instantly output an advanced compensation flow rate to intervene when faced with a sudden temperature rise, and then smoothly transition to the control logic of basic heat exchange demand.

[0054] At this point, the final control flow rate of the compressor was obtained.

[0055] S500 controls the water pump speed and compares the thermal resistance to determine the water circuit status.

[0056] It should be noted that, considering that the abnormal increase in the actual thermal resistance value is a direct reflection of the degree of scaling inside the pipeline, and that when the thermal resistance increases to a certain proportion, the system will lose its heat dissipation margin to cope with the rated load, this invention reduces the risk of thermal damage to the machine body caused by poor heat dissipation by comparing the dynamic thermal resistance calculation results with the preset scaling alarm threshold.

[0057] Specifically, the final control flow rate is output to the variable frequency drive of the cooling water pump corresponding to the compressor cooling water system. The variable frequency drive of the cooling water pump adjusts the speed of the water pump motor according to the instruction corresponding to the final control flow rate, so as to perform closed-loop adjustment control of the compressor cooling water flow rate.

[0058] The actual thermal resistance value of the compressor is compared with a preset scaling alarm threshold. When the actual thermal resistance value is less than the scaling alarm threshold, the current cooling water circuit is determined to be in normal condition. When the actual thermal resistance value is greater than or equal to the scaling alarm threshold, it is determined that the scaling or corrosion inside the cooling water circuit is severe, and the system hardware outputs a cleaning and maintenance alarm signal to the external central control room terminal. For example, the scaling alarm threshold is set to 1.5 times the reference thermal resistance, calibrated based on the heat exchange efficiency decay characteristics of the compressor heat exchanger under scaling conditions.

[0059] This completes the adaptive control of compressor cooling.

[0060] While various embodiments of the invention have been shown and described in this specification, it will be apparent to those skilled in the art that such embodiments are provided by way of example only. Many modifications, alterations, and alternatives will occur to those skilled in the art without departing from the spirit and essence of the invention.

Claims

1. A compressor cooling adaptive control method based on heat load prediction, characterized in that, include: Collect compressor operating data, including discharge pressure, suction pressure, compressor speed, compressor surface temperature, cooling water inlet temperature, cooling water outlet temperature, and cooling water flow rate; By setting a window and combining the ratio of the compressor's discharge pressure to its suction pressure within the window with the load percentage of the compressor's speed, and by weighting the cumulative heat load index of the compressor based on the residual heat over time, the cumulative heat load index of the compressor is obtained. The compressor is Cumulative heat load index at any time for: ； Indicates the total number of sampling points within the window; , Indicates the first in the window The pressure ratio and compressor speed of the compressor at each sampling point; This indicates the compressor's rated maximum speed; Indicates the first in the window The timestamp corresponding to each sampling point; Indicates the preset maximum residual heat duration; An evaluation window is set up, and the actual thermal resistance value of the compressor is obtained based on the time-series cumulative change characteristics of the machine body surface temperature, cooling water inlet temperature and cooling water flow rate collected in the evaluation window. The compressor is Actual thermal resistance at time for: ； This represents the reference thermal resistance under initial clean conditions. Indicates the scaling effect coefficient; This indicates the total number of preset sampling points included in the evaluation window; , , Indicates the first evaluation window The surface temperature of the machine body, the inlet temperature of the cooling water, and the effective cooling heat power of the cooling water at each sampling point; Indicates the first preset minute value; The target cooling flow rate of the compressor is obtained by combining the cumulative heat load index with the actual thermal resistance value and integrating it with the discrete change rate of the machine surface temperature. The compressor is Target cooling flow rate at any time for: ； This indicates the minimum cooling water flow rate required to maintain basic heat exchange. Indicates the heat compensation coefficient; express The theoretical heat transfer demand intensity of the constant cooling system; Indicates the temperature rise compensation coefficient; , express , The surface temperature of the organism at any given time; Indicates the sampling time interval; Represents the maximum value function; The determination of the theoretical heat transfer demand intensity of the cooling system includes: Calculate the difference between the preset upper limit of the compressor's safe temperature and the current surface temperature of the compressor body, and truncate the difference of the surface temperature of the compressor body to a value no less than the preset second minimum value using a maximum value function; divide the product of the compressor's cumulative heat load index and the actual thermal resistance value at the current moment by the truncated difference of the surface temperature of the compressor body to obtain the theoretical heat exchange demand intensity of the cooling system at the current moment. The target cooling flow rate is smoothly corrected based on a preset adaptive response factor to obtain the final control flow rate; The speed of the cooling water pump is controlled based on the final control flow rate; the status of the cooling water circuit is determined based on the relationship between the actual thermal resistance value and the preset scaling alarm threshold.

2. The compressor cooling adaptive control method based on heat load prediction according to claim 1, characterized in that, The collected compressor operating data includes: Piezoresistive pressure sensors are installed on the compressor's intake and exhaust pipes to continuously collect exhaust and intake pressures; Hall effect speed sensors are installed on the compressor's main shaft to continuously collect compressor speeds; platinum resistance temperature sensors are installed on the compressor's cylinder surface to continuously collect surface temperatures; temperature sensors are installed at the cooling water inlet and outlet to continuously collect cooling water inlet and outlet temperatures; electromagnetic flow meters are installed on the cooling water pipeline to continuously collect cooling water flow rates; all sensors and electromagnetic flow meters collect data at preset sampling time intervals.

3. The compressor cooling adaptive control method based on heat load prediction according to claim 1, characterized in that, The acquisition of the final control traffic includes: The adaptive response factor is set, and the product of the adaptive response factor and the target cooling flow rate at the current sampling time is added to the product of the complement of the adaptive response factor and the target cooling flow rate at the previous sampling time to obtain the final control flow rate of the compressor.

4. The compressor cooling adaptive control method based on heat load prediction according to claim 1, characterized in that, The method of controlling the speed of the cooling water pump based on the final controlled flow rate includes: The final control flow rate is output to the variable frequency drive of the cooling water pump corresponding to the compressor cooling water system. The variable frequency drive of the cooling water pump adjusts the speed of the water pump motor according to the command corresponding to the final control flow rate, so as to perform closed-loop adjustment control of the compressor cooling water flow rate.

5. The compressor cooling adaptive control method based on heat load prediction according to claim 1, characterized in that, The step of determining the cooling water circuit status based on the relationship between the actual thermal resistance value and the preset scaling alarm threshold includes: The actual thermal resistance value of the compressor is compared with a preset scaling alarm threshold. When the actual thermal resistance value is less than the scaling alarm threshold, the current cooling water circuit is determined to be in normal condition. When the actual thermal resistance value is greater than or equal to the scaling alarm threshold, the scaling or corrosion inside the cooling water circuit is determined to be severe, and the system hardware outputs a cleaning and maintenance alarm signal to the external central control room terminal.

6. The compressor cooling adaptive control method based on heat load prediction according to claim 1, characterized in that, Obtaining the effective cooling heat power of the cooling water includes: Subtract the cooling water inlet temperature from the current cooling water outlet temperature to obtain the actual temperature rise of the cooling water at the current moment. Calculate the product of the specific heat capacity of the cooling water, the density of the cooling water, the current cooling water flow rate, and the current actual temperature rise of the cooling water to obtain the effective cooling heat power of the cooling water at the current moment.

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