Air compressor thermal management control method and system

Abstract

The present invention relates to the field of data processing technology, and the present invention relates to an air compressor thermal management control method and system, including: obtaining the operating data and start-stop frequencies of different air compressors, and dividing the air compressors into long-time air compressors and short-time air compressors according to the start-stop frequencies; inputting the data of these two types of air compressors into a machine model to obtain a first prediction value and a second prediction value, and calculating corresponding weights; the first weight is positively correlated with the start-stop frequency of the short-time air compressor and negatively correlated with the total start-stop frequency; the second weight is positively correlated with the start-stop frequency of the long-time air compressor and negatively correlated with the total start-stop frequency; weighting the two prediction values ​​to obtain the first start-stop frequency, and combining the air compressor attenuation rate to calculate the second start-stop frequency; using the second start-stop frequency to control the temperature parameter data during the operation of the air compressor. The present invention solves the problem of effective control of thermal management of air compressors.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology. More specifically, the present invention relates to a thermal management control method and system for an air compressor. Background Art

[0002] Air compressors are one of the key equipment in industrial production and are widely used in manufacturing, construction, mining, energy and other fields. The main function of air compressors is to provide power through compressed air to drive various mechanical equipment. However, air compressors generate a lot of heat energy during operation. If this heat is not effectively managed and utilized, it will not only reduce the working efficiency of the equipment, but also may cause equipment overheating, increased wear, frequent failures and other problems, thereby affecting the continuity and economic benefits of the production process. The thermal management technology of air compressors mainly focuses on two aspects: one is to reduce the heat generated during the operation of the air compressor, and the other is to effectively recover and reuse the generated heat. Reducing the heat generated by air compressors is usually achieved by optimizing the design, improving the operation control algorithm, and adopting an efficient heat dissipation system. With the development of intelligent industrial equipment, more and more research has begun to focus on how to improve the thermal management effect of air compressors through real-time monitoring and intelligent control. Therefore, how to effectively manage and recycle the heat of air compressors has become an important research direction in the development of air compressor technology.

[0003] At present, the thermal management of air compressors faces many challenges. First, due to the large differences in heat generation and heat dissipation capabilities of different types of air compressors under different working conditions, a single type of thermal management solution is often difficult to apply to multiple scenarios. In addition, the start and stop frequency of the air compressor also has a direct impact on its thermal management effect. Frequent start and stop may cause the heat of the equipment to rise sharply, while long-term operation may cause excessive heat accumulation and failure to dissipate heat in time. Therefore, it is difficult for existing technologies to achieve effective control of air compressor thermal management. Summary of the invention

[0004] In order to solve the problem in the above background technology that it is difficult to effectively control the thermal management of the air compressor, the present invention provides solutions in the following aspects.

[0005] In a first aspect, the present invention provides an air compressor thermal management control method, comprising:

[0006] The operation data and start / stop frequencies of different air compressors in the current time period are obtained, and the air compressors are divided into short-time air compressors and long-time air compressors based on the start / stop frequencies, wherein the air compressors with a start / stop frequency greater than a set threshold are long-time air compressors, and the air compressors with a start / stop frequency less than or equal to the set threshold are short-time air compressors; the operation data of the short-time air compressor and the operation data of the long-time air compressor are respectively input into the machine model, and a first prediction value and a second prediction value are output; and the first weight corresponding to the first prediction value and the second weight corresponding to the second prediction value are respectively calculated; the first weight is positively correlated with the start / stop frequency of the short-time air compressor, and negatively correlated with the total start / stop frequency of the short-time air compressor and the long-time air compressor; the second weight is positively correlated with the start / stop frequency of the long-time air compressor, and negatively correlated with the total start / stop frequency of the short-time air compressor and the long-time air compressor; the first prediction value and the second prediction value are weighted to obtain the first start / stop frequency; the air compressor attenuation rate is obtained, the air compressor attenuation rate is multiplied by the first start / stop frequency to obtain the second start / stop frequency, and the temperature parameter data during the operation of the air compressor is controlled based on the second start / stop frequency.

[0007] The above technical solution obtains the operating data of the short-time air compressor and the long-time air compressor from two perspectives, and comprehensively considers the impact of the start-stop frequency on the air compressor. From a multi-angle analysis, it can improve the effective control of the air compressor thermal energy.

[0008] Furthermore, the first weight α corresponding to the first predicted value is calculated using the formula:

[0009]

[0010] In the formula, a represents the start and stop frequency of the short-time air compressor in the current time period, and c represents the total start and stop frequency of the short-time air compressor and the long-time air compressor in the current time period;

[0011] Calculate the second weight β corresponding to the second predicted value, the formula is:

[0012]

[0013] Where b represents the start and stop frequency of the long-term air compressor in the current time period.

[0014] The above technical solution not only improves the system's dynamic response capability to the operating status of the air compressor through weight calculation based on the start-stop frequency, but also balances the impact of different air compressors and provides more accurate prediction and optimization control under complex working conditions, thereby improving the stability and efficiency of the system.

[0015] Furthermore, the first start-stop frequency γ is calculated using the formula:

[0016]

[0017] Wherein, ε represents the first predicted value, and η represents the second predicted value.

[0018] The above technical solution can comprehensively reflect the operating status of multiple air compressors by weighted averaging the prediction results of different air compressors, dynamically adjust the prediction results, and improve the prediction accuracy and energy efficiency management level of the system. At the same time, it avoids the limitations brought by a single prediction and improves the stability and reliability of the system.

[0019] Furthermore, it also includes obtaining the operating data and start / stop frequencies of different air compressors in the current time period through a digital input port or a communication interface of a programmable logic controller or a microcontroller.

[0020] Furthermore, the operating data includes: cooling water inlet temperature, cooling water outlet temperature, water inlet flow rate and water outlet flow rate.

[0021] Furthermore, the machine model is a support vector machine model.

[0022] Furthermore, it also includes training the machine model, specifically:

[0023] The operating data of different air compressors are input into the pre-built machine model for training. During the training process, the loss between the output prediction value and the label is calculated;

[0024] Use gradient descent to adjust machine model parameters to minimize prediction error;

[0025] Iteratively adjust the parameters of the machine model until the loss is less than a certain value or the set number of training times is reached, and finally a trained machine model is obtained.

[0026] In a second aspect, the present invention provides an air compressor thermal management control system, comprising a memory and a processor, wherein the memory stores computer program instructions, and when the computer program instructions are executed by the processor, an air compressor thermal management control method as described above is implemented.

[0027] The beneficial effects of the present invention are:

[0028] The present invention optimizes the operation and energy consumption management of air compressors through intelligent control strategies. First, the air compressors are divided into short-time air compressors and long-time air compressors, and the operating status of the air compressors is accurately predicted based on the start-stop frequency, thereby reducing frequent starts and stops and improving the overall operating efficiency. In addition, by calculating the weights of short-time air compressors and long-time air compressors, it is possible to dynamically adapt to the operating modes of different air compressors, thereby enhancing the flexibility and robustness of the system. While taking into account the attenuation rate of the air compressor, this method effectively reduces excessive wear of the equipment, extends the service life of the equipment, and reduces maintenance costs; and adjusts heat recovery at appropriate start-stop frequencies to maximize the utilization of waste heat, thereby reducing energy waste and reducing the overall energy consumption of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] By reading the following detailed description with reference to the accompanying drawings, the above and other objects, features and advantages of the exemplary embodiments of the present invention will become readily understood. In the accompanying drawings, several embodiments of the present invention are shown in an exemplary and non-limiting manner, and the same or corresponding reference numerals represent the same or corresponding parts, wherein:

[0030] Figure 1 is a flow chart schematically showing a method for controlling thermal management of an air compressor according to an embodiment of the present invention;

[0031] Figure 2 FIG. 4 is a block diagram schematically showing a structure of a thermal management control system for an air compressor according to an embodiment of the present invention. DETAILED DESCRIPTION

[0032] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0033] The specific embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0034] An embodiment of a thermal management control method for an air compressor.

[0035] like Figure 1 As shown, a flow chart of a thermal management control method for an air compressor according to an embodiment of the present invention comprises the following steps:

[0036] S1: Obtain the operation data and start / stop frequency of different air compressors in the current time period, and divide the air compressors into short-time air compressors and long-time air compressors according to the set threshold.

[0037] In one embodiment, the current time period may be one day or one week, and the operating data and start / stop frequencies of different air compressors in the current time period may be obtained through the digital input port or communication interface of the programmable logic controller or microcontroller. Of course, the operating data and start / stop frequencies may also be directly collected through a sensor network.

[0038] Among them, the operating data includes the cooling water inlet temperature, cooling water outlet temperature, water inlet flow rate and water outlet flow rate. If the cooling water inlet temperature is too high, the cooling system may need more power to maintain effective heat dissipation and increase energy consumption. If the water inlet temperature is appropriate, the workload of the cooling system can be reduced, thereby saving energy. The cooling water outlet temperature can reflect the heat release during the operation of the air compressor. If the cooling water outlet temperature is too high, it may mean that the cooling effect is not good and the air compressor fails to effectively remove the heat, which may cause the equipment to overheat and malfunction. The water inlet flow rate determines the circulation speed of the cooling water and directly affects the cooling capacity of the air compressor. If the water inlet flow rate is insufficient, the cooling water cannot effectively absorb and remove the heat generated by the air compressor, which will cause the equipment to overheat. The change in the water outlet flow rate can be used to monitor whether the cooling system is working properly. If the water outlet flow rate is too low, it may mean that the cooling system is blocked, the pump fails, or the water flow in the cooling pipe is not smooth.

[0039] Exemplarily, the above-mentioned set threshold value may be 3 times / day. Of course, it may also be determined according to actual conditions, and the air compressors may be divided into short-time air compressors and long-time air compressors according to the set threshold value.

[0040] S2: Inputting the operation data of the short-time air compressor and the long-time air compressor into the machine model respectively, and outputting the first prediction value and the second prediction value.

[0041] In one embodiment, the machine model can adopt a support vector machine model or a random forest model. Taking the support vector machine model as an example, training the support vector machine model includes: obtaining a training set; wherein the training set includes the operation data of the short-time air compressor and the long-time air compressor; wherein the labels are manually set.

[0042] The training set is input into the pre-built support vector machine model for training. During the training process, the loss between the output prediction value and the label is calculated; the support vector machine model parameters are adjusted using the gradient descent method to minimize the prediction error; the support vector machine model parameters are iteratively adjusted until the loss is less than a certain value or the set number of training times is reached, and finally a trained support vector machine model is obtained.

[0043] Finally, the operation data of the short-time air compressor and the operation data of the long-time air compressor are respectively input into the trained support vector machine model, and the first prediction value and the second prediction value are output.

[0044] S3: Calculate the weights corresponding to the first prediction value and the second prediction value respectively, and weight the prediction value and the corresponding weight to obtain the first start-stop frequency.

[0045] In one embodiment, the first weight α corresponding to the first prediction value is calculated using the formula:

[0046]

[0047] In the formula, a represents the start and stop frequency of the short-time air compressor in the current time period, and c represents the total start and stop frequency of the short-time air compressor and the long-time air compressor in the current time period;

[0048] Calculate the second weight β corresponding to the second predicted value, the formula is:

[0049]

[0050] Where b represents the start and stop frequency of the long-term air compressor in the current time period.

[0051] Calculate the first start-stop frequency γ, the formula is:

[0052]

[0053] Wherein, ε represents the first predicted value, and η represents the second predicted value.

[0054] For example, assuming that the start and stop frequency of the short-time air compressor is 6 times / day, the start and stop frequency of the long-time air compressor is 2 times / day, the first prediction value is 4, and the second prediction value is 12, then the total start and stop frequency of the short-time air compressor and the long-time air compressor is 8 times / day. Substituting into the above formula, the first weight α corresponding to the first prediction value is 0.75, the second weight β corresponding to the second prediction value is 0.25, and the first start and stop frequency is 3.

[0055] S4: Calculate a second start-stop frequency by combining the air compressor attenuation rate and the first start-stop frequency, and control the temperature parameter data during the operation of the air compressor based on the second start-stop frequency.

[0056] In one embodiment, the attenuation rate of the air compressor can be obtained by regularly detecting key performance parameters of the air compressor, such as exhaust pressure, exhaust temperature, specific power, etc., and comparing them with the initial parameters of the air compressor to calculate the attenuation rate. For example, the air compressor attenuation rate can be obtained by subtracting the current performance from the initial performance and comparing it with the initial performance. Of course, the attenuation rate can also be calculated by the energy efficiency ratio of the air compressor.

[0057] The air compressor attenuation rate is multiplied by the first start-stop frequency to obtain a second start-stop frequency, and the second start-stop frequency is used to adjust the operation cycle of the air compressor to control the temperature parameter data during the operation of the air compressor.

[0058] The scheme of the present invention obtains the operating data and start-stop frequency of the air compressor, divides the air compressor into short-term and long-term categories based on the start-stop frequency, and uses the machine model to calculate the corresponding prediction value and weight, and then weights to obtain the start-stop frequency, and then controls the operating temperature by adjusting the operating cycle of the air compressor. This method can achieve accurate management of the heat energy of the air compressor, effectively reduce the temperature fluctuation caused by frequent start-stop or long-term operation of the air compressor, and improve the overall efficiency of the system and the life of the equipment.

[0059] An embodiment of a thermal management control system for an air compressor:

[0060] like Figure 2 As shown, a structural block diagram of an air compressor thermal management control system according to an embodiment of the present invention includes a processor and a memory.

[0061] The present invention also provides an air compressor thermal management control system. Figure 2 As shown, the system includes a processor and a memory, wherein the memory stores computer program instructions, and when the computer program instructions are executed by the processor, an air compressor thermal management control method according to the present invention described above is implemented.

[0062] The air compressor thermal management control system also includes other components familiar to those skilled in the art, such as a communication interface, and the configuration and functions of the components are known in the art, so they will not be described in detail here.

[0063] In the present invention, the aforementioned memory may be any tangible medium containing or storing a program that may be used by or in combination with an instruction execution system, apparatus or device. For example, a computer-readable storage medium may be any suitable magnetic storage medium or magneto-optical storage medium, such as a resistive random access memory RRAM (Resistive Random Access Memory), a dynamic random access memory DRAM (Dynamic Random Access Memory), a static random access memory SRAM (Static Random-Access Memory), an enhanced dynamic random access memory EDRAM (Enhanced Dynamic Random Access Memory), a high-bandwidth memory HBM (High-Bandwidth Memory), a hybrid memory cube HMC (Hybrid Memory Cube), etc., or any other medium that may be used to store the required information and may be accessed by an application, a module, or both. Any such computer storage medium may be part of a device or accessible or connectable to a device. Any application or module described in the present invention may be implemented using computer-readable / executable instructions that may be stored or otherwise maintained by such a computer-readable medium.

[0064] In the description of this specification, "plurality" or "several" means at least two, such as two, three or more, etc., unless otherwise clearly defined.

[0065] Although this specification has shown and described a number of embodiments of the present invention, it will be apparent to those skilled in the art that such embodiments are provided by way of example only. Those skilled in the art will conceive of many modifications, changes and alternatives without departing from the ideas and spirit of the present invention. It should be understood that in the practice of the present invention, various alternatives to the embodiments of the present invention described herein may be employed.

Claims

1. A method for thermal management control of an air compressor, characterized in that: include: Obtain the operation data of different air compressors in the current time period and their start-stop frequencies, and divide the air compressors into short-time air compressors and long-time air compressors based on the start-stop frequencies, wherein the air compressors with a start-stop frequency greater than a set threshold are short-time air compressors, and the air compressors with a start-stop frequency less than or equal to the set threshold are long-time air compressors; The operation data of the short-time air compressor and the operation data of the long-time air compressor are respectively input into the machine model, and the first prediction value and the second prediction value are output; and the first weight corresponding to the first prediction value and the second weight corresponding to the second prediction value are respectively calculated; the first weight is positively correlated with the start-stop frequency of the short-time air compressor, and negatively correlated with the total start-stop frequency of the short-time air compressor and the long-time air compressor; the second weight is positively correlated with the start-stop frequency of the long-time air compressor, and negatively correlated with the total start-stop frequency of the short-time air compressor and the long-time air compressor; the first prediction value and the second prediction value are weighted to obtain the first start-stop frequency; The air compressor attenuation rate is obtained, the air compressor attenuation rate is multiplied by the first start-stop frequency to obtain a second start-stop frequency, and the temperature parameter data during the operation of the air compressor is controlled based on the second start-stop frequency.

2. The air compressor thermal management control method according to claim 1, characterized in that: Calculate the first weight corresponding to the first predicted value , the formula is: ； In the formula, Indicates the start and stop frequency of the short-term air compressor in the current time period. Indicates the total start and stop frequency of the short-term air compressor and the long-term air compressor in the current time period; Calculate the second weight corresponding to the second predicted value , the formula is: ； In the formula, Indicates the start and stop frequency of the long-term air compressor in the current time period.

3. The air compressor thermal management control method according to claim 2, characterized in that: Calculate the first start-stop frequency , the formula is: ； In the formula, represents the first predicted value, Represents the second predicted value.

4. The air compressor thermal management control method according to claim 1, characterized in that: The method also includes obtaining the operation data and start / stop frequency of different air compressors in the current time period through a digital input port or a communication interface of a programmable logic controller or a microcontroller.

5. The air compressor thermal management control method according to claim 1, characterized in that: The operating data include: cooling water inlet temperature, cooling water outlet temperature, water inlet flow rate and water outlet flow rate.

6. The air compressor thermal management control method according to claim 1, characterized in that: The machine model is a support vector machine model.

7. The air compressor thermal management control method according to claim 1, characterized in that: It also includes training machine models, specifically: The operating data of different air compressors are input into the pre-built machine model for training. During the training process, the loss between the output prediction value and the label is calculated; the machine model parameters are adjusted using the gradient descent method to minimize the prediction error; the machine model parameters are iteratively adjusted until the loss is less than a certain value or the set number of training times is reached, and finally a trained machine model is obtained.

8. An air compressor thermal management control system, characterized in that: The invention comprises a memory and a processor, wherein the memory stores computer program instructions, and when the computer program instructions are executed by the processor, an air compressor thermal management control method as claimed in any one of claims 1 to 7 is implemented.

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