Energy-saving optimization control method and system for air compressor and readable storage medium

Abstract

The invention provides an energy-saving optimization control method and system for an air compressor and a readable storage medium. The method comprises the steps that operation parameters of the air compressor and the current air use requirement of an air use end are obtained in real time; the current compression capacity of the air compressor is obtained through analysis according to the operation parameters; key operation parameters of the air compressor are dynamically adjusted according to the current air consumption demand and the current compression capacity so that the current compression capacity can be matched with the current air consumption demand, and the key operation parameters comprise the motor rotating speed, the air compressor load rate and the motor starting and stopping time. According to the energy-saving optimization control method for the air compressor, on the basis of real-time monitoring and analysis of the operation parameters of the air compressor and the current air consumption demand of the air consumption end, the key operation parameters of the air compressor are dynamically adjusted, so that the air production capacity of the air compressor is accurately matched with the actual air consumption demand, energy waste is avoided, and the energy conservation and emission reduction effects are achieved. Meanwhile, the stable operation and the service life of the equipment are considered, and the overall energy-saving optimization target is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of air compressors, and in particular to an energy-saving optimization control method and system for air compressors and a readable storage medium. Background Art

[0002] As a widely used general-purpose mechanical equipment, air compressors play a key role in providing compressed air in the production process of many industries. However, traditional air compressor control methods are often relatively extensive. Most of them work continuously according to fixed pressure setting values ​​and operating modes, and cannot dynamically adjust the operating status according to actual gas demand, resulting in a large amount of energy waste. For example, in some production workshops with unstable gas demand, air compressors may be in full-load operation for a long time. Even if the actual gas consumption at the gas-using end is reduced, the air compressor still maintains high energy output, causing unnecessary electricity consumption; at the same time, frequent starting and stopping will also have a greater impact on the mechanical parts of the air compressor, affecting the service life of the equipment and increasing maintenance costs. Summary of the invention

[0003] The purpose of the present invention is to provide an energy-saving optimization control method for an air compressor to solve the problems existing in the existing air compressors.

[0004] The present invention provides an energy-saving optimization control method for an air compressor, the method comprising: Real-time acquisition of the operating parameters of the air compressor and the current gas demand of the gas user, the operating parameters including the air inlet pressure, the air outlet pressure, the motor speed, the gas volume of the gas storage tank and the motor temperature; Analyzing the operating parameters to obtain the current compression capacity of the air compressor; The key operating parameters of the air compressor are dynamically adjusted according to the current gas demand and the current compression capacity so that the current compression capacity matches the current gas demand. The key operating parameters include the motor speed, the air compressor load rate, and the motor start and stop time.

[0005] The above-mentioned energy-saving optimization control method for the air compressor is based on real-time monitoring and analysis of the air compressor operating parameters and the current gas demand at the gas user end. By dynamically adjusting the key operating parameters of the air compressor, the gas production capacity of the air compressor is accurately matched with the actual gas demand, thereby avoiding energy waste. At the same time, the stable operation and service life of the equipment are taken into account to achieve the overall energy-saving optimization goal.

[0006] Furthermore, the method for obtaining the air pressure at the air inlet includes: An intake pressure sensor is installed at the air inlet of the air compressor to monitor the pressure value of the gas entering the air compressor in real time.

[0007] Furthermore, the method for obtaining the air pressure at the air outlet includes: An outlet pressure sensor is installed at the outlet of the air compressor to obtain the pressure value of the output gas of the air compressor in real time.

[0008] Furthermore, the method for obtaining the motor speed includes: A speed sensor is provided on the driving motor of the air compressor to obtain the real-time speed of the motor.

[0009] Furthermore, the method further comprises: When it is predicted that the gas demand is reduced and the outlet pressure is close to the preset upper limit pressure value, a command is sent to the driver of the air compressor drive motor according to the fuzzy PID control algorithm to gradually reduce the motor speed, thereby reducing the gas production rate of the air compressor; When the predicted gas demand increases and the outlet pressure approaches the preset lower pressure limit, the motor speed is increased to ensure sufficient gas supply.

[0010] Furthermore, the method further comprises: By analyzing the ratio of the motor's real-time power to the rated power, the current load rate of the air compressor is calculated in real time; Adjust the load status of the air compressor based on the gas demand forecast results.

[0011] Furthermore, the method further comprises: When the gas storage in the gas tank reaches the high liquid level or the gas flow rate is continuously lower than the set low flow threshold and the outlet pressure is within a safe and reasonable range, after a certain delay confirmation time, a stop command is issued to stop the air compressor smoothly; When the gas reserve in the gas tank drops to a low liquid level or the gas flow rate is higher than the set start flow threshold and the outlet pressure is low, the air compressor is started.

[0012] Furthermore, the method for obtaining the current gas demand includes: By combining historical data with current real-time data, an autoregressive moving average model and long-short-term memory network are used to build a gas demand forecasting model; The gas demand forecasting model is used to predict the gas flow change trend and gas consumption peak and valley values ​​at the gas consumption end within a preset time period.

[0013] The present invention also provides an energy-saving optimization control system for an air compressor, comprising: Data acquisition module, used to obtain the operating parameters of the air compressor and the current gas demand of the gas user in real time; A data analysis and prediction module, used to obtain the current compression capacity of the air compressor according to the operating parameter analysis; The control module is used to dynamically adjust the key operating parameters of the air compressor according to the current gas demand and the current compression capacity so that the current compression capacity matches the current gas demand.

[0014] The present invention also provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the steps in the energy-saving optimization control method for an air compressor as described in any one of the above are implemented. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is a flow chart of the energy-saving optimization control method of the air compressor in the first embodiment of the present invention; Figure 2 It is a module diagram of the energy-saving optimization control system of the air compressor in the second embodiment of the present invention.

[0016] The following specific implementation manner will further illustrate the present invention in conjunction with the above-mentioned drawings. DETAILED DESCRIPTION

[0017] In order to facilitate understanding of the present invention, the present invention will be described more fully below with reference to the relevant drawings. Several embodiments of the present invention are provided in the drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein. On the contrary, the purpose of providing these embodiments is to make the disclosure of the present invention more thorough and comprehensive.

[0018] It should be noted that when an element is referred to as being "fixed to" another element, it may be directly on the other element or there may be a central element. When an element is considered to be "connected to" another element, it may be directly connected to the other element or there may be a central element at the same time. The terms "vertical", "horizontal", "left", "right" and similar expressions used herein are for illustrative purposes only.

[0019] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which the present invention belongs. The terms used herein in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more of the related listed items.

[0020] See also Figure 1 The present invention provides an energy-saving optimization control method for an air compressor, the method comprising steps S01 to S03: Step S01, obtaining in real time the operating parameters of the air compressor and the current gas demand of the gas user, wherein the operating parameters include the air inlet pressure, the air outlet pressure, the motor speed, the gas volume of the gas storage tank, and the motor temperature; Step S02, obtaining the current compression capacity of the air compressor according to the operating parameter analysis; Step S03, dynamically adjusting the key operating parameters of the air compressor according to the current gas demand and the current compression capacity so that the current compression capacity matches the current gas demand, the key operating parameters including the motor speed, the air compressor load rate and the motor start and stop time.

[0021] The above-mentioned energy-saving optimization control method for the air compressor is based on real-time monitoring and analysis of the air compressor operating parameters and the current gas demand at the gas user end. By dynamically adjusting the key operating parameters of the air compressor, the gas production capacity of the air compressor is accurately matched with the actual gas demand, thereby avoiding energy waste. At the same time, the stable operation and service life of the equipment are taken into account to achieve the overall energy-saving optimization goal.

[0022] In one embodiment of the present invention, the method for obtaining the air pressure at the air inlet includes: An intake pressure sensor is installed at the air inlet of the air compressor to monitor the pressure value of the gas entering the air compressor in real time. The method for obtaining the air pressure at the outlet includes: installing an outlet pressure sensor at the outlet of the air compressor to obtain the pressure value of the output gas of the air compressor in real time. The method for obtaining the motor speed includes: equipping the driving motor of the air compressor with a speed sensor to obtain the real-time speed of the motor. Specifically, an intake pressure sensor is installed at the air inlet of the air compressor to monitor the pressure of the gas entering the air compressor in real time, so as to judge the influence of the intake state on the compression efficiency of the air compressor; an outlet pressure sensor is installed at the outlet to accurately grasp the pressure of the output gas of the air compressor. The pressure value is one of the important indicators to measure whether the air compressor meets the gas demand and judge whether the operating state is reasonable. A speed sensor is equipped on the driving motor of the air compressor to obtain the real-time speed of the motor. Since the gas production efficiency of the air compressor is closely related to the motor speed, monitoring the speed can provide basic data for subsequent control adjustments. A liquid level sensor (for a gas tank system that reflects the gas volume through the liquid level) or a gas flow sensor (for the case of directly measuring the gas flow) is installed on the gas tank to accurately understand the storage volume or real-time flow of the gas in the gas tank, and then infer the gas usage at the gas user end, providing a basis for the matching control of the air compressor's gas production and gas usage. At the same time, a temperature sensor is installed to monitor the operating temperature of key components of the air compressor (such as motors, cylinders, etc.) to ensure that the equipment operates in a safe and reasonable temperature range, and the temperature data can also assist in analyzing the equipment's operating energy efficiency and potential fault hazards.

[0023] In one embodiment of the present invention, the real-time data of the operating parameters are preprocessed to eliminate abnormal data points (for example, data that obviously deviates from the normal range due to temporary sensor failure, etc.), and data standardization and other operations are performed to ensure the accuracy of subsequent analysis.

[0024] In one embodiment of the present invention, the method further comprises: When it is predicted that the gas demand is reduced and the outlet pressure is close to the preset upper limit pressure value, a command is sent to the driver of the air compressor drive motor according to the fuzzy PID control algorithm to gradually reduce the motor speed, thereby reducing the gas production rate of the air compressor; When the predicted gas demand increases and the outlet pressure approaches the preset lower limit pressure value, the motor speed is increased to ensure sufficient gas supply. In this process, the parameters of the fuzzy PID control algorithm (proportional coefficient, integral time constant, differential time constant, etc.) will be adaptively adjusted according to the actual operating conditions to ensure the rapidity, accuracy and stability of speed control.

[0025] In one embodiment of the present invention, the method further comprises: By analyzing the ratio of the motor's real-time power to the rated power, the current load rate of the air compressor is calculated in real time; Adjust the load status of the air compressor based on the gas demand forecast results.

[0026] For example, when it is predicted that the gas demand will be at a low level for a long period of time, the air intake volume can be reduced by controlling the opening of the air compressor intake valve (using an electric regulating valve, and the control module sends a signal to accurately control the valve opening and closing angle) to make the air compressor operate in a more energy-saving low-load range; during peak gas consumption periods, the air intake volume is appropriately increased and the load rate is increased to meet gas demand, avoid affecting production due to insufficient gas supply, and ensure that the overall operating energy efficiency is at a high level.

[0027] In one embodiment of the present invention, the method further comprises: When the gas storage in the gas tank reaches the high liquid level or the gas flow rate is continuously lower than the set low flow threshold and the outlet pressure is within a safe and reasonable range, after a certain delay confirmation time, a stop command is issued to stop the air compressor smoothly; When the gas reserve in the gas tank drops to a low liquid level or the gas flow rate is higher than the set start flow threshold and the outlet pressure is low, the air compressor is started.

[0028] It should be noted that in order to avoid equipment damage and energy waste caused by frequent start and stop of the air compressor, scientific and reasonable start and stop conditions are set. When the gas reserves in the gas tank reach the high liquid level (for the case of liquid level monitoring) or the gas flow rate continues to be lower than the set low flow threshold and the outlet pressure is within a safe and reasonable range, after a certain delay confirmation time (to prevent misjudgment due to instantaneous fluctuations in gas consumption), the control module issues a stop command to stop the air compressor smoothly; conversely, when the gas reserves in the gas tank drop to the low liquid level or the gas flow rate is higher than the set start flow threshold and the outlet pressure is low, the air compressor is started. During the start and stop process, soft start technology is used (by controlling the rising rate of the starting current and voltage, reducing the starting impact, and protecting the motor and power grid equipment) to ensure the smooth start and stop of the air compressor.

[0029] In one embodiment of the present invention, the effectiveness of the current control strategy is verified based on feedback data. If it is found that the actual operating effect deviates from the expectation (such as the actual gas usage is significantly different from the predicted result, or the energy efficiency of the air compressor does not reach the expected target), the relevant parameters in the control strategy (such as fuzzy PID control parameters, valve opening adjustment range, etc.) are promptly fine-tuned and optimized to ensure that the air compressor is always in an efficient and energy-saving operating state.

[0030] In one embodiment of the present invention, the method for obtaining the current gas demand includes: By combining historical data with current real-time data, an autoregressive moving average model and long-short-term memory network are used to build a gas demand forecasting model; The gas demand forecasting model is used to predict the gas flow change trend and gas consumption peak and valley values ​​at the gas consumption end within a preset time period.

[0031] Specifically, by combining historical data with current real-time data, and using advanced time series analysis methods (such as the autoregressive moving average model ARIMA) and machine learning algorithms (such as the long short-term memory network LSTM, which is good at processing data with time series characteristics and can well capture the law of changes in gas demand over time) to build a gas demand forecasting model, it can predict the gas flow change trend at the gas user end in a short period of time (for example, in the next 5-30 minutes) as well as key information such as gas peak and valley values, and provide forward-looking guidance for the precise control of the air compressor.

[0032] See also Figure 2 The embodiment of the present invention further provides an energy-saving optimization control system for an air compressor, comprising: The data acquisition module is used to obtain the operating parameters of the air compressor and the current gas demand of the gas user in real time; specifically, the data acquisition module includes the above-mentioned intake pressure sensor, outlet pressure sensor, speed sensor, liquid level sensor (or gas flow sensor) and temperature sensor, etc. These sensors are distributed in key positions of the air compressor system and are responsible for collecting various operating data and converting them into electrical signals or digital signals, which are sent to the data processing and control unit in real time through wired (such as industrial Ethernet, shielded cable and other communication methods) or wireless (such as Zigbee, LoRa and other wireless communication protocols) transmission methods.

[0033] The data analysis and prediction module is used to obtain the current compression capacity of the air compressor according to the operating parameter analysis; the data analysis and prediction module is mainly composed of a data acquisition module, a data analysis and prediction module, a control strategy generation module and a feedback and optimization module (the function of each module is as described in the above-mentioned air compressor energy-saving optimization control method). The unit receives data from the sensor unit, and after complex data processing, analysis, strategy generation and feedback optimization processes, sends precise control instructions to the execution unit to realize intelligent energy-saving optimization control of the air compressor system.

[0034] The control module is used to dynamically adjust the key operating parameters of the air compressor according to the current gas demand and the current compression capacity so that the current compression capacity matches the current gas demand.

[0035] The energy-saving optimization control system of the above-mentioned air compressor is based on real-time monitoring and analysis of the air compressor operating parameters and the current gas demand at the gas user end. By dynamically adjusting the key operating parameters of the air compressor, the gas production capacity of the air compressor is accurately matched with the actual gas demand, thereby avoiding energy waste. At the same time, it takes into account the stable operation and service life of the equipment to achieve the overall energy-saving optimization goal.

[0036] The present invention also provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the steps in the energy-saving optimization control method for an air compressor as described in any one of the above are implemented.

[0037] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, a magnetic disk, or an optical disk), and includes a number of instructions for enabling a terminal device (which can be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to execute the methods described in each embodiment of the present application.

[0038] The above-mentioned embodiments only express several implementation methods of the present invention, and the description thereof is relatively specific and detailed, but it cannot be understood as limiting the scope of the patent of the present invention. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

Claims

1. An energy-saving optimization control method for an air compressor, characterized in that: The method comprises: Real-time acquisition of the operating parameters of the air compressor and the current gas demand of the gas user, the operating parameters including the air inlet pressure, the air outlet pressure, the motor speed, the gas volume of the gas storage tank and the motor temperature; Analyzing the operating parameters to obtain the current compression capacity of the air compressor; The key operating parameters of the air compressor are dynamically adjusted according to the current gas demand and the current compression capacity so that the current compression capacity matches the current gas demand. The key operating parameters include the motor speed, the air compressor load rate, and the motor start and stop time.

2. The energy-saving optimization control method for an air compressor according to claim 1, characterized in that: The method for obtaining the air pressure at the air inlet comprises: An intake pressure sensor is installed at the air inlet of the air compressor to monitor the pressure value of the gas entering the air compressor in real time.

3. The energy-saving optimization control method for an air compressor according to claim 1, characterized in that: The method for obtaining the air pressure at the air outlet comprises: An outlet pressure sensor is installed at the outlet of the air compressor to obtain the pressure value of the output gas of the air compressor in real time.

4. The energy-saving optimization control method for an air compressor according to claim 1, characterized in that: The method for obtaining the motor speed comprises: A speed sensor is provided on the driving motor of the air compressor to obtain the real-time speed of the motor.

5. The energy-saving optimization control method for an air compressor according to claim 1, characterized in that: The method further comprises: When it is predicted that the gas demand is reduced and the outlet pressure is close to the preset upper limit pressure value, a command is sent to the driver of the air compressor drive motor according to the fuzzy PID control algorithm to gradually reduce the motor speed, thereby reducing the gas production rate of the air compressor; When the predicted gas demand increases and the outlet pressure approaches the preset lower pressure limit, the motor speed is increased to ensure sufficient gas supply.

6. The energy-saving optimization control method for an air compressor according to claim 1, characterized in that: The method further comprises: By analyzing the ratio of the motor's real-time power to the rated power, the current load rate of the air compressor is calculated in real time; Adjust the load status of the air compressor based on the gas demand forecast results.

7. The energy-saving optimization control method for an air compressor according to claim 1, characterized in that: The method further comprises: When the gas storage in the gas tank reaches the high liquid level or the gas flow rate is continuously lower than the set low flow threshold and the outlet pressure is within a safe and reasonable range, after a certain delay confirmation time, a stop command is issued to stop the air compressor smoothly; When the gas reserve in the gas tank drops to a low liquid level or the gas flow rate is higher than the set start flow threshold and the outlet pressure is low, the air compressor is started.

8. The energy-saving optimization control method for an air compressor according to claim 1, characterized in that: The method for obtaining the current gas demand includes: By combining historical data with current real-time data, an autoregressive moving average model and long-short-term memory network are used to build a gas demand forecasting model; The gas demand forecasting model is used to predict the gas flow change trend and gas consumption peak and valley values ​​at the gas consumption end within a preset time period.

9. An energy-saving optimization control system for an air compressor, characterized in that: include: Data acquisition module, used to obtain the operating parameters of the air compressor and the current gas demand of the gas user in real time; A data analysis and prediction module, used to obtain the current compression capacity of the air compressor according to the operating parameter analysis; The control module is used to dynamically adjust the key operating parameters of the air compressor according to the current gas demand and the current compression capacity so that the current compression capacity matches the current gas demand.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps in the energy-saving optimization control method for an air compressor as described in any one of claims 1 to 8 are implemented.

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