An automatic control method and system for an air compressor

Abstract

The application relates to the technical field of air compressor control, and specifically discloses an automatic control method and system for an air compressor, which obtains the change trend of real-time pressure data when the air compressor is running, receives the gas demand requests of multiple gas-using devices in a set period, infers the unannounced gas-using events possibly existing in the current period by analyzing the change trend of the real-time pressure data and combining the gas demand requests, further fuses the unannounced gas-using events and the gas demand requests of all the gas-using devices by using preset gas-using priority rules, generates an ordered gas demand queue, and solves the problem that information flow is difficult to coordinate when multiple gas-using modes coexist. Finally, a gas demand visualization list is formed based on the gas demand queue, and a gas production strategy of the air compressor is planned according to the list, so that the air compressor can adjust the gas production in advance, thereby solving the problems that the gas supply pressure is unstable in the gas-using scene, the production quality is affected, and the energy use efficiency is low in the prior art.

Description

Technical Field

[0001] This application relates to the field of air compressor control technology, and more specifically, to an automated control method and system for air compressors. Background Technology

[0002] In modern industrial production, air compressor systems are a key power source for maintaining the normal operation of production lines. To improve operating efficiency and extend equipment life, variable frequency drive technology has been widely used in air compressor control, adjusting the motor speed in real time to match air demand.

[0003] However, in real-world, complex industrial environments, gas usage patterns are often diverse, including periodic high-flow-rate demands, randomly fluctuating low-flow-rate demands, and gas consumption by precision equipment requiring extremely high pressure stability. Traditional variable frequency control systems, due to their passive response characteristics, struggle to effectively handle these complex and ever-changing gas usage scenarios. In particular, when faced with sudden surges in flow-rate demands, they may experience unstable gas supply pressure, impacting production quality and reducing energy efficiency.

[0004] There is currently no effective technical solution to the above problems. Summary of the Invention

[0005] The purpose of this application is to provide an automated control method and system for air compressors, which aims to solve the problem that in the existing industrial gas environment, it is difficult to effectively cope with diverse gas usage patterns, especially when facing sudden large flow demands, which may lead to unstable gas supply pressure, affect production quality, and reduce energy efficiency.

[0006] To solve the above problems, the solution proposed in this application is as follows:

[0007] As one aspect of this application, an automated control method for an air compressor is provided, comprising:

[0008] Obtain the real-time pressure data change trend of the air compressor during operation;

[0009] It receives air demand requests from multiple air-consuming devices connected to the air compressor at a set period.

[0010] Analyze the changing trends of real-time pressure data and combine them with the gas demand requests of multiple gas-consuming devices to infer unannounced gas consumption events within the current cycle;

[0011] The gas demand queue is generated by merging unannounced gas consumption events and gas demand requests from multiple gas-consuming devices using preset gas consumption priority rules.

[0012] A visual list of gas demand is generated based on the gas demand queue, and the gas production strategy of the air compressor is planned according to the visual list of gas demand.

[0013] Furthermore, the analysis of real-time pressure data trends and the combination of gas demand requests from multiple gas-consuming devices to infer unannounced gas consumption events within the current period includes:

[0014] Confirm whether there is any overlap in the gas consumption periods of each gas-consuming device, and confirm whether the time interval between the start times of gas consumption of two adjacent gas-consuming devices exceeds the preset time window;

[0015] If so, the gas demand requests of multiple gas-consuming devices are processed by integrating the gas demand requests of gas-consuming devices that have overlapping gas consumption periods and adjacent gas consumption start times, resulting in an integrated gas demand request.

[0016] Furthermore, the analysis of real-time pressure data trends and the combination of gas demand requests from multiple gas-consuming devices to infer unannounced gas consumption events within the current period includes:

[0017] Identify trends in real-time pressure data;

[0018] When the real-time pressure data shows a downward trend, record the time point when the real-time pressure data is acquired and calculate the rate of decrease of the real-time pressure data at this time.

[0019] If the time node for acquiring the real-time pressure data is confirmed to be within the gas consumption period indicated in the gas consumption demand request, and the rate of decrease of the real-time pressure data exceeds the preset rate threshold, it is confirmed that there is an unannounced gas consumption event during the operation of the air compressor.

[0020] Furthermore, after confirming that the acquisition time of the real-time pressure data falls within the gas consumption period indicated in the gas demand request, and that the rate of decrease of the real-time pressure data exceeds a preset rate threshold, the process of confirming that the air compressor is operating without prior notice of a gas consumption event includes:

[0021] Set the duration for the estimated gas consumption of unannounced gas consumption events;

[0022] Based on the rated parameters of the air compressor and the rate of decrease of real-time pressure data, the estimated gas consumption for unannounced gas consumption events is calculated.

[0023] By structurally combining the inferred gas consumption, the duration of the inferred gas consumption, and the acquisition time point corresponding to the real-time pressure data, gas demand parameters associated with unannounced gas consumption events are obtained.

[0024] Furthermore, the step of using preset gas consumption priority rules to merge unannounced gas consumption events and gas demand requests from multiple gas-consuming devices to generate a gas demand queue includes:

[0025] A gas consumption priority rule is set, wherein the gas consumption priority rule includes a first priority rule and a second priority rule. The first priority rule indicates that if the gas consumption start time of the gas-consuming devices is different, they are sorted in ascending order according to the gas consumption start time. The second priority rule indicates that if the gas consumption start time of the gas-consuming devices is the same, they are sorted in descending order according to the preset gas consumption priority of the gas-consuming devices.

[0026] A gas demand queue is created using unannounced gas consumption events and gas demand requests from multiple gas-consuming devices. The gas demand queue includes event entries sorted according to gas consumption priority rules.

[0027] Furthermore, after creating a gas demand queue using unannounced gas consumption events and gas demand requests from multiple gas-consuming devices, the process includes:

[0028] Obtain the identification and operating mode of multiple gas-consuming devices;

[0029] Obtain the inherent gas consumption range and default gas consumption of multiple gas-consuming devices in their respective operating modes;

[0030] Compare the gas consumption reported in the gas demand requests of multiple gas-consuming devices with the corresponding inherent gas consumption range;

[0031] When the reported gas consumption exceeds the inherent gas consumption range, the default gas consumption is used as the gas consumption requested in the gas demand request.

[0032] Update the gas demand queue.

[0033] Furthermore, the process of forming a visualized gas demand list based on the gas demand queue, and planning the air compressor's gas production strategy according to the visualized gas demand list, includes:

[0034] Identify the gas-consuming equipment with the highest priority in gas demand from the visualized gas demand list;

[0035] Monitor the pressure status of the gas-consuming area where the gas-consuming equipment with the highest priority gas demand is located;

[0036] When the pressure condition becomes abnormal, emergency intervention is performed on the air compressor's air production capacity.

[0037] Furthermore, the pressure status of the gas-consuming area where the gas-consuming equipment with the highest priority for monitoring gas demand is located includes:

[0038] Based on multiple pressure sensors pre-deployed in the gas consumption area with the highest priority for gas demand, pressure data detected by multiple pressure sensors is received.

[0039] A consistency check is performed on the data from the multiple pressure sensors to obtain the consistency check results.

[0040] When the consistency check results indicate the presence of an abnormal sensor, identify the abnormal sensor;

[0041] Data is fused from the readings of the remaining pressure sensors (excluding the faulty ones) to obtain calibrated data, which is used to indicate the pressure status of the gas-consuming area where the gas-consuming equipment with the highest gas demand priority is located.

[0042] Furthermore, the emergency intervention on the air compressor's gas production capacity when the pressure state becomes abnormal includes:

[0043] When the pressure state becomes abnormal, assess the type and degree of the pressure abnormality to distinguish whether the pressure abnormality is a momentary fluctuation or a continuous decrease.

[0044] Calculate the gas production required to meet increased demand based on the type and severity of the pressure anomaly.

[0045] Based on the required increase in air production and the real-time operating status of each air compressor in the air compressor unit, the air compressors are pressurized to improve air production capacity.

[0046] As a second aspect of this application, an automated control system for an air compressor is provided, comprising:

[0047] The data acquisition module is used to acquire the changing trend of real-time pressure data during the operation of the air compressor;

[0048] The information receiving module is used to receive gas demand requests from multiple gas-consuming devices connected to the air compressor at a set period.

[0049] The demand inference module is used to analyze the changing trend of real-time pressure data and combine it with the gas demand requests of multiple gas-consuming devices to infer unannounced gas consumption events in the current cycle.

[0050] A view construction module is used to merge unannounced gas consumption events and gas demand requests from multiple gas-consuming devices using preset gas consumption priority rules and generate a gas demand queue.

[0051] The gas production planning module is used to generate a visual list of gas demand based on the gas demand queue, and to plan the gas production strategy of the air compressor according to the visual list of gas demand.

[0052] As can be seen from the above, the automated control method and system for air compressors provided in this application can comprehensively perceive the real-time status and predicted demand of the system by acquiring the changing trend of real-time pressure data during the operation of the air compressor and receiving air demand requests from multiple air-consuming devices at a set period. Based on this, by analyzing the changing trend of real-time pressure data and combining it with air demand requests, it infers possible unannounced air consumption events within the current period, thereby overcoming the shortcomings of traditional predictive control that relies solely on early warning signals and improving the system's response to sudden changes in air consumption. Furthermore, by using preset air consumption priority rules to merge unannounced air consumption events and air demand requests from all air-consuming devices, an ordered air demand queue is generated, solving the problem of difficulty in coordinating different information flows when multiple air consumption modes coexist. Ultimately, a visual list of gas demand is formed based on this gas demand queue, and the gas production strategy of the air compressor is planned accordingly. This allows the air compressor to adjust the gas production in advance, avoiding the response lag and pressure fluctuation caused by physical inertia in traditional frequency conversion control. This solves the problems of unstable gas supply pressure, affecting production quality and low energy efficiency in existing technologies under gas consumption scenarios. Attached Figure Description

[0053] Figure 1 A flowchart illustrating an automated control method for an air compressor, provided as an embodiment of this application;

[0054] Figure 2 A system structure block diagram of an automated control system for an air compressor provided in an embodiment of this application;

[0055] Reference numerals: 100, Automated control system for air compressor; 101, Data acquisition module; 102, Information receiving module; 103, Demand inference module; 104, View construction module; 105, Gas production planning module. Detailed Implementation

[0056] To better illustrate the present invention, the invention will now be described in further detail with reference to the accompanying drawings.

[0057] It should be understood that, in order to make the objectives, technical solutions, and advantages of the embodiments of this disclosure clearer, the technical solutions of the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this disclosure, and not all embodiments. The components of the embodiments of this disclosure described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this disclosure provided in the accompanying drawings is not intended to limit the scope of the claimed disclosure, but merely represents selected embodiments of this disclosure. All other embodiments obtained by those skilled in the art based on the embodiments of this disclosure without inventive effort are within the scope of protection of this disclosure.

[0058] The following description uses at least one specific embodiment as an example. In this embodiment:

[0059] like Figure 1 As shown, an automated control method for an air compressor is provided, including:

[0060] Step S1: Obtain the trend of real-time pressure data during air compressor operation;

[0061] Step S2: Receive gas demand requests from multiple gas-consuming devices connected to the air compressor at a set period.

[0062] Step S3: Analyze the changing trend of real-time pressure data and combine it with the gas demand requests of multiple gas-consuming devices to infer unannounced gas consumption events in the current cycle.

[0063] Step S4: Use preset gas consumption priority rules to merge unannounced gas consumption events and gas consumption demand requests from multiple gas-consuming devices to generate a gas consumption demand queue.

[0064] Step S5: Based on the gas demand queue, form a visual list of gas demand and plan the gas production strategy of the air compressor according to the visual list of gas demand.

[0065] To better understand the automated control method proposed in this application, it is necessary to explain some key terms and implementation environments involved.

[0066] Gas demand request refers to a request sent by a gas-consuming device or its control system to an air compressor for information such as its expected gas consumption and the time period for gas consumption.

[0067] Unannounced gas usage events refer to gas usage activities that actually occur without prior notice of a gas demand request, typically manifested as a sudden drop in system pressure.

[0068] Gas priority rules are a set of pre-defined decision criteria used to prioritize and resolve conflicts among multiple gas demands.

[0069] The gas demand queue is a sequence formed by sorting all known and inferred gas demands according to gas demand priority rules.

[0070] A visual gas demand list is an intuitive display generated based on a gas demand queue. It is usually presented in the form of charts, making it easy for operators or control systems to understand and plan.

[0071] The automated control method of this application first requires acquiring the real-time pressure data trend during air compressor operation. This can be achieved by deploying a pressure sensor on the main air supply pipeline of the air compressor. The pressure sensor continuously monitors the pressure within the pipeline and transmits the collected pressure data to the control system. The control system can receive this data at a preset sampling frequency (e.g., once per second or higher) and analyze the continuous pressure values ​​to identify rising, falling, or stable pressure trends. For example, the trend can be determined by calculating the pressure difference at consecutive time points.

[0072] Simultaneously, the system receives air demand requests from multiple air-consuming devices connected to the air compressor at set intervals. These devices can send these requests to the control system in various ways. For example, some devices may have communication interfaces that allow them to proactively report their impending air demand, including the expected air volume and duration, to the air compressor control system via industrial Ethernet (such as Modbus TCP / IP, Profinet) or fieldbus (such as CANopen, DeviceNet) protocols at preset intervals (e.g., every minute or every five minutes). Alternatively, the air-consuming devices can integrate a module that automatically generates and sends air demand requests when it detects that the device is about to start or change its operating mode.

[0073] Next, the system analyzes the changing trend of real-time pressure data and combines it with gas demand requests from multiple gas-consuming devices to infer unannounced gas consumption events within the current period. In one implementation, the changing trend of real-time pressure data can be identified first. When a decreasing trend is detected, the system records the acquisition time of the real-time pressure data and calculates the rate of decrease. Subsequently, the system confirms whether the acquisition time of the real-time pressure data falls within the gas consumption period indicated in the received gas demand requests. If the acquisition time is not within any known gas consumption period, and the rate of decrease of the real-time pressure data exceeds a preset rate threshold, it can be confirmed that the air compressor is operating with an unannounced gas consumption event. For example, if the system detects a sharp drop in pressure within a short period at a certain time, and no gas-consuming device has issued a gas demand request, nor is any known gas-consuming device currently consuming gas, then it can be inferred that an unannounced gas consumption event exists.

[0074] Furthermore, this method uses preset gas consumption priority rules to merge unannounced gas consumption events and gas demand requests from multiple gas-consuming devices to generate a gas demand queue. The gas consumption priority rules can be preset. For example, a first priority rule can be set, indicating that if the gas consumption start times of the devices are different, they are sorted in ascending order of gas consumption start time. This means that devices with earlier gas consumption start times will receive higher priority. Additionally, a second priority rule can be set, indicating that if the gas consumption start times of the devices are the same, they are sorted in descending order of their preset gas consumption priority. For example, devices on critical production lines can be assigned a higher preset gas consumption priority. The control system collects all known gas demand requests (including announced requests from devices and inferred unannounced events) and sorts them according to these priority rules to create the gas demand queue.

[0075] Finally, a visualized gas demand list is created based on the gas demand queue, and the gas production strategy of the air compressors is planned according to this list. The visualized gas demand list presents information from the gas demand queue in an intuitive way, such as using a timeline chart to show the gas consumption and priority of different gas-consuming devices at different times. Operators or automated control systems can understand the gas load distribution based on this visualized list. Based on this, the control system can plan the gas production strategy of the air compressors, such as starting standby air compressors in advance, adjusting the motor speed of variable frequency air compressors, and optimizing the loading and unloading sequence of multiple air compressors, to ensure sufficient gas supply capacity during peak gas consumption periods and reduce energy consumption during off-peak gas consumption periods.

[0076] By combining real-time data analysis and demand forecasting, and introducing priority management and visual planning, proactive control of air compressor operation is achieved, thereby improving the operating efficiency and stability of air compressors, reducing energy consumption, and ensuring that all connected devices can obtain a stable and reliable supply of compressed air in complex and ever-changing industrial environments.

[0077] In some embodiments of this application, the air compressor automation control method receives air demand requests from multiple air-consuming devices connected to the air compressor at a set period. However, in practical applications, these air demand requests may overlap in time or the time interval between the start of air consumption between adjacent air-consuming devices may be too short. If not handled properly, this may lead to inaccurate or inefficient subsequent air consumption event inference and air production strategy planning.

[0078] To address this, further steps are proposed before analyzing the changing trends of real-time pressure data and combining it with gas demand requests from multiple gas-consuming devices to infer unannounced gas consumption events within the current period, including:

[0079] Confirm whether there is any overlap in the gas consumption periods of each gas-consuming device, and confirm whether the time interval between the start times of gas consumption of two adjacent gas-consuming devices exceeds the preset time window;

[0080] If so, the gas demand requests of multiple gas-consuming devices are processed by integrating the gas demand requests of gas-consuming devices that have overlapping gas consumption periods and adjacent gas consumption start times, resulting in an integrated gas demand request.

[0081] Specifically, upon receiving gas demand requests from multiple gas-consuming devices, these requests first need to be preprocessed. This includes confirming whether there is time overlap between the gas consumption periods of different devices. For example, if one device's gas consumption period is T1-T2 and another's is T3-T4, if T3 falls between T1 and T2, or T1 falls between T3 and T4, then time overlap is considered to exist. Simultaneously, it is also necessary to confirm whether the time interval between the start times of two adjacent gas-consuming devices exceeds a preset time window. The preset time window can be set according to the needs of the actual industrial scenario. For example, if two gas-consuming devices have start times only a few seconds or minutes apart, they may be considered as continuous gas consumption events.

[0082] If any of the above conditions are met—that is, if there is an overlap in gas usage periods or an excessively short interval between gas usage start times—then it is necessary to process the gas demand requests from multiple gas-consuming devices. Specifically, this involves integrating the gas demand requests from devices whose usage periods overlap and whose gas usage start times are adjacent. This integration process can merge these overlapping or adjacent requests into a single new gas demand request. The purpose is to eliminate redundant information, simplify the subsequent analysis process, and more accurately reflect the actual gas demand.

[0083] In some preferred embodiments, it is assumed that the air compressor is connected to three air-consuming devices A, B, and C. Within a certain set period, the system receives the following air demand requests:

[0084] Device A: Gas usage starts at 10:00 and lasts for 15 minutes, with a gas consumption of 1.

[0085] Device B: Gas usage starts at 10:05 and lasts for 10 minutes, with a gas consumption of 2 times.

[0086] Equipment C: Gas usage starts at 10:30 and lasts for 20 minutes, with a gas consumption of 3 times.

[0087] First, the system checks for overlap in the gas usage periods of each gas-consuming device. It finds that device A's gas usage period is 10:00-10:15, and device B's is 10:05-10:15. The gas usage periods of device B and device A overlap. Simultaneously, the system checks the time interval between the start times of gas usage for two adjacent devices. The time interval between the start times of device A and device B is 5 minutes. If the preset time window is 10 minutes, then 5 minutes is less than 10 minutes, satisfying the adjacent condition.

[0088] Therefore, the system processes the gas demand requests from devices A and B. The gas demand requests from devices A and B are integrated to obtain a single integrated gas demand request. For example, the new gas usage start time is 10:00, the duration is 15 minutes (covering all gas usage periods of A and B), and the gas consumption is X1 + X2. The gas demand request from device C remains unchanged because it does not overlap with or adjoin the aforementioned request. Thus, subsequent analysis will be based on the integrated gas demand request (representing A and B) and the gas demand request from device C, thereby simplifying the data structure and providing a more accurate view of gas demand.

[0089] Furthermore, the analysis of real-time pressure data trends and the combination of gas demand requests from multiple gas-consuming devices to infer unannounced gas consumption events within the current period includes:

[0090] Identify trends in real-time pressure data;

[0091] When the real-time pressure data shows a downward trend, record the time point when the real-time pressure data is acquired and calculate the rate of decrease of the real-time pressure data at this time.

[0092] If the time node for acquiring the real-time pressure data is confirmed to be within the gas consumption period indicated in the gas consumption demand request, and the rate of decrease of the real-time pressure data exceeds the preset rate threshold, it is confirmed that there is an unannounced gas consumption event during the operation of the air compressor.

[0093] Specifically, identifying trends in real-time pressure data can be achieved by continuously monitoring pressure sensor data within the air compressor system. For example, a sampling frequency can be set to periodically acquire pressure readings, and by comparing consecutive pressure readings, it can be determined whether the pressure is rising, falling, or remaining stable.

[0094] Furthermore, when a downward trend in real-time pressure data is detected, the system immediately records the specific time point at which the pressure data was acquired. Simultaneously, based on the difference between the current pressure value and the pressure value at the previous time point, and the time interval, the system calculates the rate of decrease in the real-time pressure data. This rate of decrease reflects the impact of sudden increases in gas consumption or leaks on the system pressure.

[0095] Confirming that the real-time pressure data acquisition time point falls within the gas consumption period indicated in the gas demand request involves comparing the time of the current pressure drop event with the known, previously announced gas consumption periods of the gas-consuming equipment. If the pressure drop occurs outside the announced gas consumption period of a gas-consuming equipment, or if it occurs within the gas consumption period but the rate of drop is abnormal, further assessment is required. Simultaneously, the rate of drop in the real-time pressure data is compared with a preset rate threshold. This rate threshold is set through simulation / empirical analysis based on the normal operating characteristics of the air compressor system. When the pressure drop rate exceeds this preset rate threshold, it indicates an unusual or unexpected gas consumption behavior. When both conditions—that is, the pressure drop time point is not within the announced gas consumption period (or within the gas consumption period but the drop is abnormal) and the rate of drop exceeds the threshold—are simultaneously met, the system can confirm that the air compressor is operating with an unannounced gas consumption event.

[0096] By analyzing the changing trends of real-time pressure data and cross-validating this with gas demand requests from gas-consuming equipment, unannounced gas consumption events can be inferred. Specifically, when an unannounced gas consumption event occurs in an air compressor system, it typically causes a rapid drop in system pressure within a short period. By identifying this downward trend and recording its occurrence time and rate of decline, abnormal gas consumption behavior can be initially identified. Furthermore, comparing the occurrence time of this abnormal pressure drop event with the gas consumption period indicated in the known gas demand requests can rule out pressure fluctuations caused by normally announced gas consumption. Simultaneously, by setting and comparing the rate of decline of real-time pressure data with a preset rate threshold, normal pressure fluctuations can be distinguished from significant pressure drops caused by sudden, large-scale gas consumption. Only when the pressure drop occurs outside of the announced gas consumption period (or within the announced gas consumption period but with an abnormal rate of decline) and the rate of decline exceeds the preset threshold is it confirmed as an unannounced gas consumption event, thus avoiding misjudgment.

[0097] Furthermore, after confirming that the acquisition time of the real-time pressure data falls within the gas consumption period indicated in the gas demand request, and that the rate of decrease of the real-time pressure data exceeds a preset rate threshold, the process of confirming that the air compressor is operating without prior notice of a gas consumption event includes:

[0098] Set the duration for the estimated gas consumption of unannounced gas consumption events;

[0099] Based on the rated parameters of the air compressor and the rate of decrease of real-time pressure data, the estimated gas consumption for unannounced gas consumption events is calculated.

[0100] By structurally combining the inferred gas consumption, the duration of the inferred gas consumption, and the acquisition time point corresponding to the real-time pressure data, gas demand parameters associated with unannounced gas consumption events are obtained.

[0101] Among them, the purpose of setting a duration for the inferred gas consumption of unannounced gas consumption events is to set a duration for unannounced gas consumption events.

[0102] The inferred gas consumption for unannounced gas usage events is calculated based on the rated parameters of the air compressor and the rate of pressure drop in real-time data. This involves identifying a pressure drop and confirming the existence of an unannounced gas consumption event, then using the air compressor's rated production capacity, current system pressure, and the observed rate of pressure drop, and employing a pre-defined mathematical model to estimate the actual gas consumption causing the pressure drop. For example, the gas consumption within a specific time period can be deduced from the magnitude of the pressure drop, system volume, and the air compressor's production capacity. The purpose is to transform the qualitative "unannounced gas usage event" into a quantitative "inferred gas consumption," providing specific data for subsequent gas production planning.

[0103] Finally, the inferred gas consumption, the duration of the inferred gas consumption, and the acquisition time of the real-time pressure data are structurally combined to obtain gas demand parameters associated with unannounced gas consumption events. Specifically, the calculated inferred gas consumption, the set duration, and the acquisition time of the real-time pressure data (i.e., the start time of the unannounced gas consumption event) are integrated into a standardized data structure. For example, a data package containing fields such as "Gas Consumption," "Duration," and "Start Time" can be formed. The purpose is to represent unannounced gas consumption events in a format similar to that of announced gas demand requests, facilitating subsequent integration with announced gas demand requests.

[0104] By immediately quantifying and parameterizing unannounced gas usage events after confirmation, the limitations of simply identifying the existence of events without effectively integrating them into the overall planning are overcome.

[0105] In this embodiment, the step of using preset gas consumption priority rules to merge unannounced gas consumption events and gas demand requests from multiple gas-consuming devices to generate a gas demand queue includes:

[0106] A gas consumption priority rule is set, wherein the gas consumption priority rule includes a first priority rule and a second priority rule. The first priority rule indicates that if the gas consumption start time of the gas-consuming devices is different, they are sorted in ascending order according to the gas consumption start time. The second priority rule indicates that if the gas consumption start time of the gas-consuming devices is the same, they are sorted in descending order according to the preset gas consumption priority of the gas-consuming devices.

[0107] A gas demand queue is created using unannounced gas consumption events and gas demand requests from multiple gas-consuming devices. The gas demand queue includes event entries sorted according to gas consumption priority rules.

[0108] Specifically, the purpose of setting gas consumption priority rules is to provide a clear ranking basis for various gas consumption demands, so as to ensure that the gas production capacity of air compressors can be rationally allocated under the condition of limited resources. Among them, the gas consumption priority rules are further subdivided into first priority rules and second priority rules to deal with gas consumption conflicts at different levels.

[0109] The primary priority rule is set as follows: if the gas-consuming equipment has different start times, it will be sorted in ascending order of start time. All gas demands (including pre-announced gas demand requests and inferred unannounced gas demand events) will first be sorted according to their planned or inferred start times, with earlier start times receiving higher priority. The purpose is to ensure that the air compressor can respond to the earliest gas demand in chronological order, thereby avoiding production interruptions or efficiency reductions due to delayed responses.

[0110] The second priority rule is set as follows: if the gas-consuming devices have the same gas consumption start time, they are sorted in descending order according to their preset gas consumption priority. This rule addresses the issue of how to prioritize multiple gas consumption demands when they have the same start time. In this case, the system will sort the devices based on their preset importance or urgency, with higher-priority devices receiving gas first. For example, devices on critical production lines may be assigned a higher preset gas consumption priority to ensure they receive priority when using gas simultaneously with other devices. The preset gas consumption priority can be manually configured or dynamically adjusted through system learning, based on factors such as the device's production importance, its impact on the production process, and the amount of gas consumed.

[0111] After setting the above priority rules, a gas demand queue will be created using unannounced gas consumption events and gas demand requests from multiple gas-consuming devices. This gas demand queue is an ordered list containing event entries strictly sorted according to the first and second priority rules described above. Each event entry represents a specific gas demand and includes detailed information about that demand, such as the gas-consuming device identifier, gas start time, gas consumption amount, duration, and preset gas priority.

[0112] In some preferred embodiments, a specific example is given below. Suppose that in a production workshop, three gas-consuming devices A, B, and C are connected, and the system infers an unannounced gas consumption event D.

[0113] Equipment A's gas demand request: Gas usage start time is 9:00 AM, and the preset gas usage priority is high.

[0114] Equipment B's gas demand request: Gas usage start time is 9:30 AM, and the preset gas usage priority is medium.

[0115] Equipment C's gas demand request: Gas usage start time is 9:00 AM, and the preset gas usage priority is medium.

[0116] Unannounced gas usage event D: The estimated start time for gas usage is 9:00 AM, and the system default priority is high (or set according to the estimated urgency level).

[0117] According to the scheme in this application, the process of creating the gas demand queue is as follows:

[0118] First, apply the first priority rule and sort in ascending order according to the start time of gas usage.

[0119] The following are gas usage requirements that start at 9:00: Equipment A, Equipment C, Event D.

[0120] The gas usage start time is 9:30. The requirement is for equipment B.

[0121] The preliminary sorting result is: (A, C, D), B.

[0122] Secondly, for requests with the same gas usage start time (i.e., requests at 9:00: device A, device C, event D), the second priority rule is applied, and the requests are sorted in descending order according to the preset gas usage priority.

[0123] Device A has a high priority.

[0124] Device C has a medium priority.

[0125] Event D has a high priority.

[0126] In the 9:00 requirement, device A and event D both have high priority, while device C has medium priority. If priorities are the same, they can be further sorted according to device identifier or other secondary rules (e.g., unannounced events take precedence over announced events, or according to alphabetical order of device identifiers). Assuming unannounced event D is assigned a higher internal priority, or that the system defaults to prioritizing unannounced events when priorities are the same, the requirement order for 9:00 would be: Event D, Device A, Device C.

[0127] Finally, all demands are merged and a gas demand queue is generated:

[0128] 1. Unannounced gas usage event D (gas usage start time 9:00, high priority)

[0129] 2. Device A (Gas usage starts at 9:00 AM, high priority)

[0130] 3. Equipment C (Gas usage start time 9:00, medium priority)

[0131] 4. Device B (Gas usage start time 9:30, medium priority)

[0132] Therefore, the air compressor will plan its gas production strategy according to this orderly gas demand queue, prioritizing the gas demand of event D and equipment A, followed by equipment C, and finally equipment B, thereby ensuring the rational allocation of gas resources and the optimization of air compressor operation.

[0133] In some of the embodiments described above in this application, a preset gas consumption priority rule is proposed to merge unannounced gas consumption events and gas demand requests from multiple gas-consuming devices to generate a gas demand queue. However, in the implementation process, if the gas consumption data reported by the gas-consuming devices is inaccurate or exceeds their actual operating capacity, the generated gas demand queue may not accurately reflect the actual gas demand, thereby affecting the rationality and efficiency of the air compressor's gas production strategy.

[0134] In this regard, after creating a gas demand queue using unannounced gas usage events and gas demand requests from multiple gas-consuming devices, the process includes:

[0135] Obtain the identification and operating mode of multiple gas-consuming devices;

[0136] Obtain the inherent gas consumption range and default gas consumption of multiple gas-consuming devices in their respective operating modes;

[0137] Compare the gas consumption reported in the gas demand requests of multiple gas-consuming devices with the corresponding inherent gas consumption range;

[0138] When the reported gas consumption exceeds the inherent gas consumption range, the default gas consumption is used as the gas consumption requested in the gas demand request.

[0139] Update the gas demand queue.

[0140] Specifically, obtaining the identifiers and operating modes of multiple gas-consuming devices refers to identifying the unique identity of each device and its current operating status or mode by communicating with the devices or reading from a pre-set device management database. The device identifier uniquely identifies the device, while the operating mode indicates the specific operating state of the device, such as "standby," "low-load operation," "high-load operation," or a specific process flow mode. Different operating modes typically correspond to different gas consumption characteristics.

[0141] Furthermore, obtaining the inherent gas consumption range and default gas consumption of multiple gas-consuming devices in their corresponding operating modes refers to retrieving gas consumption data associated with a specific gas-consuming device and its operating mode from a pre-configured device parameter library or database. The inherent gas consumption range defines the minimum and maximum gas consumption theoretically or actually allowed for the device in that operating mode, aiming to provide a reasonable physical or operational boundary for the gas consumption data. The default gas consumption is a preset, safe, or typical gas consumption value that the system can adopt when reported gas consumption data is abnormal, aiming to ensure reasonable gas production planning even under abnormal data conditions.

[0142] In practical applications, comparing the gas consumption reported in the gas demand requests of multiple gas-consuming devices with their corresponding inherent gas consumption range involves logically judging the specific gas consumption value reported by each device in its gas demand request against the inherent gas consumption range obtained from a parameter library. Specifically, this comparison process aims to confirm whether the reported gas consumption falls between the preset minimum and maximum gas consumption.

[0143] Specifically, when the reported gas consumption exceeds the inherent gas consumption range, using the default gas consumption as the requested gas consumption means that once the gas consumption reported by the gas-consuming equipment is found to be below the lower limit or above the upper limit of the inherent gas consumption range, the system will determine that the reported gas consumption is abnormal or unreliable. In this case, to ensure the rationality of subsequent gas production planning, the system will no longer use the abnormal reported value, but will automatically replace it with the preset default gas consumption. The purpose is to correct inaccurate gas demand and prevent planning deviations caused by erroneous data.

[0144] Therefore, updating the gas demand queue refers to rewriting or modifying the updated gas consumption information in the gas demand request after the aforementioned verification and correction. The purpose is to ensure that all gas consumption data in the gas demand queue is verified and consistent with the actual operating capacity of the equipment, providing accurate basic data for subsequent gas production strategy planning.

[0145] In some preferred embodiments, a specific example is given below. For instance, suppose a gas-consuming device is identified as "Sandblasting Machine A," and its current operating mode is "High-Pressure Sandblasting." The system queries that the inherent air consumption range of "Sandblasting Machine A" in "High-Pressure Sandblasting" mode is 20-30 cubic meters per minute, with a default air consumption of 25 cubic meters per minute. If "Sandblasting Machine A" reports an air consumption of 40 cubic meters per minute in its air demand request, this value exceeds the inherent air consumption range of 20-30 cubic meters per minute. In this case, the solution of this application will automatically adopt 25 cubic meters per minute as the air consumption of "Sandblasting Machine A" and update the corresponding entry in the air demand queue. In this way, even if the device reports abnormal air consumption, the system can still plan air production based on reasonable default values, avoiding air supply imbalances caused by erroneous data.

[0146] In some of the embodiments described above in this application, although it is possible to form a visual list of gas demand based on the gas demand queue and plan the gas production strategy of the air compressor, in actual operation, even with a perfect gas production strategy, there may be sudden and unexpected abnormal pressure in the gas consumption area. In particular, for high-priority gas consumption equipment, if the pressure status of its area is not responded to and intervened in a timely and effective manner, it may lead to the interruption of key production links or equipment damage.

[0147] In response, the process of creating a visual gas demand list based on the gas demand queue and then planning the air compressor's gas production strategy according to the visual gas demand list includes:

[0148] Identify the gas-consuming equipment with the highest priority in gas demand from the visualized gas demand list;

[0149] Monitor the pressure status of the gas-consuming area where the gas-consuming equipment with the highest priority gas demand is located;

[0150] When the pressure condition becomes abnormal, emergency intervention is performed on the air compressor's air production capacity.

[0151] Specifically, identifying the gas-consuming equipment with the highest priority in the visualized gas demand list means selecting the highest priority equipment from all current or upcoming gas-consuming equipment in the generated visualized gas demand list.

[0152] Furthermore, monitoring the pressure status of the gas-consuming area where the highest-priority gas-consuming equipment is located refers to continuously acquiring and analyzing real-time pressure data for that area. This monitoring aims to understand the gas supply status of key areas in real time, so as to promptly detect potential pressure anomalies. Pressure status monitoring can be achieved by deploying pressure sensors in the area and continuously acquiring and analyzing the sensor data.

[0153] When the pressure condition becomes abnormal, emergency intervention is implemented to control the air compressor's gas production capacity. This means that once the pressure in a high-priority gas-consuming area deviates from the normal range (e.g., the pressure remains below the safety threshold or drops sharply), an emergency response mechanism is activated to adjust the air compressor's operating parameters. This may involve increasing the air compressor's speed or starting a standby air compressor to rapidly increase gas production and stabilize the gas supply pressure in that area. This intervention aims to prevent abnormal pressure from adversely affecting high-priority gas-consuming equipment and ensure its normal operation.

[0154] This application's solution compensates for potential response delays when relying solely on preset strategies by introducing real-time monitoring and emergency intervention mechanisms for high-priority gas-consuming equipment, based on the planned gas production strategy. First, it identifies the gas-consuming equipment with the highest priority gas demand, allowing the system to focus its attention on the critical links that have the greatest impact on overall operation, avoiding resource dispersion. Second, it continuously monitors the pressure status of the gas-consuming area where the high-priority equipment is located, ensuring real-time awareness of the gas supply status in key areas. Once an abnormal pressure is detected, the system can quickly assess and initiate emergency intervention measures, thereby restoring gas supply pressure within a short time and preventing further deterioration of the abnormal situation.

[0155] In some preferred embodiments, suppose a factory's air compressor system provides compressed air to a critical production line (e.g., a production line for precision instrument manufacturing), which is designated as the highest-priority air-consuming device. During normal operation, the air compressor system supplies air stably according to a preset air production strategy. However, at some point, a sudden failure of a pneumatic actuator on the production line causes a sharp increase in air consumption in that area, resulting in the pressure sensor in that area detecting a persistent pressure below a safe threshold. At this point, the control method of this application immediately identifies the critical production line as the highest-priority air-consuming device and monitors the abnormal pressure state in its area. The system quickly assesses the type and extent of the pressure drop and immediately initiates emergency intervention measures, such as sending instructions to the air compressor unit to increase air production within a short period or starting a backup air compressor to supplement the air supply. Through this emergency intervention, the air supply pressure of the critical production line is quickly restored, avoiding production interruptions or product quality problems caused by insufficient pressure, thereby ensuring the smooth operation of high-priority production tasks.

[0156] In some of the embodiments described above in this application, the pressure status of the gas-consuming area where the gas-consuming equipment with the highest gas demand priority is located is monitored. However, in the implementation process, if only a single sensor is relied upon or the data from multiple sensors is not effectively verified, the judgment of the pressure status may be biased, thereby affecting the accuracy of subsequent gas production strategies and the timeliness of emergency intervention. In this regard, this application further proposes to optimize the monitoring of the pressure status.

[0157] The pressure status of the gas-consuming equipment in the area with the highest priority for monitoring gas demand includes:

[0158] Based on multiple pressure sensors pre-deployed in the gas consumption area with the highest priority for gas demand, pressure data detected by multiple pressure sensors is received.

[0159] A consistency check is performed on the data from the multiple pressure sensors to obtain the consistency check results.

[0160] When the consistency check results indicate the presence of an abnormal sensor, identify the abnormal sensor;

[0161] Data is fused from the readings of the remaining pressure sensors (excluding the faulty ones) to obtain calibrated data, which is used to indicate the pressure status of the gas-consuming area where the gas-consuming equipment with the highest gas demand priority is located.

[0162] Specifically, multiple pressure sensors are pre-deployed in areas with the highest gas demand priority. These pressure sensors are configured to detect pressure data in the area in real time and send the detected data to the control system. Receiving pressure data from multiple pressure sensors aims to avoid data distortion caused by the failure of a single sensor through redundancy.

[0163] The consistency check of the data from the multiple pressure sensors involves comparing and verifying data from different pressure sensors to determine if there are significant differences between them. For example, a preset deviation threshold can be set; if the average or median of any sensor reading exceeds this threshold, an inconsistency is considered to exist. The purpose of this step is to promptly identify and isolate sensors that may be faulty or have inaccurate readings.

[0164] When the consistency check reveals an abnormal sensor, the system will identify it. An abnormal sensor may exhibit readings that consistently deviate from the normal range. Identifying abnormal sensors helps prevent erroneous data from negatively impacting the overall pressure status assessment.

[0165] Furthermore, data fusion is performed on the readings of the remaining pressure sensors (excluding the faulty ones) to obtain calibrated data. Data fusion techniques can employ various methods; for example, an arithmetic or weighted average can be calculated from the valid readings of the remaining sensors to integrate information from various valid data sources, thereby generating a more reliable pressure status indication. This calibrated data is used to accurately indicate the actual pressure status of the gas-consuming area where the gas-consuming equipment with the highest gas demand priority is located, providing a data foundation for subsequent gas production strategy planning and emergency intervention.

[0166] In some preferred embodiments, a specific example is given below. Suppose that in an industrial production line, there is a critical production area with the highest priority for gas demand, and the gas supply pressure in this area is crucial. To accurately monitor the pressure status of this area, three pressure sensors, namely sensor A, sensor B, and sensor C, are pre-deployed.

[0167] Under normal operating conditions, sensor A detects a pressure of 5.0 bar, sensor B detects a pressure of 5.1 bar, and sensor C detects a pressure of 4.9 bar. Upon receiving this data, the system performs a consistency check. Since all three readings are within a preset reasonable deviation range (e.g., a deviation threshold of 0.2 bar), the consistency check result indicates no abnormal sensors. At this point, the system fuses the readings from these three sensors, for example using a simple averaging method, to obtain the calibrated pressure data as (5.0 + 5.1 + 4.9) / 3 = 5.0 bar. This data is used to indicate the actual pressure state of the area.

[0168] In one specific implementation, if at a certain moment sensor A detects a pressure of 5.0 bar, sensor B detects a pressure of 5.1 bar, and sensor C suddenly detects a pressure of 2.0 bar, during a consistency check, the system finds that the reading of sensor C deviates significantly from the readings of sensors A and B, exceeding a preset deviation threshold. At this point, the system will identify sensor C as an abnormal sensor. Subsequently, the system will exclude the reading of sensor C and perform data fusion only based on the readings of sensors A and B, for example, taking the average value (5.0 + 5.1) / 2 = 5.05 bar, to obtain the calibrated pressure data. In this way, even if one sensor malfunctions or has an abnormal reading, the system can still accurately determine the pressure status of the critical area based on a reliable data source, avoiding misjudgments caused by a single sensor failure.

[0169] In some embodiments described above, this application proposes emergency intervention to control the air compressor's gas production capacity when an abnormal pressure condition occurs. However, in its implementation, if the specific type and degree of the pressure abnormality are not distinguished, the intervention measures may not be precise enough. For example, there may be over-intervention for instantaneous fluctuations or insufficient response to severe abnormalities with a continuous decrease, thus affecting stability. Therefore, this application further proposes a specific method for emergency intervention to control the air compressor's gas production capacity when an abnormal pressure condition occurs, aiming to make more refined adjustments based on the actual abnormal situation.

[0170] When the pressure condition becomes abnormal, emergency intervention is performed on the air compressor's air production capacity, including:

[0171] When the pressure state becomes abnormal, assess the type and degree of the pressure abnormality to distinguish whether the pressure abnormality is a momentary fluctuation or a continuous decrease.

[0172] Calculate the gas production required to meet increased demand based on the type and severity of the pressure anomaly.

[0173] Based on the required increase in air production and the real-time operating status of each air compressor in the air compressor unit, the air compressors are pressurized to improve air production capacity.

[0174] Specifically, assessing the type and severity of pressure anomalies to distinguish between transient fluctuations and sustained declines means that after detecting a pressure anomaly, the system analyzes multiple dimensions, such as the rate of change, duration, and magnitude of deviation from the normal range of pressure data, to determine whether the current anomaly is a temporary, self-recoverable fluctuation or a sustained decline requiring immediate action. For example, if the pressure drops slightly and then quickly rebounds within a very short period, it may be classified as a transient fluctuation; if the pressure continues to decline rapidly and remains below the safety threshold for an extended period, it is classified as a sustained decline.

[0175] Specifically, the calculation of the required additional gas production based on the type and severity of the pressure anomaly can be understood as follows: after identifying the anomaly type, the system uses a preset model and considers the severity of the current anomaly (e.g., the rate of pressure drop, the magnitude of deviation from the target pressure) to calculate the additional gas production needed. For example, a slight, sustained pressure drop might require a smaller increase; a severe, sustained pressure drop would require a larger increase to quickly restore pressure.

[0176] In practical applications, based on the required increase in air production and the real-time operating status of each air compressor in the air compressor unit, the air compressors are pressurized to improve air production capacity. Specifically, after determining the required additional air production, the system comprehensively considers real-time operating parameters of all air compressors in the unit, such as current operating load, maintenance status, and energy efficiency. For example, the system can choose to start a standby air compressor, adjust the loading / unloading points of existing operating air compressors, or increase the operating frequency of variable frequency air compressors to improve air production capacity and thus ensure stable pressure in the air-consuming area.

[0177] By introducing an assessment of the type and severity of pressure anomalies, emergency interventions can be finely adjusted according to the actual situation. When an abnormal pressure condition occurs, the anomaly is first intelligently identified and classified, distinguishing between instantaneous fluctuations and sustained declines, avoiding unnecessary over-intervention for short-term fluctuations. For confirmed sustained decline anomalies, the required increase in gas production can be accurately calculated based on its severity. Furthermore, when performing pressurization operations, the real-time operating status of each air compressor in the air compressor unit is comprehensively considered, allowing the increase in gas production capacity to be carried out in an optimized manner, such as prioritizing the selection of more efficient air compressors or starting standby units.

[0178] In some preferred embodiments, suppose an air compressor system on an industrial production line detects a pressure drop in the air consumption area. The system first activates a pressure anomaly assessment mechanism. If monitoring data shows that the pressure drops by 0.1 MPa within 5 seconds, but then rapidly recovers to the normal range within the next 10 seconds, the system will classify it as a transient fluctuation and may choose not to immediately increase the large-scale air production capacity, but instead continue monitoring to avoid unnecessary intervention.

[0179] For example, if monitoring data shows that the pressure is continuously decreasing at a rate of 0.05 MPa / second, and drops by 1.5 MPa within 30 seconds, remaining below the preset minimum safe pressure threshold, the system will classify this as a severe anomaly. In this case, the system will calculate, based on the rate and magnitude of the pressure drop, that an immediate increase in gas production of 20 cubic meters per minute is needed. Subsequently, the system will query the real-time operating status of each air compressor in the air compressor unit. For instance, if it finds that one variable frequency air compressor is currently operating at 70% load, while another fixed frequency air compressor is in standby mode, the system will prioritize instructing the variable frequency air compressor to increase its load to 95%, and simultaneously start the standby fixed frequency air compressor, allowing it to quickly enter a loading state. This rapidly increases the total gas production capacity to the required level, ensuring that the normal operation of the production line is not affected. In this way, the system can take the most appropriate and effective intervention measures based on the actual abnormal situation.

[0180] As a second aspect of this application, such as Figure 2 As shown, an automated control system 100 for an air compressor is provided, comprising:

[0181] Data acquisition module 101, the data acquisition module 101 is used to acquire the changing trend of real-time pressure data during the operation of the air compressor;

[0182] Information receiving module 102 is used to receive gas demand requests from multiple gas-consuming devices connected to the air compressor at a set period.

[0183] Demand inference module 103 is used to analyze the changing trend of real-time pressure data and combine it with the gas demand requests of multiple gas-consuming devices to infer unannounced gas consumption events in the current cycle.

[0184] The view construction module 104 is used to merge unannounced gas consumption events and gas demand requests from multiple gas-consuming devices using preset gas consumption priority rules and generate a gas demand queue.

[0185] Gas production planning module 105 is used to form a visual list of gas demand based on the gas demand queue, and to plan the gas production strategy of the air compressor according to the visual list of gas demand.

[0186] This application provides an automated control method and system for air compressors. By acquiring the changing trend of real-time pressure data during air compressor operation and receiving air demand requests from multiple air-consuming devices at set intervals, it can comprehensively perceive the real-time status and predicted demand of the system. Based on this, it analyzes the changing trend of real-time pressure data and combines it with air demand requests to infer possible unannounced air consumption events within the current period, thereby compensating for the shortcomings of traditional predictive control that relies solely on early warning signals and improving the system's response to sudden changes in air consumption. Furthermore, it uses preset air consumption priority rules to merge unannounced air consumption events and air demand requests from all air-consuming devices to generate an ordered air demand queue, solving the problem of difficulty in coordinating different information flows when multiple air consumption modes coexist. Finally, based on this air demand queue, a visualized air demand list is formed, and the air compressor's air production strategy is planned accordingly. This allows the air compressor to adjust its air production in advance, avoiding the response lag and pressure fluctuations caused by physical inertia in traditional frequency converter control. This solves the problems of unstable air supply pressure, impact on production quality, and low energy efficiency in existing technologies under various air consumption scenarios.

[0187] Finally, it should be noted that the above-described embodiments are merely specific implementations of this disclosure, used to illustrate the technical solutions of this disclosure, and not to limit them. The protection scope of this disclosure is not limited thereto. Although this disclosure has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can still modify or easily conceive of changes to the technical solutions described in the foregoing embodiments, or make equivalent substitutions for some of the technical features within the scope of the technology disclosed in this disclosure. Such modifications, changes, or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this disclosure, and should all be covered within the protection scope of this disclosure.

Claims

1. An automated control method for an air compressor, characterized in that, include: Obtain the real-time pressure data change trend of the air compressor during operation; It receives air demand requests from multiple air-consuming devices connected to the air compressor at a set period. By analyzing the changing trend of real-time pressure data and combining it with the gas demand requests of multiple gas-consuming devices, unannounced gas consumption events in the current cycle can be inferred. Specifically, when the changing trend of real-time pressure data is downward, the acquisition time node of the real-time pressure data is recorded and the rate of decrease of the real-time pressure data at this time is calculated. It is confirmed that the acquisition time node of the real-time pressure data is within the gas consumption period indicated in the gas demand request, and the rate of decrease of the real-time pressure data exceeds the preset rate threshold. This confirms that there are unannounced gas consumption events during the operation of the air compressor. A gas demand queue is generated by merging unannounced gas consumption events and gas demand requests from multiple gas-consuming devices using a preset gas consumption priority rule. The gas consumption priority rule includes a first priority rule and a second priority rule. The first priority rule indicates that if the gas consumption start times of the gas-consuming devices are different, they are sorted in ascending order according to the gas consumption start time. The second priority rule indicates that if the gas consumption start times of the gas-consuming devices are the same, they are sorted in descending order according to the preset gas consumption priority of the gas-consuming devices. The gas demand queue is created using unannounced gas consumption events and gas demand requests from multiple gas-consuming devices. The gas demand queue includes event entries sorted according to the gas consumption priority rule. A visual list of gas demand is generated based on the gas demand queue, and the gas production strategy of the air compressor is planned according to the visual list of gas demand.

2. The automated control method for an air compressor according to claim 1, characterized in that, The analysis of real-time pressure data trends, combined with gas demand requests from multiple gas-consuming devices, to infer unannounced gas consumption events within the current period includes: Confirm whether there is any overlap in the gas consumption periods of each gas-consuming device, and confirm whether the time interval between the start times of gas consumption of two adjacent gas-consuming devices exceeds the preset time window; If so, the gas demand requests of multiple gas-consuming devices are processed by integrating the gas demand requests of gas-consuming devices that have overlapping gas consumption periods and adjacent gas consumption start times, resulting in an integrated gas demand request.

3. The automated control method for an air compressor according to claim 1, characterized in that, When it is confirmed that the acquisition time of the real-time pressure data is within the gas consumption period indicated in the gas consumption demand request, and the rate of decrease of the real-time pressure data exceeds a preset rate threshold, after confirming that the air compressor has an unannounced gas consumption event during operation, the process includes: Set the duration for the estimated gas consumption of unannounced gas consumption events; Based on the rated parameters of the air compressor and the rate of decrease of real-time pressure data, the estimated gas consumption for unannounced gas consumption events is calculated. By structurally combining the inferred gas consumption, the duration of the inferred gas consumption, and the acquisition time point corresponding to the real-time pressure data, gas demand parameters associated with unannounced gas consumption events are obtained.

4. The automated control method for an air compressor according to claim 1, characterized in that, After creating a gas demand queue using unannounced gas usage events and gas demand requests from multiple gas-consuming devices, the process includes: Obtain the identification and operating mode of multiple gas-consuming devices; Obtain the inherent gas consumption range and default gas consumption of multiple gas-consuming devices in their respective operating modes; Compare the gas consumption reported in the gas demand requests of multiple gas-consuming devices with the corresponding inherent gas consumption range; When the reported gas consumption exceeds the inherent gas consumption range, the default gas consumption is used as the gas consumption requested in the gas demand request. Update the gas demand queue.

5. The automated control method for an air compressor according to claim 1, characterized in that, The process of creating a visual gas demand list based on the gas demand queue, and then planning the air compressor's gas production strategy according to the visual gas demand list, includes: Identify the gas-consuming equipment with the highest priority in gas demand from the visualized gas demand list; Monitor the pressure status of the gas-consuming area where the gas-consuming equipment with the highest priority gas demand is located; When the pressure condition becomes abnormal, emergency intervention is performed on the air compressor's air production capacity.

6. The automated control method for an air compressor according to claim 5, characterized in that, The pressure status of the gas-consuming equipment in the area with the highest priority for monitoring gas demand includes: Based on multiple pressure sensors pre-deployed in the gas consumption area with the highest priority for gas demand, pressure data detected by multiple pressure sensors is received. A consistency check is performed on the data from the multiple pressure sensors to obtain the consistency check results. When the consistency check results indicate the presence of an abnormal sensor, identify the abnormal sensor; Data is fused from the readings of the remaining pressure sensors (excluding the faulty ones) to obtain calibrated data, which is used to indicate the pressure status of the gas-consuming area where the gas-consuming equipment with the highest gas demand priority is located.

7. The automated control method for an air compressor according to claim 5, characterized in that, When the pressure condition becomes abnormal, emergency intervention is performed on the air compressor's air production capacity, including: When the pressure state becomes abnormal, assess the type and degree of the pressure abnormality to distinguish whether the pressure abnormality is a momentary fluctuation or a continuous decrease. Calculate the gas production required to meet increased demand based on the type and severity of the pressure anomaly. Based on the required increase in air production and the real-time operating status of each air compressor in the air compressor unit, the air compressors are pressurized to improve air production capacity.

8. An automated control system for an air compressor, characterized in that, include: The data acquisition module is used to acquire the changing trend of real-time pressure data during the operation of the air compressor; The information receiving module is used to receive gas demand requests from multiple gas-consuming devices connected to the air compressor at a set period. The demand inference module is used to analyze the changing trend of real-time pressure data and combine it with the gas demand requests of multiple gas-consuming devices to infer unannounced gas consumption events in the current period. Specifically, when the changing trend of real-time pressure data is downward, the module records the acquisition time node of the real-time pressure data and calculates the rate of decrease of the real-time pressure data at this time. It also confirms that the acquisition time node of the real-time pressure data is within the gas consumption period indicated in the gas demand request, and that the rate of decrease of the real-time pressure data exceeds a preset rate threshold. In this case, it is confirmed that the air compressor has unannounced gas consumption events during operation. A view construction module is used to merge unannounced gas consumption events and gas demand requests from multiple gas-consuming devices using preset gas consumption priority rules to generate a gas demand queue. The gas consumption priority rules include a first priority rule and a second priority rule. The first priority rule indicates that if the gas consumption start times of the devices are different, they are sorted in ascending order according to the start time. The second priority rule indicates that if the gas consumption start times of the devices are the same, they are sorted in descending order according to the preset gas consumption priority of the devices. The gas demand queue is created using unannounced gas consumption events and gas demand requests from multiple gas-consuming devices, and the gas demand queue includes event entries sorted according to the gas consumption priority rules. The gas production planning module is used to generate a visual list of gas demand based on the gas demand queue, and to plan the gas production strategy of the air compressor according to the visual list of gas demand.

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