Decentralized air compressor joint control system

Abstract

The invention provides a decentralized air compressor joint control system, relates to the technical field of air compressor equipment, adopts a distributed cooperative control scheme, and realizes cooperative control among equipment in an air compression system through modes such as CAN communication. The state of each device is adjusted in real time on the basis of the running state of the air compressor and the change of the actual gas consumption of a user, so that the stable running of the system is realized, and meanwhile, the energy-saving effect is realized; comprising an air compressor and a post-processing equipment group connected with the air compressor, and the air compressor and each post-processing equipment in the post-processing equipment group are provided with standard CAN communication interfaces; the air compressor is directly connected with each post-processing device through a CAN (Controller Area Network) bus to form a master-slave-free distributed control framework; and the post-processing equipment is configured to acquire the running state data of the air compressor in real time through the CAN bus, and autonomously adjust the running parameters of the post-processing equipment based on preset control logic so as to realize cooperative running with the air compressor.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of air compressor equipment, in particular to a decentralized air compressor joint control system. BACKGROUND

[0002] The traditional air compressor joint control system generally needs a main controller as the leading working system; wherein, the air compressor joint control system each device is provided with a standard RS485 interface, so the main controller of the joint control system is needed as the master station to communicate data with the standard interface of each independent device, to achieve data detection, control, fault interlocking and other functions.

[0003] However, in the actual operation process, the main disadvantage of this control system is that the main controller needs to be kept working, if the main controller fails or is powered off for maintenance, the entire system cannot continue to work automatically, and even stops running; each device to the joint control system needs to be arranged with control lines, the wiring is complex, the line is long and the cost is high; the air compressor, the cold dryer, the suction dryer and other devices are mostly composed of different brands of systems at present, the integration difficulty is high, the non-standardization degree is high, and the implementation cost is high; the joint control system has a fixed non-standard combination, and each integration needs to be designed according to the actual situation, and the flexibility is low. SUMMARY

[0004] I. Technical problems solved The present application proposes a decentralized air compressor joint control system to solve the problems of the prior art, adopts a distributed collaborative control scheme, and realizes the coordinated control between each device in the compressed air system through CAN communication and other ways, and adjusts the state of each device in real time according to the running state of the air compressor and the change of the actual gas consumption of the user, to realize the stable operation of the system and the energy saving effect.

[0005] II. Specific technical scheme A decentralized air compressor joint control system, comprising an air compressor and a post-processing device group connected with the air compressor, the air compressor and each post-processing device in the post-processing device group are provided with a standard CAN communication interface; the air compressor and each post-processing device are directly connected through a CAN bus, forming a distributed control architecture without master and slave; the post-processing device is configured to obtain the running state data of the air compressor in real time through the CAN bus, and autonomously adjust its own running parameters based on a preset control logic, to realize collaborative operation with the air compressor.

[0006] The implementation and working principle of this solution is as follows: Each device in the air compressor and post-processing equipment group is equipped with a standard CAN communication interface and is directly connected via a CAN bus, forming a masterless distributed control architecture. This provides the physical basis for real-time and reliable data exchange between devices. Compared with the traditional RS485 master-slave mode, it supports simultaneous communication between multiple masters, avoiding the communication bottleneck of the master controller, which is a prerequisite for realizing a distributed architecture. It also completely eliminates the single point of failure in the system. In traditional systems, a failure of the master controller will lead to system paralysis, while in this architecture, if any device fails, the remaining devices can still continue to operate collaboratively based on the last received valid information, thus significantly improving system reliability. The air compressor's operating status data is obtained in real time via the CAN bus, and its own operating parameters are autonomously adjusted based on preset control logic, realizing intelligent and precise on-demand control of the system. The post-processing equipment no longer passively executes commands but actively responds to changes in system operating conditions, thereby achieving optimal energy efficiency. At the same time, localized decision-making reduces communication latency and results in faster response speed.

[0007] Preferably, the post-processing equipment group includes at least one of a refrigerated dryer, an oil remover, an adsorption dryer, and a filter; the operating status data of the air compressor includes at least one of start / stop status, operating frequency, and real-time gas production; the adjustment of the operating parameters includes at least one of start / stop sequence control, load adjustment, module activation quantity control, and adsorption time control.

[0008] Preferably, the refrigerated dryer in the post-processing equipment group is configured to dynamically adjust its cooling capacity according to the real-time air output of the air compressor using a PID algorithm. The beneficial effect of this preferred option is that this solution uses the "real-time air output of the air compressor" as a process variable, compares it with the set value of "the required cooling capacity corresponding to the target air output", obtains the deviation, and calculates the output through the deviation value, thus achieving a precise and smooth match between the cooling capacity and the air output. This avoids the fluctuations and energy waste caused by traditional on / off control or simple proportional control, resulting in significant energy-saving effects.

[0009] Preferably, the oil separator in the post-processing equipment group is configured to dynamically adjust the number of its internal modules activated based on a fuzzy control algorithm according to the real-time air output of the air compressor. The advantages of this preferred configuration are that it overcomes the nonlinearity and large lag problems in module start-stop control. This control process is closer to human expert experience and is more stable and intelligent than simple threshold control. While ensuring the oil removal effect, it avoids frequent start-stop of modules, extends equipment life, and saves energy.

[0010] Preferably, the adsorption dryer in the post-processing equipment group is configured to calculate a cumulative processing capacity based on the real-time gas output of the air compressor, its own inlet temperature, and operating temperature, and dynamically adjust its adsorption time based on the cumulative value. The beneficial effect of this preferred configuration is that the controller performs integral calculation on the gas output and corrects it in combination with the influence of temperature on the adsorbent capacity to obtain an intelligent cumulative value that reflects the "actual adsorption load". When the cumulative value is lower than the saturation threshold, it is determined that the adsorbent still has capacity, thereby automatically extending the adsorption time and delaying the energy-consuming regeneration process. This achieves a transition from time-based regeneration to load-based regeneration, significantly reducing the regeneration gas consumption of the adsorption dryer.

[0011] Preferably, the system further includes a drain valve installed on the post-processing equipment; the drain valve is configured to dynamically adjust its draining frequency according to the real-time air output of the air compressor or the overall operating status of the system; the beneficial effect of this preferred embodiment is that the drain valve controller is connected to the CAN bus to obtain system load information; under high load, condensate is generated quickly, increasing the draining frequency; under low load or when the system is stopped, the draining frequency is reduced or even draining is suspended, avoiding the waste of traditional timed draining that still discharges air when the equipment is not working, further reducing compressed air loss and making it more energy-efficient.

[0012] Preferably, at least one post-processing device is also equipped with an RS485 communication interface. The post-processing device is configured to establish a communication connection with an air compressor that only has an RS485 interface via the RS485 communication interface, and to share the acquired air compressor data with other devices in the system via the CAN bus. The advantages of this preferred embodiment are that its internal microcontroller runs a dual-stack protocol. On one hand, it communicates with the old air compressor in master-slave mode via the RS485 interface to acquire its data; on the other hand, it repackages the data into standard CAN messages and broadcasts them to the distributed system. This solves the problem of compatibility between new technologies and existing equipment, allows users to progressively upgrade the system, protects existing investments, lowers the implementation threshold, and greatly improves practicality and market adaptability.

[0013] Preferably, the operation of the system includes the following steps: after the air compressor starts, it broadcasts its startup status via the CAN bus; after each device in the post-processing equipment group detects the startup status of the air compressor via the CAN bus, it starts autonomously according to a preset logical sequence; during operation, each post-processing device acquires the operating frequency or air production data of the air compressor in real time, and autonomously adjusts its own load based on its own preset algorithm to match the operating conditions of the air compressor; after the air compressor stops, each post-processing device stops autonomously according to a preset logical sequence.

[0014] The beneficial effects of this invention are as follows: 1. The system reliability has achieved a qualitative leap, completely eliminating the bottleneck of single point of failure. Through the masterless distributed architecture based on CAN bus, each device has autonomous decision-making capabilities. When any device fails or is under maintenance, the remaining devices can still autonomously coordinate through bus communication and continue to operate in a degraded manner. This solves the fundamental weakness of traditional master-slave control systems that are completely paralyzed due to the failure of the master controller, greatly improves the availability and maintenance convenience of the system, and ensures the continuity of production.

[0015] 2. Each post-processing device (such as a refrigerated dryer and a desiccant dryer) acquires real-time air compressor operating data and applies intelligent algorithms such as PID and fuzzy control to dynamically adjust its own load. This transforms the system from a rough overall start-up and shutdown to a fine-grained coordinated adjustment, achieving precise matching between gas production and processing load, and significantly reducing ineffective energy consumption.

[0016] 3. Significantly enhanced integration and flexibility, combining standardization and strong compatibility. The system adopts a unified CAN interface and communication protocol, enabling plug-and-play functionality and greatly simplifying wiring and debugging. Simultaneously, the innovative RS485-CAN protocol conversion design allows for seamless integration with a large number of traditional devices on the market, protecting user investment. This combination of standardization and compatibility makes the system flexible in configuration and easy to expand, significantly reducing installation and modification costs and timelines. Attached Figure Description

[0017] Figure 1 This is a logical schematic diagram of a decentralized air compressor control system according to the present invention. Detailed Implementation

[0018] The preferred embodiments of the present invention will now be described in detail with reference to the accompanying drawings, so that the advantages and features of the present invention can be more easily understood by those skilled in the art, thereby providing a clearer and more explicit definition of the scope of protection of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0019] like Figure 1 As shown: See Example 1 Figure 1 The decentralized air compressor control system in this embodiment includes a variable frequency air compressor, a refrigerated dryer, an adsorption dryer, and an oil remover. Each device is equipped with an intelligent controller, and the controller is equipped with a CAN communication interface that conforms to the CAN protocol. All devices are connected in a bus topology through a CAN bus composed of a shielded twisted pair cable to form a physical peer-to-peer network.

[0020] To achieve true plug-and-play functionality, this invention defines a Device Description File (DDF) for each device. When a new device, such as a newly added filter, is powered on and connected to the CAN bus, its controller first broadcasts an online announcement message containing its unique ID. Any existing device in the system, such as an air compressor acting as a logic coordinator, will request the DDF upon receiving it. The DDF uses standard JSON or XML format and includes the device type, processing capacity range, supported operating parameters, collaborative control parameters, energy consumption model coefficients, and a list of required data from other devices. After parsing the DDF, existing devices can understand the capabilities and requirements of the new device and dynamically adjust the system's collaborative logic without manual configuration. This mechanism overcomes the technical challenges of integrating heterogeneous devices.

[0021] Example 2: This embodiment pre-configures control algorithms for each device. In specific implementation, the refrigerated dryer adopts an adaptive PID control algorithm. The controller of the refrigerated dryer continuously acquires the operating frequency (f) of the air compressor from the CAN bus. An initial frequency-gas production (Q) conversion model (Q = k * f + b) is pre-stored in the controller. To improve accuracy, the model has a self-learning function: in the early stage of stable operation, the system will synchronously record the frequency f and the rate of change of total pipeline pressure (dp / dt, which indirectly reflects the flow rate), and use the least squares method to calibrate the initial coefficients k and b online to obtain a mapping curve that is more consistent with the actual working conditions.

[0022] In practice, the calibrated gas production (Q) is used as the process variable (PV) of the PID controller. It is compared with the set value (SV, i.e., the cooling capacity corresponding to the target gas production) to produce a deviation e(t). The controller outputs a control signal according to the preset algorithm to adjust the power of the refrigeration compressor. This achieves a precise and smooth match between the gas production and the cooling capacity, avoiding overcooling or insufficient cooling, and resulting in significant energy savings.

[0023] The controller of the oil separator takes the real-time gas production (Q) as input and fuzzifies it into linguistic variables such as "small", "medium", and "large". Based on the preset fuzzy rule base, it performs inference and finally defuzzifies it into a precise number of modules to be turned on. This method is suitable for nonlinear and large hysteresis coefficients such as the start and stop of oil separator modules. Its control process is more stable and more intelligent than simple threshold control, avoiding frequent start and stop of modules and saving energy while ensuring the oil removal effect.

[0024] In practice, in addition to the gas production (Q), the desiccant controller also monitors the inlet temperature (T_in) and the operating temperature (T_work). It calculates the "equivalent treatment load" L = ∫(Q * φ(T_in, T_work)) dt in real time, where φ is the temperature correction factor. When the cumulative load value L is lower than the saturation threshold L_sat, the controller automatically extends the current adsorption cycle. By changing the control benchmark from a fixed time to the actual adsorption load, unnecessary regeneration gas consumption under low load conditions is significantly reduced, effectively lowering energy consumption.

[0025] In practice, the electronic drain valves below each post-processing device are also connected to the intelligent controller of their respective devices. The controller intelligently adjusts the opening frequency and duration of the drain valves based on the overall operating conditions of the system—especially the air output of the air compressor. During periods of low air consumption, the number of draining operations is reduced to avoid wasting compressed air.

[0026] Example 3: To address the reliability challenges of distributed systems in industrial environments, this solution also incorporates a state machine-based distributed fault-tolerance mechanism. Each device maintains a system state mapping table and its own fault-tolerance state machine. Devices periodically broadcast heartbeat messages on the bus to indicate their own liveness. Simultaneously, they listen for the heartbeats of other devices.

[0027] Under normal conditions, all devices operate with normal heartbeats and coordinate according to preset logic. For fault detection, if a device, such as a refrigerated dryer, does not receive a heartbeat from the air compressor within a timeout period, it will not immediately stop but will switch to a "suspected air compressor fault" state. In this state, the refrigerated dryer will operate according to predefined safety policies, such as stopping after 5 minutes of continuous operation or maintaining minimum cooling power and issuing an alarm. Simultaneously, it will notify other devices of this situation via the CAN bus, and the desiccant dryer can adjust its regeneration strategy upon receiving the notification.

[0028] System Reconfiguration: If the refrigerated dryer itself is a protocol gateway and fails, the system's preset backup gateway, such as the desiccant dryer, will attempt to take over the communication tasks with the RS485 air compressor. This mechanism ensures that the system degrades rather than completely collapses when some devices or communication links fail, greatly improving availability.

[0029] This solution also boasts strong compatibility. The refrigerated air dryer is additionally equipped with an RS485 interface. When it needs to connect to a traditional air compressor that only supports the RS485 Modbus protocol, its internal protocol conversion gateway program is activated. This program obtains data from the traditional air compressor through RS485 polling, then encapsulates it into a standard CAN message and broadcasts it to the bus, allowing the traditional equipment to seamlessly integrate into the distributed system and effectively improving compatibility. When connecting a traditional air compressor that only has an RS485 interface, there is no need to modify the air compressor itself. This design greatly enhances the practicality and market adaptability of the system. It allows users to gradually upgrade the system, protect existing investments, solve the problem of integrating new technologies with old equipment, and lower the implementation threshold.

[0030] The system startup process is as follows: When the user starts the air compressor, its intelligent controller will immediately broadcast a status frame containing data such as its device ID, operating status "started", and current operating frequency to the network via the CAN bus; the controllers of the refrigerated dryer, desiccant dryer, and oil remover continuously listen to the CAN bus; once the "started" status frame of the air compressor is parsed, they will not act immediately, but will start autonomously in sequence according to the internally preset startup logic order, such as: refrigerated dryer → oil remover → desiccant dryer, and their delay parameters.

[0031] This process achieves masterless scheduling. Traditional systems require the main controller to issue start commands one by one, while this system relies on the status awareness and autonomous decision-making between devices to eliminate the risk of single point of failure of the main controller. Even if a post-processing device such as the oil separator temporarily fails, it will not affect the start-up and operation of the air compressor and other devices such as the refrigerated dryer or desiccant dryer, thus significantly improving the system reliability.

[0032] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims.

Claims

1. A decentralized air compressor control system, comprising an air compressor and a post-processing equipment group connected to the air compressor, characterized in that: The air compressor and each post-processing device in the post-processing equipment group are equipped with a standard CAN communication interface; the air compressor and each post-processing device are directly connected through the CAN bus to form a masterless distributed control architecture; the post-processing device is configured to acquire the operating status data of the air compressor in real time through the CAN bus, and autonomously adjust its own operating parameters based on preset control logic to achieve coordinated operation with the air compressor.

2. The decentralized air compressor control system according to claim 1, characterized in that: The post-processing equipment group includes at least one of a refrigerated dryer, an oil remover, an adsorption dryer, and a filter; The operating status data of the air compressor includes at least one of start / stop status, operating frequency, and real-time gas production; the adjustment of the operating parameters includes at least one of start / stop sequence control, load adjustment, module activation quantity control, and adsorption time control.

3. The decentralized air compressor control system according to claim 2, characterized in that: The refrigerated dryer in the post-processing equipment group is configured to dynamically adjust its cooling capacity according to the real-time air output of the air compressor using a PID algorithm.

4. The decentralized air compressor control system according to claim 2, characterized in that: The oil separator in the post-processing equipment group is configured to dynamically adjust the number of its internal modules activated based on a fuzzy control algorithm according to the real-time air output of the air compressor.

5. The decentralized air compressor control system according to claim 2, characterized in that: The adsorption dryer in the post-processing equipment group is configured to calculate the cumulative processing capacity based on the real-time gas output of the air compressor, its own inlet temperature, and operating temperature, and dynamically adjust its adsorption time based on the cumulative value.

6. The air compressor system according to any one of claims 1 to 5, characterized in that, The system also includes a drain valve installed on the post-processing equipment; the drain valve is configured to dynamically adjust its draining frequency according to the real-time air output of the air compressor or the overall operating status of the system.

7. The decentralized air compressor control system according to claim 1, characterized in that: At least one post-processing device is also equipped with an RS485 communication interface; the post-processing device is configured to establish a communication connection with an air compressor that only has an RS485 interface through the RS485 communication interface, and to share the acquired air compressor data with other devices in the system through the CAN bus.

8. The decentralized air compressor control system according to claim 1, characterized in that, The system operates in the following steps: After the air compressor starts, it broadcasts its startup status via the CAN bus; each device in the post-processing equipment group detects the startup status of the air compressor via the CAN bus and starts autonomously according to a preset logical sequence; during operation, each post-processing device acquires the operating frequency or air production data of the air compressor in real time and adjusts its own load autonomously based on its own preset algorithm to match the operating conditions of the air compressor; after the air compressor stops, each post-processing device stops autonomously according to a preset logical sequence.

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