A method and system for optimizing ventilation in a poultry house based on a CAN bus

Abstract

The application discloses a kind of based on CAN bus's poultry house ventilation optimization method and system, it is related to poultry house environment control and ventilation automation technical field, including the communication network that central control node, environment monitoring node and execution equipment node are connected by twisted-pair CAN bus composition, in combination with the number of poultry, weight and rearing parameter, the target air exchange of each partition is exported by the environmental comprehensive correction factor including temperature deviation and ammonia concentration deviation calculation term;And according to rated frequency conversion into fan operating frequency set value, through CAN control message is issued to execution node drive actual ventilation equipment action;Dynamic comparison is carried out to ventilation instruction and actual state deviation, introduce frequency change slope limit and correction coefficient self-adaptive adjustment.The method is disclosed in the application, and unified communication and multi-factor ventilation demand calculation are carried out through CAN bus, realize poultry house environment accurate control, fan energy efficiency is promoted and continuously stable operation, significantly improve air quality and reduce breeding risk.

Description

Technical Field

[0001] This invention relates to the field of poultry house environmental control and ventilation automation technology, specifically a poultry house ventilation optimization method and system based on CAN bus. Background Technology

[0002] With the rapid development of modern large-scale farming, the environmental control of poultry houses has gradually evolved from traditional manual experience-based management towards automation and intelligence. As a core means of ensuring poultry health, growth rate, and production performance, the ventilation system's operation and control directly affect key ecological factors such as temperature, humidity, ammonia concentration, and airflow direction. Currently, poultry house ventilation equipment is generally equipped with fan frequency converters, air intake devices, and various air quality sensors, and is gradually introducing digital communication networks to achieve status monitoring and parameter adjustment. The CAN bus, widely used in industrial control, is favored by many poultry equipment manufacturers for interconnecting poultry house electromechanical equipment due to its advantages such as strong real-time performance, high anti-interference capability, and low cost. However, at present, most poultry house ventilation control still relies on simple on / off control driven by local measurement values ​​or fixed airflow curve adjustment, lacking the ability to respond precisely to the coupling relationships of multiple environmental factors and dynamic load demands.

[0003] Although existing poultry house ventilation management systems can collect parameters such as temperature and humidity and regulate fan output, they still have significant shortcomings in complex environmental conditions. Firstly, current technologies generally deploy sensors and control equipment separately, resulting in inconsistent data acquisition links, weak communication stability, and difficulty in maintaining long-term reliability in high-dust, high-humidity poultry house environments, as well as insufficient inter-device coordination. Secondly, most ventilation strategies are still based on single-parameter trigger adjustments (such as increasing fan speed when temperature exceeds limits), failing to fully consider the differences in actual ventilation needs caused by changes in poultry numbers and weight leading to respiratory metabolism and pollutant accumulation, especially lacking the ability to calculate load in real time based on ammonia concentration changes, resulting in weak control basis. Furthermore, existing ventilation outputs mostly use fixed frequency or simple proportional control, lacking a matching mechanism for differences in the rated airflow of ventilation equipment, failing to achieve a precise mapping between target ventilation volume and equipment capacity, and posing a risk of both increased energy consumption and insufficient ventilation. Finally, most existing technologies use open-loop or weak closed-loop regulation, lacking the ability to handle abnormal operating conditions such as the actuator failing to reach the set value or sensor offline, leading to accumulated deviations or even failure in environmental control. Summary of the Invention

[0004] In view of the above-mentioned problems, the present invention is proposed.

[0005] Therefore, the technical problem solved by this invention is that existing poultry house ventilation control methods suffer from inconsistent communication links that are easily interfered with, overly coarse estimation of ventilation demand and lack of multi-factor coupling calculations such as ammonia, insufficient matching between ventilation equipment operation and load capacity, lack of a sound adaptive handling mechanism for anomalies and faults, and the problem of how to achieve precise and highly reliable dynamic control of ventilation in harsh breeding environments.

[0006] To address the aforementioned technical problems, this invention provides the following technical solution: a CAN bus-based method for optimizing poultry house ventilation, comprising constructing a communication network within the poultry house consisting of a central control node, an environmental monitoring node, and execution device nodes connected by a twisted-pair CAN bus; collecting environmental data based on sensor units; combining poultry numbers, weights, and feeding parameters, outputting the target air exchange rate for each zone through an environmental comprehensive correction factor including temperature deviation and ammonia concentration deviation calculation items; obtaining the fan frequency ratio through the target air exchange rate, converting it into a fan operating frequency setpoint based on the rated frequency, and sending it to the execution node via CAN control messages to drive the actual ventilation equipment operation; receiving environmental monitoring feedback and fan operation feedback, dynamically comparing the deviation between ventilation commands and actual states, introducing frequency change slope limits and adaptive adjustments of correction coefficients, and implementing fault judgment and ventilation capacity compensation strategies for sensor node heartbeat loss and fan operation abnormality nodes.

[0007] As a preferred embodiment of the CAN bus-based poultry house ventilation optimization method described in this invention, the central control node connected by the twisted-pair CAN bus includes a twisted-pair CAN bus with a twisted-pair backbone topology, terminating resistors at both ends of the bus, and each node connected to the network via an industrial-grade CAN transceiver; the nodes use a 24V industrial power input and are configured with DC-DC isolation circuits and surge protection and electromagnetic interference suppression circuits; both environmental monitoring nodes and execution device nodes are equipped with unique address encoding fields, and the CAN message ID includes the device type, area number, and node sequence number; monitoring data messages and control command messages are sent periodically according to a standardized frame format; the central control node maintains node linearity management and communication health monitoring based on heartbeat frame parsing.

[0008] As a preferred embodiment of the CAN bus-based poultry house ventilation optimization method described in this invention, the environmental monitoring node includes a temperature and humidity digital acquisition unit, an electrochemical ammonia acquisition unit, an infrared carbon dioxide acquisition unit, and a differential pressure acquisition unit, and is connected to a microcontroller via I²C, UART, and analog acquisition interfaces; the monitoring node performs filtering, calibration, and out-of-bounds rejection on the acquired data, and encodes the temperature, humidity, gas concentration, and negative pressure data into a CAN frame for transmission after encoding them with a uniform byte length; the central control node performs data fusion processing on the measured data within the same area, and obtains representative environmental values ​​for each area through invalid value discrimination and averaging strategies.

[0009] As a preferred embodiment of the CAN bus-based poultry house ventilation optimization method described in this invention, the following steps are taken: The target ventilation volume for each zone is output by combining the number of poultry, their weight, and feeding parameters, through an environmental comprehensive correction factor that includes calculations for temperature deviation and ammonia concentration deviation. This includes the environmental status parameters and feeding parameters maintained internally by the central control node, including zone temperature, ammonia concentration, number of poultry, average weight, basic ventilation reference volume, temperature setpoint, ammonia reference upper limit, and correction adjustment parameters. The central control node calculates ventilation demand at fixed time intervals, determines the environmental correction amount based on temperature deviation and ammonia exceedance, and then combines the number and weight of poultry in each zone to obtain the total ventilation volume for the target zone.

[0010] As a preferred embodiment of the CAN bus-based poultry house ventilation optimization method described in this invention, the step of sending CAN control messages to the execution nodes to drive the actual ventilation equipment includes the central control node calling the equipment parameter table to determine the total rated air volume of each zone's fans, and determining the fan operating frequency and air inlet device opening setting value according to the target ventilation volume; the central control node implements minimum and maximum allowable range limits on the setting value, and sets the change step size and change slope; the setting value is scaled and filled into the CAN control message and then sent to the corresponding execution node, so that the fan driver and air inlet drive component run according to the setting value.

[0011] As a preferred embodiment of the CAN bus-based poultry house ventilation optimization method described in this invention, the following steps are taken: receiving environmental monitoring feedback and fan operation feedback; dynamically comparing the deviation between ventilation commands and actual states; introducing frequency change slope limits and adaptive adjustment of correction coefficients; and implementing fault judgment and ventilation capacity compensation strategies for sensor node heartbeat loss and fan operation abnormality nodes. This includes the central control node continuously comparing the deviation between real-time environmental feedback parameters and fan feedback states. When temperature and ammonia concentration deviate from the target range, the adjustment coefficient of the corresponding environmental factors in ventilation demand is increased. When the actual equipment feedback does not meet the set requirements, the central control node executes compensation adjustment and refresh frequency acceleration strategies, and sets an upper limit for the single-cycle adjustment amount.

[0012] As a preferred embodiment of the CAN bus-based poultry house ventilation optimization method described in this invention, the following steps are implemented: receiving environmental monitoring feedback and fan operation feedback; dynamically comparing the deviation between ventilation commands and actual states; introducing frequency change slope limits and adaptive adjustment of correction coefficients; and implementing fault judgment and ventilation capacity compensation strategies for sensor node heartbeat loss and fan operation abnormality nodes. This includes the central control node judging communication faults of environmental monitoring nodes by counting lost heartbeat frames, and using a neighborhood environmental parameter interpolation strategy to supplement data when monitoring node data is missing. When the execution equipment feedback is abnormal or the action fails, the central control node marks the action as abnormal, starts a backup fan according to the equipment redundancy configuration strategy, and appropriately adjusts the air intake direction and opening to maintain ventilation capacity within a safe operating range, while recording the fault event.

[0013] Another objective of this invention is to provide a CAN bus-based poultry house ventilation optimization system that can obtain the fan frequency ratio through the target air exchange rate, convert it into the fan operating frequency set value based on the rated frequency, and send it to the execution node through CAN control messages to drive the actual ventilation equipment to operate. This solves the problem of insufficient matching between ventilation equipment operation and load capacity in current poultry house ventilation control methods.

[0014] As a preferred embodiment of the CAN bus-based poultry house ventilation optimization system described in this invention, it includes: a data sensing module, a demand calculation module, and a closed-loop control module; the path planning module is used to construct a CAN-based communication network to collect poultry house zone temperature, gas concentration, and negative pressure environment data, and to perform data fusion and effectiveness processing; the PID control module is used to determine the target ventilation volume for each zone based on environmental parameters and feeding information, and to convert monitoring data into ventilation control quantities; the smoothing module is used to issue fan and air intake action commands and to perform deviation correction, fault judgment, and ventilation capacity compensation based on feedback.

[0015] A computer device includes a memory and a processor, the memory storing a computer program, the processor executing the computer program to implement a CAN bus-based method for optimizing poultry house ventilation.

[0016] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of a CAN bus-based method for optimizing poultry house ventilation.

[0017] The beneficial effects of this invention are as follows: The poultry house ventilation optimization method based on CAN bus provided by this invention constructs a unified communication architecture based on a twisted-pair CAN bus for a central control node, environmental monitoring nodes, and execution device nodes. This achieves real-time interaction between environmental data acquisition and ventilation execution commands on the same industrial-grade anti-interference communication link, ensuring the stability of data transmission and the synchronization of equipment linkage in high-dust and high-humidity environments in poultry houses. Regarding ventilation demand calculation, this invention proposes a strategy that uses the number and weight of poultry as the load basis, combined with comprehensive environmental correction based on temperature deviation and ammonia concentration deviation, to obtain the target air exchange rate. This allows ventilation regulation to no longer rely on a single temperature trigger logic, but can dynamically match changes in poultry metabolism and ammonia accumulation, improving the consistency between ventilation decisions and actual breeding needs. At the execution layer, this invention accurately maps and sets parameters for fan operating frequency and air inlet opening based on the target air exchange rate, effectively avoiding the problem of unbalanced output from multiple fans or wasted ventilation capacity, improving fan utilization efficiency and energy consumption rationality. Furthermore, this invention introduces a dual-channel feedback mechanism involving both environment and equipment, progressively correcting ventilation deviations over continuous cycles. It also features online detection and compensation capabilities for sensor malfunctions and fan abnormalities, giving the system strong stable operation and self-recovery capabilities. Therefore, this invention can continuously maintain poultry house air quality within a suitable range under varying environmental loads, significantly improving the accuracy, reliability, and operational safety of ventilation control. Attached Figure Description

[0018] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 The first embodiment of the present invention provides an overall flowchart of a CAN bus-based method for optimizing poultry house ventilation. Detailed Implementation

[0020] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.

[0021] Example 1, referring to Figure 1 As one embodiment of the present invention, a method for optimizing poultry house ventilation based on a CAN bus is provided, comprising: S1: Construct a communication network within the poultry house, consisting of a central control node, an environmental monitoring node, and an execution device node connected by a twisted-pair CAN bus, and collect environmental data based on sensor units.

[0022] Furthermore, a CAN bus-based ventilation control communication network was constructed within the poultry house. Twisted-pair cable was used as the physical medium for the CAN bus, with a trunk series topology. 120Ω matching terminating resistors were installed at both ends of the poultry house to ensure consistent bus impedance. The bus cabling was laid along the overhead racks or dedicated cable trays on the side walls of the poultry house, avoiding long-distance parallel laying with high-voltage power lines. Communication lines crossed perpendicularly with power lines. The bus length was controlled within the CAN standard's recommended range based on the poultry house structure. Continuity, impedance, and insulation tests were performed after cabling was completed.

[0023] Sensor nodes need to be installed in the poultry house to collect environmental parameters such as temperature, humidity, ammonia concentration, carbon dioxide concentration, and negative pressure. Each sensor node includes an MCU, a CAN controller, a CAN transceiver chip, a power conversion circuit, and corresponding sensor components. All nodes are powered by a unified 24V industrial power supply and are locally DC-DC isolated. Each node has a unique and fixed CAN node address, which is configured via a DIP switch or flash memory preset. The node address encoding uses a combination of partition number and node serial number for easy identification.

[0024] Actuation nodes are installed in different ventilation zones of the poultry house to control the frequency conversion of fans, the opening degree of air inlets, and the start and stop of evaporative cooling pumps. Each actuation node is internally equipped with an MCU, CAN transceiver, power drive interface, and motor control interface. Fan control uses standard Modbus-RTU to CAN conversion or directly sends frequency setpoints to the frequency converter in a combined analog-digital format. Air inlet control outputs the opening position via a motor drive with a feedback encoder. The drive interface and the actuator are connected by an independent cable with proper moisture-proof and insulation treatment.

[0025] A central control node is deployed in the poultry house ventilation management area. This node contains a high-performance MCU or industrial control motherboard, integrating a CAN bus transceiver interface and storage unit for message parsing, data distribution, and control command calculation. An opto-isolated transceiver is used between the central control node and the field CAN bus to resist electromagnetic interference in the high humidity and strong induction environment of the poultry house. The central node is equipped with a UPS backup power interface to support communication maintenance and parameter storage during power outages.

[0026] It should be noted that the CAN bus communication layer adopts the standard CAN2.0B protocol, with a baud rate uniformly set to 250kbps. This parameter is written to all slave nodes via a configuration message broadcast by the master node. Communication uses an 11-bit standard frame ID encoding method, defining a three-level encoding structure of device type, address, and function code. The device type distinguishes between sensor nodes, execution nodes, and the central node; the address field corresponds to a unique node number; and the function code indicates whether the current frame is for data reporting, parameter setting, or operational status feedback. All nodes send heartbeat frames according to a set period, with the frame content including the node ID and operational status bits. The communication protocol includes a frame loss identification mechanism; for example, if no message is received from a node for three consecutive heartbeat cycles, the central node records it as a communication anomaly.

[0027] Each sensor node's internal MCU is responsible for acquiring sensor ADC data or reading digital communication data. Parameters such as temperature, humidity, gas concentration, and negative pressure are scaled and encoded before being written into the CAN data segment, using a fixed-length frame structure for easy parsing by the central node. Data unit conversion rules are maintained in a unified table at the central node; the nodes only perform simple calculations, reducing network load and node computational pressure.

[0028] The central control node is responsible for caching all data frames from sensor nodes and execution nodes, mapping them to partition management data structures based on the node ID table, and applying a unified timestamp via a local clock. Status information from each execution node, such as fan speed feedback, drive current value, and inlet window position value, is reported periodically via dedicated status frames. The central node maintains a real-time node list in memory for dynamically recording device linearity and communication health.

[0029] To ensure data transmission reliability in the high humidity, high dust, and high electromagnetic interference environment of poultry houses, all CAN transceivers use low-temperature resistant and enhanced EMI-immune chips; TVS diodes are added to segmented bus traces to absorb surges; LC filter networks are added to the power input terminals of nodes; and all communication connections are sealed with industrial waterproof connectors. The node housing is made of corrosion-resistant materials and has a stress-relieving structure for cable outlets.

[0030] Furthermore, multiple environmental monitoring nodes are arranged inside the poultry house. Each node includes digital temperature and humidity sensors, ammonia detection sensors, carbon dioxide detection sensors, a differential pressure measurement unit, a microcontroller, a CAN controller, a CAN transceiver circuit, a power conversion circuit, and a mounting bracket. The temperature and humidity sensors use chip-type digital probes with compensation mechanisms, connected to the microcontroller via an I²C interface. The ammonia sensor uses an electrochemical gas detection component, connected to the microcontroller's internal ADC channel via an analog signal input. Carbon dioxide detection uses an NDIR non-dispersive infrared module, connected to the microcontroller via UART serial communication. The differential pressure acquisition component uses a differential pressure sensor with a range of 0 to ±200 Pa, connected to the node's internal analog acquisition circuit via a shielded cable. All sensing units are installed inside a small, breathable, dustproof, and moisture-proof housing, with a removable protective mesh for easy periodic maintenance.

[0031] Each monitoring node is powered by a 24V industrial power input, which is converted by DC-DC to 12V and 5V regulated outputs to supply the sensors and microcontrollers respectively. A TVS transient suppressor and LC filter circuit are configured at the node input to reduce surges and interference generated by the poultry house motors. The node housing is made of corrosion-resistant ABS or metal-coated material, with an aluminum heat sink embedded on the back for heat dissipation during long-term operation.

[0032] The microcontroller at the monitoring node periodically triggers data acquisition tasks, with an acquisition cycle set to 5 seconds. Internally, it runs a calibration algorithm to perform offset compensation and filtering on the sensor data. After digitizing parameters such as temperature, humidity, ammonia concentration, carbon dioxide concentration, and negative pressure, the measured values ​​are converted to scaled integer formats, such as temperature expressed in 0.1℃ units, humidity in 1% accuracy units, gas concentration in ppm integers, and negative pressure in Pa. The data is then written to a fixed byte address in the CAN data segment via a parameter packaging program, maintaining a consistent byte order and type encoding for each field.

[0033] It should be noted that CAN communication adopts the ISO11898 standard wiring method. In the communication link, the CAN transceiver chip of the monitoring node is connected to the external CAN bus through an opto-isolator. The bus is laid with twisted-pair shielded cable, and the cabling is arranged in a trunk series according to the overall layout of the poultry house. The cable is covered with a flame-retardant protective layer to adapt to the high humidity and high corrosion environment of the poultry house. The bus baud rate is set to 250kbps. The CAN controller is configured with the number of transmission retries, arbitration delay, and timeout parameters. The node transmission queue adopts a priority scheduling strategy, arranging environmental data frames after heartbeat frames.

[0034] The environmental data frames sent by the monitoring nodes use an 11-bit standard frame ID, which distinguishes device type, area number, node sequence number, and function category through field encoding. The transmission cycle is 5 seconds, and the incrementing frame counter and local time counter are updated with each transmission, allowing the central control node to analyze data validity based on time series during parsing. If a monitoring node fails to receive the arbitration signal or experiences a transmission failure, it will automatically retransmit in the next cycle, while simultaneously recording the error count in memory for maintenance purposes.

[0035] The central control node continuously listens for bus messages via the CAN transceiver interface and parses environmental parameter data frames and heartbeat frames separately. Internally, the central node maintains a node mapping table, writing the region number, node sequence number, and collected data carried in each frame into the corresponding buffer. The data management program stores the most recent sets of collected values ​​in a cyclic overwrite manner, while also incorporating CRC checks and out-of-bounds judgments, marking abnormal collected values ​​(such as negative values ​​or values ​​exceeding a set range) as invalid. Every second, the central node counts and compares the heartbeat frames of all monitored nodes; if no heartbeat frame is detected for a node within a specific consecutive counting threshold, the node is marked as offline.

[0036] In areas with harsh poultry house environments, a transparent protective sleeve is used to encapsulate the sensor probe to prevent bird droppings, dust, and moisture from directly covering the sensitive components. Monitoring nodes are arranged according to the principle of equidistant spacing, with a height of 30-60cm above the poultry to avoid direct contact and ensure representative air sampling. Sensor cables use connectors with a seven-day immersion resistance rating, and the inlet uses a rubber-pressed stress-relief structure to prevent breakage due to vibration.

[0037] S2: Combining poultry numbers, weight, and feeding parameters, the target ventilation rate for each zone is output through an environmental comprehensive correction factor that includes calculations for temperature deviation and ammonia concentration deviation.

[0038] Furthermore, a ventilation demand calculation program is pre-programmed into the central control node, and this program runs continuously after power-on. The central control node continuously receives data frames from environmental monitoring nodes via the CAN communication interface, writing the area number, node number, temperature, ammonia concentration, and other fields carried in each data frame into the environmental data buffer in its internal RAM. The environmental data buffer is indexed according to the poultry house's physical zoning numbers, with each zoning corresponding to a recording unit. Each recording unit includes the latest temperature value, ammonia concentration value, and sampling timestamp from several monitoring nodes. For multiple temperature values ​​within the same zoning, the central control node iterates through the recording units, eliminating outliers. For example, if the temperature value of a node differs from the temperature values ​​of other nodes in the same zoning by more than a preset threshold, that value is marked as invalid and not included in the averaging calculation. After eliminating outliers, the remaining valid measurements are arithmetically averaged to obtain the current representative temperature value for that zoning, and this value is written into the corresponding temperature field in the zoning environmental status table.

[0039] The processing of ammonia concentration data is similar to that of temperature. Data sets are established by zone, and faulty or obviously unreasonable data is filtered out through boundary checks and data jump judgments. The filtered ammonia concentration values ​​are then averaged to obtain the representative ammonia concentration value for that zone and saved to the ammonia field of the zone's environmental status table. In addition to real-time temperature and ammonia concentration, the zone's environmental status table also stores information such as the number of poultry, average weight per bird, basic ventilation rate, target comfort temperature, upper limit of ammonia reference, temperature correction factor, ammonia correction factor, and temperature difference normalization parameters. These static parameters are written uniformly during equipment installation and commissioning via an external configuration terminal or host computer and stored in the non-volatile memory of the central control node. During operation, these parameters are read from this memory and loaded into RAM for use by the calculation program.

[0040] The ventilation demand calculation program is triggered at fixed time intervals, such as 30 seconds per calculation cycle. At the beginning of each calculation cycle, the program sequentially reads the real-time temperature, ammonia concentration, target comfort temperature, ammonia reference upper limit, and corresponding correction coefficients and temperature difference normalization parameters for each zone from the zone's environmental status table. It first calculates the comprehensive environmental correction factor, expressed as:

[0041] in, This indicates the ventilation zone number, used to identify different physical areas within the poultry house; For the first Comprehensive environmental correction factor for each zone; For the first The current temperature value represented by the partition is obtained by averaging data collected by the temperature sensors within that partition. The target comfort temperature for the corresponding feeding stage in this zone is stored in the parameter configuration area; This is a temperature normalization reference difference used to compress the numerical scale of temperature deviations; it is usually set to 3 to 5 during debugging. This is a temperature correction factor; For the first The current zone represents the ammonia concentration, which is obtained through ammonia sensor data acquisition and averaging. This is the upper reference concentration for ammonia, corresponding to the recommended limit in the feeding standards. This is the ammonia correction factor.

[0042] It should be noted that after the central control node completes the calculation of the comprehensive environmental correction factor for each zone, it will... The target ventilation volume for a given zone is calculated by combining the number of poultry, average weight per bird, and basic ventilation coefficient. The number of poultry can be entered by the feeding management system during batch feeding or flock transfer, or manually after inventory. The average weight per bird can be updated every few days based on sampling weighing results during actual operation. The basic ventilation coefficient is determined during the commissioning phase based on feeding guidelines or empirical trials. The ventilation demand calculation program uses the following formula to calculate the target ventilation volume:

[0043] in, For the first The target ventilation rate for a zone is used to characterize the total ventilation required for that zone under the current feeding conditions and environmental conditions. For the first Number of poultry within the zone; The average weight of each bird; The basic ventilation volume coefficient represents the baseline ventilation volume per kilogram of body weight under standard environmental conditions.

[0044] Write the calculation results into the target air exchange rate field of the zone ventilation demand table, and apply safety upper and lower limit constraints in the program. Within the numerical range allowed by equipment capacity and feeding safety, any excess is handled through truncation.

[0045] After the calculation is completed, the ventilation demand table for each zone saves the target ventilation volume for the current moment. The central control node uses this table as a basis to convert the target ventilation volume into the fan frequency set value and the air inlet opening set value in the subsequent control process, and periodically updates the contents of the table according to the new sensor data, so that the ventilation control process can continuously track the changes in the poultry house environment and feeding parameters.

[0046] S3: Obtain the fan frequency ratio through the target air exchange volume, convert it into the fan operating frequency set value based on the rated frequency, and send it to the execution node through CAN control message to drive the actual ventilation equipment to operate.

[0047] Furthermore, after completing the calculation of the ventilation demand for each zone, the central control node writes the target air exchange rate value for each zone into a zone ventilation demand table stored in RAM. To adjust the ventilation equipment, the central control node pre-establishes a ventilation equipment parameter table in its storage unit. This parameter table records information such as the equipment number, rated air volume, rated operating frequency, operating status feedback address, and execution node communication address for all fans in each zone. During each ventilation calculation cycle, the central control node calls the equipment parameter table to calculate the... The rated air volume values ​​of all working fans within a zone are summed to determine the total air volume capacity of that zone. The rated air volume values ​​of the equipment are entered and stored during the equipment installation and commissioning phase based on the parameters on the equipment nameplate or on-site test results.

[0048] The central control node calculates the operating frequency ratio of the zoned fans based on the ratio between the target air exchange rate and the sum of the rated air volume. When using this ratio, the central control node employs a linear approximation, treating the actual air output of the fans as directly proportional to the output frequency. To avoid calculation complexity due to differences in the capacity of individual fans, the central control node uses a uniform frequency ratio control method for multiple fans within the same area. The fan frequency ratio is expressed as:

[0049] in, For the first The frequency ratio of the fans in the zone is a dimensionless real number, representing the ratio coefficient between the actual operating frequency and the rated frequency. For the first The sum of the rated air volume of all fans within a zone is obtained by summing the rated air volume parameters of the fans in the equipment parameter table.

[0050] The central control node uses floating-point or fixed-point division operations during execution, and sets upper and lower limit constraints. When the operating ratio is less than the preset minimum allowable ratio, The cutoff value is set to the minimum allowable value to ensure that the fan does not enter a stall state; when When the operating ratio exceeds the maximum, limit it to the maximum value range to ensure that the equipment operates within the permissible operating conditions.

[0051] After obtaining the fan frequency ratio Then, the central control node converts it into the actual frequency setpoint through multiplication and writes it into the wind turbine setting parameter table. Let the rated operating frequency of the wind turbine be... The central control node then calculates the target frequency setpoint for the fan according to the following formula:

[0052] in, For the first The target operating frequency for the fans in each zone is set. This is the fan frequency ratio value after upper and lower limit processing. The target ventilation demand is converted into a control variable usable by the execution nodes. The central control node calculates and then... Write to the fan control data area.

[0053] To control the actuators, the central control node generates control messages according to the CAN address and function code configuration of each zone's fan actuator node, following the actuator node identification sequence. The control message contains the corresponding... The numerical values ​​are converted to integer data using a fixed scaling factor and placed into the CAN data field to ensure that the data transmission format is consistent with the parsing rules of the execution node. The message ID adopts an encoding scheme in the form of device type, area number, and node number. Fan control command messages are separated from sensor data messages so that ventilation adjustment commands are prioritized during bus arbitration.

[0054] After receiving control commands from the central control node, the execution node writes the target frequency setpoint from the message into the frequency setting register of its local frequency inverter. Some execution nodes support a feedback mechanism, sending a status feedback frame back to the central control node after execution. The central control node compares the fan feedback value with the setpoint. If the deviation is outside the set range for several consecutive cycles, the central control node invokes safety adjustment strategies, such as increasing the output frequency refresh rate or adjusting the signal change slope, to ensure a smooth frequency change process.

[0055] For poultry houses with strict requirements for airflow and negative pressure linkage within the same area, the central control node, in addition to setting the fan frequency, can further calculate the inlet opening adjustment and issue it for execution via independent control messages. The inlet control logic uses the area negative pressure measurement value as feedback. When the central control node detects that the area negative pressure deviates too much from the preset reference value, it will adjust the opening output appropriately. However, the specific actions of the following logic are not expressed using mathematical formulas, but rather using internally written opening adjustment curves or gear control tables to ensure reliable adjustment actions and easy equipment adaptation.

[0056] After each wind turbine control command is issued, the central control node retains the current control command and the feedback status of the execution node, and records the data to the operation log buffer. The buffer adopts a cyclic overwrite mechanism to save the control variable change trend of the most recent few hours, so that subsequent analysis, debugging and verification have data traceability and process traceability.

[0057] S4: Receives environmental monitoring feedback and fan operation feedback, dynamically compares the deviation between ventilation commands and actual conditions, introduces frequency change slope limits and correction coefficients for adaptive adjustment, and executes fault judgment and ventilation capacity compensation strategies for sensor node heartbeat loss and fan operation abnormality nodes.

[0058] Furthermore, after issuing the ventilation command, the central control node continuously receives status messages from the environmental monitoring nodes and execution device nodes via the CAN bus, parses the message content, and writes it into the real-time operating status buffer. This buffer maintains the latest environmental parameter records for each zone and the execution status records for each fan and air intake mechanism. The buffer uses a chained structure to store the timestamp and actual collected value for each sample. The central control node internally sets a timer to periodically read these status data and compare them with the latest set control values.

[0059] For environmental parameter feedback, the central control node reads real-time values ​​such as temperature, ammonia concentration, and negative pressure from the zone environmental status table and compares them with the target environmental parameter range corresponding to the commands issued in the previous control cycle. If the temperature of a zone exceeds the preset maximum temperature limit, the central control node invokes the internal ventilation increment adjustment logic to increase the fan frequency ratio of the corresponding zone by a predefined increment value. The updated frequency setting value is then reissued to the execution node in a newly generated control message to shorten the temperature response time. Regarding ammonia concentration feedback, when a representative concentration is detected to exceed the ammonia reference limit, the central control node temporarily raises the ammonia correction parameter to a higher sensitivity level to further increase ventilation volume in the next cycle's ventilation calculation. Furthermore, for negative pressure parameters, when the negative pressure of a zone is detected to be lower than the preset minimum target value, the central control node automatically triggers the opening expansion logic. This increases the air supply by reducing the fan frequency increase or instructing the air intake mechanism to increase its opening, preventing insufficient ventilation efficiency due to excessively low negative pressure.

[0060] In the equipment feedback section, the central control node parses the actual operating frequency, drive current, speed feedback values, or status flags of the fans transmitted back from the execution nodes. When the actual operating frequency deviates from the set value beyond the allowable error range, the central control node records the equipment as an abnormal deviation state and repeatedly issues commands, gradually increasing the output command refresh frequency as needed to accelerate equipment adjustment. If the deviation fails to converge after multiple consecutive cycles, the central control node invokes the equipment parameter compensation mechanism to introduce additional frequency compensation for that zone, thereby maintaining overall ventilation capacity without relying on local equipment feedback. Simultaneously, for feedback from the air intake mechanism, if the executed position is detected as not reaching the target position, the central control node rewrites the position command into the execution queue and continuously monitors the feedback value to prevent control loss.

[0061] The central control node maintains a set of adjustable correction parameters, including temperature correction coefficient, ammonia correction coefficient, minimum frequency limit, and maximum frequency increment step. When the environment of a certain zone deviates from the target range for an extended period, such as excessively high temperatures for multiple consecutive control cycles, the central control node activates adaptive parameter adjustment logic to adjust the temperature correction coefficient for that zone. The temperature deviation is increased in a fixed increment, thus giving it greater weight in subsequent calculations and automatically tightening the temperature control strategy. Similarly, when an ammonia concentration is detected to be increasing periodically, the ammonia correction factor is adjusted. Within a limited range, the influence of ammonia in the ventilation demand calculation is temporarily increased to enhance gas dilution. After the correction factor is adjusted, the central control node writes the changed parameters to the current RAM usage area, but it does not immediately harden them to non-volatile memory. Instead, it performs short-term observation first, and then determines whether a long-term correction is needed after the trend stabilizes.

[0062] To avoid the physiological impact of drastic fluctuations on poultry, the central control node incorporates slope constraint logic in all adjustment executions. Specifically, within two adjacent control cycles, the operating frequency is set for the target wind turbines in the same zone. The change in frequency must not exceed the preset maximum frequency transition, for example, no more than 10% of the rated frequency. When the updated setting exceeds this upper limit, the central control node will cut it off at the maximum allowable change and delay the remaining change to subsequent cycles, thus ensuring that frequency adjustment is carried out gradually. Similarly, in the control of the air inlet position, the change in opening is limited to the maximum displacement angle range in a single cycle to keep the actuator operating smoothly.

[0063] The central control node logs all adjustment actions. The logs include fields such as timestamps, control input values, actual feedback values, deviation judgment results, and parameter adjustment behaviors. The log data uses a cyclic overwrite structure, retaining a certain number of the most recent records. Maintenance personnel can read the log content through the host computer interface for subsequent debugging, verification, and mechanical equipment performance evaluation.

[0064] Through the above closed-loop adjustment process, the central control node continuously and dynamically corrects the ventilation output based on environmental and equipment feedback, and records the adjustment process and parameter changes, making the operation process dynamically traceable and maintainable.

[0065] It should be noted that during operation, the central control node continuously receives heartbeat and status feedback messages from the environmental monitoring and execution nodes via CAN bus listening. The central control node maintains a node online information table in its internal RAM, recording the past heartbeat reception timestamps and the timestamp of the latest status message for each node. The node online information table uses a sliding window counting structure, setting a consecutive heartbeat loss count for each node. When the number of consecutive missing heartbeats reaches a set threshold, the node is marked as having a communication anomaly. After marking, the central control node writes the node ID to the communication fault queue for reference by both the communication maintenance program and the ventilation control program.

[0066] For environmental monitoring nodes experiencing communication anomalies, the central control node retains the last valid data collected by that node in the original zonal environmental status table, while simultaneously freezing the validity flag of that data to prevent it from participating in the calculation of the zonal representative value. During the environmental data fusion process, when some or all environmental monitoring nodes in a zonal are offline, the central control node activates environmental parameter interpolation logic. This interpolation logic uses data from valid monitoring nodes in neighboring zonals as a reference, performing a weighted average based on physical distance or airflow direction to obtain the immediate replacement parameter value for that zonal. Simultaneously, to avoid numerical jumps introduced by interpolation, the central control node imposes a limit on the variation of the interpolation results, ensuring that the change per cycle does not exceed a preset maximum offset, thereby ensuring that the data used for subsequent ventilation demand calculations remains stable and controllable.

[0067] For fault diagnosis of execution nodes, the central control node parses the status feedback frames returned by the execution nodes, checking the fan operating status bit, encoder position feedback bit, drive current feedback, and operating alarm flag bit, etc. When the feedback value indicates that the equipment is not executing the control commands issued by the central control node, such as when the actual operating frequency is consistently lower than [a certain value], [further details are needed]. If the error exceeds the set error range, or if the actual opening position remains unchanged, the central control node will mark the execution node as having an abnormal operation. If an abnormal increase in current or an internal equipment fault alarm occurs simultaneously, the status will be escalated to an equipment fault state, and the node will be immediately added to the equipment fault queue and the fault response process will be triggered.

[0068] In the fault response process, the central control node first broadcasts a fault information message on the CAN bus, writing the faulty equipment type, equipment number, and its zone code into the message data segment, allowing on-duty personnel to be promptly notified via the host computer or alarm device. Subsequently, the central control node enters the ventilation capacity compensation logic, increasing the frequency of the remaining fans in the zone containing the faulty equipment by gradually raising their frequency setpoints to the maximum permissible operating range at a fixed ratio. If a backup fan exists in the equipment parameter table for that zone, the central control node can send an activation command to the backup fan to ensure minimal ventilation capacity deviation. To prevent the deterioration of local negative pressure distribution and disruption of airflow organization, the central control node simultaneously issues an opening adjustment command to the air intake devices in that zone, making the airflow supply direction more uniform. Under multi-equipment failure conditions, the central control node prioritizes ensuring the ventilation capacity of the core area of ​​the poultry house, compressing the ventilation volume in the peripheral areas as necessary, but not allowing the ventilation volume to fall below the basic safety threshold.

[0069] To ensure the continued accuracy of fault detection information, the central control node continues to receive status feedback frames from abnormal nodes after a fault is determined. When communication or equipment operation is restored within a certain number of consecutive cycles, the central control node reverts the fault state to normal operation and recalibrates the equipment performance parameters based on the control deviations recorded during the fault period. For example, for fan equipment exhibiting aging trends, the central control node will appropriately lower its rated airflow value or raise the minimum operating ratio value to automatically compensate for subsequent ventilation demand calculations. Performance parameter adjustments are first implemented in RAM and then synchronously hardened to non-volatile memory after stability is confirmed, to avoid unpredictable behavior caused by sudden parameter changes.

[0070] In fault or performance degradation management, the central control node continuously records relevant data, forming a fault event log table. This table includes complete fields such as fault identification time, node ID, equipment type, current environmental parameters, control deviation, compensation strategy type, and recovery process data. The log table is timestamped and stores data from the most recent few days in a circular queue, allowing maintenance personnel to access it at any time via a host computer to review changes in equipment operating status and provide a data foundation for predictive maintenance strategies.

[0071] Through this degradation control mechanism, even if some sensors or actuators fail, the central control node can still achieve adaptive recovery of ventilation capacity and safe and continuous operation, giving poultry house environmental management a strong fault tolerance and enabling long-term operational performance tracking.

[0072] Example 2, one embodiment of the present invention, provides a method for optimizing poultry house ventilation based on CAN bus. To verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation experiments.

[0073] First, an experimental area was selected in a single enclosed poultry house at a large-scale layer hen farm. The poultry house had an area of ​​approximately 1200 m² and was divided into three independent ventilation zones: A, B, and C. Each zone housed 600 80-day-old layer hens. The ventilation optimization system based on the CAN bus described in this invention was installed on-site, including one central control node, nine environmental monitoring nodes (three per zone, distributed at different locations in the front, middle, and rear), and six execution device nodes (two fans per zone). The monitoring nodes were networked using a twisted-pair CAN bus, powered by a 24V industrial power supply, and equipped with anti-vibration mounting brackets. Sensors collected environmental data such as temperature, ammonia concentration, and negative pressure, and uploaded them to the central control node every 10 seconds. The number of poultry, average weight, and target environmental parameters were pre-entered into the non-volatile memory of the central node.

[0074] The ventilation system was divided into two control groups: the control group used a traditional temperature-on-off ventilation strategy, where the fan only started and stopped when the temperature reached the upper limit and did not participate in zonal regulation; the experimental group applied the CAN bus centralized dynamic ventilation control method proposed in this invention, which independently calculated the real-time ventilation demand of each zone, and the control message was sent from the control node to the corresponding fan driver for execution. The experiment lasted for 7 days, and environmental parameter data, fan operating frequency, and poultry status monitoring were recorded daily for each zone.

[0075] During the trial operation, one morning, a communication interruption occurred at an environmental monitoring node at the rear of Zone A. The system automatically activated a neighboring monitoring data interpolation strategy, preventing amplification of system deviations. During this period, a fan drive belt slipped in Zone B, causing a decrease in operating efficiency. The system automatically identified the fan's operational deviation and increased the operating frequency of another fan in the same zone to maintain ventilation capacity above the safe threshold. During the afternoon when temperatures remained consistently high, the system employed a gradual fan frequency increase strategy, effectively reducing the impact of sudden wind speed changes on poultry comfort. Furthermore, when ammonia concentration increased, the ventilation volume automatically increased according to load adjustments. All operational statuses were logged in real time for easy traceability.

[0076]

[0077] As shown in Table 1, under the same climatic conditions and breeding scale, the experimental group implemented in this invention significantly outperformed the traditional strategy in terms of key environmental indicators and operational performance. Firstly, regarding average temperature control, the experimental group's temperature was approximately 2.0℃ to 2.5℃ lower than the control group, indicating that dynamic calculation of ventilation demand is more timely in responding to changes in poultry metabolic heat release and the external environment than fixed start-stop logic, keeping the poultry in a more suitable growth temperature range. Secondly, regarding ammonia concentration, the experimental group's concentration decreased by approximately 40% compared to the control group. This demonstrates that ventilation control is not only based on temperature deviation but also comprehensively considers the risk of air pollution accumulation caused by fecal matter and respiration, effectively avoiding the common phenomenon of temperature compliance but deteriorating air quality.

[0078] Furthermore, the negative pressure stability rate was significantly improved (the average stability rate of the experimental group exceeded 90%), indicating that the fan capacity matching and opening control strategy of this invention can maintain balanced airflow and reduce turbulent dead zones. Fan energy consumption data shows that, under the premise of better air quality, the daily energy consumption of the experimental group was still about 15% lower than that of the control group, demonstrating the energy-saving effect of matching equipment output with demand. The number of abnormal operating condition responses was significantly reduced, indicating that the closed-loop feedback and adaptive parameter adjustment mechanism enhanced the system's self-recovery capability, avoiding the propagation of fault chains and interruption of environmental control. More importantly, the mortality rate of the experimental group decreased by about 40% to 50%, which directly reflects the improvement in poultry health and has both economic and animal welfare benefits.

[0079] In summary, this invention achieves precise ventilation, optimal energy efficiency, and stable continuous operation—achievements that traditional systems cannot reach—through highly reliable information interaction via CAN bus, multi-factor ventilation demand modeling, precise fan frequency setting, and adaptive fault-tolerant control. It demonstrates innovation, advancement, and significant practical value in actual aquaculture scenarios.

[0080] Example 3, an embodiment of the present invention, provides a poultry house ventilation optimization system based on CAN bus, including a data sensing module, a demand calculation module, and a closed-loop control module.

[0081] The path planning module is used to build a CAN-based communication network to collect data on temperature, gas concentration and negative pressure environment of poultry house zones, and to perform data fusion and effectiveness processing; the PID control module is used to determine the target ventilation volume of each zone based on environmental parameters and feeding information, and to convert monitoring data into ventilation control quantities; the smoothing module is used to issue fan and air intake action commands and to perform deviation correction, fault judgment and ventilation capacity compensation based on feedback.

[0082] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0083] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-including system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0084] More specific examples (a non-exhaustive list) of computer-readable media include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which programs can be printed, because programs can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0085] It should be understood that various parts of the present invention can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc. It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

[0086] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for optimizing poultry house ventilation based on CAN bus, characterized in that, include: A communication network consisting of a central control node, an environmental monitoring node, and an execution device node connected by a twisted-pair CAN bus is constructed in the poultry house, and environmental data is collected based on the sensor unit. Based on the number of poultry, their weight, and feeding parameters, the target ventilation rate for each zone is output through an environmental comprehensive correction factor that includes calculations for temperature deviation and ammonia concentration deviation. The fan frequency ratio is obtained by the target air exchange volume, and the fan operating frequency set value is converted into the rated frequency. The set value is then sent to the execution node via CAN control message to drive the actual ventilation equipment to operate. It receives feedback from environmental monitoring and fan operation, dynamically compares the deviation between ventilation commands and actual conditions, introduces frequency change slope limits and correction coefficients for adaptive adjustment, and implements fault judgment and ventilation capacity compensation strategies for sensor node heartbeat loss and fan operation abnormality nodes.

2. The method for optimizing poultry house ventilation based on CAN bus as described in claim 1, characterized in that: The central control node connected by the twisted-pair CAN bus includes a twisted-pair CAN bus with a twisted-pair backbone topology, terminating resistors at both ends of the bus, and each node is connected to the network through an industrial-grade CAN transceiver. The node uses a 24V industrial power input and is equipped with DC-DC isolation circuits and surge protection and electromagnetic interference suppression circuits; Both environmental monitoring nodes and execution device nodes are equipped with a unique address encoding field. The CAN message ID includes the device type, area number, and node sequence number. Monitoring data messages and control command messages are sent periodically according to a standardized frame format. The central control node maintains the node's online management and communication health monitoring based on heartbeat frame parsing.

3. The method for optimizing poultry house ventilation based on CAN bus as described in claim 2, characterized in that: The environmental monitoring node includes a temperature and humidity digital acquisition unit, an electrochemical ammonia acquisition unit, an infrared carbon dioxide acquisition unit, and a differential pressure acquisition unit, and is connected to a microcontroller through I²C, UART, and analog signal acquisition interfaces. The monitoring node performs filtering, calibration, and out-of-bounds rejection on the collected data, and encodes the temperature, humidity, gas concentration, and negative pressure data into a CAN frame for transmission after encoding them with a uniform byte length. The central control node performs data fusion processing on the intermediate data within the same area, and obtains the representative environmental values ​​of each area through invalid value discrimination and averaging strategies.

4. The method for optimizing poultry house ventilation based on CAN bus as described in claim 3, characterized in that: The system combines the number of poultry, their weight, and feeding parameters. It outputs the target ventilation volume for each zone through an environmental comprehensive correction factor that includes calculations for temperature deviation and ammonia concentration deviation. The central control node maintains the zone's environmental status parameters and feeding parameters, including zone temperature, ammonia concentration, number of poultry, average weight, basic ventilation reference volume, temperature setpoint, ammonia reference upper limit, and correction adjustment parameters. The central control node calculates ventilation demand at fixed time intervals, determines environmental correction based on temperature deviation and ammonia exceedance, and then calculates the total ventilation volume for the target zone by combining the number and weight of poultry in each zone.

5. The poultry house ventilation optimization method based on CAN bus as described in claim 4, characterized in that: The process of sending CAN control messages to the execution node to drive the actual ventilation equipment includes the central control node calling the equipment parameter table to determine the total rated air volume of each zone fan, and determining the fan operating frequency and air inlet device opening setting value according to the target ventilation volume. The central control node imposes minimum and maximum allowable range limits on the setpoints, and sets the step size and slope of change. After the set value is scaled and filled into the CAN control message, it is sent to the corresponding execution node, so that the fan driver and the air intake drive component can run according to the set value.

6. The method for optimizing poultry house ventilation based on CAN bus as described in claim 5, characterized in that: The received environmental monitoring feedback and fan operation feedback dynamically compare the deviation between ventilation commands and actual status, introduce frequency change slope limits and adaptive adjustment of correction coefficients, and implement fault judgment and ventilation capacity compensation strategies for sensor node heartbeat loss and fan operation abnormal nodes. The central control node continuously compares the deviation between real-time environmental feedback parameters and fan feedback status, and increases the adjustment coefficient of the corresponding environmental factors in ventilation demand when the temperature and ammonia concentration deviate from the target range. When the actual equipment feedback does not meet the set requirements, the central control node executes a compensation adjustment and refresh frequency acceleration strategy, and sets an upper limit on the adjustment amount per cycle.

7. The method for optimizing poultry house ventilation based on CAN bus as described in claim 6, characterized in that: The received environmental monitoring feedback and fan operation feedback dynamically compare the deviation between ventilation commands and actual conditions, introduce frequency change slope limits and adaptive adjustment of correction coefficients, and implement fault judgment and ventilation capacity compensation strategies for sensor node heartbeat loss and fan operation abnormality nodes. The central control node judges the communication failure of environmental monitoring nodes by counting heartbeat frame loss, and uses a neighborhood environmental parameter interpolation strategy to supplement data when monitoring node data is missing. When the equipment reports an abnormality or fails to perform an action, the central control node marks the abnormal action and starts the backup fan according to the equipment redundancy configuration strategy. At the same time, it adjusts the air intake direction and opening to maintain the ventilation capacity within the safe operating range and records the fault event.

8. A system employing the CAN bus-based ventilation optimization method as described in any one of claims 1 to 7, characterized in that: It includes a data sensing module, a demand calculation module, and a closed-loop control module; The path planning module is used to build a CAN-based communication network to collect data on temperature, gas concentration and negative pressure environment in the poultry house zones, and to perform data fusion and effectiveness processing. The PID control module is used to determine the target ventilation volume for each zone based on environmental parameters and feeding information, and to convert monitoring data into ventilation control volume. The smoothing module is used to issue fan and air intake action commands and perform deviation correction, fault determination and ventilation capacity compensation based on feedback.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the CAN bus-based poultry house ventilation optimization method as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the CAN bus-based poultry house ventilation optimization method as described in any one of claims 1 to 7.

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