Disinfecting and killing system with uniform spraying concentration in breeding house

Abstract

The invention relates to the technical field of livestock sterilization, in particular to a sterilization system for uniformizing spray concentration in a breeding house, which comprises a sensor network, a control center and an execution mechanism, compared with the defects of low regulation and control precision, low response speed and high energy consumption due to direct rough regulation and control according to the concentration of a disinfectant in the prior art, the scheme adopts a disinfectant concentration variable coefficient as a core index, and a control proportional term, an integral term and a differential term of the frequency conversion fan are accurately calculated through a PID algorithm; intelligent adjustment of the rotating speed of the draught fan is achieved, weight distribution strategies in different ventilation modes are combined, the concentration distribution uniformity and response speed of the disinfectant are remarkably improved, the energy utilization efficiency is optimized, and efficient disinfection and energy-saving operation of the pig house environment are ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of livestock disinfection and sterilization, and particularly to a disinfection and sterilization system for uniformizing the spray concentration in a breeding house. Background Art

[0002] In existing disinfection and sterilization systems for pig houses or other enclosed spaces, a regulation method based directly on the disinfectant concentration is usually adopted. However, this method has significant drawbacks. First, the regulation accuracy is low because only regulating based on the absolute value of the disinfectant concentration cannot accurately reflect the uniformity of the disinfectant distribution in the space. Second, the response speed is slow. When the disinfectant concentration changes, the system often cannot make rapid adjustments, resulting in poor disinfection and sterilization effects. Finally, the energy consumption is high because of the lack of a refined regulation strategy, and the system often maintains a roughly constant disinfectant concentration level with high energy consumption.

[0003] To solve these problems, the present invention proposes a disinfection and sterilization system for uniformizing the spray concentration in a breeding house. The system takes the coefficient of variation of the disinfectant concentration as the core index, and accurately calculates the proportional term, integral term, and differential term of the control of the variable-frequency fan through the PID algorithm to realize the intelligent adjustment of the fan speed. At the same time, the system also combines the weight distribution strategy under different ventilation modes to further optimize the distribution and response speed of the disinfectant concentration. In this way, the present invention aims to significantly improve the uniformity and response speed of the disinfectant concentration distribution, while optimizing the energy utilization efficiency to ensure the efficient disinfection and sterilization and energy-saving operation of the pig house or other enclosed space environment. Summary of the Invention

[0004] To overcome the problems raised in the above background art, the present invention proposes a disinfection and sterilization system for uniformizing the spray concentration in a breeding house.

[0005] The technical solution of the present invention is as follows: A disinfection and sterilization system for uniformizing the spray concentration in a breeding house, comprising:

[0006] A sensor network for collecting the disinfectant distribution and wind speed data in the pig house by using sensor technology;

[0007] A control center for processing and analyzing the data collected by the sensor network and generating specific regulation strategies;

[0008] An actuator for acting according to the regulation strategies generated by the control center to regulate the disinfectant concentration, disinfectant distribution, and ventilation volume in the pig house.

[0009] Preferably, the sensor network includes:

[0010] A11: A dual-channel laser particle counter, set in two groups, respectively installed at the proximal and distal ends of the ventilation opening to be prepared, for measuring the disinfectant concentration data in the pigsty;

[0011] A12: An ultrasonic anemometer, used for real-time monitoring of wind speed and air flow direction to identify the ventilation mode of the pigsty;

[0012] A13: An infrared thermal imager, used for monitoring the disinfectant sedimentation temperature field in the pigsty.

[0013] Preferably, the control center includes:

[0014] A21: A main control loop, which takes the coefficient of variation of disinfectant concentration as the core index, generates an air volume control strategy through the PID algorithm, and adjusts the speed of the variable-frequency fan;

[0015] A22: A secondary control loop, which generates a control strategy dynamically according to the disinfectant concentration difference between the proximal and distal ends of the ventilation opening through proportional-integral control, and adjusts the working parameters of the piezoelectric atomization array.

[0016] Preferably, the actuator includes:

[0017] A31: Four groups of variable-frequency fans, respectively set at the ventilation openings at both ends of the long axis of the pigsty and the ventilation windows in the middle sections of the inner side walls of the pigsty, used for accelerating the air flow mixing during longitudinal ventilation and reducing the wind speed during transverse ventilation to reduce the loss of fog particles;

[0018] A32: A piezoelectric atomization array, used for spraying atomized disinfectant according to the control strategy generated by the secondary control loop and according to the set working parameters, including a spray pipe installed on the inner ceiling of the pigsty and nozzles evenly distributed on the spray pipe.

[0019] Preferably, when the main control loop takes the coefficient of variation of disinfectant concentration as the core index, generates an air volume control strategy through the PID algorithm, and adjusts the speed of the variable-frequency fan, it specifically includes:

[0020] S11: Data acquisition and calculation, extracting the data collected by the dual-channel laser particle counter, and calculating the coefficient of variation of disinfectant concentration according to the following formula:

[0021]

[0022] Among them, σ is the standard deviation of the disinfectant concentration at the proximal and distal ends of the ventilation opening, μ is the average value of the disinfectant concentration at the proximal and distal ends of the ventilation opening, and CV is the coefficient of variation of disinfectant concentration;

[0023] S12: Error calculation, calculating the error of the disinfectant concentration distribution at the proximal and distal ends of the ventilation opening, where the calculation principle formula is:

[0024] CV error = CV setpoint -CV measured ;

[0025] Wherein, CV setpoint is the system preset threshold, CV error is the real-time error, CV measured is the real-time coefficient of variation of the disinfectant concentration;

[0026] S13: PID term calculation, calculate the control proportional term, control integral term and control differential term of the variable-frequency fan through the following formula:

[0027] P main = K p ·CV error ;

[0028]

[0029] Wherein, P main is the control proportional term of the variable-frequency fan, K p is the proportional gain coefficient, I main is the control integral term of the variable-frequency fan, K i is the integral gain coefficient, D main is the control differential term of the variable-frequency fan, K d is the differential gain coefficient, t is time;

[0030] S14: Output synthesis and fan speed regulation, calculate the adjustment amount of the output speed of the variable-frequency fan by calculating the control proportional term, control integral term and control differential term of the variable-frequency fan;

[0031] S15: Weight distribution, distribute the adjustment amount according to different ventilation modes, wherein, the ventilation modes include longitudinal ventilation and transverse ventilation. Among them, in the case of longitudinal ventilation, that is, when the wind speed is greater than 1.2 m / s, the weight ratio of the main control loop is 65%, and the weight ratio of the secondary control loop is 35%. In the case of transverse ventilation, the weight ratio of the main control loop is 40%, and the weight ratio of the secondary control loop is 60%. Among them, the ratio of the main control loop is the ratio of the adjustment amount of the variable-frequency fan, and the ratio of the magnetic control loop is the ratio of the adjustment amount of the piezoelectric atomization array.

[0032] Preferably, when obtaining the adjustment amount of the output speed of the variable-frequency fan by calculating the control proportional term, control integral term and control differential term of the variable-frequency fan, the calculation principle formula is:

[0033] V new = V base + ΔV;

[0034] Among them, V new is the target rotational speed value of the variable-frequency fan calculated based on the control proportional term, the control integral term, and the control differential term of the variable-frequency fan. V base is the preset rotational speed of the variable-frequency fan in the current ventilation mode, and ΔV is the adjustment amount of the variable-frequency fan calculated based on the control proportional term, the control integral term, and the control differential term of the variable-frequency fan. Among them, ΔV = P main + I main + D main .

[0035] Preferably, when the secondary control loop dynamically generates a control strategy according to the disinfectant concentration difference between the proximal end and the distal end of the ventilation opening and adjusts the working parameters of the piezoelectric atomization array, it specifically includes:

[0036] S21: Data acquisition and concentration difference calculation, calculating the concentration difference based on the data collected by the dual-channel laser particle counter. Among them, the principle formula is:

[0037] ΔC = C near - C far ;

[0038] Among them, ΔC is the concentration difference, C near is the disinfectant concentration at the proximal end of the ventilation opening, and C far is the disinfectant concentration at the distal end of the ventilation opening;

[0039] S22: Error calculation, calculating the error between the real-time concentration difference of the disinfectant and the target value according to the following formula:

[0040] ΔC error = ΔC setpoint - ΔC;

[0041] Among them, ΔC setpoint is the set target value, and ΔC error is the error between the real-time concentration difference of the disinfectant and the target value;

[0042] S23: PI term calculation, calculating the control proportional term of the piezoelectric atomization array and the control integral term of the piezoelectric atomization array according to the following formula:

[0043] P sub = K p · ΔC error ;

[0044]

[0045] Among them, P main is the control proportional term of the piezoelectric atomization array, Kp is the proportional gain coefficient, I main is the control integral term of the piezoelectric atomization array, K i is the integral gain coefficient, and t is time;

[0046] S24: Output synthesis and spray parameter adjustment. Calculate the output adjustment amount of the piezoelectric atomization array through the following formula:

[0047] ΔS = P sub + I sub ;

[0048] where, when ΔS is less than 0, increase the nozzle opening at the distal end of the vent, decrease the nozzle opening at the proximal end of the vent, and decrease the atomization particle size at the distal end of the vent; when ΔS is greater than 0, decrease the nozzle opening at the distal end of the vent, increase the nozzle opening at the proximal end of the vent, and decrease the atomization particle size at the proximal end of the vent;

[0049] S25: Weight allocation. Perform weight allocation using the weight allocation method in step S15.

[0050] Preferably, the control center further includes a model predictive controller for performing the following steps:

[0051] S31: Establish a dynamic prediction model to predict the change of disinfectant concentration within the next 5 steps;

[0052] S32: Generate an optimal control sequence of the fan speed and spray parameters by minimizing the objective function J = 0.6CV + 0.3ΔC + 0.1E through rolling optimization, where E is the total energy consumption per unit disinfection cycle, and the total energy consumption E per unit disinfection cycle is calculated through the following formula:

[0053]

[0054] where, P fan is the fan power, P spray is the spray power, N p is the number of steps in the prediction time domain.

[0055] Preferably, when the model predictive controller establishes a dynamic prediction model, it discretizes the transfer function into a state space equation, where, is the delay term, 3.2S represents the inertial settling of fog particles, 1.5S is the air flow inertia of the ventilation system, L represents the length of the pigsty, V represents the real-time wind speed, s represents the Laplace variable, and specifically includes:

[0056] S41: Discretize the delay term in the transfer function into a transmission delay with an integer step size;

[0057] S42: Convert the inertial link into a discrete state - space equation using the zero - order hold method ;

[0058] S43: Expand the state - space to include the number of delay steps T s is the sampling period.

[0059] Preferably, when generating the optimal control sequence of the fan speed and the spraying parameters by minimizing the objective function J = 0.6CV+0.3ΔC + 0.1E through rolling optimization, it specifically includes:

[0060] S51: Set the prediction horizon N p = 5 steps and the control horizon N c = 5 steps;

[0061] S52: Calculate the control sequence that minimizes the objective function J through a quadratic programming solver.

[0062] Preferably, the model predictive controller includes a ventilation mutation detection module. The ventilation mutation detection module is used to trigger a feed - forward compensation mechanism when the wind speed change rate is greater than 0.5m / s 2 . Among them, the principle formula of the feed - forward compensation mechanism is:

[0063] u spray (k)=u MPC (k)+K f ·ΔV;

[0064] Among them, u spray (k) is the spraying pressure control amount at the k - th moment, u MPC (k) is the spraying pressure control amount calculated by the model predictive controller at the k - th moment, K f is the feed - forward gain coefficient, and K f = 0.05MPa / (m / s), and ΔV is the current wind speed change rate.

[0065] Advantages of the present invention

[0066] 1. Compared with the prior art that directly conducts rough regulation based on the disinfectant concentration, which has the disadvantages of low regulation accuracy, slow response speed, and high energy consumption, this solution uses the coefficient of variation of the disinfectant concentration as the core index, accurately calculates the proportional term, integral term, and differential term of the control of the variable - frequency fan through the PID algorithm, realizes the intelligent adjustment of the fan speed, and combines the weight - distribution strategy under different ventilation modes, not only significantly improves the uniformity and response speed of the disinfectant concentration distribution, but also optimizes the energy - utilization efficiency, ensuring the efficient disinfection and energy - saving operation of the pigsty environment;

[0067] 2. Compared with the prior art that only performs immediate regulation based on the current state and lacks effective prediction of future states, which may lead to drawbacks such as regulation lag and increased energy consumption, this solution introduces a model predictive controller in the control center. By establishing a dynamic prediction model to predict the changes in the future disinfectant concentration and rolling optimization to generate the optimal control sequence of the fan speed and spraying parameters, it not only realizes the advanced regulation of the disinfectant concentration but also effectively reduces the total energy consumption per disinfection cycle by optimizing the objective function, significantly improving the regulation accuracy and energy efficiency level of the system and ensuring the continuous safety and energy-saving operation of the pigsty environment;

[0068] 3. Compared with the prior art that lacks a rapid response mechanism when the wind speed suddenly changes, resulting in an imbalance in the disinfectant concentration distribution and regulation lag, this solution integrates a ventilation mutation detection module in the model predictive controller. When the wind speed change rate exceeds the set threshold, it quickly triggers a feedforward compensation mechanism. By introducing the wind speed change rate as the feedforward compensation amount, it adjusts the spray pressure control amount in real time, effectively offsetting the impact of the wind speed mutation on the disinfectant distribution, significantly improving the response speed and stability of the system, and ensuring the continuous uniform distribution and efficient disinfection of the disinfectant concentration in the pigsty. BRIEF DESCRIPTION OF THE DRAWINGS

[0069] Figure 1 The structural schematic diagram of the disinfection system for uniform spray concentration in the breeding house of the present invention is shown;

[0070] Figure 2 The working process schematic diagram of the main control loop in the disinfection system for uniform spray concentration in the breeding house of the present invention is shown. DETAILED DESCRIPTION OF THE INVENTION

[0071] The present invention will be further described below with reference to the drawings and embodiments.

[0072] Please refer to Figure 1-2 , the present invention provides an embodiment: A disinfection system for uniform spray concentration in a breeding house, including:

[0073] A sensor network for collecting the disinfectant distribution and wind speed data in the pigsty using sensor technology;

[0074] A control center for processing and analyzing the data collected by the sensor network and generating specific regulation strategies;

[0075] An actuator for acting according to the regulation strategies generated by the control center to regulate the disinfectant concentration, disinfectant distribution, and ventilation volume in the pigsty.

[0076] As described above, the present invention integrates a sensor network, a control center, and an actuator to achieve uniform disinfection of the disinfectant concentration and distribution in the pigsty. At the same time, precise regulation is carried out according to real-time wind speed data, effectively improving the disinfection efficiency and uniformity, and ensuring the hygienic safety of the pigsty environment.

[0077] Preferably, the sensor network includes:

[0078] A11: A dual-channel laser particle counter, which is set in two groups and installed at the proximal and distal ends of the prepared ventilation opening respectively, for measuring the disinfectant concentration data in the pigsty;

[0079] A12: An ultrasonic anemometer, which is used to monitor the wind speed and air flow direction in real time and identify the ventilation mode of the pigsty;

[0080] A13: An infrared thermal imager, which is used to monitor the disinfectant sedimentation temperature field in the pigsty.

[0081] As described above, the present invention integrates a dual-channel laser particle counter (precisely measuring the disinfectant concentration), an ultrasonic anemometer (monitoring the wind speed and air flow direction in real time), and an infrared thermal imager (monitoring the disinfectant sedimentation temperature field). This sensor network can comprehensively and real-time capture the environmental data in the pigsty, providing a scientific basis for precisely regulating the disinfectant concentration and distribution, and significantly enhancing the disinfection effect and the hygienic management level of the pigsty environment.

[0082] Preferably, the control center includes:

[0083] A21: A main control loop, which is used to take the coefficient of variation of the disinfectant concentration as the core index, generate an air volume control strategy through the PID algorithm, and adjust the rotational speed of the variable-frequency fan;

[0084] A22: A secondary control loop, which is used to dynamically generate a control strategy according to the disinfectant concentration difference between the proximal and distal ends of the ventilation opening, and adjust the working parameters of the piezoelectric atomization array through proportional-integral control.

[0085] As described above, the present invention adopts the PID algorithm in the main control loop, takes the coefficient of variation of the disinfectant concentration as the index, precisely regulates the rotational speed of the variable-frequency fan to achieve air volume optimization; at the same time, the secondary control loop flexibly adjusts the parameters of the piezoelectric atomization array according to the disinfectant concentration difference at both ends of the ventilation opening through proportional-integral control, ensuring the uniform distribution and efficient utilization of the disinfectant concentration, and significantly improving the disinfection effect and energy efficiency of the pigsty environment.

[0086] Preferably, the actuator includes:

[0087] A31: Variable-frequency fans, which are set in four groups and are respectively arranged at the ventilation openings at both ends of the long axis of the pigsty and at the ventilation windows in the middle sections of the inner side walls of the pigsty, and are used to accelerate the air flow mixing during longitudinal ventilation and reduce the wind speed during transverse ventilation to reduce the loss of mist particles;

[0088] A32: Piezoelectric atomization array, which is used to spray atomized disinfectant according to the control strategy generated by the secondary control loop and according to the set working parameters, and includes a spray pipe installed on the inner ceiling of the pigsty and nozzles evenly distributed on the spray pipe.

[0089] As described above, the actuator of the present invention intelligently adjusts the wind speed at different positions in the pigsty through four groups of variable-frequency fans, which not only accelerates the air flow mixing during longitudinal ventilation, but also reduces the loss of mist particles during transverse ventilation; at the same time, the piezoelectric atomization array sprays atomized disinfectant through the spray pipe on the ceiling and its evenly distributed nozzles according to the precise control strategy, ensuring the uniform distribution and efficient utilization of the disinfectant, and greatly optimizing the disinfection effect and resource utilization rate of the pigsty environment.

[0090] Preferably, when the main control loop generates a air volume control strategy through the PID algorithm with the coefficient of variation of disinfectant concentration as the core index and adjusts the rotation speed of the variable-frequency fan, it specifically includes:

[0091] S11: Data collection and calculation, extracting the data collected by the dual-channel laser particle counter and calculating the coefficient of variation of disinfectant concentration according to the following formula:

[0092]

[0093] Wherein, σ is the standard deviation of the disinfectant concentration at the proximal and distal ends of the ventilation opening, μ is the average value of the disinfectant concentration at the proximal and distal ends of the ventilation opening, and CV is the coefficient of variation of disinfectant concentration;

[0094] S12: Error calculation, calculating the error of the disinfectant concentration distribution at the proximal and distal ends of the ventilation opening, wherein the calculation principle formula is:

[0095] CV error = CV setpoint - CV measured ;

[0096] Wherein, CV setpoint is the system preset threshold, CV error is the real-time error, and CV measured is the real-time coefficient of variation of disinfectant concentration;

[0097] S13: PID term calculation, calculating the control proportional term of the variable-frequency fan, the control integral term of the variable-frequency fan and the control differential term of the variable-frequency fan through the following formula:

[0098] Pmain = K p ·CV error ;

[0099]

[0100] Wherein, P main is the control proportional term of the variable-frequency fan, K p is the proportional gain coefficient, I main is the control integral term of the variable-frequency fan, K i is the integral gain coefficient, D main is the control differential term of the variable-frequency fan, K d is the differential gain coefficient, and t is time;

[0101] S14: Output synthesis and fan speed regulation. By calculating the control proportional term of the variable-frequency fan, the control integral term of the variable-frequency fan, and the control differential term of the variable-frequency fan, the regulation amount of the output speed of the variable-frequency fan is obtained;

[0102] S15: Weight distribution. According to different ventilation modes, the regulation amount is distributed. Among them, the ventilation modes include longitudinal ventilation and transverse ventilation. Among them, in the case of longitudinal ventilation, that is, when the wind speed is greater than 1.2 m / s, the weight ratio of the main control loop is 65%, and the weight ratio of the secondary control loop is 35%. In the case of transverse ventilation, the weight ratio of the main control loop is 40%, and the weight ratio of the secondary control loop is 60%. Among them, the ratio of the main control loop is the ratio of the regulation amount of the variable-frequency fan, and the ratio of the magnetic control loop is the ratio of the regulation amount of the piezoelectric atomization array.

[0103] As described above, compared with the prior art, which directly conducts rough regulation based on the disinfectant concentration, the present invention has the disadvantages of low regulation accuracy, slow response speed, and high energy consumption. This solution uses the coefficient of variation of the disinfectant concentration as the core index, accurately calculates the control proportional term, integral term, and differential term of the variable-frequency fan through the PID algorithm, realizes intelligent regulation of the fan speed, and combines the weight distribution strategy under different ventilation modes, not only significantly improves the uniformity and response speed of the disinfectant concentration distribution, but also optimizes the energy utilization efficiency, ensuring efficient disinfection and energy-saving operation of the pigsty environment.

[0104] Preferably, when obtaining the regulation amount of the output speed of the variable-frequency fan by calculating the control proportional term of the variable-frequency fan, the control integral term of the variable-frequency fan, and the control differential term of the variable-frequency fan, the calculation principle formula is:

[0105] V new = V base + ΔV;

[0106] Wherein, V newV is the target rotational speed value of the variable-frequency fan calculated based on the proportional term, integral term, and derivative term of the control of the variable-frequency fan. base is the preset rotational speed of the variable-frequency fan under the current ventilation mode, and ΔV is the adjustment amount of the variable-frequency fan calculated based on the proportional term, integral term, and derivative term of the control of the variable-frequency fan. Among them, ΔV = P main + I main + D main .

[0107] As described above, compared with the prior art that directly adjusts the rotational speed of the variable-frequency fan according to a simple difference or a fixed ratio, the present invention has the disadvantages of inaccurate adjustment, easy to cause system oscillation or response lag. This solution uses the PID algorithm to comprehensively calculate the proportional term, integral term, and derivative term of the control of the variable-frequency fan, and accurately calculates the target rotational speed value and adjustment amount of the variable-frequency fan based on this, realizing the fine and dynamic regulation of the fan rotational speed. It not only improves the accuracy and stability of system regulation, but also effectively avoids system oscillation, ensuring the uniform distribution and efficient disinfection of the disinfectant concentration in the pigsty.

[0108] Preferably, when the secondary control loop dynamically generates a control strategy according to the disinfectant concentration difference between the proximal end and the distal end of the ventilation opening and adjusts the working parameters of the piezoelectric atomization array, it specifically includes:

[0109] S21: Data acquisition and concentration difference calculation. Calculate the concentration difference according to the data collected by the dual-channel laser particle counter. Among them, the principle formula is:

[0110] ΔC = C near - C far ;

[0111] Among them, ΔC is the concentration difference, C near is the disinfectant concentration at the proximal end of the ventilation opening, and C far is the disinfectant concentration at the distal end of the ventilation opening;

[0112] S22: Error calculation. Calculate the error between the real-time concentration difference of the disinfectant and the target value according to the following formula:

[0113] ΔC error = ΔC setpoint - ΔC;

[0114] Among them, ΔC setpoint is the set target value, and ΔC error is the error between the real-time concentration difference of the disinfectant and the target value;

[0115] S23: PI term calculation. Calculate the control proportional term of the piezoelectric atomization array and the control integral term of the piezoelectric atomization array according to the following formula:

[0116] P sub = K p ·ΔC error ;

[0117]

[0118] where P main is the control proportional term of the piezoelectric atomization array, K p is the proportional gain coefficient, I main is the control integral term of the piezoelectric atomization array, K i is the integral gain coefficient, and t is time;

[0119] S24: Output synthesis and spray parameter adjustment. Calculate the output adjustment amount of the piezoelectric atomization array according to the following formula:

[0120] ΔS = P sub + I sub ;

[0121] where, when ΔS is less than 0, increase the nozzle opening at the distal end of the ventilation opening, decrease the nozzle opening at the proximal end of the ventilation opening, and decrease the atomization particle size at the distal end of the ventilation opening; when ΔS is greater than 0, decrease the nozzle opening at the distal end of the ventilation opening, increase the nozzle opening at the proximal end of the ventilation opening, and decrease the atomization particle size at the proximal end of the ventilation opening;

[0122] S25: Weight assignment. Perform weight assignment using the weight assignment method in step S15.

[0123] As described above, compared with the prior art that directly performs simple adjustment based on the disinfectant concentration difference, the present invention has the disadvantages of low adjustment accuracy, difficulty in achieving uniform distribution, and resource waste. This solution adopts a proportional-integral control strategy, dynamically calculates the control proportional term and integral term of the piezoelectric atomization array according to the disinfectant concentration difference between the proximal end and the distal end of the ventilation opening, and precisely adjusts the nozzle opening and atomization particle size accordingly, realizing fine control of the disinfectant distribution and efficient utilization of resources. At the same time, combined with the weight assignment under different ventilation modes, the flexibility and accuracy of the system adjustment are further improved, ensuring uniform distribution of the disinfectant concentration in the pigsty and efficient disinfection and significantly improving the overall disinfection effect and resource utilization rate.

[0124] Preferably, the control center further includes a model predictive controller for performing the following steps:

[0125] S31: Establish a dynamic prediction model to predict the change of the disinfectant concentration within the next 5 steps;

[0126] S32: Minimize the objective function J = 0.6CV + 0.3ΔC + 0.1E through rolling optimization to generate an optimal control sequence for the fan speed and spraying parameters. Here, E is the total energy consumption per disinfection cycle, and the total energy consumption E per disinfection cycle is calculated by the following formula:

[0127]

[0128] where P fan is the fan power, P spray is the spraying power, and N p is the number of steps in the prediction horizon.

[0129] As described above, compared with the prior art which only performs immediate regulation based on the current state and lacks effective prediction of future states, this may lead to drawbacks such as regulation lag and increased energy consumption. In this solution, a model predictive controller is introduced into the control center. By establishing a dynamic prediction model to predict the change of the future disinfectant concentration and generating an optimal control sequence for the fan speed and spraying parameters through rolling optimization, it not only realizes the advanced regulation of the disinfectant concentration but also effectively reduces the total energy consumption per disinfection cycle by optimizing the objective function, significantly improving the regulation accuracy and energy efficiency level of the system, and ensuring the continuous safety and energy-saving operation of the pig house environment.

[0130] Preferably, when the model predictive controller establishes a dynamic prediction model, the transfer function is discretized into a state-space equation, where is the delay term, 3.2S represents the inertial of fog particle sedimentation, 1.5S is the inertial of the air flow in the ventilation system, L represents the length of the pig house, V represents the real-time wind speed, s represents the Laplace variable, and specifically includes:

[0131] S41: Discretize the delay term in the transfer function into a transmission delay with an integer step size;

[0132] S42: Use the zero-order hold method to convert the inertial link into a discrete state-space equation;

[0133] S43: Expand the state space to include the delay steps T s is the sampling period.

[0134] As described above, compared with the prior art that directly uses a continuous-domain model for predictive control, which may lead to insufficient prediction accuracy due to the failure to fully consider the system delay and inertia characteristics, in this solution, in the model predictive controller, the delay term and the inertia link in the transfer function are discretized separately. By discretizing the delay term into a transmission delay with an integer step size and using the zero-order hold method to convert the inertia link into a discrete state-space equation, and at the same time expanding the state space to include the number of delay steps, the dynamic characteristics of fog droplet sedimentation and the airflow inertia of the ventilation system are accurately described, significantly improving the accuracy and reliability of the dynamic prediction model, providing a solid foundation for generating the optimal control sequence, and ensuring the precise regulation and efficient disinfection of the disinfectant concentration in the pigsty.

[0135] Preferably, when generating the optimal control sequence of the fan speed and spray parameters by minimizing the objective function J = 0.6CV + 0.3ΔC + 0.1E through rolling optimization, it specifically includes:

[0136] S51: Set the prediction horizon N p = 5 steps and the control horizon N c = 5 steps;

[0137] S52: Calculate the control sequence that minimizes the objective function J through a quadratic programming solver.

[0138] As described above, compared with the prior art in which the prediction horizon and control horizon are set unreasonably, or a simple iterative method is used to solve the optimal control sequence, which may lead to low solution efficiency and deviation of the optimal solution, in this solution, during the rolling optimization process, the number of steps of the prediction horizon and control horizon are reasonably set, and the control sequence that minimizes the objective function is accurately calculated through an efficient quadratic programming solver, which not only improves the solution efficiency and accuracy, but also ensures the generation of the optimal control sequence, thereby realizing the precise regulation of the fan speed and spray parameters, and further optimizing the distribution and energy efficiency level of the disinfectant concentration in the pigsty.

[0139] Preferably, the model predictive controller includes a ventilation mutation detection module, and the ventilation mutation detection module is used to trigger a feedforward compensation mechanism when the wind speed change rate is greater than 0.5 m / s 2 At this time, the principle formula of the feedforward compensation mechanism is:

[0140] u spray (k)=u MPC (k)+K f ·ΔV;

[0141] Among them, u spray (k) is the spray pressure control amount at the k-th moment, u MPC (k) is the spray pressure control amount calculated by the model predictive controller at the k-th moment, Kf is the feedforward gain coefficient, and K f = 0.05 MPa / (m / s), and ΔV is the current wind speed change rate.

[0142] As described above, compared with the prior art, the present invention lacks a rapid response mechanism when the wind speed suddenly changes, resulting in the disadvantages of unbalanced distribution of the disinfectant concentration and lag in regulation. In this solution, a ventilation mutation detection module is integrated into the model predictive controller. When the wind speed change rate exceeds the set threshold, the feedforward compensation mechanism is quickly triggered. By introducing the wind speed change rate as the feedforward compensation amount, the spray pressure control amount is adjusted in real time, effectively offsetting the influence of the sudden wind speed change on the disinfectant distribution, significantly improving the response speed and stability of the system, and ensuring the continuous and uniform distribution and efficient disinfection of the disinfectant concentration in the pigsty.

[0143] The embodiments of the present invention have been described in detail above in conjunction with the accompanying drawings. However, the present invention is not limited to the above embodiments, and various changes can be made without departing from the spirit of the present invention within the scope of knowledge possessed by those skilled in the art.

Claims

1. A disinfection system for uniform spray concentration in a breeding house, characterized by: Included are: A sensor network for collecting disinfectant distribution and wind speed data in pig houses using sensor technology; The control center is used to process and analyze the data collected by the sensor network and generate specific control strategies; The actuator is used to act according to the control strategy generated by the control center to control the disinfectant concentration, disinfectant distribution and ventilation volume in the pig house.

2. A disinfection system for uniform spray concentration in a breeding house according to claim 1, characterized in that: The sensor network includes: A11: Dual-channel laser particle counter, set up in two groups, installed at the near and far ends of the preparation vents, used to measure disinfectant concentration data in the pig house; A12: Ultrasonic anemometer, used to monitor wind speed and airflow direction in real time and identify the ventilation mode of the pig house; A13: Infrared thermal imager, used to monitor the disinfectant settling temperature field in the pig house.

3. A disinfection system for uniform spray concentration in a breeding house according to claim 2, characterized in that: The control center includes: A21: Main control loop, used to generate air volume control strategy through PID algorithm with the coefficient of variation of disinfectant concentration as the core indicator, and adjust the speed of variable frequency fan; A22: Secondary control loop, used to dynamically generate a control strategy through proportional-integral control to adjust the operating parameters of the piezoelectric atomization array according to the difference in disinfectant concentration at the proximal and distal ends of the vent.

4. A disinfection system for uniform spray concentration in a breeding house according to claim 3, characterized in that: The implementing agencies include: A31: Variable frequency fans, set in four groups, are respectively set at the vents at both ends of the long axis of the pig house and the ventilation windows in the middle of the walls on both sides of the pig house, which are used to accelerate the mixing of airflow during longitudinal ventilation and reduce the wind speed during transverse ventilation to reduce the loss of fog particles; A32: Piezoelectric atomization array, used to spray atomized disinfectant according to the set working parameters based on the control strategy generated by the secondary control loop, including a spray pipe installed on the ceiling inside the pig house and nozzles evenly distributed on the spray pipe.

5. A disinfection system for uniform spray concentration in a breeding house according to claim 4, characterized in that: The main control loop uses the coefficient of variation of disinfectant concentration as the core indicator, generates an air volume control strategy through the PID algorithm, and adjusts the speed of the variable frequency fan, specifically including: S11: Data collection and calculation: extract the data collected by the dual-channel laser particle counter and calculate the coefficient of variation of the disinfectant concentration according to the following formula: Wherein, σ is the standard deviation of the disinfectant concentration at the proximal and distal ends of the vent, μ is the average of the disinfectant concentration at the proximal and distal ends of the vent, and CV is the coefficient of variation of the disinfectant concentration; S12: Error calculation, calculating the error of the disinfectant concentration distribution at the proximal and distal ends of the vent, wherein the calculation principle formula is: CV error =CV setpoint -CV measured ; Among them, CV setpoint Preset threshold for the system, CV error is the real-time error, CV measured is the coefficient of variation of real-time disinfectant concentration; S13: PID item calculation, the control proportional item of the variable frequency fan, the control integral item of the variable frequency fan and the control differential item of the variable frequency fan are calculated by the following formula: P main =K p ·CV error ; Among them, P main is the control proportional term of the variable frequency fan, K p is the proportional gain coefficient, I main is the control integral term of the variable frequency fan, K i is the integral gain coefficient, D main is the control differential term of the variable frequency fan, K d is the differential gain coefficient, t is the time; S14: output synthesis and fan speed adjustment, by calculating the control proportional term of the variable frequency fan, the control integral term of the variable frequency fan and the control differential term of the variable frequency fan, the adjustment amount of the output speed of the variable frequency fan is obtained; S15: Weight allocation, allocate the adjustment amount according to different ventilation modes, where the ventilation modes include longitudinal ventilation and transverse ventilation. In the case of longitudinal ventilation, that is, the wind speed is greater than 1.2m / s, the weight of the main control loop accounts for 65%, and the weight of the secondary control loop accounts for 35%. In the case of transverse ventilation, the weight of the main control loop accounts for 40%, and the weight of the secondary control loop accounts for 60%. Among them, the proportion of the main control loop is the proportion of the variable frequency fan adjustment amount, and the proportion of the magnetic control loop is the proportion of the piezoelectric atomization array adjustment amount.

6. A disinfection system for uniform spray concentration in a breeding house according to claim 5, characterized in that: When the output speed adjustment amount of the variable frequency fan is obtained by calculating the control proportional term, the control integral term and the control differential term of the variable frequency fan, the calculation principle formula is: V new =V base +ΔV; Among them, V new V is the target speed value of the variable frequency fan calculated based on the control proportional term, the control integral term and the control differential term of the variable frequency fan. base is the preset speed of the variable frequency fan in the current ventilation mode, ΔV is the adjustment amount of the variable frequency fan calculated according to the control proportional term of the variable frequency fan, the control integral term of the variable frequency fan and the control differential term of the variable frequency fan, where ΔV=P main +I main +D main .

7. A disinfection system for uniform spray concentration in a breeding house according to claim 6, characterized in that: The secondary control loop dynamically generates a control strategy through proportional-integral control according to the concentration difference of the disinfectant at the proximal and distal ends of the vent to adjust the working parameters of the piezoelectric atomization array, specifically including: S21: Data collection and concentration difference calculation: concentration difference calculation is performed based on the data collected by the dual-channel laser particle counter, wherein the principle formula is: ΔC=C near -C far ; Where ΔC is the concentration difference, C near is the disinfectant concentration near the vent, C far is the disinfectant concentration at the far end of the vent; S22: Error calculation, the error between the real-time concentration difference of the disinfectant and the target value is calculated according to the following formula: ΔC error =ΔC setpoint -ΔC; Where, ΔC setpoint is the set target value, ΔC error is the error between the real-time concentration difference of the disinfectant and the target value; S23: PI term calculation, calculate the control proportional term of the piezoelectric atomization array and the control integral term of the piezoelectric atomization array according to the following formula: P sub =K p ·ΔC error ; Among them, P main is the control proportional term of the piezoelectric atomization array, K p is the proportional gain coefficient, I main is the control integral term of the piezoelectric atomization array, K i is the integral gain coefficient, t is the time; S24: Output synthesis and spray parameter adjustment. The output adjustment amount of the piezoelectric atomization array is calculated by the following formula: ΔS=P sub +I sub ; Wherein, when ΔS is less than 0, the nozzle opening at the far end of the vent is increased, the nozzle opening at the near end of the vent is decreased, and the atomized particle size at the far end of the vent is decreased; when ΔS is greater than 0, the nozzle opening at the far end of the vent is decreased, the nozzle opening at the near end of the vent is increased, and the atomized particle size at the near end of the vent is decreased; S25: Weight allocation: weight allocation is performed using the weight allocation method in step S15.

8. A disinfection system for uniform spray concentration in a breeding house according to claim 7, characterized in that: The control center also includes a model predictive controller that performs the following steps: S31: Establish a dynamic prediction model to predict the change of disinfectant concentration within the next 5 steps; S32: Minimize the objective function J=0.6CV+0.3ΔC+0.1E through rolling optimization to generate the optimal control sequence of the fan speed and the spray parameters, where E is the total energy consumption per unit disinfection cycle, and the total energy consumption E per unit disinfection cycle is calculated by the following formula: Among them, P fan is the fan power, P spray is the spray power, N p is the number of steps in the prediction time domain.

9. A disinfection system for uniform spray concentration in a breeding house according to claim 8, characterized in that: When establishing a dynamic prediction model, the model predictive controller transfers the function Discretized into state space equations, where is the delay term, 3.2S represents the inertia of fog particle settling, 1.5S represents the inertia of ventilation system airflow, L represents the length of the pig house, V represents the real-time wind speed, and s represents the Laplace variable, which includes: S41: The delay term in the transfer function The transmission delay is discretized into integer steps; S42: Use the zero-order hold method to hold the inertia link Convert to discrete state space equations; S43: Extending the state space to include delay steps T s is the sampling period.

10. A disinfection system for uniform spray concentration in a breeding house according to claim 9, characterized in that: When the objective function J=0.6CV+0.3ΔC+0.1E is minimized by rolling optimization, the optimal control sequence of fan speed and spray parameters is generated, which specifically includes: S51: Setting the prediction time domain N p = 5 steps and control time domain N c =5 steps; S52: Calculate the control sequence that minimizes the objective function J through a quadratic programming solver.

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