A warm air speed synchronous monitoring method for avionics test

Abstract

This application discloses a method for synchronous monitoring of temperature and wind speed for avionics testing, comprising: establishing independent temperature and wind speed control closed loops inside a temperature chamber, each closed loop consisting of a controlled air outlet unit and at least one designated associated monitoring point, synchronously and in real-time acquiring the temperature and wind speed values ​​of the monitoring point; performing coordinated control calculations: comparing the values ​​with the target temperature and target wind speed values ​​set for the control closed loop, respectively, to generate temperature deviation signals and wind speed deviation signals; performing integrated calculations on the temperature deviation signals and wind speed deviation signals to generate control commands; and adjusting the actuator action of the corresponding air outlet unit to change the airflow rate and temperature. This application achieves coupled control of temperature and wind speed by establishing multiple independent temperature and wind speed control closed loops, each using a multivariable PID algorithm to perform integrated coordinated calculations on the temperature and wind speed deviations of associated monitoring points, and outputting a single command to adjust the airflow rate and temperature of the air outlet.

Description

Technical Field

[0001] This application relates to the field of equipment testing technology, specifically a method for synchronous monitoring of temperature and wind speed for avionics testing. Background Technology

[0002] In the research, development, certification and factory testing of avionics equipment, it is necessary to test its performance and reliability in harsh environments such as extreme temperatures and complex airflow.

[0003] Environmental test chambers (temperature chambers) are key equipment for simulating such test environments. High-precision temperature control is a fundamental requirement for such tests. This is usually achieved by placing temperature sensors inside the chamber and using closed-loop control (such as PID control) to adjust the heating or cooling power and damper opening. With the continuous improvement of the integration and power consumption of avionics equipment, the complexity of its heat dissipation characteristics is increasing. The uniformity of temperature field distribution has become a key factor affecting the accuracy and repeatability of test results. That is, in addition to the temperature itself, the uniformity of wind speed in the test area has a decisive impact on the heat exchange efficiency of the equipment surface and the internal temperature gradient. If only the average temperature is controlled while ignoring the wind speed distribution, different parts of the tested equipment may be in substantially different thermal environments, resulting in inaccurate test conditions and failing to truly reflect the equipment performance.

[0004] In existing technologies, temperature control is achieved by arranging temperature sensors inside the chamber and adjusting the total air volume or heating power. However, the key wind speed (airflow velocity) field inside the chamber is not effectively monitored and actively adjusted. This results in the wind speed distribution inside the chamber being uncontrollable and extremely uneven when conducting tests that require specific temperature and wind speed conditions simultaneously. This creates an uncontrollable interference variable, which seriously affects the accuracy of the test conditions and the repeatability of the test results.

[0005] Therefore, it is necessary to provide a method for synchronous monitoring of temperature and wind speed for avionics testing to solve the above problems.

[0006] It should be noted that the information disclosed in this background section is only for understanding the background technology of this application concept, and therefore may include information that does not constitute prior art. Summary of the Invention

[0007] Based on the aforementioned problems in the existing technology, the problem to be solved by this application is to provide a method for synchronous monitoring of temperature and wind speed for avionics testing, so as to achieve the effect of coupled control of temperature and wind speed.

[0008] The technical solution adopted by this application to solve its technical problem is: a method for synchronous monitoring of temperature and wind speed for avionics testing, comprising: Multiple independent temperature and air velocity control closed loops are established inside the incubator. Each closed loop consists of a controlled air outlet unit and at least one designated and associated monitoring point. At each of the aforementioned monitoring points, the temperature and wind speed values ​​at that monitoring point are collected synchronously and in real time. For each independent control loop, perform collaborative control calculations: compare the real-time temperature and wind speed values ​​collected from the associated monitoring points with the target temperature and target wind speed values ​​set for that control loop, respectively, and generate temperature deviation signals and wind speed deviation signals. The temperature deviation signal and the wind speed deviation signal are processed in an integrated manner using the same control algorithm to generate a unified control command. The parameters of the control algorithm are tuned in a coordinated manner based on the control characteristics of temperature and wind speed. Based on the unified control command, the action of the actuator corresponding to the air outlet unit is adjusted, thereby changing the flow rate and temperature of the airflow delivered by the air outlet unit.

[0009] Furthermore, the multiple independent temperature and velocity control closed loops are established, specifically by regularly arranging multiple temperature and velocity dual-sensor sensors as monitoring points in the three-dimensional space inside the temperature chamber. Multiple air outlets driven by servo valves are set at the air supply end of the incubator as the air outlet units; By using a spatial location matching algorithm, each sensor is dynamically assigned a spatially closest air outlet, and a corresponding control link is established.

[0010] Furthermore, the rule arrangement is specifically as follows: based on the effective volume of the temperature chamber and the size of the device under test, a cubic monitoring area that completely covers the device is determined; the temperature and speed combined sensor is arranged at the vertices and the center point of each face of this cubic area to form at least 9 key monitoring points, so as to achieve all-round synchronous monitoring of the environmental parameters around the device with the minimum number of sensors.

[0011] Furthermore, the control algorithm specifically employs a multivariable PID control algorithm, the operation of which is as follows: For each control closed loop, a coupled PID controller is set up. The input of the controller is a two-dimensional deviation signal e(k)=[e_T(k), e_V(k)]^T, where e_T(k) is the temperature deviation and e_V(k) is the wind speed deviation. The controller outputs a one-dimensional control quantity u(k), and the control law is implemented through a 1x2 gain matrix, and u(k) = Kp*e(k) + Ki*Σe(j) + Kd*Δe(k), where Kp, Ki, and Kd are parameter matrices or coefficients that have been co-tuned, so that the control quantity u(k) can simultaneously respond to the deviation and changing trend of temperature and wind speed.

[0012] Furthermore, the unified control instructions are specifically generated by the ladder diagram program within the programmable logic controller. This ladder diagram program implements an independent control loop thread for each control closed loop. Each thread executes sequentially: analog input sampling, sensor data filtering, setpoint comparison, integrated control calculation, control output, and actuator position feedback comparison. All threads are executed by the PLC scheduler through time-sharing cyclic scanning.

[0013] Furthermore, the method also includes a dynamic uniformity compliance determination step: during the control process, the standard deviation σ_T of temperature values ​​and the standard deviation σ_V of wind speed values ​​at all monitoring points are calculated in real time; When both σ_T and σ_V are simultaneously less than the preset temperature uniformity threshold and the wind speed uniformity threshold are less than the preset wind speed uniformity threshold, and this condition is maintained for a specified time, it indicates that the uniformity of the equipment performance test environment meets the standard.

[0014] Furthermore, the coordinated tuning of the parameter matrix is ​​achieved through the following steps: During the system initialization phase, a step response test is performed on each independent control loop in sequence, and the temperature and wind speed response curves of the sensors in the independent control loop under the unit opening change of the air outlet are collected simultaneously; Based on the two sets of response curves, a set of Kp, Ki, Kd parameters that make the dynamic performance of both the temperature loop and the wind speed loop optimal and the mutual interference minimal are calculated by using a decoupling compensation algorithm or a multivariable frequency domain tuning method, and these parameters are configured into the coupled PID controller of the corresponding closed loop.

[0015] Furthermore, the control algorithm includes a dynamic decoupling compensation process in the integrated operation, the specific process of which is as follows: Within each control cycle, based on the real-time temperature and wind speed values ​​at the current monitoring points, the coupling interference ΔV_T of temperature on wind speed and the coupling interference ΔT_V of wind speed on temperature are calculated using the pre-stored cross-influence coefficient matrix. Before generating the unified control command, ΔV_T is subtracted from the original wind speed deviation signal and ΔT_V is subtracted from the original temperature deviation signal. Then, the control algorithm is used to calculate the compensated deviation signal to actively cancel the dynamic coupling between control channels.

[0016] Furthermore, the spatial location matching algorithm also includes an adaptive re-matching process during operation, specifically: During the control process, the opening degree of the actuator of each air outlet unit is continuously monitored. If the opening degree of a certain air outlet unit continuously reaches the preset limit opening threshold, it is determined that the adjustment capacity of the air outlet unit is saturated. The system will automatically trigger a rematch calculation, temporarily disconnect the fixed link between the air outlet unit with saturated adjustment capacity and its associated monitoring point, and perform global optimization matching again based on the parameters of all current monitoring points and the status of each air outlet unit to generate and switch to a new control link allocation scheme.

[0017] Furthermore, after the dynamic uniformity attainment determination step, the system automatically enters the active uniformity maintenance phase: After determining that the uniformity meets the standard, the target temperature value and target wind speed value in the collaborative control calculation are switched to the average temperature and average wind speed of all monitoring points at the moment the standard is met. At the same time, the integral coefficient in the control algorithm is adjusted to a smaller maintenance value, and the proportional coefficient is increased, with the average temperature and average wind speed as the set targets for continued control.

[0018] The beneficial effects of this application are as follows: This application provides a method for synchronous monitoring of temperature and wind speed for avionics testing. By establishing multiple independent temperature and wind speed control closed loops, each closed loop uses a multivariable PID algorithm to perform integrated collaborative calculation on the temperature and wind speed deviations of the associated monitoring points, and outputs a single command to link and adjust the flow rate and temperature of the air outlet, thereby realizing the coupled control of temperature and wind speed.

[0019] In addition to the purposes, features, and advantages described above, this application has other purposes, features, and advantages. A further detailed description of this application will be provided below with reference to the figures. Attached Figure Description

[0020] The accompanying drawings, which form part of this application, are used to provide a further understanding of this application. The illustrative embodiments and descriptions of this application are used to explain this application and do not constitute an undue limitation of this application. In the drawings: Figure 1 This is an overall schematic diagram of a method for synchronous monitoring of temperature and wind speed for avionics testing according to this application. Detailed Implementation

[0021] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. This application will now be described in detail with reference to the accompanying drawings and embodiments.

[0022] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0023] like Figure 1 As shown, this application provides a method for synchronous monitoring of temperature and wind speed for avionics testing, including: Multiple independent temperature and air velocity control closed loops are established inside the incubator. Each closed loop consists of a controlled air outlet unit and at least one designated and associated monitoring point. At each of the aforementioned monitoring points, the temperature and wind speed values ​​at that monitoring point are collected synchronously and in real time. For each independent control loop, perform collaborative control calculations: compare the real-time temperature and wind speed values ​​collected from the associated monitoring points with the target temperature and target wind speed values ​​set for that control loop, respectively, and generate temperature deviation signals and wind speed deviation signals. The temperature deviation signal and the wind speed deviation signal are processed in an integrated manner using the same control algorithm to generate a unified control command. The parameters of the control algorithm are tuned in a coordinated manner based on the control characteristics of temperature and wind speed. Based on the unified control command, the action of the actuator corresponding to the air outlet unit is adjusted, thereby changing the flow rate and temperature of the airflow delivered by the air outlet unit.

[0024] Based on the above embodiments, each independent control closed loop is a minimal, complete control unit, consisting of a controlled air outlet unit and at least one designated associated monitoring point forming a logical control loop. The air outlet unit has the ability to adjust the airflow and temperature, for example, it is composed of a proportional air valve driven by a servo motor and an electric heating wire or a cooling coil.

[0025] For example, firstly, multiple temperature and speed sensors are arranged in the three-dimensional space inside the temperature chamber according to the test requirements. The installation positions of these sensors constitute the monitoring points. At the same time, multiple air outlets driven by servo valves and whose opening degree can be adjusted independently and precisely are set at the air supply end of the temperature chamber (such as the top static pressure box and the side wall air supply plate). These air outlets are the aforementioned air outlet units.

[0026] After the hardware deployment is completed, it is necessary to establish a control association between the monitoring points and the air outlet units, that is, to form a closed loop. This invention uses a spatial location matching algorithm to achieve this association. Its core logic is to dynamically assign each sensor to an air outlet with the closest spatial distance and store the three-dimensional coordinates of all sensors and all air outlets in the temperature chamber coordinate system.

[0027] The aforementioned spatial location matching algorithm calculates the Euclidean distance from each sensor to all air outlets and selects the air outlet with the closest distance as its main control unit, thereby establishing a one-to-one control link in logic and reducing coupling interference between channels.

[0028] The aforementioned spatial location matching algorithm also includes an adaptive re-matching process during operation, specifically: During the control process, the opening degree of the actuator of each air outlet unit is continuously monitored. If the opening degree of a certain air outlet unit continuously reaches the preset limit opening threshold, it is determined that the adjustment capacity of the air outlet unit is saturated. The system will automatically trigger a rematch calculation, temporarily disconnect the fixed link between the air outlet unit with saturated adjustment capacity and its associated monitoring point, and perform global optimization matching again based on the parameters of all current monitoring points and the status of each air outlet unit to generate and switch to a new control link allocation scheme.

[0029] The control link allocation scheme includes: temporarily disconnecting the fixed link, that is, disconnecting the control link between the saturated air outlet unit and one or more monitoring points currently associated with it; Based on the current status parameters of all monitoring points and the current status of all air outlet units, the global optimization matching algorithm is run again. The optimization objective of the new algorithm is not only to be the closest, but also to include load balancing, maximizing adjustment capability, etc. The status parameters include at least the temperature and wind speed deviation values ​​or their spatial urgency.

[0030] For example, the monitoring point controlled by the original saturated air outlet can be reassigned to another air outlet that is a little further away but whose current opening is only 50% and has sufficient adjustment margin.

[0031] The monitoring point is a specific location in the space used to sense the environmental status of that point. For example, in a large walk-in incubator, monitoring points can be set near multiple key locations such as the front, back, top, and sides of the equipment, and each monitoring point can be assigned an air outlet that has the most direct and fastest spatial impact on it, such as an air supply nozzle located directly above it, thereby forming a one-to-one or one-to-many control closed loop.

[0032] To achieve synchronous monitoring and control, a temperature and speed dual-sensor capable of simultaneously measuring temperature and wind speed is required, such as a miniature wind speed, direction and temperature sensor based on the thermal film principle. In each control cycle, temperature and wind speed signals from all sensors are simultaneously collected and uploaded to achieve synchronous acquisition.

[0033] The above rules are arranged as follows: First, based on the effective internal volume of the chamber and the actual external dimensions of the device under test, a cubic monitoring area is determined in three-dimensional space. This area should completely cover the device under test, and leave a certain space on the outer side of each surface to monitor the boundary layer where the device under test exchanges heat with the chamber environment.

[0034] Then, temperature and velocity sensors are arranged at 14 locations, including the eight vertices and the center points of the six outer surfaces of the aforementioned cubic monitoring area. These 14 points form a three-dimensional sensing network covering all six directions and corners of the device under test: front, back, left, right, top, and bottom. The vertices are used to capture the extreme points of the spatial field in three-dimensional directions, while the face centers are used to sense the state of the central area of ​​each major plane. Through these 14 points (in cases with lower requirements, only 8 vertices can be arranged, or 8 vertices plus the center points of a few key surfaces), comprehensive synchronous monitoring of the device's surrounding environmental parameters can be achieved with the most economical sensor cost.

[0035] For each independent control closed loop, a coordinated control operation is performed. For example, when associating monitoring point A with air outlet unit A1, the following process is executed: The real-time temperature and wind speed values ​​collected by monitoring point A associated with the closed loop are compared with the target temperature and target wind speed values ​​preset for the closed loop. The target values ​​can be uniformly set according to the requirements of the test outline, or different values ​​can be set for closed loops at different locations to achieve gradient environment simulation.

[0036] Then, deviations are generated, and temperature deviation and wind speed deviation are calculated as deviation signals. The two deviation signals together constitute the current control error state of the closed loop.

[0037] Based on the above embodiments, in the traditional method, the temperature deviation signal and the wind speed deviation signal are usually sent to two independent controllers for independent calculation, and then two control commands are output separately, resulting in the two adjustment processes being disconnected and the responses being asynchronous. Therefore, in this embodiment, the same control algorithm is used to perform integrated calculations on the temperature deviation signal and the wind speed deviation signal to generate a unified control command.

[0038] This control algorithm can be implemented using a multivariable PID controller, and the operation of the multivariable PID control algorithm is as follows: A coupled PID controller is set up for each control closed loop. The input of the controller is a two-dimensional deviation signal e(k)=[e_T(k), e_V(k)]^T, where e_T(k) is the temperature deviation, that is, the change in deviation between the current cycle and the previous cycle, e_V(k) is the wind speed deviation, k represents the k-th control cycle, and T is the transpose sign. The controller outputs a one-dimensional control quantity u(k). This single control quantity u(k) is used simultaneously to adjust the opening of the air outlet damper and the heating or cooling power. The control law refers to a mathematical mapping relationship used to map a two-dimensional deviation signal into a unified control quantity. In this embodiment, the control law is implemented using a 1x2 gain matrix, and its discrete form can be expressed as: u(k) = Kp*e(k)+Ki*Σe(j)+Kd*Δe(k), where Kp, Ki, and Kd are parameter matrices or coefficients that have been co-tuned rather than independent scalars, so that the control quantity u(k) can simultaneously respond to the deviations and trends of temperature and wind speed.

[0039] For example, for the proportional term, Kp can be regarded as a row vector [Kp_T, Kp_V], then Kp*e(k) = Kp_T * e_T(k) + Kp_V * e_V(k), where e_T(k) is the temperature deviation and e_V(k) is the wind speed deviation. The weighted sum of the two determines the proportional adjustment intensity. If Kp_T is large, it means that the controller is more sensitive to the temperature deviation; if Kp_V is large, it is more sensitive to the wind speed deviation. This means that the control quantity u is the weighted sum of the temperature deviation and the wind speed deviation. The ratio of Kp_T to Kp_V reflects the weight allocation of the controller when responding to the temperature deviation and the wind speed deviation.

[0040] Based on the same principle, the integral term Ki and the differential term Kd also adopt the matrix form of the corresponding dimension to ensure that the historical cumulative effect and rate of change of temperature and wind speed deviation are synchronously coupled into the unified control quantity.

[0041] The purpose of coordinated tuning is to find a set of optimal Kp, Ki, Kd parameters through system identification and optimization algorithms, so that the control quantity u(k) can respond to the deviation of temperature and wind speed, the accumulation of deviation (integral term), and the trend of deviation change (differential term) with the best dynamic performance. Since the Kp, Ki, Kd parameters are tuned based on the joint response of the coupled system, this set of parameters contains decoupling information. Therefore, the generation process of the control quantity u(k) itself actively compensates for the coupling between channels, thereby minimizing the mutual interference between the temperature loop and the wind speed loop.

[0042] Specifically, the coordinated tuning is achieved through the following steps: During the system initialization phase, a step response test is performed on each independent control loop in sequence, and the temperature and wind speed response curves of the sensors in the independent control loop are collected simultaneously under the unit opening change of the air outlet; Based on the two sets of response curves, a set of Kp, Ki, and Kd parameters that make the dynamic performance of both the temperature loop and the wind speed loop optimal and the mutual interference minimal are calculated by using a decoupling compensation algorithm or a multivariable frequency domain tuning method, and these parameters are configured into the coupled PID controller of the corresponding closed loop.

[0043] For example, during initial debugging or regular maintenance, the system enters the initialization or self-tuning phase and operates each independent control loop in sequence. The specific operation method is: fix all other conditions and apply a step signal with a unit opening change only to the air outlet unit associated with the closed loop. While applying a step change, the temperature response curve and wind speed response curve returned by the associated sensors within the closed loop are simultaneously acquired. These two curves contain all the information about the dynamic characteristics of the closed loop: the gain, time constant, and pure time delay of the temperature loop; the gain, time constant, and pure time delay of the wind speed loop; and the coupling relationship between the two loops, such as the dynamic effect of the change in the opening of the damper on the temperature. Based on the two acquired response curves, the controller parameters are calculated using a multivariable system identification and tuning method. Specifically, the following methods can be used: Decoupling compensation algorithm: First, identify the coupling model of the closed loop (such as the transfer function matrix) based on the response curve, then design a feedforward decoupler, and then perform conventional PID tuning on the two pseudo-independent loops after decoupling. Multivariable frequency domain tuning method: Based directly on frequency response data, with the goal of satisfying frequency domain indicators such as gain margin, phase margin, and coupling degree, optimize the calculation of Kp, Ki, Kd matrices; Regardless of the method used, the ultimate goal is to calculate a set of Kp, Ki, Kd parameters that achieve the optimal dynamic performance of both the temperature loop and the wind speed loop, while minimizing the mutual dynamic interference between the two loops. This set of parameters is then configured into the corresponding coupled PID controller function block of the closed loop, enabling it to have optimal cooperative control capability for that specific physical location.

[0044] The unified control instructions are generated by the ladder diagram program within the programmable logic controller. This ladder diagram program implements an independent control loop thread for each control closed loop. Each thread executes sequentially: analog input sampling, sensor data filtering, setpoint comparison, integrated control calculation, control output, and actuator position feedback comparison. All threads are executed by the PLC scheduler in a time-sharing cyclic scan.

[0045] The above process uses a programmable logic controller (PLC) as the core control unit. The PLC has a deterministic scan cycle and a certain anti-interference capability. Furthermore, the control logic is implemented through ladder diagram programs within the PLC, creating an independent control loop thread for each independent control closed loop.

[0046] Alternatively, other programming languages ​​conforming to the IEC 61131-3 standard, such as Structured Text (ST), can be used to write control algorithms to achieve the same function. This structured text code can be directly embedded into the PLC operating environment. Specific implementation methods are not described in detail, but can be referred to existing technologies.

[0047] Each control loop thread executes the following steps sequentially within each PLC scan cycle: Read the analog signals from the sensors associated with this thread and convert them into digital quantities; Digital filtering (such as moving average filtering or first-order lag filtering) is applied to the sampled values ​​to eliminate on-site noise and interference. Read the target temperature and target wind speed of the closed loop, compare them with the filtered actual values, and calculate the deviations e_T and e_V; Call the encapsulated multivariable PID algorithm function block, input e_T and e_V, and calculate the control command u; The control command u is converted into an analog signal and sent to the actuator through the PLC's analog output module. This actuator can be a servo valve driver or a heater regulator. The valve position feedback signal of the servo valve is read and compared with the output control command to form a position follow-up inner loop, ensuring that the actuator is accurately positioned.

[0048] Based on the above embodiments, the method also includes a dynamic uniformity compliance determination process, which is used to assess whether the environment meets the test requirements. Specifically, during system operation, the standard deviation σ_T of temperature values ​​and the standard deviation σ_V of wind speed values ​​of all monitoring points are calculated in real time. The standard deviation is a core indicator in statistics for measuring the dispersion of a set of data. The smaller the value, the closer the readings of all monitoring points are to their average value, that is, the better the spatial uniformity.

[0049] According to the requirements of the test standard, two thresholds are preset: temperature uniformity threshold θ_T (e.g., ±0.5℃ or ±1.0℃) and wind speed uniformity threshold θ_V (e.g., ±0.2m / s or ±0.5m / s). The judgment logic is an AND relationship, that is, it must be satisfied at the same time: the calculated temperature standard deviation σ_T < θ_T, and the wind speed standard deviation σ_V < θ_V.

[0050] Because there may be instantaneous fluctuations, it is necessary to add a duration requirement. For example, the above-mentioned dual compliance status must be continuously and stably maintained for a specified time, such as 5 minutes. Only when σ_T and σ_V are below the threshold for multiple consecutive calculation cycles can it be finally determined that the uniformity of the equipment performance test environment has met the standard. At this point, a prompt signal can be given to indicate that the environment has met the testing requirements and that formal equipment performance testing or data recording can begin.

[0051] After the dynamic uniformity compliance determination step, it automatically enters the active uniformity maintenance stage: After determining that the uniformity meets the standard, the target temperature value and target wind speed value in the collaborative control calculation are switched to the average temperature and average wind speed of all monitoring points at the moment the standard is met. At the same time, the integral coefficient in the control algorithm is adjusted to a smaller maintenance value, and the proportional coefficient is increased, with the average temperature and average wind speed as the set targets for continued control.

[0052] Once the uniformity is determined to have stabilized and met the target, the system automatically enters the active uniformity maintenance phase. At this point, the initial theoretical global target value is no longer used. Instead, the target temperature and target wind speed values ​​in the collaborative control calculations of each independent control loop are switched to the average of the actual measured values ​​at all monitoring points at the instant the target is met. The new temperature setpoint T_set_new = the average of the temperature readings Ti at all monitoring points at the moment the target is reached.

[0053] The new wind speed setpoint V_set_new = the average value of the wind speed readings Vi at all monitoring points at the moment the target is met.

[0054] This average value represents a uniform and stable actual environmental state. Using this average value as a new target, the control target changes from reaching a certain preset absolute value to maintaining the uniform distribution state that has been achieved. While switching the target settings, adjust the parameters in the control algorithm: Adjust the integral coefficient Ki to a smaller maintenance value (e.g., reduce it to 1 / 3 or 1 / 2 of the original set value); because during the maintenance phase, the main task is to suppress small disturbances rather than eliminate large steady-state errors, reducing the integral action can prevent the integrator from saturating due to excessive accumulation under small deviations, thereby avoiding low-frequency oscillations in the system.

[0055] Increasing the proportional gain Kp makes the system more sensitive and faster to small environmental disturbances, enabling it to quickly generate a small corrective action.

[0056] Using the new average values ​​(T_set_new, V_set_new) as the target, and with the adjusted control parameters, control continues. Since the setpoint has been switched to the actual average value, there is no need to continuously make large adjustments in pursuit of an absolute theoretical value. Under the premise of maintaining environmental uniformity, the frequency and amplitude of the actions of each actuator will decrease, thereby reducing energy consumption and wear of mechanical parts, and improving the long-term reliability and lifespan of the entire temperature chamber control system.

[0057] Based on multivariable control, a feedforward decoupling stage can be added to further improve control accuracy, especially for strongly coupled operating conditions. Specifically: During the system modeling or debugging phase, a cross-influence coefficient matrix is ​​obtained. This matrix quantifies the steady-state influence coefficient of temperature change on wind speed and the steady-state influence coefficient of wind speed change on temperature near the current typical operating point. This matrix is ​​then pre-stored in the controller's memory. Then, within each control cycle, the following steps are performed: Read the real-time temperature value T_act and the real-time wind speed value V_act of the current monitoring point.

[0058] Using the pre-stored cross-influence coefficient matrix, the estimated coupling interference caused by the current temperature T_act to the wind speed is calculated as ΔV_T = M_TV * (T_act - T_ref); and the estimated coupling interference caused by the current wind speed V_act to the temperature is calculated as ΔT_V = M_VT * (V_act - V_ref), where M_TV and M_VT are the cross-influence coefficients from temperature to wind speed and from wind speed to temperature, respectively, and T_ref and V_ref are the set reference values ​​for the corresponding variables.

[0059] Before feeding the original deviation signals e_T and e_V into the multivariable PID controller, feedforward compensation is performed first: The calculated temperature coupling interference ΔV_T is subtracted from the original wind speed deviation e_V to obtain the compensated wind speed deviation e_V-ΔV_T. The calculated wind speed coupling interference ΔT_V is subtracted from the original temperature deviation e_T to obtain the compensated temperature deviation e_T-ΔT_V.

[0060] The compensated deviation signal is input into the multivariable PID controller, and after integrated collaborative calculation, a unified control command is output to drive the temperature and wind speed actuators respectively. The above process is equivalent to predicting the amount of disturbance based on the model before the disturbance acts on the controlled object and produces a measurable effect, and subtracting it from the deviation signal in advance. This makes the deviation signal received by the controller more directly reflect the difference between the set value and the state of the controlled object itself, thereby generating more accurate control commands and canceling the coupling between the temperature and wind speed control channels.

[0061] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A method for synchronous monitoring of temperature and wind speed for avionics testing, characterized in that: include: Multiple independent temperature and air velocity control closed loops are established inside the incubator. Each closed loop consists of a controlled air outlet unit and at least one designated and associated monitoring point. At each of the aforementioned monitoring points, the temperature and wind speed values ​​at that monitoring point are collected synchronously and in real time. For each independent control loop, perform collaborative control calculations: compare the real-time temperature and wind speed values ​​collected from the associated monitoring points with the target temperature and target wind speed values ​​set for that control loop, respectively, and generate temperature deviation signals and wind speed deviation signals. The temperature deviation signal and the wind speed deviation signal are processed in an integrated manner using the same control algorithm to generate a unified control command. The parameters of the control algorithm are tuned in a coordinated manner based on the control characteristics of temperature and wind speed. Based on the unified control command, the action of the actuator corresponding to the air outlet unit is adjusted, thereby changing the flow rate and temperature of the airflow delivered by the air outlet unit.

2. The method for synchronous monitoring of temperature and wind speed for avionics testing according to claim 1, characterized in that: To establish the multiple independent temperature and velocity control closed loops, specifically, multiple temperature and velocity dual-sensor sensors are regularly arranged as monitoring points in the three-dimensional space inside the temperature chamber. Multiple air outlets driven by servo valves are set at the air supply end of the incubator as the air outlet units; By using a spatial location matching algorithm, each sensor is dynamically assigned a spatially closest air outlet, and a corresponding control link is established.

3. The method for synchronous monitoring of temperature and wind speed for avionics testing according to claim 2, characterized in that: The specific arrangement of the rules is as follows: Based on the effective volume of the temperature chamber and the size of the device under test, a cubic monitoring area that completely covers the device is determined; the temperature and speed combined sensor is arranged at the vertices and the center point of each face of this cubic area to form at least 9 key monitoring points, so as to achieve all-round synchronous monitoring of the environmental parameters around the device with the minimum number of sensors.

4. The method for synchronous monitoring of temperature and wind speed for avionics testing according to claim 1, characterized in that: The control algorithm specifically adopts a multivariable PID control algorithm, and its operation process is as follows: For each control closed loop, a coupled PID controller is set up. The input of the controller is a two-dimensional deviation signal e(k)=[e_T(k), e_V(k)]^T, where e_T(k) is the temperature deviation and e_V(k) is the wind speed deviation. The controller outputs a one-dimensional control quantity u(k), and the control law is implemented through a 1x2 gain matrix, and u(k) = Kp*e(k)+Ki*Σe(j)+Kd*Δe(k), where Kp, Ki, and Kd are parameter matrices or coefficients that have been co-tuned, so that the control quantity u(k) can simultaneously respond to the deviation and changing trend of temperature and wind speed.

5. A method for synchronous monitoring of temperature and wind speed for avionics testing according to claim 1, characterized in that: The unified control instructions are generated by the ladder diagram program within the programmable logic controller. This ladder diagram program implements an independent control loop thread for each control closed loop. Each thread executes sequentially: analog input sampling, sensor data filtering, setpoint comparison, integrated control calculation, control output, and actuator position feedback comparison. All threads are executed by the PLC scheduler in a time-sharing cyclic scan.

6. The method for synchronous monitoring of temperature and wind speed for avionics testing according to claim 1, characterized in that: The method also includes a dynamic uniformity compliance determination step: during the control process, the standard deviation σ_T of temperature values ​​and the standard deviation σ_V of wind speed values ​​at all monitoring points are calculated in real time; When both σ_T and σ_V are simultaneously less than the preset temperature uniformity threshold and the wind speed uniformity threshold are less than the preset wind speed uniformity threshold, and this condition is maintained for a specified time, it indicates that the uniformity of the equipment performance test environment meets the standard.

7. A method for synchronous monitoring of temperature and wind speed for avionics testing according to claim 4, characterized in that: The coordinated tuning of the parameter matrix is ​​achieved through the following steps: During the system initialization phase, a step response test is performed on each independent control loop in sequence, and the temperature and wind speed response curves of the sensors in the independent control loop are collected simultaneously under the unit opening change of the air outlet; Based on the two sets of response curves, a set of Kp, Ki, Kd parameters that make the dynamic performance of both the temperature loop and the wind speed loop optimal and the mutual interference minimal are calculated by using a decoupling compensation algorithm or a multivariable frequency domain tuning method, and these parameters are configured into the coupled PID controller of the corresponding closed loop.

8. A method for synchronous monitoring of temperature and wind speed for avionics testing according to claim 1, characterized in that: The control algorithm has a dynamic decoupling compensation process in the integrated operation, the specific process of which is as follows: Within each control cycle, based on the real-time temperature and wind speed values ​​at the current monitoring points, the coupling interference ΔV_T of temperature on wind speed and the coupling interference ΔT_V of wind speed on temperature are calculated using the pre-stored cross-influence coefficient matrix. Before generating the unified control command, ΔV_T is subtracted from the original wind speed deviation signal and ΔT_V is subtracted from the original temperature deviation signal. Then, the control algorithm is used to calculate the compensated deviation signal to actively cancel the dynamic coupling between control channels.

9. A method for synchronous monitoring of temperature and wind speed for avionics testing according to claim 2, characterized in that: The spatial location matching algorithm also includes an adaptive re-matching process during operation, specifically: During the control process, the opening degree of the actuator of each air outlet unit is continuously monitored. If the opening degree of a certain air outlet unit continuously reaches the preset limit opening threshold, it is determined that the adjustment capacity of the air outlet unit is saturated. The system will automatically trigger a rematch calculation, temporarily disconnect the fixed link between the air outlet unit with saturated adjustment capacity and its associated monitoring point, and perform global optimization matching again based on the parameters of all current monitoring points and the status of each air outlet unit to generate and switch to a new control link allocation scheme.

10. A method for synchronous monitoring of temperature and wind speed for avionics testing according to claim 6, characterized in that: After the dynamic uniformity compliance determination step, the system automatically enters the active uniformity maintenance phase: After determining that the uniformity meets the standard, the target temperature value and target wind speed value in the collaborative control calculation are switched to the average temperature and average wind speed of all monitoring points at the moment the standard is met. At the same time, the integral coefficient in the control algorithm is adjusted to a smaller maintenance value, and the proportional coefficient is increased, with the average temperature and average wind speed as the set targets for continued control.

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