Indoor temperature control adjusting method and system based on computer automation control

Abstract

The invention relates to the field of temperature control regulation, and discloses an indoor temperature control regulation method and system based on computer automatic control, which are used for solving the problem that a sensor cannot accurately acquire indoor temperature due to the influence of indoor space and wall factors during indoor temperature control regulation, and comprises the following steps: acquiring indoor space information; the method comprises the following steps of: obtaining an indoor space irregularity degree through evaluation, obtaining the number of set sensor groups according to the indoor space irregularity degree, obtaining indoor wall information, averagely dividing each wall into n sub-regions, recording the n sub-regions as sub-setting regions, and obtaining a sensor suitability index of each sub-setting region through evaluation, the setting position of the sensor group is selected according to the sensor suitability index, the initial temperature data and the humidity data are obtained, the initial temperature data are corrected to obtain the actual temperature data, the final control signal is obtained through the PID control algorithm, the indoor temperature is adjusted, and the accuracy of indoor temperature obtaining and temperature adjusting is effectively improved.

Description

Technical Field

[0001] The present invention relates to the field of temperature control and regulation, and more specifically to an indoor temperature control and regulation method and system based on computer automatic control. Background Art

[0002] Automated indoor temperature control is a system that uses intelligent technology to automatically monitor and adjust indoor temperature. It uses sensors to collect indoor environmental data in real time, and combines control algorithms to automatically adjust the operating status of temperature control devices such as air conditioners, heaters, and ventilation equipment to keep the indoor temperature within the set comfortable range.

[0003] The existing automated indoor temperature control method usually sets up a group of sensors indoors, collects indoor temperature, humidity and other environmental parameters in real time based on the sensors, and adjusts the operating state of the temperature control equipment through the PID control algorithm to achieve the set target temperature.

[0004] For example, the method for controlling and / or regulating indoor temperature in a building disclosed in the invention patent publication No. CN101288036B includes switching between heating, standby and cooling according to the uncertainty of internal heat gain and external heat gain determined at the construction stage, wherein the uncertainty is determined by the lower limit of external heat and the upper limit of external heat. The method can generally be used to control and / or regulate indoor temperature or temperature within a region, and can be particularly used in buildings that are cooled and heated by building materials, such as thermally active component systems TABS.

[0005] For example, the indoor environment control method, device and speaker disclosed in the invention patent announcement with the announcement number CN106885332B include: the speaker detects the indoor temperature information and / or humidity information of the room where the speaker is located; the speaker determines whether the indoor temperature information and / or humidity information meets the preset conditions; if it is determined that the indoor temperature information and / or humidity information does not meet the preset conditions, the speaker controls the corresponding household appliances to adjust the indoor temperature and / or humidity according to the indoor temperature information and / or humidity information. The indoor environment control method of the embodiment of the present invention can control the corresponding household appliances to automatically adjust the indoor temperature and / or humidity according to the indoor temperature and humidity conditions, thereby improving the user experience.

[0006] However, in the process of implementing the technical solution of the invention in the embodiments of the present application, the present application found that the above technology has at least the following technical problems:

[0007] However, in actual applications, due to the influence of indoor space, only one set of sensors may not be able to accurately collect indoor environmental data, and the data collected by sensors in different locations will also be different. If environmental data is collected according to the original method, the indoor temperature cannot be accurately obtained, reducing the accuracy of temperature regulation. Summary of the invention

[0008] In order to overcome the above-mentioned defects of the prior art, the present invention provides an indoor temperature control and adjustment method and system based on computer automatic control to solve the problems existing in the above-mentioned background technology.

[0009] To achieve the above object, the present invention provides the following technical solutions:

[0010] The indoor temperature control and adjustment method based on computer automatic control comprises the following steps: step 1: obtaining indoor space information, evaluating the degree of indoor space irregularity according to the indoor space information, obtaining the number of sensor groups to be set according to the degree of indoor space irregularity, wherein the sensor group comprises a temperature sensor and a humidity sensor; step 2: obtaining indoor wall information, wherein the indoor wall information is the orientation direction of the wall; each wall is evenly divided into n sub-areas, which are recorded as sub-setting areas; step 3: obtaining the sensor suitability index of each sub-setting area according to the indoor wall information evaluation; step 4: selecting the location of the sensor group according to the sensor suitability index of each sub-setting area and the number of sensor groups; step 5: obtaining initial temperature data and humidity data in real time through the temperature sensor and humidity sensor in the sensor group, and correcting the initial temperature data through the humidity data to obtain actual temperature data; step 6: obtaining a final control signal through a PID control algorithm according to the actual temperature data; step 7: adjusting the indoor temperature according to the final control signal, and continuing to return to step 5 to continue collecting the initial temperature data and humidity data.

[0011] Preferably, the steps for obtaining the degree of irregularity of the indoor space are: scanning the indoor space through computer vision technology, and generating a three-dimensional model of the indoor space, and obtaining the indoor space volume according to the three-dimensional model of the space; obtaining the surface area of ​​the space through a three-dimensional model tool, the surface area is the total area of ​​all surfaces in the space, such as walls, floors, ceilings, etc.; and obtaining the degree of irregularity of the indoor space according to the spatial volume and surface area evaluation.

[0012] Preferably, the step of obtaining the number of sensor groups to be set according to the degree of irregularity of the indoor space is: presetting an irregularity threshold, comparing the degree of irregularity of the indoor space with the irregularity threshold, if the degree of irregularity of the indoor space is less than the irregularity threshold, it is judged that the degree of irregularity of the indoor space is small, and a group of sensors is set indoors; if the degree of irregularity of the indoor space is greater than or equal to the irregularity threshold, it is judged that the degree of irregularity of the indoor space is large, and the number of sensors needs to be increased, and the number of sensor groups to be set is obtained according to the evaluation of the degree of irregularity of the indoor space.

[0013] Preferably, the sensor suitability index acquisition step is: acquiring the orientation direction of the sub-setting area, taking the south direction as the base coordinate, and obtaining the radiation reception coefficient according to the orientation direction and the base coordinate; acquiring the coordinates of the center point of the sub-setting area and the coordinates of the temperature control source, and calculating the distance between the sub-setting area and the temperature control source according to the coordinates of the center point of the sub-setting area and the coordinates of the temperature control source, which is recorded as the temperature control distance, and obtaining the temperature change sensitivity coefficient according to the temperature control distance; acquiring the average height of the indoor space, the maximum ceiling height of the indoor space and the lowest ground height through the three-dimensional model of the indoor space, and evaluating the maximum position height of the air convection according to the average height of the indoor space, the maximum ceiling height, the degree of irregularity of the indoor space and the lowest ground height; acquiring the height position of the center point of each sub-setting area, which is recorded as the height position of the sub-setting area, and obtaining the air convection coefficient according to the height position of the sub-setting area and the height of the maximum position of air convection, and the specific acquisition method is: Where AC is the air convection coefficient, h set Indicates the height position of the subsetting area, h max Expressed as the maximum air convection height, h avg Expressed as the average height of the indoor space, h fl It is expressed as the lowest ground height; the radiation reception coefficient, temperature change sensitivity coefficient and air convection coefficient are normalized, and the sensor suitability index is evaluated based on the normalized radiation reception coefficient, temperature change sensitivity coefficient and air convection coefficient.

[0014] Preferably, the steps for obtaining the radiation reception coefficient are: taking the due south direction as a unit vector and the unit vector as a reference vector; obtaining the normal vector of the sub-setting area and calculating the cosine value of the angle between the normal vector and the reference vector; using the maximum value function to obtain the radiation reception coefficient according to the cosine value of the angle between the normal vector and the reference vector.

[0015] Preferably, the step of selecting the position for setting the sensor group according to the sensor suitability index and the number of sensor groups of each sub-setting area is as follows: sorting the sensor suitability index of each sub-setting area from high to low to obtain a sub-setting area sequence set, wherein the sub-setting area sequence set includes the sorting order of the sub-setting areas and the position coordinates of each sub-setting area; if the number of sensor groups is one, selecting the sub-setting area with the highest sensor suitability index for sensor group setting, and the setting position is the middle of the sub-setting area; if the number of sensor groups is greater than one, selecting a corresponding number of sub-setting areas from high to low in the sub-setting area sequence set according to the number of sensor groups, and setting the sensor group in the middle position of the selected sub-setting area.

[0016] Preferably, the step of acquiring the initial temperature data and humidity data in real time through the temperature sensor and humidity sensor in the sensor group is: if the number of sensor groups is one, directly acquiring the initial temperature data and humidity data of the sub-setting area where the sensor group is located; if the number of sensor groups is greater than one, calculating the average sensor suitability index of the sub-setting area where the sensor group is located, and obtaining the initial temperature data according to the sensor suitability index of the sub-setting area, and the specific acquisition method is: Where, T 初始 Expressed as initial temperature data, ST i is the sensor suitability index of the sub-setting area where the i-th sensor group is located, ST 均 is the average sensor suitability index, T 初i is the temperature data obtained for the sub-setting area where the i-th sensor group is located, and W represents the number of sensor groups; calculates the average humidity data obtained for the sub-setting area where the sensor group is located, and records the average humidity data as humidity data.

[0017] Preferably, the step of correcting the initial temperature data by using the humidity data to obtain the actual temperature data is: obtaining a temperature correction factor according to the humidity data; and adding the initial temperature data and the temperature correction factor to obtain the actual temperature data.

[0018] Preferably, the steps of obtaining the final control signal through the PID control algorithm are: setting the sampling interval and setting the target temperature, calculating the temperature error based on the actual temperature data and the set target temperature; obtaining the temperature error at each time point, and using trapezoidal integration to calculate the integral term; calculating the differential term through the difference method based on the temperature error at each time point; and obtaining the final control signal based on a comprehensive evaluation of the temperature error, the integral term and the differential term.

[0019] Preferably, an indoor temperature control and adjustment system based on computer automatic control comprises: a sensor group quantity acquisition module, which is used to acquire indoor space information, and obtain the degree of indoor space irregularity according to the indoor space information, and obtain the number of sensor groups to be set according to the degree of indoor space irregularity, wherein the sensor group comprises a temperature sensor and a humidity sensor; a sensor group setting module, which is used to acquire indoor wall information, divide the wall into n sub-setting areas, obtain the sensor suitability index of each sub-setting area according to the indoor wall information evaluation, and select the location of the sensor group according to the sensor suitability index and the number of sensor groups; a temperature correction module, which is used to acquire humidity data through a humidity sensor, acquire initial temperature data through a temperature sensor, correct the initial temperature data through the humidity data to obtain actual temperature data, and transmit the actual temperature data to a control signal acquisition module; a control signal acquisition module, which is used to obtain a final control signal through a PID control algorithm according to the actual temperature data, and transmit the final control signal to a temperature adjustment module; and a temperature adjustment module, which is used to adjust the indoor temperature according to the final control signal.

[0020] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0021] 1. Obtain indoor space information, evaluate the degree of indoor space irregularity based on the indoor space information, and determine the number of sensor groups to be set based on the degree of indoor space irregularity, so that sensors can be reasonably arranged for areas with different space shapes and characteristics. Spaces with high irregularity may lead to uneven distribution of environmental parameters such as temperature and humidity. By increasing the number of sensor groups, the monitoring accuracy of environmental changes can be improved, ensuring the comprehensiveness and accuracy of data, thereby optimizing the indoor temperature control effect, reducing resource waste, and improving the system's operating efficiency and user experience.

[0022] 2. The sensor suitability index of each sub-setting area is obtained based on the indoor wall information evaluation. The location of the sensor group is selected based on the sensor suitability index of each sub-setting area and the number of sensor groups, which can accurately match the functional requirements of the sensor with the actual environmental characteristics. Areas with high sensor suitability index usually have better data collection conditions, such as strong radiation receiving ability or stable environmental parameters, thereby improving the working efficiency and monitoring accuracy of the sensor. By optimizing the setting location, the use of redundant sensors can be reduced, the system cost can be reduced, and the overall effect and intelligence level of indoor environmental control can be improved.

[0023] 3. Correcting the initial temperature data with humidity data to obtain the actual temperature data can more accurately reflect the real thermal comfort state of the indoor environment. Humidity has a significant impact on the perceived temperature. For example, high humidity may cause a stuffy feeling, while low humidity may make the human body feel cooler. Combining humidity data with temperature correction can make up for the shortcomings of simple temperature measurement, making the control system more in line with the user's comfort needs, thereby improving the accuracy of temperature control and user experience, while optimizing energy efficiency.

[0024] 4. According to the actual temperature data, the final control signal is obtained through the PID control algorithm, which can realize the precise dynamic adjustment of the temperature control equipment and ensure that the indoor temperature reaches the target value quickly and stably. The PID control algorithm generates the optimal control signal by comprehensively considering the current temperature error (proportional term), historical error (integral term) and error change trend (differential term), which not only avoids overshoot and oscillation during the temperature adjustment process, but also effectively reduces the steady-state error. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 A flow chart of an indoor temperature control method based on computer automated control provided in an embodiment of the present application.

[0026] Figure 2 A schematic diagram of the radiation reception coefficient of the sub-setting area in the embodiment of the present application.

[0027] Figure 3 This is a structural diagram of an indoor temperature control and regulation system based on computer automated control provided in an embodiment of the present application. DETAILED DESCRIPTION

[0028] The technical solution of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the present invention. In addition, the forms of the various structures recorded in the following embodiments are merely illustrative. The indoor temperature control method and system based on computer automatic control involved in the present invention are not limited to the various structures recorded in the following embodiments. All other implementations obtained by ordinary technicians in this field without making creative work belong to the scope of protection of the present invention.

[0029] The present invention provides an indoor temperature control method based on computer automatic control, such as Figure 1 As shown, the following steps are included:

[0030] Step 1: Acquire indoor space information, evaluate the degree of indoor space irregularity according to the indoor space information, and obtain the number of sensor groups to be set according to the degree of indoor space irregularity. The sensor groups include temperature sensors and humidity sensors.

[0031] In this embodiment, it should be specifically explained that the steps for obtaining the degree of irregularity of the indoor space are:

[0032] Through computer vision technology, the indoor space is scanned and a three-dimensional model of the indoor space is generated. The indoor space volume is obtained based on the three-dimensional model of the space.

[0033] Use 3D modeling tools to obtain the surface area of ​​the space. The surface area is the total area of ​​all surfaces in the space, such as walls, floors, ceilings, etc.

[0034] The degree of indoor space irregularity is obtained by evaluating the spatial volume and surface area. The specific method is as follows:

[0035]

[0036] In the formula, UT represents the degree of irregularity of the indoor space, A represents the surface area, and V represents the volume of the space. Used to normalize the effects of volume for comparison with surface area.

[0037] In this embodiment, it should be specifically explained that the steps of scanning the indoor space and generating a three-dimensional model of the indoor space by using computer vision technology are as follows:

[0038] Place the scanning device at different locations in the room and start scanning the space. During the scanning process, the device will obtain depth information and color information in the space through laser, infrared or structured light. Capture the scan data at each location and scan from multiple locations. After each scan, move the device to a new location to ensure that all areas of the room are covered;

[0039] The data from the scanning process may contain noise. To remove inaccurate point cloud data and fill in missing data, commonly used techniques include filtering and surface reconstruction.

[0040] After multiple scans, point cloud data from multiple perspectives are obtained. The point cloud data from multiple perspectives are merged through point cloud registration technology, and the point cloud data from different perspectives are aligned into a unified coordinate system;

[0041] Through Poisson surface reconstruction, the point cloud data is converted into a three-dimensional mesh. In the process of converting the point cloud to the mesh, there may be holes or incomplete areas. At this time, an automatic repair algorithm can be used to fill the missing areas and generate a complete three-dimensional model.

[0042] The Poisson surface reconstruction algorithm is a 3D surface reconstruction method based on the Poisson equation, which is used to reconstruct a smooth and continuous 3D surface from sparse point cloud data. The algorithm solves a Poisson equation and uses the normal vector information of the point cloud to infer and fill in the missing surface area. The core idea of ​​the algorithm is to regard the point cloud data as a solution to a passive Poisson equation, and obtain a smooth and physically compliant 3D surface by minimizing an energy function based on the local normal vector of the point cloud.

[0043] In this embodiment, it should be specifically explained that the steps of obtaining the number of sensor groups to be set according to the degree of irregularity of the indoor space are as follows:

[0044] Preset an irregularity threshold, compare the indoor space irregularity with the irregularity threshold, if the indoor space irregularity is less than the irregularity threshold, it is judged that the indoor space irregularity is small, and a group of sensors is set indoors; if the indoor space irregularity is greater than or equal to the irregularity threshold, it is judged that the indoor space irregularity is large, and the number of sensors needs to be increased. The number of sensor groups to be set is obtained according to the indoor space irregularity evaluation. The specific acquisition method is:

[0045]

[0046] Where N sg It is represented by the number of sensor groups, UT is represented by the degree of indoor space irregularity, UT′ is represented by the irregularity threshold, Indicates that The calculation result is rounded up.

[0047] Step 2: Obtain indoor wall information from the building archives, where the indoor wall information is the orientation of the wall; divide each wall into n sub-areas on average, recorded as sub-setting areas;

[0048] Step 3: Evaluate the sensor suitability index of each sub-setting area based on the indoor wall information;

[0049] In this embodiment, it should be specifically explained that the steps for obtaining the sensor suitability index are:

[0050] Get the orientation direction of the sub-setting area, take the south direction as the base coordinate, and get the radiation reception coefficient according to the orientation direction and the base coordinate;

[0051] Get the coordinates of the center point of the sub-setting area and the coordinates of the temperature control source. Calculate the distance between the sub-setting area and the temperature control source based on the coordinates of the center point of the sub-setting area and the coordinates of the temperature control source, record it as the temperature control distance, and get the temperature change sensitivity coefficient based on the temperature control distance. The specific acquisition method is:

[0052]

[0053] In the formula, SC represents the temperature change sensitivity coefficient, and TC represents the temperature control distance;

[0054] The average height of the indoor space is obtained through the three-dimensional model of the indoor space, and the maximum ceiling height and the lowest ground height of the indoor space are obtained. According to the average height of the indoor space, the maximum ceiling height, the degree of irregularity of the indoor space and the lowest ground height, the maximum position height of air convection is evaluated. The specific acquisition method is as follows:

[0055] h max =h avg +UT×(h ce -h fl );

[0056] In the formula, h max Expressed as the maximum air convection height, h avg It is expressed as the average height of the indoor space, UT is expressed as the degree of irregularity of the indoor space, h ce Expressed as the maximum ceiling height, h fl Expressed as the lowest ground height;

[0057] Get the height position of the center point of each sub-setting area, record it as the height position of the sub-setting area, and get the air convection coefficient according to the height position of the sub-setting area and the height of the maximum position of air convection. The specific acquisition method is:

[0058]

[0059] Where AC is the air convection coefficient, h set Indicates the height position of the subsetting area, h max Expressed as the maximum air convection height, h avg Expressed as the average height of the indoor space, h fl Expressed as the lowest ground height;

[0060] The radiation reception coefficient, temperature change sensitivity coefficient and air convection coefficient are normalized, and the sensor suitability index is obtained by evaluating the normalized radiation reception coefficient, temperature change sensitivity coefficient and air convection coefficient. The specific acquisition method is:

[0061]

[0062] Wherein, ST represents the sensor suitability index, RE represents the radiation reception coefficient. A higher radiation reception coefficient means that the wall is subjected to stronger thermal radiation and the temperature fluctuates greatly, which is suitable for installing sensors. SC represents the temperature change sensitivity coefficient. A higher temperature change sensitivity coefficient means that the temperature fluctuation in this area is large. AC represents the air convection coefficient. The area with a higher air convection coefficient has smaller temperature fluctuation and is not suitable for setting sensors.

[0063] In this embodiment, it should be specifically explained that Figure 2 As shown, the steps for obtaining the radiation reception coefficient are:

[0064] The south direction is taken as the unit vector B = (0, -1, 0), and the unit vector is taken as the reference vector;

[0065] Get the normal vector of the sub-setting area and calculate the cosine value of the angle between the normal vector and the reference vector. The specific acquisition method is:

[0066] Where cosθ represents the cosine value of the angle between the normal vector and the reference vector, θ represents the angle between the normal vector and the reference vector, F is the normal vector of the sub-setting area, B is the unit vector, ‖F‖ is the modulus of the normal vector of the sub-setting area, and ‖B‖ is the modulus of the reference vector;

[0067] Use the maximum value function to obtain the radiation reception coefficient according to the cosine value of the angle between the normal vector and the reference vector. The specific acquisition method is:

[0068] RE = max(0, cosθ);

[0069] In the formula, RE represents the radiation reception coefficient, and cosθ represents the cosine value of the angle between the normal vector and the reference vector;

[0070] Table 1 Radiation reception coefficient of sub-setting area

[0071]

[0072]

[0073] As shown in Table 1, in a specific embodiment, by analyzing the cosine value of the angle between the normal vector of the sub-setting area and the reference vector (south direction), the difference in radiation receiving capabilities of different sub-setting areas can be found. For example, the radiation receiving coefficient of the sub-setting area with a normal vector of (0, -1, 0) reaches 1, indicating that the area is completely facing the reference direction and has the strongest radiation receiving capability. The radiation receiving coefficient of the sub-setting area with a normal vector of (0, -0.2, 0.9) is 0.219, indicating that the area is relatively far away from the reference direction and has a weaker radiation receiving capability. The differences in these radiation receiving coefficients reflect the receiving capability characteristics of different sub-setting areas in the reference direction. This analysis can be further used to optimize the sensor layout. By selecting an area with a higher radiation receiving coefficient, the accuracy and effectiveness of the sensor can be improved, providing a basis for indoor environment control.

[0074] Step 4: Select the location of the sensor group setting according to the sensor suitability index and the number of sensor groups in each sub-setting area;

[0075] In this embodiment, it should be specifically explained that the steps of selecting the location of the sensor group setting according to the sensor suitability index and the number of sensor groups in each sub-setting area are:

[0076] Sort the sensor suitability index of each sub-setting area from high to low to obtain a sub-setting area sequence set, wherein the sub-setting area sequence set includes a sub-setting area sorting order and a position coordinate of each sub-setting area;

[0077] If the number of sensor groups is one, the sub-setting area with the highest sensor suitability index is selected for sensor group setting, and the setting position is the middle of the sub-setting area;

[0078] If the number of sensor groups is greater than one, a corresponding number of sub-setting areas are selected from high to low in the sub-setting area sequence set according to the number of sensor groups, and the sensor groups are set at the middle positions of the selected sub-setting areas.

[0079] Step 5: Acquire initial temperature data and humidity data in real time through the temperature sensor and humidity sensor in the sensor group, and correct the initial temperature data through the humidity data to obtain actual temperature data;

[0080] In this embodiment, it should be specifically explained that the steps of acquiring the initial temperature data and humidity data in real time through the temperature sensor and humidity sensor in the sensor group are as follows:

[0081] If the number of sensor groups is one, the initial temperature data and humidity data of the sub-setting area where the sensor group is located are directly obtained;

[0082] If the number of sensor groups is greater than one, the average sensor suitability index of the sub-setting area where the sensor group is located is calculated, and the initial temperature data is obtained according to the sensor suitability index evaluation of the sub-setting area. The specific acquisition method is:

[0083]

[0084] Where, T 初始 Expressed as initial temperature data, ST i is the sensor suitability index of the sub-setting area where the i-th sensor group is located, ST 均 is the average sensor suitability index, T 初i The temperature data obtained for the sub-setting area where the i-th sensor group is located, W represents the number of sensor groups;

[0085] The average humidity data obtained in the sub-setting area where the sensor group is located is calculated, and the average humidity data is recorded as humidity data.

[0086] When the humidity is high, the air contains more water vapor, causing the temperature felt by the human body (felt temperature) to be higher than the temperature measured by the sensor. When the humidity is low, the air contains less water vapor, the evaporation effect is more significant, and the temperature felt by the human body is usually lower than the temperature measured by the sensor.

[0087] In this embodiment, it should be specifically explained that the steps of correcting the initial temperature data by using the humidity data to obtain the actual temperature data are:

[0088] The temperature correction factor is obtained according to the humidity data. The specific method is as follows:

[0089]

[0090] In the formula, C H is the temperature correction factor, γ is the proportional coefficient, which is used to adjust the overall effect of humidity on temperature correction. In this embodiment, γ is set to 0.02, H is the humidity data, It is a standardized adjustment factor, and no adjustment is made when the humidity is 50%;

[0091] The initial temperature data and the temperature correction factor are added together to obtain the actual temperature data.

[0092] Step 6: According to the actual temperature data, the final control signal is obtained through the PID control algorithm;

[0093] PID control algorithm is a feedback control algorithm commonly used in automatic control systems. It generates a control signal by calculating the weighted sum of the proportional, integral and differential terms. The proportional term adjusts the control output according to the current error, the integral term adjusts according to the historical error accumulation to eliminate the steady-state error, and the differential term predicts the future trend according to the rate of change of the error to suppress system overshoot and oscillation. By continuously adjusting the control signal, the PID algorithm can make the system output as close to the desired target value as possible and keep it stable.

[0094] In this embodiment, it should be specifically explained that the steps of obtaining the final control signal through the PID control algorithm are:

[0095] Set the sampling interval, obtain the set target temperature, and calculate the temperature error based on the actual temperature data and the set target temperature. The specific acquisition method is:

[0096] e(t)=T 目标 -T 实际 ;

[0097] Where e(t) is the temperature error at the current time point, T 目标 Indicated as the set target temperature, T 实际 Represented as actual temperature data;

[0098] Get the temperature error at each time point and use trapezoidal integration to calculate the integral term. The specific acquisition method is:

[0099]

[0100] Where I(t) is the integral term, e(t j ) represents the temperature error at the jth time point, and Δt is the sampling interval;

[0101] Trapezoidal integration is a numerical integration method used to estimate the integral value of a function within a certain interval. It obtains an approximate value of the integral by approximating the area under the curve as the sum of the areas of multiple trapezoids. Specifically, the trapezoidal integration method approximates the curve of each small interval as a trapezoid, and uses the function values ​​at the two end points of the interval to calculate the area of ​​the trapezoid. In PID control, trapezoidal integration is used to calculate the integral term of the error, gradually accumulate the temperature error, and update the integral value through the trapezoidal rule at each time point to obtain a more accurate control signal.

[0102] According to the temperature error at each time point, the differential term is calculated by the difference method. The specific acquisition method is:

[0103]

[0104] In the formula, D(t) represents the differential term, e(t) represents the temperature error at the current time point, and e(t-1) represents the temperature error at the previous time point;

[0105] The difference method is a numerical calculation method used to approximate the derivative or differential of a function. The rate of change of a function is estimated by calculating the difference between two adjacent points. In temperature control, the difference method is often used to estimate the rate of change of the error over time, that is, the differential term of the error. Specifically, the difference method calculates the difference between the error at the current moment and the error at the previous moment, and then divides it by the time interval to obtain the rate of change of the error.

[0106] The final control signal is obtained by comprehensive evaluation of temperature error, integral term and differential term. The specific acquisition method is as follows:

[0107] u(t)=sign(e(t))×(K p ×|e(t)|+K q ×|I(t)|+K d ×|D(t)|);

[0108] Where u(t) is the final control signal, e(t) is the temperature error at the current time point, sign(e(t)) is the sign function, when e(t)>0, it returns +1, indicating heating; when e(t)<0, it returns -1, indicating cooling, I(t) is the integral term, D(t) is the differential term, and K p , K q , K d Expressed as the weight coefficient of temperature error, integral term and differential term.

[0109] Step 7: Adjust the indoor temperature according to the final control signal, and return to step 5 to continue collecting initial temperature data and humidity data.

[0110] In this embodiment, it should be specifically explained that Figure 3 As shown, the indoor temperature control and regulation system based on computer automatic control includes:

[0111] A sensor group quantity acquisition module is used to acquire indoor space information, and obtain the degree of indoor space irregularity according to the indoor space information, and obtain the number of sensor groups to be set according to the degree of indoor space irregularity, wherein the sensor group includes a temperature sensor and a humidity sensor;

[0112] A sensor group setting module is used to obtain indoor wall information, divide the wall into n sub-setting areas, evaluate the sensor suitability index of each sub-setting area according to the indoor wall information, and select the location of the sensor group according to the sensor suitability index and the number of sensor groups;

[0113] A temperature correction module is used to obtain humidity data through a humidity sensor, obtain initial temperature data through a temperature sensor, correct the initial temperature data through the humidity data to obtain actual temperature data, and transmit the actual temperature data to the control signal acquisition module;

[0114] A control signal acquisition module is used to obtain a final control signal through a PID control algorithm according to actual temperature data, and transmit the final control signal to a temperature adjustment module;

[0115] The temperature adjustment module is used to adjust the indoor temperature according to the final control signal.

[0116] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

[0117] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. Indoor temperature control method and system based on computer automatic control, characterized in that: The following steps are involved: Step 1: Acquire indoor space information, evaluate the degree of indoor space irregularity according to the indoor space information, and obtain the number of sensor groups to be set according to the degree of indoor space irregularity. The sensor groups include temperature sensors and humidity sensors. Step 2: Obtain indoor wall information, which is the orientation direction of the wall; divide each wall into n sub-areas on average, recorded as sub-setting areas; Step 3: Evaluate the sensor suitability index of each sub-setting area based on the indoor wall information; Step 4: Select the location of the sensor group setting according to the sensor suitability index and the number of sensor groups in each sub-setting area; Step 5: Acquire initial temperature data and humidity data in real time through the temperature sensor and humidity sensor in the sensor group, and correct the initial temperature data through the humidity data to obtain actual temperature data; Step 6: According to the actual temperature data, the final control signal is obtained through the PID control algorithm; Step 7: Adjust the indoor temperature according to the final control signal, and return to step 5 to continue collecting initial temperature data and humidity data.

2. The indoor temperature control method and system based on computer automatic control according to claim 1, characterized in that: The steps for obtaining the degree of irregularity of the indoor space are as follows: Through computer vision technology, the indoor space is scanned and a three-dimensional model of the indoor space is generated. The indoor space volume is obtained based on the three-dimensional model of the space. Use 3D modeling tools to obtain the surface area of ​​the space. The surface area is the total area of ​​all surfaces in the space, such as walls, floors, ceilings, etc. The degree of indoor spatial irregularity is assessed based on spatial volume and surface area.

3. The indoor temperature control method and system based on computer automatic control according to claim 1, characterized in that: The step of obtaining the number of sensor groups to be set according to the degree of irregularity of the indoor space is as follows: An irregularity threshold is preset, and the degree of indoor space irregularity is compared with the irregularity threshold. If the degree of indoor space irregularity is less than the irregularity threshold, it is judged that the degree of indoor space irregularity is small, and a group of sensors is set indoors; if the degree of indoor space irregularity is greater than or equal to the irregularity threshold, it is judged that the degree of indoor space irregularity is large, and the number of sensors needs to be increased. The number of sensor groups to be set is obtained according to the evaluation of the degree of indoor space irregularity.

4. The indoor temperature control method and system based on computer automatic control according to claim 1, characterized in that: The steps for obtaining the sensor suitability index are as follows: Get the orientation direction of the sub-setting area, take the south direction as the base coordinate, and get the radiation reception coefficient according to the orientation direction and the base coordinate; Obtain the coordinates of the center point of the sub-setting area and the coordinates of the temperature control source, calculate the distance between the sub-setting area and the temperature control source according to the coordinates of the center point of the sub-setting area and the coordinates of the temperature control source, record it as the temperature control distance, and obtain the temperature change sensitivity coefficient according to the temperature control distance; The average height of the indoor space, the maximum ceiling height of the indoor space and the lowest ground height are obtained through the three-dimensional model of the indoor space. The maximum position height of air convection is evaluated based on the average height of the indoor space, the maximum ceiling height, the degree of irregularity of the indoor space and the lowest ground height. Get the height position of the center point of each sub-setting area, record it as the height position of the sub-setting area, and get the air convection coefficient according to the height position of the sub-setting area and the height of the maximum position of air convection. The specific acquisition method is: Where AC is the air convection coefficient, h set Indicates the height position of the subsetting area, h max Expressed as the height of the maximum air convection position, h avg Expressed as the average height of the indoor space, h fl Expressed as the lowest ground height; The radiation reception coefficient, temperature change sensitivity coefficient and air convection coefficient are normalized, and the sensor suitability index is evaluated based on the normalized radiation reception coefficient, temperature change sensitivity coefficient and air convection coefficient.

5. The indoor temperature control method and system based on computer automatic control according to claim 4, characterized in that: The radiation reception coefficient acquisition step is: Take the south direction as the unit vector and the unit vector as the reference vector; Get the normal vector of the sub-setting area, and calculate the cosine value of the angle between the normal vector and the reference vector; The maximum value function is used to obtain the radiation reception coefficient according to the cosine value of the angle between the normal vector and the reference vector.

6. The indoor temperature control method and system based on computer automatic control according to claim 1, characterized in that: The step of selecting the location of the sensor group setting according to the sensor suitability index and the number of sensor groups in each sub-setting area is: Sort the sensor suitability index of each sub-setting area from high to low to obtain a sub-setting area sequence set, wherein the sub-setting area sequence set includes a sub-setting area sorting order and a position coordinate of each sub-setting area; If the number of sensor groups is one, the sub-setting area with the highest sensor suitability index is selected for sensor group setting, and the setting position is the middle of the sub-setting area; If the number of sensor groups is greater than one, a corresponding number of sub-setting areas are selected from high to low in the sub-setting area sequence set according to the number of sensor groups, and the sensor groups are set at the middle positions of the selected sub-setting areas.

7. The indoor temperature control method and system based on computer automatic control according to claim 1, characterized in that: The steps of obtaining the initial temperature data and humidity data in real time through the temperature sensor and humidity sensor in the sensor group are as follows: If the number of sensor groups is one, the initial temperature data and humidity data of the sub-setting area where the sensor group is located are directly obtained; If the number of sensor groups is greater than one, the average sensor suitability index of the sub-setting area where the sensor group is located is calculated, and the initial temperature data is obtained according to the sensor suitability index evaluation of the sub-setting area. The specific acquisition method is: Where, T 初始 Expressed as initial temperature data, ST i is the sensor suitability index of the sub-setting area where the i-th sensor group is located, ST 均 is the average sensor suitability index, T 初i The temperature data obtained for the sub-setting area where the i-th sensor group is located, W represents the number of sensor groups; The average humidity data obtained in the sub-setting area where the sensor group is located is calculated, and the average humidity data is recorded as humidity data.

8. The indoor temperature control method and system based on computer automatic control according to claim 1, characterized in that: The steps of correcting the initial temperature data by humidity data to obtain the actual temperature data are as follows: Get the temperature correction factor based on the humidity data; The initial temperature data and the temperature correction factor are added together to obtain the actual temperature data.

9. The indoor temperature control method and system based on computer automatic control according to claim 1, characterized in that: The steps of obtaining the final control signal through the PID control algorithm are: Set the sampling interval and the target temperature, and calculate the temperature error based on the actual temperature data and the set target temperature; Get the temperature error at each time point and calculate the integral term using trapezoidal integration; According to the temperature error at each time point, the differential term is calculated by the difference method; The final control signal is obtained based on a comprehensive evaluation of the temperature error, integral term, and differential term.

10. An indoor temperature control and adjustment system based on computer automatic control, used to implement the indoor temperature control and adjustment method based on computer automatic control according to any one of claims 1 to 9, characterized in that: The system comprises: A sensor group quantity acquisition module is used to acquire indoor space information, and obtain the degree of indoor space irregularity according to the indoor space information, and obtain the number of sensor groups to be set according to the degree of indoor space irregularity, wherein the sensor group includes a temperature sensor and a humidity sensor; A sensor group setting module is used to obtain indoor wall information, divide the wall into n sub-setting areas, evaluate the sensor suitability index of each sub-setting area according to the indoor wall information, and select the location of the sensor group according to the sensor suitability index and the number of sensor groups; A temperature correction module is used to obtain humidity data through a humidity sensor, obtain initial temperature data through a temperature sensor, correct the initial temperature data through the humidity data to obtain actual temperature data, and transmit the actual temperature data to the control signal acquisition module; A control signal acquisition module is used to obtain a final control signal through a PID control algorithm according to actual temperature data, and transmit the final control signal to a temperature adjustment module; The temperature adjustment module is used to adjust the indoor temperature according to the final control signal.

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