Coating room temperature and humidity control system based on Internet of Things

Abstract

The invention relates to the technical field of coating environment control, and discloses a coating room temperature and humidity control system based on the Internet of Things, which comprises a data acquisition module, a data processing module, a control analysis module and a control execution module, by reasonably arranging the sensors and dividing key positions, the temperature and humidity conditions in the coating chamber are comprehensively mastered. Interference is removed through data filtering, the sensor weight is considered through data fusion, it is guaranteed that the processing result is accurate, and a foundation is laid for regulation and control; meanwhile, the temperature and humidity deviation is calculated according to a preset interval, a corresponding control signal is generated, the intensity is determined, and precise regulation and control are achieved; the air conditioner, the humidifier and other equipment are accurately operated according to the signal intensity, and the temperature and humidity are stabilized by combining the adjustment precision; on the whole, the system achieves automatic, intelligent and precise control, the coating process quality is improved, the product percent of pass is guaranteed, the production efficiency is improved, and the cost is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of coating environment control, and in particular to a coating room temperature and humidity control system based on the Internet of Things. Background Art

[0002] In today's industrial manufacturing field, coating technology plays a vital role and is widely used in many industries such as automobile manufacturing, home appliance production, and various mechanical equipment manufacturing. The quality of coating is not only related to the appearance of the product, but also has a profound impact on the product's protection performance and service life. However, the environmental temperature and humidity conditions in the coating room have always been one of the key factors restricting the improvement of coating quality.

[0003] Traditionally, the control of temperature and humidity in the painting room faces many difficulties. On the one hand, most of them rely on manual monitoring and adjustment. Workers need to enter the painting room regularly and use conventional temperature and humidity measurement tools to measure at a limited number of locations. Then, they rely on experience to manually operate air conditioners, humidifiers, dehumidifiers and other equipment to control the ambient temperature and humidity. This manual method has obvious defects. First, it is impossible to achieve real-time monitoring. The changes in temperature and humidity are immediate. Manual timed detection is very likely to miss key change nodes, resulting in the inability to make timely adjustments, which in turn affects the painting effect. Second, there are subjective differences in manual judgment. Different workers have different understandings of the appropriate range of temperature and humidity, which makes the adjustment results lack consistency and accuracy, which is not conducive to ensuring stable painting quality.

[0004] On the other hand, even if some paint rooms use sensor-assisted monitoring, they are still insufficient in data processing and overall environmental control. Simple sensor layouts often make it difficult to fully cover every corner of the paint room, and cannot accurately capture the true temperature and humidity conditions in each part of the space. In addition, when analyzing and utilizing the collected data, there is a lack of scientific and reasonable data processing mechanisms. For example, the data in the actual environment may not be fully considered to be susceptible to external interference and fluctuations, and only conventional simple calculations are performed. This makes it difficult for control decisions made based on these data to effectively adapt to the complex environment of the entire paint room space, and ultimately cannot ensure that the temperature and humidity are uniformly and stably maintained within the ideal range.

[0005] In view of the high sensitivity of the coating process to the ambient temperature and humidity and the various limitations of existing control methods, and relying on the development advantages of Internet of Things technology, it is particularly urgent to develop an efficient, accurate and intelligent Internet of Things control system specifically for the temperature and humidity control of the coating room. Summary of the invention

[0006] The purpose of the present invention is to provide a painting room temperature and humidity control system based on the Internet of Things, which solves the technical problems raised in the background technology.

[0007] The purpose of the present invention can be achieved through the following technical solutions:

[0008] The painting room temperature and humidity control system based on the Internet of Things includes:

[0009] The data acquisition module is used to set temperature sensors and humidity sensors at multiple key locations in the painting room, and collect temperature data and humidity data in the painting room in real time at a specified acquisition frequency;

[0010] A data processing module is used to pre-process the temperature data and humidity data in the painting room. The pre-processing includes data filtering and data fusion. The average temperature and average humidity of the painting room space are determined through pre-processing.

[0011] The control analysis module is used to determine the temperature deviation and humidity deviation at each acquisition time node according to the preset target temperature range and target humidity range, and then generate corresponding control signals according to the temperature deviation and humidity deviation, and determine the temperature control signal strength and humidity control signal strength;

[0012] The control execution module is used to control the air conditioner, humidifier and dehumidifier placed in the painting room according to the temperature control signal strength and the humidity control signal strength.

[0013] As a further solution of the present invention: wherein, by measuring the length, width and height of the painting room space, the painting room space is divided into m×n×p cubic units according to the length, width and height of the painting room space, and the center position or a suitable representative point of each cubic unit is determined as the key position.

[0014] As a further solution of the present invention: at the same time, the temperature data and humidity data acquired by the temperature sensor and the humidity sensor at each acquisition time node within the specified period are marked as T (i，j，k)，t and H (i，j，k)，t ;

[0015] Among them, (i, j, k) represents the coordinate position of the relevant sensor in the painting room space, i = 1, 2, ... m, j = 1, 2, ... n, k = 1, 2, ... p, t = 1, 2, ... e, and m represents the number of cubic units divided along the X axis in the painting room space, n represents the number of cubic units divided along the Y axis in the painting room space, p represents the number of cubic units divided along the Z axis in the painting room space, and e represents the number of acquisition time nodes within a specified period.

[0016] As a further solution of the present invention: the pretreatment method is as follows:

[0017] Step K1, data filtering:

[0018] The median filter algorithm is used to filter the collected data;

[0019] The specific method is as follows:

[0020] Step K1.1, select a time node t and a coordinate position (i, j, k) to collect temperature data T (i,j,k)，t For example:

[0021] Then obtain the temperature data T (i,j,k)，t q moments before and after;

[0022] Step K1.2, the temperature data including the current moment and the q acquisition time nodes before and after form a data sequence, and the data sequence contains 2q + 1 acquisition time nodes in total;

[0023] The data sequence is as follows:

[0024] {T (i,j,k),t-q ,...,T (i,j,k),t ,...,T (i,j,k),t+q};

[0025] Step K1.3, sort the data sequence from small to large, and then take the middle value as the filtered temperature data T1 (i,j,k),t ;

[0026] Step K1.4, follow the method from Step 1.1 to Step 1.3 to collect the temperature data T of other time nodes t and other coordinate positions (i, j, k) (i,j,k)，t Perform filtering processing;

[0027] Step K1.5, follow the method from Step 1.1 to Step 1.4 to collect humidity data H at all time nodes t and all coordinate positions (i, j, k) (i,j,k)，t Perform filtering and obtain the filtered humidity data H1 (i,j,k),t ;

[0028] Step K2, data fusion:

[0029] The average temperature and humidity of the painting room space are calculated by using the weighted average method and by assigning different weight coefficients in advance according to the location of the sensor and its representativeness of the overall environment.

[0030] The calculation formula is as follows:

[0031]

[0032] Where TP t is the average temperature of the painting room space at the corresponding acquisition time node t, β(i,j,k) Different weight coefficients are pre-assigned according to the location of the sensor and its representativeness to the overall environment;

[0033]

[0034] In the formula, HP t is the average humidity of the painting room space at the corresponding collection time node t;

[0035] As a further solution of the present invention: the analysis method of the control analysis module is as follows:

[0036] Step G1: Extract target temperature and humidity range

[0037] Extract the target temperature range and target humidity range pre-set according to the coating room and mark them as [T min ,T max ] and [H min ,H max ];

[0038] Among them, T min is the minimum temperature in the target temperature range, T max is the maximum temperature in the target temperature range;

[0039] Step G2: Calculate temperature and humidity deviation

[0040] pass:

[0041]

[0042] Calculate the temperature deviation TC at each acquisition time node t respectively t and humidity deviation HC t ;

[0043] Step G3: Generate temperature and humidity control signals

[0044] The temperature and humidity control signals are determined according to the temperature deviation and humidity deviation; the specific method is as follows:

[0045] If TC t >0, a temperature-down control signal is generated;

[0046] If TC t When <0, a temperature increase control signal is generated;

[0047] If TC t =0, no corresponding temperature adjustment control signal is generated;

[0048] If HC t When >0, a humidity downward control signal is generated;

[0049] If HC t When <0, a humidity increase control signal is generated;

[0050] If HC t =0, no corresponding humidity adjustment control signal is generated;

[0051] Step G4: Determine the signal strength of temperature and humidity control

[0052] Determine the temperature control signal strength and the humidity control signal strength by combining the preset signal strength ratio coefficients corresponding to the temperature and humidity respectively;

[0053] The specific determination method is as follows:

[0054] UT t =TC t ×KT

[0055] Where UT t The signal strength is controlled by temperature, and KT is the signal strength proportional coefficient corresponding to the preset temperature;

[0056] UH t =HC t ×KH

[0057] Where, UH t The signal strength is controlled by temperature, and KH is the signal strength proportional coefficient corresponding to the preset humidity;

[0058] As a further solution of the present invention: the control method of the control execution module is as follows:

[0059] When the temperature control signal strength UT t >0, the air conditioning cooling power will be increased;

[0060] When the temperature control signal strength UT t When <0, the air conditioning heating power is increased;

[0061] When the humidity control signal strength UH t >0, the dehumidifier power is increased or the humidifier power is reduced;

[0062] When the humidity control signal strength UH t When <0, the humidifier power is increased or the dehumidifier power is reduced;

[0063] As a further solution of the present invention: during the control process, the equipment operating state is gradually adjusted according to the control signal strength and the adjustment accuracy, wherein the temperature adjustment accuracy of the air conditioner, and the humidity adjustment accuracy of the humidifier and dehumidifier are obtained from their corresponding product manuals.

[0064] Beneficial effects of the present invention:

[0065] The present invention can comprehensively and meticulously grasp the temperature and humidity conditions at different positions in the painting room by setting temperature sensors and humidity sensors at multiple key positions in the painting room and collecting data in real time according to the specified collection frequency. At the same time, the key positions are determined by dividing the painting room space into multiple cubic units according to the length, width and height, which further ensures the rationality and representativeness of the spatial distribution of the collected data, making the monitoring of the temperature and humidity of the entire painting room environment more accurate, which is conducive to subsequent precise control.

[0066] The present invention uses a median filter algorithm to filter the collected temperature and humidity data, which can effectively remove interference factors such as abnormal values ​​and noise that may appear during the collection process. For example, in an actual coating room environment, there may be situations where electromagnetic interference occasionally generated by electrical equipment affects sensor readings. By taking the middle value of the data sequence as the filtered data, the median filter can make the collected data closer to the actual environmental state, providing a reliable basis for subsequent accurate judgment of environmental temperature and humidity.

[0067] The present invention uses the weighted average method and pre-assigns different weight coefficients based on the sensor position and its representativeness to the overall environment to calculate the average temperature and average humidity. It fully considers the importance differences of sensor data at different positions, so that the final average temperature and humidity of the painting room space is more in line with the actual overall environmental conditions, avoids the errors caused by simple averaging and other methods, and improves the accuracy and scientificity of the data processing results.

[0068] The present invention can accurately calculate the temperature deviation and humidity deviation at each acquisition time node based on the pre-set target temperature range and target humidity range, and then intelligently generate corresponding control signals according to the deviation situation, and determine the reasonable temperature control signal strength and humidity control signal strength. This precise analysis method allows the system to carry out targeted and refined regulation based on the difference between the actual temperature and humidity and the target temperature and humidity, avoiding the problem of over-regulation or under-regulation, ensuring that the environment of the coating room is always maintained within the appropriate temperature and humidity range, and helping to improve the quality and effect of the coating operation.

[0069] In the present invention, the control execution module accurately controls the air conditioner, humidifier and dehumidifier placed in the painting room according to the strength of the temperature control signal and the strength of the humidity control signal. For example, according to whether the temperature control signal strength is positive or negative, the air conditioning cooling or heating power is increased accordingly; according to the positive or negative situation of the humidity control signal strength, the dehumidifier or humidifier power is reasonably increased, and the operation state of the equipment is gradually adjusted in combination with the corresponding adjustment accuracy of the equipment, so that the temperature and humidity in the painting room can stably approach and maintain within the target range, provide stable and good environmental conditions for the painting process, reduce the painting quality problems caused by inappropriate temperature and humidity, and improve production efficiency and product qualification rate.

[0070] The present invention combines the advantages of the above-mentioned various links, and the system can realize automatic, intelligent and precise control of the temperature and humidity of the painting room, effectively avoiding the problems of untimely and inaccurate manual control, so that the indoor environment of the painting room is always in an ideal state that meets the requirements of the painting process, and ultimately improves the quality of the entire painting process, ensures that the appearance of the product meets the standards, and to a certain extent improves the overall efficiency of the painting operation, and reduces the cost caused by rework due to temperature and humidity factors. BRIEF DESCRIPTION OF THE DRAWINGS

[0071] The present invention will be further described below in conjunction with the accompanying drawings.

[0072] Figure 1 It is a system block diagram of the coating room temperature and humidity control system based on the Internet of Things of the present invention.

[0073] Figure 2 It is a module flow diagram of the control and analysis module in the painting room temperature and humidity control system based on the Internet of Things of the present invention. DETAILED DESCRIPTION

[0074] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0075] Embodiment 1

[0076] See also Figure 1 and Figure 2 As shown, the present invention is a coating room temperature and humidity control system based on the Internet of Things, comprising:

[0077] The data acquisition module is used to set temperature sensors and humidity sensors at multiple key locations in the painting room, and collect temperature data and humidity data in the painting room in real time at a specified acquisition frequency;

[0078] Among them, by measuring the length, width and height of the painting room space, the painting room space is divided into m×n×p cubic units according to the length, width and height of the painting room space, and the center position or appropriate representative point of each cubic unit is determined as the key position;

[0079] At the same time, the temperature data and humidity data obtained by the temperature sensor and humidity sensor at each acquisition time node within the specified period are marked as T (i，j，k)，t and H (i，j，k)，t ;

[0080] Wherein, (i, j, k) represents the coordinate position of the relevant sensor in the painting room space, i=1, 2, ...m, j=1, 2, ...n, k=1, 2, ...p, t=1, 2, ...e, and m represents the number of cubic units divided along the X axis in the painting room space, n represents the number of cubic units divided along the Y axis in the painting room space, p represents the number of cubic units divided along the Z axis in the painting room space, and e represents the number of acquisition time nodes within a specified period;

[0081] A data processing module, used for preprocessing the temperature data and humidity data in the painting room;

[0082] Preprocessing methods include data fusion processing:

[0083] It uses the weighted average method and pre-assigns different weight coefficients according to the location of the sensor and its representativeness of the overall environment to calculate the average temperature and average humidity of the painting room space;

[0084] The calculation formula is as follows:

[0085]

[0086] Where TP t is the average temperature of the painting room space at the corresponding acquisition time node t, β (i,j,k) Different weight coefficients are pre-assigned according to the location of the sensor and its representativeness to the overall environment;

[0087]

[0088] In the formula, HP t is the average humidity of the painting room space at the corresponding collection time node t;

[0089] The control analysis module is used to determine the temperature deviation and humidity deviation at each acquisition time node according to the preset target temperature range and target humidity range, and then generate corresponding control signals according to the temperature deviation and humidity deviation;

[0090] The specific method is as follows:

[0091] Step G1, extract the target temperature range and target humidity range pre-set according to the coating room, and mark them as [T min ,T max ] and [H min ,H max ];

[0092] Among them, T min is the minimum temperature in the target temperature range, T maxis the maximum temperature in the target temperature range;

[0093] Step G2, by:

[0094]

[0095] Calculate the temperature deviation TC at each acquisition time node t respectively t and humidity deviation HC t ;

[0096] Step G3, determine the temperature and humidity control signals according to the temperature deviation and humidity deviation; the specific method is as follows:

[0097] If TC t >0, a temperature-down control signal is generated;

[0098] If TC t When <0, a temperature increase control signal is generated;

[0099] If TC t =0, no corresponding temperature adjustment control signal is generated;

[0100] If HC t When >0, a humidity downward control signal is generated;

[0101] If HC t When <0, a humidity increase control signal is generated;

[0102] If HC t =0, no corresponding humidity adjustment control signal is generated.

[0103] This embodiment sets temperature sensors and humidity sensors at multiple key positions in the painting room, and determines the key positions by dividing the cubic units according to the length, width and height of the painting room space. It can comprehensively and specifically collect temperature and humidity data at different positions in the painting room, providing a detailed data basis for subsequent precise control. The weighted average method is used for data fusion processing, and different weight coefficients are assigned in combination with the sensor position and its representativeness of the overall environment. The average temperature and average humidity of the painting room space can be accurately calculated to make the data more representative and scientific. According to the pre-set target temperature range and target humidity range, the temperature deviation and humidity deviation at each acquisition time node can be accurately determined, and the corresponding control signal can be generated to achieve effective regulation of the temperature and humidity of the painting room to keep it within the target range.

[0104] Embodiment 2

[0105] As the second embodiment of the present invention, when the present application is implemented, compared with the first embodiment, the technical solution of the present embodiment is different from that of the first embodiment only in that:

[0106] The control analysis module is also used to combine the temperature deviation and the humidity deviation with the preset signal strength proportional coefficients corresponding to the temperature and humidity respectively, to determine the temperature control signal strength and the humidity control signal strength;

[0107] The signal strength proportionality coefficient is a key parameter used to convert temperature deviation or humidity deviation into actual control signal strength; it acts as a bridge between the control analysis module and the control execution module, enabling the system to reasonably adjust the operating power of equipment such as air conditioners, humidifiers and dehumidifiers according to the size of the temperature and humidity deviation, thereby achieving precise control of the temperature and humidity of the coating room environment;

[0108] The specific determination method is as follows:

[0109] UT t =TC t ×KT

[0110] Where UT t The signal strength is controlled by temperature, and KT is the signal strength proportional coefficient corresponding to the preset temperature;

[0111] UH t =HC t ×KH

[0112] Where, UH t The signal strength is controlled by temperature, and KH is the signal strength proportional coefficient corresponding to the preset humidity;

[0113] The temperature and humidity correspond to the preset signal strength proportional coefficients respectively and are obtained as follows:

[0114] Step 1: Temperature control signal strength proportionality coefficient:

[0115] Assume that the cooling / heating power adjustment range of the air conditioner is [Pmin, Pmax], the unit is watt, denoted by W, the target temperature range of the coating room is [Tmin, Tmax], the unit is Celsius, denoted by ℃, and the measurement accuracy of the temperature sensor is DT, denoted by ℃;

[0116] First, calculate the total power range RP of temperature regulation by RP=Pmax-Pmin;

[0117] Then, the effective adjustment range RT of the temperature deviation is determined by RT=Tmax-Tmin;

[0118] Assuming that we want to evenly map the temperature deviation to the power adjustment range, the temperature control signal strength proportionality coefficient is obtained by KT = RP / RT, and its unit is W / ℃;

[0119] For example, if RP = 2000W, RT = 10°C, then KT = 200W / °C;

[0120] This means that for every 1°C temperature deviation, the control signal strength will correspond to a 200W power adjustment amplitude;

[0121] Step 2: Humidity control signal strength proportional coefficient:

[0122] For the humidifier / dehumidifier, the humidification / dehumidification adjustment range is [Qmin, Qmax], the unit is liter / hour, expressed in L / h, the target humidity range of the coating room is [Hmin, Hmax], the unit is relative humidity, expressed in %RH, and the measurement accuracy of the humidity sensor is DH, the unit is %RH;

[0123] First, the total adjustment range RQ of humidification / dehumidification is calculated by RQ=Qmax-Qmin;

[0124] Then, the effective adjustment range RH of the humidity deviation is determined by RH=Hmax-Hmin;

[0125] Then, through KH=RQ / RH, the humidity control signal intensity proportional coefficient is obtained, and its unit is L / h / %RH;

[0126] For example, if RQ = 10L / h, KH = 20%RH, then KH = 0.5L / h / %RH, that is, for every 1%RH humidity deviation, the control signal strength will correspond to a humidification / dehumidification adjustment range of 0.5L / h;

[0127] In practical applications, these coefficients may also need to be dynamically adjusted and optimized according to factors such as the specific equipment operation conditions, the actual environmental changes in the coating room, and the actual needs of the coating, in order to achieve the best temperature and humidity control effect;

[0128] Also includes:

[0129] A control execution module, used to control the air conditioner, humidifier and dehumidifier placed in the painting room according to the strength of the temperature control signal and the strength of the humidity control signal;

[0130] The control method is as follows:

[0131] When the temperature control signal strength UT t >0, the air conditioning cooling power will be increased;

[0132] When the temperature control signal strength UT t When <0, the air conditioning heating power is increased;

[0133] When the humidity control signal strength UH t>0, the dehumidifier power is increased or the humidifier power is reduced;

[0134] When the humidity control signal strength UH t When <0, the humidifier power is increased or the dehumidifier power is reduced;

[0135] During the control process, the equipment operating status is gradually adjusted according to the control signal strength and adjustment accuracy to ensure that the temperature and humidity can be stabilized within the target range. Among them, the temperature adjustment accuracy of the air conditioner and the humidity adjustment accuracy of the humidifier and dehumidifier are obtained from their corresponding product manuals.

[0136] In this embodiment, based on the first embodiment, the control analysis module further combines the temperature deviation and humidity deviation with the preset signal strength proportional coefficient to determine the temperature control signal strength and humidity control signal strength. This enables the system to reasonably adjust the operating power of equipment such as air conditioners, humidifiers and dehumidifiers according to the size of the temperature and humidity deviation, so as to achieve more accurate control of the temperature and humidity of the coating room environment. By reasonably determining the preset signal strength proportional coefficients corresponding to the temperature and humidity, the adjustment range of equipment such as air conditioners, humidifiers and dehumidifiers and the measurement accuracy of sensors are fully considered, so that the control signal strength is matched with the equipment operating characteristics, and the accuracy and effectiveness of temperature and humidity control are improved. These coefficients can be dynamically adjusted and optimized according to factors such as the specific equipment operation conditions, the actual environmental changes in the coating room, and the actual demand for coatings, so as to better adapt to different working conditions and always maintain the best temperature and humidity control effect.

[0137] Embodiment 3

[0138] As the third embodiment of the present invention, when the present application is implemented, compared with the first and second embodiments, the technical solution of this embodiment is to combine the solutions of the first and second embodiments, and the difference between the technical solution of this embodiment and the first and second embodiments is that in this embodiment:

[0139] The preprocessing method also includes data filtering, and the data filtering process step is before the data fusion step:

[0140] Data filtering uses median filtering algorithm to filter the collected data;

[0141] The specific method is as follows:

[0142] Step K1.1, select a time node t and a coordinate position (i, j, k) to collect temperature data T (i,j,k)，t For example:

[0143] Then obtain the temperature data T (i,j,k)，t q moments before and after;

[0144] Step K1.2, the temperature data including the current moment and the q acquisition time nodes before and after form a data sequence, and the data sequence contains 2q + 1 acquisition time nodes in total;

[0145] The data sequence is as follows:

[0146] {T (i,j,k),t-q ,...,T (i,j,k),t ,...,T (i,j,k),t+q};

[0147] Step K1.3, sort the data sequence from small to large, and then take the middle value as the filtered temperature data T1 (i,j,k),t ;

[0148] Step K1.4, follow the method from Step 1.1 to Step 1.3 to collect the temperature data T of other time nodes t and other coordinate positions (i, j, k) (i,j,k)，t Perform filtering processing;

[0149] Step K1.5, follow the method from Step 1.1 to Step 1.4 to collect humidity data H at all time nodes t and all coordinate positions (i, j, k) (i,j,k)，t Perform filtering and obtain the filtered humidity data H1 (i,j,k),t ;

[0150] Based on the first and second embodiments, this embodiment adds a data filtering process step and places it before data fusion, and uses a median filtering algorithm to filter the collected data. This helps to remove noise and outliers in the collected data, improve the accuracy and stability of the data, and make subsequent data-based analysis, calculation, and control operations more reliable. By filtering both temperature data and humidity data, the data quality of the entire temperature and humidity control system is further optimized, thereby improving the overall control accuracy and stability of the temperature and humidity of the coating room, ensuring that the temperature and humidity can be more stably maintained within the target range.

[0151] Embodiment 4

[0152] As the fourth embodiment of the present invention, when the present application is specifically implemented, compared with the first, second and third embodiments, the technical solution of this embodiment is to combine and implement the solutions of the above-mentioned first, second and third embodiments.

[0153] This embodiment combines the solutions of Embodiment 1, Embodiment 2, and Embodiment 3 for implementation, integrating the advantages of each embodiment. It can not only comprehensively and accurately collect temperature and humidity data at different locations in the painting room, but also obtain more accurate average temperature and humidity values ​​through scientific data processing methods. It can also effectively control equipment such as air conditioners, humidifiers and dehumidifiers based on precise control signal strength, thereby achieving all-round, high-precision, stable and reliable control of the temperature and humidity of the painting room.

[0154] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters and thresholds in the formula are set by technicians in this field according to actual conditions.

[0155] The above is only a specific implementation of the present application, but the protection range of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical range disclosed in the present application, which should be included in the protection range of the present application. Therefore, the protection range of the present application should be based on the protection range of the claims.

Claims

1. The painting room temperature and humidity control system based on the Internet of Things is characterized by: include: The data acquisition module is used to set temperature sensors and humidity sensors at multiple key locations in the painting room, and collect temperature data and humidity data in the painting room in real time at a specified acquisition frequency; A data processing module is used to pre-process the temperature data and humidity data in the painting room, and determine the average temperature and average humidity of the painting room space through pre-processing; Preprocessing includes data filtering and data fusion. Data filtering uses the median filter algorithm to filter the collected data. Data fusion uses the weighted average method and pre-assigns different weight coefficients according to the location of the sensor and its representativeness of the overall environment to calculate the average temperature and average humidity of the painting room space. The control analysis module is used to determine the temperature deviation and humidity deviation at each acquisition time node according to the preset target temperature range and target humidity range, and then generate corresponding control signals according to the temperature deviation and humidity deviation, and determine the temperature control signal strength and humidity control signal strength; The control execution module is used to control the air conditioner, humidifier and dehumidifier placed in the painting room according to the temperature control signal strength and the humidity control signal strength.

2. The painting room temperature and humidity control system based on the Internet of Things according to claim 1 is characterized in that: The data acquisition module is also used to mark the temperature data and humidity data acquired by the temperature sensor and the humidity sensor at each acquisition time node within the specified period as T (i，j，k)，t and H (i，j，k)，t ; Among them, the painting room space is divided into m×n×p cubic units, and the center position of each cubic unit is defined as the key position. (i, j, k) represents the coordinate position of the relevant sensor in the painting room space, i=1, 2, ...m, j=1, 2, ...n, k=1, 2, ...p, t=1, 2, ...e, and m represents the number of cubic units divided along the X axis in the painting room space, n represents the number of cubic units divided along the Y axis in the painting room space, p represents the number of cubic units divided along the Z axis in the painting room space, and e represents the number of acquisition time nodes within a specified period.

3. The painting room temperature and humidity control system based on the Internet of Things according to claim 2 is characterized in that: The data filtering method is as follows: Step K1.1, select a time node t and a coordinate position (i, j, k) to collect temperature data T (i,j,k)，t For example: Then obtain the temperature data T (i,j,k)，t q moments before and after; Step K1.2, the temperature data including the current time and the q acquisition time nodes before and after form a data sequence, and the data sequence contains 2q + 1 acquisition time nodes in total; Step K1.3, sort the data sequence from small to large, and then take the middle value as the filtered temperature data T1 (i,j,k),t ; Step K1.4, follow the method from Step 1.1 to Step 1.3 to collect the temperature data T of other time nodes t and other coordinate positions (i, j, k) (i,j,k)，t Perform filtering processing; Step K1.5, follow the method from Step 1.1 to Step 1.4 to collect humidity data H at all time nodes t and all coordinate positions (i, j, k) (i,j,k)，t Perform filtering and obtain the filtered humidity data H1 (i,j,k),t .

4. The painting room temperature and humidity control system based on the Internet of Things according to claim 3 is characterized in that: In StepK1.2, the data sequence is as follows: {T (i,j,k),t-q ,...,T (i,j,k),t ,...,T (i,j,k),t+q }。 5. The painting room temperature and humidity control system based on the Internet of Things according to claim 3 is characterized in that: The data fusion method is as follows: Where TP t is the average temperature of the painting room space at the corresponding acquisition time node t, β (i,j,k) Different weight coefficients are pre-assigned according to the location of the sensor and its representativeness to the overall environment; In the formula, HP t is the average humidity of the painting room space at the corresponding collection time node t.

6. The painting room temperature and humidity control system based on the Internet of Things according to claim 5 is characterized in that: The analysis method of the control analysis module is as follows: Step G1, extract the target temperature range and target humidity range pre-set according to the coating room, and mark them as [T min ,T max ] and [H min ,H max ]; Among them, T min is the minimum temperature in the target temperature range, T max is the maximum temperature in the target temperature range; Step G2, by: Calculate the temperature deviation TC at each acquisition time node t respectively t and humidity deviation HC t ; Step G3, determine the control signals of temperature and humidity according to the temperature deviation and humidity deviation; Step G4, combining the preset signal strength ratio coefficients corresponding to the temperature and humidity respectively, to determine the temperature control signal strength and the humidity control signal strength.

7. The Internet of Things-based painting room temperature and humidity control system according to claim 6 is characterized in that: Step G3 is as follows: If TC t >0, a temperature-down control signal is generated; If TC t When <0, a temperature increase control signal is generated; If TC t =0, no corresponding temperature adjustment control signal is generated; If HC t When >0, a humidity downward control signal is generated; If HC t When <0, a humidity increase control signal is generated; If HC t =0, no corresponding humidity adjustment control signal is generated.

8. The painting room temperature and humidity control system based on the Internet of Things according to claim 6 is characterized in that: The temperature control signal strength and humidity control signal strength are determined as follows: UT t =TC t ×KT Where UT t The signal strength is controlled by temperature, and KT is the signal strength proportional coefficient corresponding to the preset temperature; UH t =HC t ×KH Where, UH t The signal strength is controlled by temperature, and KH is the signal strength proportional coefficient corresponding to the preset humidity.

9. The painting room temperature and humidity control system based on the Internet of Things according to claim 8 is characterized in that: The control method of the control execution module is as follows: When the temperature control signal strength UT t >0, the air conditioning cooling power will be increased; When the temperature control signal strength UT t When <0, the air conditioning heating power is increased; When the humidity control signal strength UH t >0, the dehumidifier power is increased or the humidifier power is reduced; When the humidity control signal strength UH t When <0, the humidifier power is increased or the dehumidifier power is reduced.

10. The Internet of Things-based painting room temperature and humidity control system according to claim 9 is characterized in that: During the control process, the control execution module gradually adjusts the equipment operation state according to the control signal strength and adjustment accuracy, wherein the temperature adjustment accuracy of the air conditioner and the humidity adjustment accuracy of the humidifier and dehumidifier are obtained from their corresponding product manuals.

Images