Efficient machine room fluid dehumidification rotating wheel energy efficiency monitoring device

Abstract

The invention discloses an efficient machine room fluid dehumidification rotating wheel energy efficiency monitoring device, and relates to the technical field of environment monitoring, the efficient machine room fluid dehumidification rotating wheel energy efficiency monitoring device comprises a monitoring module and a control center, and the monitoring module comprises a receipt collection module, a communication module, a data acquisition card and a secondary data processing chip. According to the system, data monitoring is conducted on the dehumidifier through the receipt collection module, a large amount of data is collected, and therefore an operation state model and an energy efficiency change curve are established through the secondary data processing chip and the cloud computing platform, and the data, collected by the receipt collection module, of the dehumidifier in the working process are sent to the cloud computing platform through the secondary data processing chip; the method comprises the following steps: processing data through an algorithm, substituting the data into an operation state model, calculating the energy efficiency of the dehumidifier, and judging the energy efficiency change of the dehumidifier according to an energy efficiency change curve so as to judge the working state of the dehumidifier, so that the operation parameters of the dehumidifier are adjusted according to the monitoring data so as to realize the optimal dehumidification effect and energy utilization efficiency.

Description

Technical Field

[0001] The invention relates to the technical field of environmental monitoring, and in particular to a high-efficiency machine room fluid dehumidification wheel energy efficiency monitoring device. Background Art

[0002] As a high-efficiency dehumidification equipment, rotary dehumidifier is widely used in industry, medicine, food and other fields. However, in actual operation, the performance of rotary dehumidifier may be affected by many factors, such as wheel blockage, abnormal regeneration air temperature, motor failure, etc. These factors seriously affect the energy efficiency of rotary dehumidifier.

[0003] The monitoring methods in the existing technology often have problems such as low accuracy and slow response speed. In addition, the algorithms of the existing monitoring devices are outdated, and the results obtained are difficult to meet the needs of real-time energy efficiency monitoring of rotary dehumidifiers. Summary of the invention

[0004] The purpose of the present invention is to provide a high-efficiency machine room fluid dehumidification wheel energy efficiency monitoring device, which can monitor multiple key parameters of the rotary dehumidifier in real time, and process and analyze the monitoring data through advanced data analysis algorithms, thereby achieving a comprehensive and accurate evaluation of the operating status of the rotary dehumidifier.

[0005] In order to achieve the above-mentioned purpose, the present invention adopts the following technical scheme: a high-efficiency machine room fluid dehumidification wheel energy efficiency monitoring device, including a monitoring module and a control center, the monitoring module includes a data collection module, a communication module, a data acquisition card and a secondary data processing chip, the data collection module includes an air humidity sensor, an air composition sensor, a photoelectric sensor, a heat detection module, a pressure sensor, an air flow sensor and a fault detection module, the photoelectric sensor includes a reflection plate, the heat detection module includes an air temperature sensor, a motor temperature sensor, an optical fiber temperature sensor and an infrared thermal imaging sensor, the fault detection module includes an acoustic sensor and a vibration sensor, the control center includes a communication module, a processing module, an audible and visual alarm module and a display, the processing module includes a data management module and a device control chip, the data management module includes a secondary data processing chip and a storage module, and the audible and visual alarm module includes a buzzer and an indicator light.

[0006] As a further description of the above technical solution:

[0007] The air humidity sensor is installed inside the air inlet pipe, air outlet pipe, regeneration air inlet pipe and regeneration air outlet pipe of the dehumidifier, the pressure sensor is installed inside the air inlet pipe, air outlet pipe, regeneration area, adsorption area and regeneration air inlet pipe and regeneration air outlet pipe of the dehumidifier, the air flow sensor is installed inside the air inlet pipe, air outlet pipe, regeneration air inlet pipe and regeneration air outlet pipe, and the air composition sensor is installed inside the air inlet pipe.

[0008] As a further description of the above technical solution:

[0009] The photoelectric sensor includes a reflecting plate, and the photoelectric sensor is installed inside an outer shell corresponding to the outer surface of the wheel. The reflecting plate is installed on the outer surface of the wheel. Through the cooperation of the photoelectric sensor and the reflecting plate, the rotation speed of the wheel can be detected to ensure that the wheel runs stably at the set speed and angle, and to ensure the synchronization and coordination of the dehumidification and regeneration processes. If the wheel speed is abnormal, it may affect the dehumidification effect and the regeneration effect of the adsorbent, and reduce the energy efficiency of the system.

[0010] As a further description of the above technical solution:

[0011] The air temperature sensor is installed in the heating module, air inlet pipe, air outlet pipe, air inlet pipe and air outlet pipe of the dehumidifier and the side of the air duct of the heating fan. The air temperature sensors are evenly arranged in the air inlet pipe and air outlet pipe of the regeneration zone at a certain interval to accurately measure the regeneration air temperature and monitor the temperature changes of these key parts in real time. When the temperature exceeds the set threshold, the control system can take timely measures, such as reducing the heating power or stopping heating, to prevent overheating and damage of components, ensure the safe and stable operation of the system, and avoid energy waste caused by excessive heating. The air temperature sensor is installed near the elbows of the air inlet pipe and the air outlet pipe and the entrances of each branch pipe of the tee. It can monitor the temperature difference caused by the turning of the air flow and the temperature changes of the regeneration air in different branches. The temperature changes at these positions may indicate abnormal air flow or heat exchange problems, which helps to discover potential pipe blockages or uneven air flow problems.

[0012] As a further description of the above technical solution:

[0013] The motor temperature sensor is installed in the middle of the rotor motor heat sink, the optical fiber temperature sensor is installed inside the rotor, and the infrared thermal imaging sensor is installed outside the dehumidifier.

[0014] As a further description of the above technical solution:

[0015] The acoustic sensor and vibration sensor are both installed on one side of the rotary motor and the transmission component. The acoustic sensor can be used to monitor the operating sound of the equipment to determine whether the operating status of the equipment is normal. By detecting the noise level of the machine, if the noise increases abnormally, it may mean that the machine has failed or is inefficient. The vibration sensor can accurately capture the tiny vibration changes of the motor and monitor the vibration amplitude and frequency of the motor, which provides the possibility for early warning of motor failure. This high-precision measurement capability enables staff to promptly discover hidden dangers in the equipment. If the vibration is abnormal, it may mean that the energy consumption efficiency of the motor is reduced and timely maintenance or replacement is required to avoid major accidents, thereby improving the operating efficiency and reliability of the equipment.

[0016] As a further description of the above technical solution:

[0017] The monitoring module and the control center both contain a communication module, and the communication module includes wired communication and wireless communication.

[0018] As a further description of the above technical solution:

[0019] The energy efficiency algorithm calculation steps recorded by the secondary data processing chip and the secondary data processing chip are:

[0020] S1: Data collection: The data collection module collects various data when the dehumidifier is working normally while monitoring the dehumidifier, and collects the data monitored by the data collection module through the data acquisition card;

[0021] S2: Preliminary data processing: The data acquisition card performs preliminary data processing, using a combination of low-pass filtering and mean filtering to remove high-frequency noise and random interference in the data. The weak signals collected are amplified, and the amplification factor is determined according to the output signal range of the sensor and the input requirements of the processing unit to ensure that the signal is within the amplitude range. The pre-processed data is analyzed through the cloud computing platform to establish a model of the equipment operation status;

[0022] S3: Data deep processing: The data initially processed by the data acquisition card is transmitted to the data management module through the communication module, and the data is processed by the secondary data processing chip to calculate the required data and store the data in the storage module;

[0023] S4: Calculate the data. The calculation steps are as follows:

[0024] Set the intake air temperature to T 进 , the outlet temperature is T 出 , the inlet saturated vapor pressure is P 饱和进 , outlet saturated vapor pressure P 饱和出, the saturated vapor pressure is calculated by the Antony equation. 8.071317, 1730.63 and 233.426 are the values ​​of the Antony constants of water at 0-100°C.

[0025] but:

[0026] Set the intake air humidity to d 进 , the moisture content of the outlet gas is d 出 , the intake air humidity is H 进 , the outlet humidity is H 出 , the intake pressure is P 进 , outlet pressure P 出 , 0.622 is the ratio of the molecular weight of water (about 18 g / mol) to the molecular weight of dry air (about 29 g / mol),

[0027] but:

[0028] Set the dehumidification capacity to Q and the intake gas flow rate to q 进 , the intake gas density is ρ 进 , the intake air moisture content is d 进 , the intake gas flow rate is q 出 , the density of the outgoing gas is ρ 出 , the moisture content of the outlet gas is d 出 ,

[0029] Then: Q = q 进 ×ρ 进 ×d 进 -q 出 ×ρ 出 ×d 出 ;

[0030] Set the intake gas density to ρ 进 , the density of the outgoing gas is ρ 出 , gas constant R = 287 J / (kg·K), if the pressure change is small, then P 进 =P 出 ,

[0031] but:

[0032] Set the regeneration energy consumption E 再生 , the regeneration heating power is P 再生加热 , running time bit t 运 ,

[0033] Then: E 再生 =P 再生加热 ×t 运 ;

[0034] Set the wheel drive energy consumption to E 驱动, the driving motor power is P 电 , running time bit t 运 ,

[0035] Then: E 驱动 =P 电 ×t 运 ;

[0036] The energy efficiency ratio EER of the dehumidification wheel is calculated as follows:

[0037] S5: Preset algorithm: The cloud computing platform calculates the energy efficiency ratio and dehumidification capacity under different data based on a large amount of data, draws the energy efficiency change curve based on the energy efficiency ratio and dehumidification capacity, and transmits the S4 algorithm and energy efficiency change curve back to the secondary data processing chip and the secondary data processing chip through the communication module, so that the secondary data processing chip and the secondary data processing chip are preset with the data algorithm and energy efficiency change curve;

[0038] S6: The steps to establish the equipment operation status model are as follows:

[0039] A: The data of the dehumidifier under normal working conditions is collected through the data collection module, and the data is cleaned through the data acquisition card to remove abnormal values ​​and noise data. Then, the data is transmitted to the secondary data processing chip through the communication module, and the data is stored in the storage module. The data stored in the storage module is the historical data, and at the same time, it is transmitted to the cloud computing platform through the communication module. The cloud computing platform performs range standardization on the data, and the original data is linearly transformed into the interval [0, 1], and the formula is used: new data = (original data - minimum value) / (maximum value - minimum value), so as to obtain the processed new data, ensuring that data of different dimensions can be compared and analyzed;

[0040] B: Data fusion analysis:

[0041] (1) Data fusion: Utilizing the data processing capabilities of the cloud computing platform, the weighted average and Kalman filtering methods are used to fuse data from different sensors to improve data accuracy and reliability.

[0042] (2) Feature extraction: Extract the following key features from the fused data: temperature change trend, ambient temperature change, humidity change range, flow rate change range, pressure fluctuation range, and impeller speed stability. These features will be used as input variables for the multivariate regression analysis method.

[0043] C: Establish equipment operation status model

[0044] Multiple regression analysis refers to a method of considering one variable as the dependent variable and one or more other variables as independent variables, establishing a linear or nonlinear mathematical model quantitative relationship between multiple variables, and using sample data for analysis.

[0045] (1) Taking the equipment operation status, dehumidification efficiency, regeneration energy consumption, impeller drive energy consumption, and dehumidification capacity as dependent variables, and the temperature change trend, ambient temperature change, humidity change range, flow rate change range, pressure fluctuation range, and impeller speed stability as independent variables, the cloud computing platform establishes a linear relationship between the independent and dependent variables through multiple regression analysis, and establishes an equipment operation status model. At the same time, the data of different faults of the dehumidifier are brought into the equipment operation status model to determine the location of different faults in the equipment operation status model;

[0046] (2) Model training:

[0047] Use historical data to train the equipment operation status model, and continuously adjust the model parameters to enable the model to accurately reflect the relationship between the equipment operation status and various monitoring data. Use the cross-validation method to verify the model to ensure the accuracy and reliability of the model. Optimize the model based on the verification results to improve the model's prediction ability.

[0048] (3) Deploy the equipment operation status model to the secondary data processing chip through the communication module;

[0049] D: Changes in ambient temperature will cause changes in air humidity and specific heat capacity, which in turn affects the dehumidification effect and energy efficiency of the dehumidification wheel. According to the performance of the dehumidifier under different working conditions, statistical analysis and data mining methods are used to find out the relationship between temperature and humidity, air flow rate, air pressure, air flow and ambient temperature and the dehumidification effect and energy consumption, and analyze the impact of environmental factors on the dehumidifier. According to the results of data analysis and the energy efficiency change curve, a mathematical model of dehumidifier performance is established, and the mathematical model of dehumidifier performance is deployed to the secondary data processing chip through the communication module.

[0050] As a further description of the above technical solution:

[0051] The monitoring process of the energy efficiency monitoring device is as follows:

[0052] S1: pre-process the data through the data acquisition card, and transmit the pre-processed data to the secondary data processing chip and the secondary data processing chip through the communication module. After the secondary data processing chip analyzes the data and detects that the data is different from the data generated by the normal operation of the dehumidifier, the secondary data processing chip transmits the data to the processing module through the communication module, and stores the data through the storage module;

[0053] S2: The data is brought into the equipment operation status model through the secondary data processing chip to obtain the equipment operation status and determine the working condition of the dehumidifier. At the same time, the data is calculated through the S4 algorithm to obtain the energy efficiency ratio and dehumidification capacity. The energy efficiency ratio and dehumidification capacity are compared with a large amount of historical data and the energy efficiency change curve. The secondary data processing chip judges the working condition of the dehumidifier through the equipment operation status model and the energy efficiency change curve, making the secondary data processing chip judge the working condition of the dehumidifier more accurately.

[0054] S3: The secondary data processing chip brings the data into the equipment operation status model and energy efficiency change curve to determine whether the data is normal. Depending on whether the data is normal, the dehumidifier is in the following two states:

[0055] A: Normal data: The dehumidifier is working normally;

[0056] B: Abnormal data: The dehumidifier has failed and the control center immediately triggers the alarm mechanism;

[0057] S4: Alarm modes include sound and light alarm module and display prompt;

[0058] A: The indicator light flashes in different patterns according to the fault type, and the buzzer emits a continuous alarm sound;

[0059] B: The display shows specific abnormal information in a striking manner, and the abnormal information is as follows: "Inlet air humidity is too high: current humidity [actual humidity value]; exceeds normal range [normal humidity range]";

[0060] "Regeneration air temperature is abnormal: the current temperature [actual temperature value] exceeds the normal range [normal temperature range]";

[0061] "Motor heat is too high: current temperature [actual temperature value] is out of normal range [normal temperature range]"; operators can quickly locate the problem based on this information;

[0062] S5: At the same time, the secondary data processing chip determines the type and cause of the fault of the dehumidifier according to the equipment operation status model, and finds the potential fault of the dehumidifier according to the predictive ability of the equipment operation status model, and provides detailed maintenance suggestions for on-site maintenance personnel to achieve remote maintenance and management of the equipment. After the dehumidifier is repaired, the data is brought into the equipment operation status model and the energy efficiency change curve again. If the data is in the normal working condition in the equipment operation status model, and the energy efficiency ratio and dehumidification amount obtained after the data is processed by the algorithm of S4 are consistent with the energy efficiency change curve, then the dehumidifier maintenance is completed and it can work normally. Otherwise, it needs to be repaired again;

[0063] S6: Under different ambient temperature conditions, reasonably adjust the dehumidifier's air intake flow, regeneration flow and impeller speed according to the monitoring data. At the same time, install a precooler or pre-dehumidification device at the air inlet to reduce the air intake temperature and humidity, thereby improving the dehumidification energy efficiency and achieving the best dehumidification effect and energy utilization efficiency.

[0064] The present invention has the following beneficial effects:

[0065] 1. In the present invention, the data of the dehumidifier is firstly monitored through the data collection module to collect a large amount of data, so as to establish an operation status model and an energy efficiency change curve through the secondary data processing chip and the cloud computing platform. The data of the dehumidifier when working collected by the data collection module is processed by the algorithm through the secondary data processing chip, and the data is brought into the operation status model to calculate the energy efficiency of the dehumidifier. The energy efficiency change of the dehumidifier is judged according to the energy efficiency change curve, so as to judge the working status of the dehumidifier, and then adjust the operation parameters of the dehumidifier according to the monitoring data to achieve the best dehumidification effect and energy utilization efficiency.

[0066] 2. Under different ambient temperature conditions, reasonably adjust the dehumidifier's air intake flow, regeneration flow and impeller speed according to the monitoring data. At the same time, install a precooler or pre-dehumidification device at the air inlet to reduce the air intake temperature and humidity, thereby improving the dehumidification energy efficiency and achieving the best dehumidification effect and energy utilization efficiency.

[0067] 3. In the present invention, the data is brought into the equipment operation status model through the secondary data processing chip to obtain the operation status of the equipment and determine the working condition of the dehumidifier. At the same time, the data is calculated through the S4 algorithm to obtain the energy efficiency ratio and dehumidification amount. The energy efficiency ratio and dehumidification amount are compared with a large amount of historical data and the energy efficiency change curve, so that the secondary data processing chip can judge the working condition of the dehumidifier through the equipment operation status model and the energy efficiency change curve, and determine the type and cause of the fault of the dehumidifier. At the same time, the equipment operation status model can predict the potential fault of the dehumidifier according to the abnormality of the data, and provide detailed maintenance suggestions for on-site maintenance personnel to realize remote maintenance and management of the equipment.

[0068] 4. After detecting a dehumidifier failure, the control center immediately triggers the alarm mechanism. The alarm methods include sound and light alarm modules and display prompts. The indicator lights flash in different modes according to the type of failure. At the same time, the buzzer emits a continuous alarm sound. The display shows specific abnormal information in a striking manner, quickly notifying the staff of the dehumidifier failure and helping them locate the problem. BRIEF DESCRIPTION OF THE DRAWINGS

[0069] Figure 1 It is a schematic diagram of the monitoring module system of the present invention;

[0070] Figure 2 It is a schematic diagram of the data collection module system of the present invention;

[0071] Figure 3 It is a schematic diagram of the control center system of the present invention.

[0072] Legend:

[0073] 1. Monitoring module; 2. Data collection module; 21. Air humidity sensor; 22. Air composition sensor; 23. Photoelectric sensor; 231. Reflector; 24. Heat detection module; 241. Air temperature sensor; 242. Motor temperature sensor; 243. Fiber optic temperature sensor; 244. Infrared thermal imaging sensor; 25. Pressure sensor; 26. Air flow sensor; 27. Fault detection module; 271. Acoustic sensor; 272. Vibration sensor; 3. Communication module; 31. Wired communication; 32. Wireless communication; 4. Data acquisition card; 5. Secondary data processing chip; 6. Control center; 7. Processing module; 71. Data management module; 711. Secondary data processing chip; 712. Storage module; 72. Device control chip; 8. Sound and light alarm module; 81. Buzzer; 82. Indicator light; 9. Display. 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] Reference Figure 1-Figure 3An embodiment of the present invention provides: a high-efficiency machine room fluid dehumidification wheel energy efficiency monitoring device, including a monitoring module 1 and a control center 6, the monitoring module 1 includes a data collection module 2, a communication module 3, a data acquisition card 4 and a secondary data processing chip 5, the data collection module 2 includes an air humidity sensor 21, an air composition sensor 22, a photoelectric sensor 23, a heat detection module 24, a pressure sensor 25, an air flow sensor 26 and a fault detection module 27, the photoelectric sensor 23 includes a reflector 231, the heat detection module 24 includes an air temperature sensor 2 41, motor temperature sensor 242, optical fiber temperature sensor 243 and infrared thermal imaging sensor 244, the fault detection module 27 includes an acoustic sensor 271 and a vibration sensor 272, the control center 6 includes a communication module 3, a processing module 7, an audible and visual alarm module 8 and a display 9, the processing module 7 includes a data management module 71 and a device control chip 72, the data management module 71 includes a secondary data processing chip 711 and a storage module 712, the audible and visual alarm module 8 includes a buzzer 81 and an indicator light 82, and the device control chip 72 includes a database management system.

[0076] The air humidity sensor 21 is installed in the air inlet pipe, air outlet pipe, regeneration air inlet pipe and regeneration air outlet pipe of the dehumidifier, the pressure sensor 25 is installed in the air inlet pipe, air outlet pipe, regeneration area, adsorption area and regeneration air inlet pipe and regeneration air outlet pipe of the dehumidifier, the air flow sensor 26 is installed in the air inlet pipe, air outlet pipe and regeneration air inlet pipe and regeneration air outlet pipe, the air composition sensor 22 is installed in the air inlet pipe, the photoelectric sensor 23 includes a reflector 231, the photoelectric sensor 23 is installed in the shell corresponding to the outer surface of the rotor, and the reflector 231 is installed on the outer surface of the rotor, The air temperature sensor 241 is installed on the dehumidifier's rotor, heating module, air inlet pipe, air outlet pipe, air inlet pipe and air outlet pipe of the regeneration zone, and the side of the air duct of the heating fan. The motor temperature sensor 242 is installed in the middle of the rotor motor heat sink. The optical fiber temperature sensor 243 is installed inside the rotor. The infrared thermal imaging sensor 244 is installed on the outside of the dehumidifier. The acoustic sensor 271 and the vibration sensor 272 are both installed on one side of the rotor motor and the transmission component. The monitoring module 1 and the control center 6 both contain a communication module 3, and the communication module 3 includes a wired communication 31 and a wireless communication 32.

[0077] The energy efficiency algorithm calculation steps recorded by the secondary data processing chip 5 and the secondary data processing chip 711 are as follows:

[0078] S1: Data collection: The data collection module 2 collects various data when the dehumidifier is working normally while monitoring the dehumidifier, and collects the data monitored by the data collection module 2 through the data acquisition card 4;

[0079] S2: Preliminary data processing: The data acquisition card 4 performs preliminary data processing, using a combination of low-pass filtering and mean filtering to remove high-frequency noise and random interference in the data. The weak signals collected are amplified, and the amplification factor is determined according to the output signal range of the sensor and the input requirements of the processing unit to ensure that the signal is within the amplitude range. The pre-processed data is analyzed through the cloud computing platform to establish a model of the equipment operation status;

[0080] S3: Data deep processing: The data preliminarily processed by the data acquisition card 4 is transmitted to the data management module 71 through the communication module 3, and the data is processed by the secondary data processing chip 711 to calculate the required data and store the data in the storage module 712;

[0081] S4: Calculate the data. The calculation steps are as follows:

[0082] Set the intake air temperature to T 进 , the outlet temperature is T 出 , the inlet saturated vapor pressure is P 饱和进 , outlet saturated vapor pressure P 饱和出 , the saturated vapor pressure is calculated by the Antony equation. 8.071317, 1730.63 and 233.426 are the values ​​of the Antony constants of water at 0-100°C.

[0083] but:

[0084] Set the intake air humidity to d 进 , the moisture content of the outlet gas is d 出 , the intake air humidity is H 进 , the outlet humidity is H 出 , the intake pressure is P 进 , outlet pressure P 出 , 0.622 is the ratio of the molecular weight of water (about 18 g / mol) to the molecular weight of dry air (about 29 g / mol),

[0085] but:

[0086] Set the dehumidification capacity to Q and the intake gas flow rate to q 进 , the intake gas density is ρ 进 , the intake air moisture content is d 进 , the intake gas flow rate is q 出 , the density of the outgoing gas is ρ 出 , the moisture content of the outlet gas is d 出 ,

[0087] Then: Q = q 进 ×ρ 进 ×d 进 -q出 ×ρ 出 ×d 出 ;

[0088] Set the intake gas density to ρ 进 , the density of the outgoing gas is ρ 出 , gas constant R = 287 J / (kg·K), if the pressure change is small, then P 进 =P 出 ,

[0089] but:

[0090] Set the regeneration energy consumption E 再生 , the regeneration heating power is P 再生加热 , running time bit t 运 ,

[0091] Then: E 再生 =P 再生加热 ×t 运 ;

[0092] Set the wheel drive energy consumption to E 驱动 , the driving motor power is P 电 , running time bit t 运 ,

[0093] Then: E 驱动 =P 电 ×t 运 ;

[0094] The energy efficiency ratio EER of the dehumidification wheel is calculated as follows:

[0095] S5: Preset algorithm: The cloud computing platform calculates the energy efficiency ratio and dehumidification amount under different data based on a large amount of data, draws an energy efficiency change curve based on the energy efficiency ratio and dehumidification amount, and transmits the algorithm and energy efficiency change curve of S4 back to the secondary data processing chip 5 and the secondary data processing chip 711 through the communication module 3, so that the secondary data processing chip 5 and the secondary data processing chip 711 are preset with data algorithms and energy efficiency change curves;

[0096] S6: The steps to establish the equipment operation status model are as follows:

[0097] A: The data of the dehumidifier under normal working condition is collected through the data collection module 2, and the data is cleaned through the data acquisition card 4 to remove abnormal values ​​and noise data. Then, the data is transmitted to the secondary data processing chip 711 through the communication module 3, and the data is stored in the storage module 712. The data stored in the storage module 712 is the historical data, and at the same time, it is transmitted to the cloud computing platform through the communication module 3. The cloud computing platform performs range standardization on the data, and the original data is linearly transformed into the interval [0, 1], and the formula is introduced: new data = (original data - minimum value) / (maximum value - minimum value), so as to obtain the processed new data, ensuring that data of different dimensions can be compared and analyzed;

[0098] B: Data fusion analysis:

[0099] (1) Data fusion: Utilizing the data processing capabilities of the cloud computing platform, the weighted average and Kalman filtering methods are used to fuse data from different sensors to improve data accuracy and reliability.

[0100] (2) Feature extraction: Extract the following key features from the fused data: temperature change trend, ambient temperature change, humidity change range, flow rate change range, pressure fluctuation range, and impeller speed stability. These features will be used as input variables for the multivariate regression analysis method.

[0101] C: Establish equipment operation status model

[0102] Multiple regression analysis refers to a method of considering one variable as the dependent variable and one or more other variables as independent variables, establishing a linear or nonlinear mathematical model quantitative relationship between multiple variables, and using sample data for analysis.

[0103] (1) Taking the equipment operation status, dehumidification efficiency, regeneration energy consumption, impeller drive energy consumption, and dehumidification capacity as dependent variables, and the temperature change trend, ambient temperature change, humidity change range, flow rate change range, pressure fluctuation range, and impeller speed stability as independent variables, the cloud computing platform establishes a linear relationship between the independent and dependent variables through multiple regression analysis, and establishes an equipment operation status model. At the same time, the data of different faults of the dehumidifier are brought into the equipment operation status model to determine the location of different faults in the equipment operation status model;

[0104] (2) Model training:

[0105] Use historical data to train the equipment operation status model, and continuously adjust the model parameters to enable the model to accurately reflect the relationship between the equipment operation status and various monitoring data. Use the cross-validation method to verify the model to ensure the accuracy and reliability of the model. Optimize the model based on the verification results to improve the model's prediction ability.

[0106] (3) Deploy the device operation status model to the secondary data processing chip 711 through the communication module 3;

[0107] D: Changes in ambient temperature will cause changes in air humidity and specific heat capacity, which in turn affect the dehumidification effect and energy efficiency of the dehumidification wheel. According to the performance of the dehumidifier under different working conditions, statistical analysis and data mining methods are used to find out the relationship between temperature and humidity, air flow rate, air pressure, air flow and ambient temperature and the dehumidification effect and energy consumption, and analyze the impact of environmental factors on the dehumidifier. According to the results of data analysis and the energy efficiency change curve, a mathematical model of dehumidifier performance is established, and the mathematical model of dehumidifier performance is deployed to the secondary data processing chip 5 through the communication module.

[0108] The monitoring process of the energy efficiency monitoring device is as follows:

[0109] S1: pre-process the data through the data acquisition card 4, and transmit the pre-processed data to the secondary data processing chip 711 and the secondary data processing chip 5 through the communication module 3. After the secondary data processing chip 711 analyzes the data and detects that the data is different from the data generated by the normal operation of the dehumidifier, the secondary data processing chip 5 transmits the data to the processing module 7 through the communication module 3, and stores the data through the storage module 712;

[0110] S2: The data is brought into the equipment operation state model through the secondary data processing chip 711 to obtain the operation state of the equipment and determine the working condition of the dehumidifier. At the same time, the data is calculated through the algorithm of S4 to obtain the energy efficiency ratio and dehumidification amount. The energy efficiency ratio and dehumidification amount are compared with a large amount of historical data and the change curve of energy efficiency, so that the secondary data processing chip 711 can judge the working condition of the dehumidifier through the equipment operation state model and the change curve of energy efficiency, so that the secondary data processing chip 711 can judge the working condition of the dehumidifier more accurately;

[0111] S3: The secondary data processing chip 711 brings the data into the equipment operation status model and the energy efficiency change curve to determine whether the data is normal. Depending on whether the data is normal, the dehumidifier is in the following two states:

[0112] A: Normal data: The dehumidifier is working normally;

[0113] B: Abnormal data: The dehumidifier has failed and the control center 6 immediately triggers the alarm mechanism;

[0114] S4: The alarm mode includes the sound and light alarm module 8 and the display 9 prompt,

[0115] A: The indicator light 82 flashes in different patterns depending on the type of fault, and the buzzer (81) emits a continuous alarm sound;

[0116] B: The display 9 displays specific abnormal information in a striking manner, and the abnormal information is as follows: "Inlet air humidity is too high: current humidity [actual humidity value]; exceeds normal range [normal humidity range]";

[0117] "Regeneration air temperature is abnormal: the current temperature [actual temperature value] exceeds the normal range [normal temperature range]";

[0118] "Motor heat is too high: current temperature [actual temperature value] is out of normal range [normal temperature range]"; operators can quickly locate the problem based on this information;

[0119] S5: At the same time, the secondary data processing chip 711 determines the type and cause of the fault of the dehumidifier according to the equipment operation status model, and provides detailed maintenance suggestions for on-site maintenance personnel to realize remote maintenance and management of the equipment. After the dehumidifier is repaired, the data is brought into the equipment operation status model and the energy efficiency change curve again. If the data is in a normal working condition in the equipment operation status model, and the energy efficiency ratio and dehumidification amount obtained after the data is processed by the algorithm of S4 are consistent with the energy efficiency change curve, then the dehumidifier maintenance is completed and can work normally. Otherwise, it needs to be repaired again;

[0120] S6: Under different ambient temperature conditions, reasonably adjust the dehumidifier's air intake flow, regeneration flow and impeller speed according to the monitoring data. At the same time, install a precooler or pre-dehumidification device at the air inlet to reduce the air intake temperature and humidity, thereby improving the dehumidification energy efficiency and achieving the best dehumidification effect and energy utilization efficiency.

[0121] In one embodiment, the collected and processed data are stored, and the data in the storage module 712 are all historical data. The equipment operation status model is established through an algorithm. By learning from a large amount of historical data, the trend prediction effect of the model is improved. The model can accurately evaluate the energy efficiency of the dehumidification wheel under different working conditions and predict the changing trend of energy efficiency, so as to more accurately determine whether there is a potential fault in the equipment.

[0122] In one embodiment, air humidity sensors 21 are arranged at multiple points in different cross-sections of the air inlet pipe, the air outlet pipe, the regeneration air inlet pipe and the regeneration air outlet pipe to obtain the distribution of air humidity in the pipe and fully understand the humidity changes of the air in the process of flowing through the dehumidification wheel. The humidity sensor installed in the air inlet pipe of the dehumidification wheel can measure the air humidity entering the dehumidification wheel in real time. Through this data, the initial humidity condition of the air to be treated can be understood, and basic information can be provided for evaluating the workload of the dehumidification wheel, thereby determining whether the dehumidification wheel is operating under appropriate working conditions. The air humidity sensor 21 of the air outlet pipe is used to detect the humidity of the air after being treated by the dehumidification wheel. By comparing the humidity of the air outlet pipe with the humidity of the air inlet pipe, the dehumidification efficiency of the dehumidification wheel can be directly obtained. If the humidity in the air outlet pipe is still high, it means that the dehumidification wheel may have performance degradation, adsorbent aging or abnormal wheel speed, and further inspection and maintenance are needed. Humidity sensors 21 are installed inside the air inlet pipe, air outlet pipe, regeneration air inlet pipe and regeneration air outlet pipe of the dehumidifier to monitor the humidity changes in different areas inside the wheel, which helps to gain a deeper understanding of the dehumidification and regeneration process and promptly discover abnormal humidity in the local area of ​​the wheel. Abnormally high humidity data in the air outlet pipe indicates that the adsorbent in this area is close to saturation or there is an airflow short circuit problem. Air humidity sensors 21 are installed in the regeneration air inlet pipe and the regeneration air outlet pipe to detect the changes in air humidity when the regeneration air passes through the regeneration area. Combined with the humidity changes in the adsorption area and the regeneration area, it can more accurately detect the humidity changes in the adsorption area and the regeneration area. The adsorption condition of the dehumidification wheel is obtained. Abnormal humidity in the regeneration air exhaust pipe may affect the regeneration effect of the adsorbent, and then affect the energy efficiency and service life of the entire dehumidification wheel. The pressure sensor 25 can measure the pressure changes in different parts of the dehumidifier. The pressure data can reflect the airflow resistance of the system and help determine whether there are problems such as pipe blockage, filter blockage or wheel blockage. If the air inlet pipe pressure is too high and the air outlet pipe pressure is too low, it means that the dehumidifier is blocked, resulting in reduced air flow and reduced dehumidification effect. Timely discovery and resolution of these problems can ensure the normal operation of the system and improve energy efficiency. Pressure sensors 25 are installed on the regeneration air inlet pipe and the regeneration air exhaust pipe to monitor the pressure changes during the regeneration process, which is convenient for evaluating the flow condition and The regeneration effect of the adsorbent. When the pressure sensor 25 detects abnormal data, it means that the regeneration air channel is blocked or the resistance of the adsorbent layer is too large. The regeneration system needs to be inspected and maintained to ensure that the adsorbent can be effectively regenerated and maintain the high performance of the dehumidification wheel. The air flow sensor 26 is installed on the inlet and outlet pipes of the dehumidification wheel to measure the air flow entering and exiting the dehumidification wheel. The air flow is one of the important factors affecting the dehumidification effect and energy efficiency. By monitoring the flow data, it can be ensured that the system operates within the designed flow range. Excessive air flow will lead to a decrease in the dehumidification effect, while too small a flow will make the utilization rate of the dehumidification wheel insufficient, resulting in energy waste. According to the data of the flow sensor, the speed of the fan can be adjusted to optimize the air flow.Improve the energy efficiency of the dehumidification wheel. The air humidity sensor 21 installed on the regeneration air inlet pipe and the regeneration air outlet pipe can monitor the regeneration air flow in real time and feed the data back to the control system so as to adjust the speed of the regeneration fan as needed to ensure the efficient regeneration process, thereby indirectly improving the overall energy efficiency of the dehumidification wheel. The appropriate regeneration air flow can ensure the full regeneration of the adsorbent and improve the cycle life of the dehumidification wheel. The probes of the pressure sensor 25 and the air flow sensor 26 are streamlined to reduce interference with the airflow. The air humidity sensor 21 is used to detect impurities, pollutants or special gas components in the air, which will affect the adsorption performance and life of the dehumidification wheel and reduce the energy efficiency of the dehumidification wheel. By monitoring the pollutant concentration, it provides a reference for the maintenance and operation optimization of the wheel. Timely filtering, purification and other measures can be taken to protect the dehumidification wheel and extend its service life, while ensuring the dehumidification effect and energy efficiency of the dehumidifier.

[0123] In one embodiment, the acoustic sensor 271 can be used to monitor the operating sound of the equipment to determine whether the operating status of the equipment is normal. By detecting the noise level of the machine, if the noise increases abnormally, it may mean that the machine has failed or is inefficient. The vibration sensor 272 can accurately capture the slight vibration changes of the motor and monitor the vibration amplitude and frequency of the motor. If the vibration is abnormal, it may mean that the energy efficiency of the motor is reduced and maintenance or replacement is required in time to avoid major accidents, thereby improving the operating efficiency and reliability of the equipment. This high-precision measurement capability can provide early warning at the early stage of motor failure, allowing staff to promptly discover hidden dangers in the equipment. Through the cooperation of the photoelectric sensor 23 and the reflector 231, the speed of rotation of the wheel can be detected to ensure that the wheel runs stably at the set speed and angle, thereby ensuring the synchronization and coordination of the dehumidification and regeneration processes. If the wheel speed is abnormal, it may affect the dehumidification effect and the regeneration effect of the adsorbent, and reduce the energy efficiency of the system. The air temperature sensors 241 are evenly arranged at certain intervals inside the air inlet pipe and the air outlet pipe of the regeneration zone to accurately measure the regeneration wind temperature and monitor the temperature changes of these key parts in real time. When the temperature exceeds the set threshold, the control system can take timely measures, such as reducing the heating power or stopping heating, to prevent components from overheating and damage, ensure the safe and stable operation of the system, and avoid energy waste caused by excessive heating. The air temperature sensor 241 is installed near the elbows of the air inlet pipe and the air outlet pipe and the entrances of each branch pipe of the tee. It can monitor the temperature difference caused by the turning of the air flow and the regeneration wind temperature changes of different branches. The temperature changes at these positions may indicate abnormal airflow or heat exchange problems, which helps to detect potential pipe blockages or uneven airflow problems.

[0124] In one embodiment, the motor temperature sensor 242 is installed in the motor coil part by means of thermal conductive glue or a special clamp to ensure good heat conduction and accurately reflect the temperature changes during the operation of the motor. The optical fiber temperature sensor 243 is installed near the surface of the rotor and maintains a certain distance from the rotor. This distance is determined according to the field of view and measurement range of the sensor. This non-contact installation method avoids the heat conduction problem caused by the direct contact between the traditional contact temperature sensor and the rotor, and will not affect the temperature field distribution on the surface of the rotor. At the same time, it can also monitor the temperature of the rotor when it is working, and can obtain the temperature changes of the rotor during operation in real time and accurately, which provides a reliable basis for judging the thermal equilibrium state of the rotor and whether there is local overheating. Abnormal changes in the rotor temperature may be related to factors such as air flow, heating power, and adsorbent performance. Excessive temperature of the rotor may be due to insufficient air flow or excessive heating power, resulting in heat being unable to Timely dissipation, while too low temperature may affect the regeneration effect of the adsorbent and reduce the energy efficiency of the dehumidification wheel. The system parameters can be optimized and adjusted to change the heat of the wheel. A precooler can be installed at the air inlet to reduce the intake temperature. In a high humidity environment, the intake air can first be passed through the cooling coil to reduce the temperature so that part of the water vapor condenses and precipitates, and then processed by the rotary dehumidifier to avoid overheating of the wheel. The wheel is at a suitable operating temperature, which helps to optimize the operating parameters of the wheel to improve energy efficiency and improve the energy efficiency and performance of the dehumidification wheel. The infrared thermal imaging sensor 244 monitors the ambient temperature around the dehumidification wheel, which helps to analyze the impact of environmental factors on the dehumidifier. Changes in ambient temperature may cause changes in parameters such as air humidity and specific heat capacity, thereby affecting the dehumidification effect and energy efficiency of the dehumidification wheel. Under different ambient temperature conditions, the operating parameters of the dehumidifier can be adjusted according to the monitoring data to achieve the best dehumidification effect and energy utilization efficiency.

[0125] Finally, it should be noted that the above is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, it is still possible for those skilled in the art to modify the technical solutions described in the aforementioned embodiments or to make equivalent substitutions for some of the technical features therein. 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.

Claims

1. A high-efficiency machine room fluid dehumidification wheel energy efficiency monitoring device, comprising a monitoring module (1) and a control center (6), characterized in that: The monitoring module (1) comprises a data collection module (2), a communication module (3), a data acquisition card (4) and a secondary data processing chip (5); the data collection module (2) comprises an air humidity sensor (21), an air composition sensor (22), a photoelectric sensor (23), a heat detection module (24), a pressure sensor (25), an air flow sensor (26) and a fault detection module (27); the photoelectric sensor (23) comprises a reflection plate (231); the heat detection module (24) comprises an air temperature sensor (241), a motor temperature sensor (242), an optical fiber sensor (233), a heat detection module (24), a pressure sensor (25), an air flow sensor (26) and a fault detection module (27); The device comprises a temperature sensor (243) and an infrared thermal imaging sensor (244); the fault detection module (27) comprises an acoustic sensor (271) and a vibration sensor (272); the control center (6) comprises a communication module (3), a processing module (7), an audible and visual alarm module (8) and a display (9); the processing module (7) comprises a data management module (71) and a device control chip (72); the data management module (71) comprises a secondary data processing chip (711) and a storage module (712); and the audible and visual alarm module (8) comprises a buzzer (81) and an indicator light (82).

2. According to claim 1, a high-efficiency machine room fluid dehumidification wheel energy efficiency monitoring device is characterized by: The air humidity sensor (21) is installed inside the air inlet pipe, air outlet pipe, regeneration air inlet pipe and regeneration air outlet pipe of the dehumidifier, the pressure sensor (25) is installed inside the air inlet pipe, air outlet pipe, regeneration area, adsorption area and regeneration air inlet pipe and regeneration air outlet pipe of the dehumidifier, the air flow sensor (26) is installed inside the air inlet pipe, air outlet pipe and regeneration air inlet pipe and regeneration air outlet pipe, and the air composition sensor (22) is installed inside the air inlet pipe.

3. According to claim 1, a high-efficiency machine room fluid dehumidification wheel energy efficiency monitoring device is characterized by: The photoelectric sensor (23) comprises a reflective plate (231), the photoelectric sensor (23) is mounted inside a housing corresponding to the outer surface of the rotating wheel, and the reflective plate (231) is mounted on the outer surface of the rotating wheel.

4. The high-efficiency machine room fluid dehumidification wheel energy efficiency monitoring device according to claim 1 is characterized by: The air temperature sensor (241) is installed on the side of the air duct of the dehumidifier's wheel, heating module, air inlet pipe, air outlet pipe and heating fan. The air temperature sensor (241) is installed near the elbows of the air inlet pipe and the air outlet pipe and the inlets of each branch pipe of the tee.

5. The high-efficiency machine room fluid dehumidification wheel energy efficiency monitoring device according to claim 1 is characterized by: The motor temperature sensor (242) is installed at the middle position of the rotor motor heat sink, the optical fiber temperature sensor (243) is installed inside the rotor, and the infrared thermal imaging sensor (244) is installed outside the dehumidifier.

6. The high-efficiency machine room fluid dehumidification wheel energy efficiency monitoring device according to claim 1 is characterized by: The acoustic sensor (271) and the vibration sensor (272) are both installed on one side of the rotary motor and the transmission component.

7. The high-efficiency machine room fluid dehumidification wheel energy efficiency monitoring device according to claim 1 is characterized by: The monitoring module (1) and the control center (6) both contain a communication module (3), the communication module (3) includes wired communication (31) and wireless communication (32), and the data management module (71) is connected to the cloud server via the wireless communication (32).

8. A high-efficiency machine room fluid dehumidification wheel energy efficiency monitoring device according to claim 1, characterized in that: The energy efficiency algorithm calculation steps recorded in the secondary data processing chip (5) and the secondary data processing chip (711) are as follows: S1: Data collection: The data collection module (2) collects various data when the dehumidifier is working normally while monitoring the dehumidifier, and collects the data monitored by the data collection module (2) through the data acquisition card (4); S2: Preliminary data processing: The data acquisition card (4) performs preliminary data processing, using a combination of low-pass filtering and mean filtering to remove high-frequency noise and random interference in the data. The weak signals collected are amplified, and the amplification factor is determined according to the output signal range of the sensor and the input requirements of the processing unit to ensure that the signal is within the amplitude range. The pre-processed data is analyzed through the cloud computing platform to establish a device operation status model; S3: Data in-depth processing: The data preliminarily processed by the data acquisition card (4) is transmitted to the data management module (71) through the communication module (3), and the data is processed by the secondary data processing chip (711), the required data is calculated, and the data is stored in the storage module (712); S4: Calculate the data. The calculation steps are as follows: Set the intake air temperature to T 进 , the outlet temperature is T 出 , the inlet saturated vapor pressure is P 饱和进 , outlet saturated vapor pressure P 饱和出 , the saturated vapor pressure is calculated by the Antony equation. 8.071317, 1730.63 and 233.426 are the values ​​of the Antony constants of water at 0-100°C. but: Set the intake air humidity to d 进 , the moisture content of the outlet gas is d 出 , the intake air humidity is H 进 , the outlet humidity is H 出 , the intake pressure is P 进 , outlet pressure P 出 , 0.622 is the ratio of the molecular weight of water (about 18 g / mol) to the molecular weight of dry air (about 29 g / mol), but: Set the dehumidification capacity to Q and the intake gas flow rate to q 进 , the intake gas density is ρ 进 , the intake air moisture content is d 进 , the intake gas flow rate is q 出 , the density of the outgoing gas is ρ 出 , the moisture content of the outlet gas is d 出 , Then: Q = q 进 ×ρ 进 ×d 进 -q 出 ×ρ 出 ×d 出 ; Set the intake gas density to ρ 进 , the density of the outgoing gas is ρ 出 , gas constant R = 287 J / (kg·K), if the pressure change is small, then P 进 =P 出 , but: Set the regeneration energy consumption E 再生 , the regeneration heating power is P 再生加热 , running time bit t 运 , Then: E 再生 =P 再生加热 ×t 运 ; Set the wheel drive energy consumption to E 驱动 , the driving motor power is P 电 , running time bit t 运 , Then: E 驱动 =P 电 ×t 运 ; The energy efficiency ratio EER of the dehumidification wheel is calculated as follows: S5: Preset algorithm: The cloud computing platform calculates the energy efficiency ratio and dehumidification amount under different data based on a large amount of data, draws an energy efficiency change curve based on the energy efficiency ratio and the dehumidification amount, and transmits the algorithm and energy efficiency change curve of S4 back to the secondary data processing chip (5) and the secondary data processing chip (711) through the communication module (3), so that the data algorithm and energy efficiency change curve are preset in the secondary data processing chip (5) and the secondary data processing chip (711); S6: The steps to establish the equipment operation status model are as follows: A: The data of the dehumidifier under normal working conditions is collected through the data collection module (2), and the data is cleaned through the data acquisition card (4) to remove abnormal values ​​and noise data. Then, the data is transmitted to the secondary data processing chip (711) through the communication module (3), and the data is stored in the storage module (712). The data stored in the storage module (712) is the historical data. At the same time, it is transmitted to the cloud computing platform through the communication module (3). The cloud computing platform performs range standardization processing on the data, and the original data is linearly transformed into the interval [0, 1], and is brought into the formula: new data = (original data - minimum value) / (maximum value - minimum value), so as to obtain the processed new data, ensuring that data of different dimensions can be compared and analyzed; B: Data fusion analysis: (1) Data fusion: Utilizing the data processing capabilities of the cloud computing platform, the weighted average and Kalman filtering methods are used to fuse data from different sensors to improve data accuracy and reliability. (2) Feature extraction: Extract the following key features from the fused data: temperature change trend, ambient temperature change, humidity change range, flow rate change range, pressure fluctuation range, and impeller speed stability. These features will be used as input variables for the multivariate regression analysis method. C: Establish equipment operation status model Multiple regression analysis refers to a method of considering one variable as the dependent variable and one or more other variables as independent variables, establishing a linear or nonlinear mathematical model quantitative relationship between multiple variables, and using sample data for analysis. (1) Taking the equipment operation status, dehumidification efficiency, regeneration energy consumption, impeller drive energy consumption, and dehumidification capacity as dependent variables, and the temperature change trend, ambient temperature change, humidity change range, flow rate change range, pressure fluctuation range, and impeller speed stability as independent variables, the cloud computing platform establishes a linear relationship between the independent and dependent variables through multiple regression analysis, and establishes an equipment operation status model. At the same time, the data of different faults of the dehumidifier are brought into the equipment operation status model to determine the location of different faults in the equipment operation status model; (2) Model training: Use historical data to train the equipment operation status model, and continuously adjust the model parameters to enable the model to accurately reflect the relationship between the equipment operation status and various monitoring data. Use the cross-validation method to verify the model to ensure the accuracy and reliability of the model. Optimize the model based on the verification results to improve the model's prediction ability. (3) deploying the equipment operation status model to the secondary data processing chip (711) through the communication module (3); D: Changes in ambient temperature will cause changes in air humidity and specific heat capacity, which in turn affects the dehumidification effect and energy efficiency of the dehumidification wheel. According to the performance of the dehumidifier under different working conditions, statistical analysis and data mining methods are used to find out the relationship between temperature and humidity, air flow rate, air pressure, air flow and ambient temperature and the dehumidification effect and energy consumption, and analyze the impact of environmental factors on the dehumidifier. According to the results of data analysis and the energy efficiency change curve, a mathematical model of dehumidifier performance is established, and the mathematical model of dehumidifier performance is deployed to the secondary data processing chip (5) through the communication module.

9. A high-efficiency machine room fluid dehumidification wheel energy efficiency monitoring device according to claim 8, characterized in that: The monitoring process of the energy efficiency monitoring device is as follows: S1: pre-processing the data through the data acquisition card (4), transmitting the pre-processed data to the secondary data processing chip (711) and the secondary data processing chip (5) through the communication module (3); after the secondary data processing chip (711) analyzes the data and detects that the data is different from the data generated by the normal operation of the dehumidifier, the secondary data processing chip (5) transmits the data to the processing module (7) through the communication module (3), and stores the data through the storage module (712); S2: The data is brought into the equipment operation state model through the secondary data processing chip (711) to obtain the equipment operation state and determine the working condition of the dehumidifier. At the same time, the data is calculated through the algorithm of S4 to obtain the energy efficiency ratio and the dehumidification amount. The energy efficiency ratio and the dehumidification amount are compared with a large amount of historical data and the energy efficiency change curve, so that the secondary data processing chip (711) can judge the working condition of the dehumidifier through the equipment operation state model and the energy efficiency change curve; S3: The secondary data processing chip (711) brings the data into the equipment operation status model and the energy efficiency change curve to determine whether the data is normal. Depending on whether the data is normal, the dehumidifier is in the following two states: A: Normal data: The dehumidifier is working normally; B: Abnormal data: The dehumidifier has failed and the control center (6) immediately triggers the alarm mechanism; S4: The alarm mode includes an audible and visual alarm module (8) and a display (9) prompt. A: The indicator light (82) flashes in different patterns depending on the type of fault, and the buzzer (81) emits a continuous alarm sound; B: The display (9) displays specific abnormal information in a striking manner, and the abnormal information is as follows: "Inlet air humidity is too high: current humidity [actual humidity value]; exceeds normal range [normal humidity range]"; "Abnormal regeneration air temperature: Current temperature [actual temperature value] exceeds the normal range [normal temperature range]"; "Motor heat is too high: current temperature [actual temperature value] is outside the normal range [normal temperature range]"; operators can quickly locate the problem based on this information; S5: At the same time, the secondary data processing chip (711) determines the type and cause of the fault of the dehumidifier according to the equipment operation status model, and provides detailed maintenance suggestions to the on-site maintenance personnel to realize remote maintenance and management of the equipment. After the dehumidifier is repaired, the data is brought into the equipment operation status model and the energy efficiency change curve again. If the data is in a normal working condition in the equipment operation status model, and the energy efficiency ratio and dehumidification amount obtained after the data is processed by the algorithm of S4 are consistent with the energy efficiency change curve, then the dehumidifier maintenance is completed and it can work normally. Otherwise, it needs to be repaired again. S6: Under different ambient temperature conditions, reasonably adjust the dehumidifier's air intake flow, regeneration flow and impeller speed according to the monitoring data, and install a precooler or pre-dehumidification device at the air inlet to reduce the air intake temperature and humidity.

Images