Airflow optimization control system for high-voltage cable joint installation dust-free environment

Abstract

The invention, which relates to the high-voltage cable joint installation field, discloses a high-voltage cable joint installation dust-free environment airflow optimization control system comprising a multi-source data processing unit, a predictive analysis unit, a weight dynamic distribution unit and a regulation and control execution unit. According to the method, a multi-source data processing unit collects process related data and external environment data, the data are input into a predictive analysis unit, and a process related prediction module prejudges process parameter changes and outputs instructions according to a structured rule base and an LSTM model; the environmental interference pre-judgment module classifies and identifies interference types such as rainfall and temperature and influence degrees and performs graded early warning, and the priority judgment module calculates the superimposed influence of two types of prediction, defines regulation and control priorities, dynamically adjusts parameter regulation and control weights, coordinates synchronous operation of multiple devices and completes regulation and control of airflow and environmental parameters. And through predictive analysis, upgrading from passive response to active pre-judgment is realized, and the stability of a high-voltage cable joint installation environment is improved.

Description

Technical Field

[0001] This invention relates to the field of high-voltage cable joint installation technology, specifically to a dust-free environment airflow optimization control system for high-voltage cable joint installation. Background Technology

[0002] To ensure the installation quality of intermediate joints of 110kV and above high-voltage cables and avoid joint failures caused by environmental factors, it is necessary to create a dust-free environment in confined construction spaces such as cable trenches and cable wells or outdoor sites. Key parameters such as air cleanliness, temperature, humidity, and air pressure should be stably controlled within the range that meets the requirements of the construction process and adjusted through airflow optimization.

[0003] In existing technologies, during airflow optimization control, there are inherent delays in sensor data acquisition, signal transmission to the control unit, and equipment start-up and shutdown response. During the installation of high-voltage cable joints, dust generated during grinding and stripping processes increases instantaneously. In passive response mode, dust has already spread throughout the entire construction area when the equipment starts. Furthermore, after the control equipment starts, it takes a certain amount of time to bring the parameters back to the acceptable range, which can lead to a pollution window period in the construction area. This not only compromises cleanliness requirements but also affects the insulation performance and sealing effect of the joints, impacting the stability of the high-voltage cable joint installation environment. Summary of the Invention

[0004] The purpose of this invention is to provide a dust-free environment airflow optimization control system for high-voltage cable joint installation, in order to solve the problem mentioned in the background art that there are inherent delays in the sensor data acquisition, signal transmission to the control unit, and equipment start-up and shutdown response links, and that in passive response mode, dust has already spread to the entire construction area when the equipment starts up, affecting the stability of the high-voltage cable joint installation environment.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a dust-free environment airflow optimization control system for high-voltage cable joint installation, comprising a multi-source data processing unit, a predictive analysis unit, a weight dynamic allocation unit, and a control execution unit; The multi-source data processing unit is used to collect and preprocess multi-dimensional data during the installation of high-voltage cable joints, eliminate noise interference, and provide input to the predictive analysis unit after cleaning and optimization. The predictive analysis unit generates predictive instructions by anticipating changes in process trends and environmental disturbances. The predictive analysis unit includes a process correlation prediction module, an environmental interference prediction module, and a priority determination module; The process correlation prediction module, based on the long short-term memory network algorithm, predicts the parameter change trends of different processes and outputs prediction signals in advance; the environmental interference prediction module connects to on-site meteorological monitoring data to predict the impact of the external environment on the parameters inside the cabin; the priority determination module calculates the superposition value of parameter impacts and determines the control priority when the process correlation prediction module and the environmental interference prediction module are triggered at the same time. The weighted dynamic allocation unit dynamically adjusts the control weights of different parameters to take into account the different parameter priorities in different scenarios; The control execution unit executes control actions on airflow and environmental parameters based on the control results of the weighted dynamic allocation unit.

[0006] Preferably, the process association prediction module includes an association rule construction module, a prediction model construction module, and a prediction decision output module; The association rule building module provides prior knowledge to the prediction model building module by constructing a structured rule base. The prediction model building module is based on the LSTM model, strengthens the feature weights of key nodes, and outputs the predicted values ​​of particulate matter concentration, temperature, humidity, and air pressure. The prediction decision output module converts the prediction results of the prediction model building module into instructions that can be recognized by the control system, and performs secondary verification in conjunction with the rule base.

[0007] Preferably, the environmental interference prediction module includes an interference classification and prediction module and an early warning and control triggering module; The interference classification and prediction module receives data from the multi-source data processing unit to classify and predict the type of interference and its impact on cabin parameters. The early warning and control triggering module, based on the impact patterns of the interference classification and prediction module, classifies the command levels and generates early warning commands.

[0008] Preferably, in the interference classification and prediction module, the interference types are divided into rainfall, temperature, wind speed, and air pressure. Rainfall includes light rain, moderate rain, and heavy rain; temperature includes high temperature, low temperature, sudden rise, and sudden drop; wind speed includes light wind and strong wind; and air pressure includes sudden rise and sudden drop in air pressure.

[0009] Preferably, the instruction levels in the early warning and control trigger module include mild interference, moderate interference, severe interference, and extreme weather warnings.

[0010] Preferably, in the dynamic weight allocation unit, the dynamic adjustment of weight ratio includes parameter threshold proximity adjustment, interference superposition adjustment, and multi-parameter conflict adjustment. Parameter threshold proximity adjustment means that when a parameter is close to the specified threshold, its weight ratio is automatically increased. Interference superposition adjustment means that when there is external interference that increases the risk of a parameter, the weight of that parameter is increased. Multi-parameter conflict adjustment means that when multiple parameters are close to the threshold at the same time, the parameters are sorted according to their degree of influence on construction quality, and the weight of the core parameter is increased.

[0011] Preferably, the control execution unit includes a hierarchical control module and a device linkage module; The hierarchical control module is used to adjust the trigger thresholds and action priorities of each level of control, and output differentiated control actions; the equipment linkage module is used to coordinate the synchronous actions of different types of control equipment, and automatically match the corresponding equipment combinations and action sequences based on the current construction scenario and the dynamic weight allocation results.

[0012] Preferably, it also includes a clean chamber, one side of which is hinged to a door, a return air mechanism is installed on the back side of the clean chamber, and an air inlet mechanism is installed on the inside of the clean chamber. The air inlet mechanism includes connecting cylinders, and four connecting cylinders are provided. The four connecting cylinders are respectively installed at the four corners of the inside of the clean chamber. Each of the four connecting cylinders has an air outlet on one side. The top of the four connecting cylinders are fixedly connected to a multi-port pipe, and the other end of the multi-port pipe is fixedly connected to a first connecting pipe.

[0013] Preferably, a booster fan is fixedly connected to the other end of the first connecting pipe, one side of the booster fan is fixedly connected to the back side of the clean chamber, the other end of the booster fan is fixedly connected to a filter, and the other end of the filter is fixedly connected to an air inlet.

[0014] Preferably, the return air mechanism includes a filter screen, one side of which is fixedly connected to the back side of the cleanroom, and the other side of which is fixedly connected to a negative pressure box. A noise reduction plate is fixedly connected to the inside of the negative pressure box, and an exhaust fan is installed on one side of the noise reduction plate. One end of the exhaust fan is connected to the other side of the negative pressure box.

[0015] Compared with the prior art, the beneficial effects of the present invention are: 1. In this invention, a multi-source data processing unit collects process-related data and external environmental data, inputs them into a predictive analysis unit, and a process association prediction module predicts changes in process parameters and outputs instructions based on a structured rule base and LSTM model. An environmental interference prediction module classifies and identifies the types and degrees of interference such as rainfall and temperature, and issues graded warnings. A priority determination module calculates the superimposed effects of the two types of predictions and clarifies the control priority. Based on the construction scenario and the proximity of parameter thresholds, the parameter control weights are dynamically adjusted. Finally, the control execution unit matches control actions based on the degree of exceedance through a graded control module and coordinates the synchronous operation of multiple devices through an equipment linkage module to complete the control of airflow and environmental parameters. Predictive analysis achieves an upgrade from passive response to active prediction, improves the stability of the high-voltage cable joint installation environment, and reduces energy consumption and construction quality risks.

[0016] 2. In this invention, when the booster fan is started, the outside air is filtered by the filter to remove particulate matter. The booster fan pressurizes the outside air and distributes it evenly to the connecting cylinders at the four corners of the clean chamber through the first connecting pipe and the multi-port pipe. Finally, the air is blown into the chamber from the air outlet of the connecting cylinder to form a laminar airflow covering the entire chamber. The exhaust fan creates a negative pressure in the negative pressure box. The air carrying construction dust in the chamber is attracted by the negative pressure and discharged outside the chamber by the exhaust fan. This continuously maintains the circulation of clean airflow in the chamber, quickly replacing the polluted air and providing a stable dust-free operating space for the installation of high-voltage cable joints. Attached Figure Description

[0017] Figure 1 This is a schematic diagram of the airflow optimization control system for a dust-free environment during the installation of a high-voltage cable connector according to the present invention. Figure 2 This is a first three-dimensional structural diagram of a cleanroom for a dust-free environment airflow optimization control system for installing a high-voltage cable connector according to the present invention. Figure 3 This is a schematic diagram of the second three-dimensional structure of a cleanroom for a dust-free environment airflow optimization control system for installing a high-voltage cable connector according to the present invention. Figure 4 This is a schematic diagram of the internal cross-sectional structure of the cleanroom of a dust-free environment airflow optimization control system for installing a high-voltage cable connector according to the present invention. Figure 5 This is a schematic diagram of the disassembly structure of the return air mechanism of a dust-free environment airflow optimization control system for high-voltage cable joint installation according to the present invention.

[0018] In the diagram: 1. Multi-source data processing unit; 2. Predictive analysis unit; 21. Process association prediction module; 211. Association rule construction module; 212. Predictive model construction module; 213. Predictive decision output module; 22. Environmental interference prediction module; 221. Interference classification prediction module; 222. Early warning and control triggering module; 23. Priority determination module; 3. Weight dynamic allocation unit; 4. Control execution unit; 41. Hierarchical control module; 42. Equipment linkage module; 5. Door; 6. Cleanroom; 7. Air inlet mechanism; 71. Air inlet; 72. Filter; 73. Fan; 74. First connecting pipe; 75. Multi-port pipe; 76. Air outlet; 77. Connecting cylinder; 8. Return air mechanism; 81. Filter screen; 82. Noise reduction plate; 83. Exhaust fan; 84. Negative pressure box. Detailed Implementation

[0019] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0020] Example 1: Refer to Figure 1 - Figure 5 As shown: A dust-free environment airflow optimization control system for high-voltage cable joint installation includes a multi-source data processing unit 1, a predictive analysis unit 2, a weight dynamic allocation unit 3, and a control execution unit 4; The multi-source data processing unit 1 is used to collect and preprocess multi-dimensional data during the installation of high-voltage cable joints, eliminate noise interference, and provide input to the predictive analysis unit 2 after cleaning and optimization. Multi-dimensional data includes process-related data and external environmental data; Process-related data includes process trigger data, tool operation data, environmental baseline data, and historical process data. Process trigger data is collected through RFID tags and built-in sensors in tools, including start / end time, duration, and operator ID for processes such as stripping, grinding, cleaning, assembly, and curing, and is associated with differences in operating habits among different personnel. Tool operation data is collected, including the speed, power, and runtime of grinding and cutting equipment. Environmental baseline data is collected synchronously, including real-time temperature, humidity, particulate matter concentration, and air pressure data in the chamber, which serve as the benchmark for time-series correlation. Historical process data is imported from past construction records of 110kV and above cable joint installations, including process-parameter correspondences for different voltage levels, different construction sites, and different seasons.

[0021] External environmental data includes real-time weather station data, on-site micro-meteorological data, and geographical environmental data. Real-time weather station data is obtained by accessing data from official weather stations around the construction site, including temperature, relative humidity, rainfall intensity, wind speed, and air pressure. The focus is on collecting early warning signals for extreme weather such as short-term heavy rainfall and sudden temperature rises / falls. On-site micro-meteorological data is obtained by installing a miniature weather station outside the cabin to collect temperature, humidity, wind speed, and precipitation status outside the cabin, compensating for spatial deviations in official weather station data. Geographical environmental data includes pre-entered static data such as the type of construction site, surrounding obstructions, and altitude.

[0022] Predictive analysis unit 2 generates predictive instructions by anticipating changes in process trends and environmental disturbances; Predictive analysis unit 2 includes process correlation prediction module 21, environmental interference prediction module 22, and priority determination module 23; The process correlation prediction module 21 is based on the long short-term memory network algorithm to predict the parameter change trend of different processes and output the prediction signal in advance; The process association prediction module 21 includes an association rule construction module 211, a prediction model construction module 212, and a prediction decision output module 213; The association rule construction module 211 provides prior knowledge for the prediction model construction module 212 by constructing a structured rule base. Each rule in the rule base contains process conditions, parameter change rules, and document / data basis. Each time a high-voltage cable joint installation is completed, the change data is automatically entered into the rule base and the rule threshold is updated. The related parameters for the peeling process include dust concentration and airflow disturbance; the related parameters for the grinding process include dust concentration and tool power; the related parameters for the assembly process include air pressure fluctuation and personnel operation interference; and the related parameters for the curing process include temperature and humidity stability and cleanliness maintenance.

[0023] The prediction model building module 212 is based on the LSTM model, which strengthens the feature weights of key nodes such as process start time and tool power mutation, and outputs the predicted values ​​of particulate matter concentration, temperature and humidity, and air pressure for the next 10 seconds / 30 seconds / 60 seconds, as well as a binary judgment of whether they exceed the standard. The prediction decision output module 213 converts the prediction results of the prediction model construction module 212 into instructions that can be recognized by the control system, and performs secondary verification in conjunction with the rule base to avoid misjudgment.

[0024] The prediction instruction generation logic of the prediction decision output module 213 includes: when the model predicts that the particulate matter concentration will severely exceed the threshold within the next 10 seconds, and the rule base matches the dust generation pattern of the current grinding process, it outputs an instruction to immediately start severe regulation; when it predicts that the particulate matter concentration will reach the threshold of slight exceedance within the next 30 seconds, it outputs an instruction to start mild regulation in advance, reserving response time to avoid parameter exceedance; for the curing process, when it predicts that the humidity will approach the threshold within the next 60 seconds, it outputs an instruction to pre-start the dehumidification module to maintain humidity stability; when the prediction result differs greatly from the rule base, it automatically triggers double verification; if it is confirmed that the prediction deviation is greater than the threshold, it temporarily switches to conservative prediction based on the rule base to avoid erroneous regulation.

[0025] The environmental interference prediction module 22 connects to on-site meteorological monitoring data to predict the impact of the external environment on the cabin parameters. The environmental interference prediction module 22 includes an interference classification and prediction module 221 and an early warning and control triggering module 222; Interference classification and prediction module 221 receives data from multi-source data processing unit 1, classifies and predicts the type of interference and its impact on cabin parameters. The types of interference are divided into rainfall, temperature, wind speed and air pressure. Rainfall includes light rain, moderate rain and heavy rain; temperature includes high temperature, low temperature, sudden rise and sudden drop; wind speed includes light wind and strong wind; air pressure includes sudden rise and sudden drop in air pressure. Each type corresponds to a clear parameter impact pattern. Based on the impact patterns of the interference classification and prediction module 221, the early warning and control trigger module 222 classifies the command levels and generates early warning commands. The command levels include mild interference, moderate interference, severe interference, and extreme weather warnings. For mild interference, such as light rain, an early warning prompt is output, and the control system maintains its current operating state, only increasing the sampling frequency of the humidity sensor. For moderate interference, such as moderate rain, an early control command is output, activating the dehumidification module, lowering the humidity warning threshold, and reserving a control buffer. For severe interference, such as heavy rain and strong winds, an emergency control command is output, the dehumidification module operates at full capacity, the air pressure balance valve continuously replenishes clean air, and a pop-up window reminds construction personnel to reduce the frequency of entry and exit to prevent the expansion of gaps in the sealed chamber. For extreme weather warnings, a linkage protection command is output, which, in addition to activating the control equipment, simultaneously triggers the video monitoring system to record and uploads data to the remote monitoring platform in real time, facilitating decision-making by management personnel.

[0026] When the process association prediction module 21 and the environmental interference prediction module 22 are triggered simultaneously, the priority determination module 23 calculates the superimposed value of parameter influence and determines the control priority. When two types of predictions are triggered simultaneously within the same time window, the system automatically calculates the superimposed value of parameter influence. The process association prediction has a higher priority than the environmental interference prediction. When control resources are limited, priority is given to ensuring the stability of process association parameters. The dynamic weight allocation unit 3 dynamically adjusts the control weights of different parameters to address the varying priorities of parameters in different scenarios. Based on the base weights, it dynamically adjusts the weight ratios according to the real-time status of the parameters and the superposition of interference, ensuring the priority stability of core parameters. The dynamic adjustment of weight ratios includes parameter threshold proximity adjustment, interference superposition adjustment, and multi-parameter conflict adjustment. Parameter threshold proximity adjustment automatically increases the weight ratio when a parameter approaches a specified threshold. Interference superposition adjustment increases the weight of a parameter when external interference increases the risk of a parameter. Multi-parameter conflict adjustment prioritizes core parameters when multiple parameters approach their thresholds simultaneously, ranking them according to their impact on construction quality. The adjusted parameters are transmitted to the control execution unit 4 in real time, directly affecting the priority of the control strategy and resource allocation. The control execution unit 4 executes control actions on airflow and environmental parameters based on the control results of the weight dynamic allocation unit 3. The control and execution unit 4 includes a hierarchical control module 41 and an equipment linkage module 42; The graded control module 41 is used to adjust the trigger threshold and action priority of each level of control, and output differentiated control actions; The equipment linkage module 42 is used to coordinate the synchronous operation of different types of control equipment to avoid insufficient control efficiency of a single device. Based on the current construction scenario and combined with the dynamic weight allocation results, it automatically matches the corresponding equipment combination and action sequence.

[0027] Example 2: Figure 2 - Figure 5 As shown, it also includes a cleanroom 6, with a door 5 hinged to one side of the cleanroom 6. A return air mechanism 8 is installed on the back side of the cleanroom 6, and an air inlet mechanism 7 is installed on the inside of the cleanroom 6. The air inlet mechanism 7 includes four connecting cylinders 77, which are respectively installed at the four corners of the inside of the cleanroom 6. Each of the four connecting cylinders 77 has an air outlet 76 on one side. The top ends of the four connecting cylinders 77 are all fixedly connected to a multi-port pipe 75. The other end of the multi-port pipe 75 is fixedly connected to a first connecting pipe 74. The other end of the first connecting pipe 74... A booster fan 73 is fixedly connected to the back side of the cleanroom 6. One side of the booster fan 73 is fixedly connected to the back side of the cleanroom 6, and the other end of the booster fan 73 is fixedly connected to a filter 72. The other end of the filter 72 is fixedly connected to an air inlet 71. The return air mechanism 8 includes a filter screen 81. One side of the filter screen 81 is fixedly connected to the back side of the cleanroom 6, and the other side of the filter screen 81 is fixedly connected to a negative pressure box 84. A noise reduction plate 82 is fixedly connected to the inside of the negative pressure box 84. An exhaust fan 83 is installed on one side of the noise reduction plate 82, and one end of the exhaust fan 83 is connected to the other side of the negative pressure box 84.

[0028] After construction personnel or tools enter the clean chamber 6 through door 5, door 5 is closed to ensure initial isolation between the interior of the clean chamber 6 and the outside world. The booster fan 73 of the air intake mechanism 7 is then activated, drawing outside air into the filter 72. Particulate matter is removed by the filter 72, and the filtered clean air is pressurized by the booster fan 73 and delivered through the first connecting pipe 74 to the multi-port pipe 75. The multi-port pipe 75 then evenly distributes the air to four connecting cylinders 77. Finally, the clean air is blown into the clean chamber 6 from the outlet 76 of each connecting cylinder 77. The connecting tubes 77 are distributed in the four corners of the cabin, and the air outlets 76 can form a laminar airflow covering the entire cabin. Simultaneously, the exhaust fan 83 of the return air mechanism 8 is started. The operation of the exhaust fan 83 creates a negative pressure in the negative pressure box 84. The air carrying construction dust in the clean chamber 6 is attracted by the negative pressure. It first passes through the filter screen 81 to initially intercept large dust particles, and then enters the negative pressure box 84. When the air flows through the noise reduction plate 82, the operating noise of the exhaust fan 83 is weakened. Finally, the polluted air is discharged from the clean chamber 6 by the exhaust fan 83, maintaining the circulation of clean airflow in the clean chamber 6.

[0029] The usage and working principle of this device are as follows: Enter the cleanroom 6 through the hinged door 5 on one side. Close the door 5 to initially isolate the cleanroom 6 from the outside environment. The multi-source data processing unit 1 simultaneously collects multi-dimensional data, including basic environmental data and process-related data within the cleanroom 6, as well as external environmental data. This data is output to the predictive analysis unit 2. The process association prediction module 21, relying on the structured rule base of the association rule construction module 211 and the LSTM model of the prediction model construction module 212, predicts the parameter change trends of different processes and generates control commands. The environmental interference prediction module 22 identifies the interference type and parameter impact level through the interference classification prediction module 221. Then, the early warning control trigger module 222 outputs corresponding level early warning commands. The priority determination module 23 calculates the superposition value of the parameter impact of the two types of predictions to determine the control priority of the process association prediction. Finally, the weight dynamic allocation unit 3... Based on the current construction scenario and the proximity of parameter thresholds, the control weights of parameters such as particulate matter concentration, temperature, and humidity are dynamically adjusted, and the results are transmitted to the control execution unit 4. The hierarchical control module 41 matches the corresponding control level, and the equipment linkage module 42 synchronously coordinates the operation of the air intake mechanism 7 and the return air mechanism 8. The booster fan 73 is started, and the outside air is drawn into the filter 72 to filter particulate matter. After being filtered, the outside air is evenly distributed to the connecting cylinders 77 at the four corners of the clean chamber 6 through the first connecting pipe 74 and the multi-pass pipe 75. Finally, the air is blown into the chamber from the air outlet 76 of the connecting cylinder 77 to form a laminar airflow covering the entire chamber. The exhaust fan 83 is started, which creates a negative pressure in the negative pressure box 84. The air carrying construction dust in the chamber is drawn out of the chamber by the negative pressure. Subsequently, the system continuously collects real-time data through the multi-source data processing unit 1, and dynamically adjusts the operating status of equipment such as the booster fan 73 speed, the exhaust fan 83 power, and the dehumidification module after prediction and weight allocation.

[0030] Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A dust-free environment airflow optimization control system for high-voltage cable joint installation, characterized in that: It includes a multi-source data processing unit (1), a predictive analysis unit (2), a weight dynamic allocation unit (3), and a regulation execution unit (4); The multi-source data processing unit (1) is used to collect and preprocess multi-dimensional data during the installation of high-voltage cable joints, eliminate noise interference, and provide input to the predictive analysis unit (2) after cleaning and optimization. The predictive analysis unit (2) generates predictive instructions by predicting the trend of process changes and changes in environmental interference; The predictive analysis unit (2) includes a process association prediction module (21), an environmental interference prediction module (22), and a priority determination module (23). The process association prediction module (21) is based on the long short-term memory network algorithm to predict the parameter change trend of different processes and output the prediction signal in advance; the environmental interference prediction module (22) connects with the on-site meteorological monitoring data to predict the impact of the external environment on the cabin parameters; the priority determination module (23) calculates the parameter impact superposition value and determines the control priority when the process association prediction module (21) and the environmental interference prediction module (22) are triggered at the same time. The weight dynamic allocation unit (3) dynamically adjusts the control weights of different parameters according to the different priority of parameters in different scenarios; The control execution unit (4) performs control actions on airflow and environmental parameters based on the control results of the weight dynamic allocation unit (3).

2. The airflow optimization control system for high-voltage cable joint installation in a dust-free environment according to claim 1, characterized in that: The process association prediction module (21) includes an association rule construction module (211), a prediction model construction module (212), and a prediction decision output module (213). The association rule construction module (211) provides prior knowledge to the prediction model construction module (212) by constructing a structured rule base; the prediction model construction module (212) strengthens the feature weights of key nodes based on the LSTM model and outputs the predicted values ​​of particulate matter concentration, temperature and humidity and air pressure; the prediction decision output module (213) converts the prediction results of the prediction model construction module (212) into instructions that can be recognized by the control system, and performs secondary verification in conjunction with the rule base.

3. The airflow optimization control system for high-voltage cable joint installation in a dust-free environment according to claim 1, characterized in that: The environmental interference prediction module (22) includes an interference classification prediction module (221) and an early warning control triggering module (222). The interference classification and prediction module (221) receives data from the multi-source data processing unit (1) and classifies and predicts the type of interference and the degree of impact on the cabin parameters. The early warning and control triggering module (222) generates early warning commands by classifying command levels based on the influence law of the interference classification and prediction module (221).

4. The airflow optimization control system for high-voltage cable joint installation in a dust-free environment according to claim 2, characterized in that: In the interference classification and prediction module (221), the interference types are divided into rainfall, temperature, wind speed and air pressure. Rainfall includes light rain, moderate rain and heavy rain. Temperature includes high temperature, low temperature, sudden rise and sudden drop. Wind speed includes light wind and strong wind. Air pressure includes sudden rise and sudden drop in air pressure.

5. The airflow optimization control system for high-voltage cable joint installation in a dust-free environment according to claim 4, characterized in that: In the early warning and control trigger module (222), the command levels include mild interference, moderate interference, severe interference and extreme weather warning.

6. The airflow optimization control system for high-voltage cable joint installation in a dust-free environment according to claim 1, characterized in that: In the weight dynamic allocation unit (3), the dynamic adjustment of weight ratio includes parameter threshold proximity adjustment, interference superposition adjustment, and multi-parameter conflict adjustment. Parameter threshold proximity adjustment means that when a parameter is close to the specified threshold, its weight ratio is automatically increased. Interference superposition adjustment increases the weight of a parameter when external interference increases the risk of that parameter. When multiple parameters are close to their threshold values, the multi-parameter conflict adjustment prioritizes them according to their impact on construction quality.

7. The airflow optimization control system for high-voltage cable joint installation in a dust-free environment according to claim 1, characterized in that: The control execution unit (4) includes a hierarchical control module (41) and an equipment linkage module (42). The hierarchical control module (41) is used to adjust the trigger threshold and action priority of each level of control and output differentiated control actions; the equipment linkage module (42) is used to coordinate the synchronous actions of different types of control equipment and automatically match the corresponding equipment combination and action sequence according to the current construction scenario and the weight dynamic allocation result.

8. The airflow optimization control system for high-voltage cable joint installation in a dust-free environment according to claim 1, characterized in that: It also includes a clean chamber (6), one side of which is hinged with a door (5), a return air mechanism (8) is installed on the back side of the clean chamber (6), and an air inlet mechanism (7) is installed on the inside of the clean chamber (6). The air inlet mechanism (7) includes a connecting tube (77), and four connecting tubes (77) are provided. The four connecting tubes (77) are respectively installed at the four corners of the inside of the clean chamber (6). An air outlet (76) is opened on one side of each of the four connecting tubes (77). The top of the four connecting tubes (77) is fixedly connected to a multi-port pipe (75), and the other end of the multi-port pipe (75) is fixedly connected to a first connecting pipe (74).

9. A dust-free environment airflow optimization control system for high-voltage cable joint installation according to claim 8, characterized in that: The other end of the first connecting pipe (74) is fixedly connected to a booster fan (73). One side of the booster fan (73) is fixedly connected to the back side of the clean chamber (6). The other end of the booster fan (73) is fixedly connected to a filter (72). The other end of the filter (72) is fixedly connected to an air inlet (71).

10. A dust-free environment airflow optimization control system for high-voltage cable joint installation according to claim 8, characterized in that: The return air mechanism (8) includes a filter screen (81). One side of the filter screen (81) is fixedly connected to the back side of the clean chamber (6). The other side of the filter screen (81) is fixedly connected to a negative pressure box (84). A noise reduction plate (82) is fixedly connected to the inside of the negative pressure box (84). An exhaust fan (83) is installed on one side of the noise reduction plate (82). One end of the exhaust fan (83) is connected to the other side of the negative pressure box (84).

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