Low-porosity protective coating preparation system and method for weathering resistant steel for bridge

Abstract

The invention relates to the technical field of automatic control, in particular to a low-porosity protective coating preparation system and method for weathering resistant steel for bridges, and the system comprises a response offset adjustment module, a switching state judgment module, a linkage time coordination module, a drift grade linkage module and an abnormity interlocking control module. According to the method, the thickness uniformity and stability are enhanced through dynamic matching of the relation between the spraying power and the thickness increase, state recognition and interference elimination are achieved through difference comparison of multiple technological parameters, the reliability of the technological process is improved, the rhythm matching of multiple procedures is optimized in combination with time coordination and state synchronization between equipment, and the working efficiency is improved. The method has the advantages that fluctuation caused by running mismatch is reduced, drifting compensation for consistency of furnace temperature and gas flow rate is adopted, controllability of a heat treatment stage is improved, and cross-equipment parameter fluctuation correlation analysis is used, so that timely identification and treatment of abnormal states are realized, and compactness and protection performance of a coating are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of automation control technology, in particular to a low porosity protective coating preparation system and method for bridge weathering steel. BACKGROUND

[0002] The field of automation control technology includes the dynamic adjustment and closed-loop management of equipment operating parameters and process through sensor acquisition, signal transmission, data comparison, instruction generation, and device action, aiming to use the control unit to monitor and correct key physical quantities such as temperature, pressure, flow, speed, and position in real time, to ensure process stability and consistency, covering the coordinated operation of detection units, feedback control units, actuators, and human-machine interaction units, and achieving automatic monitoring and parameter adjustment of complex process through the combination of hardware and software, and is applied to material processing, equipment manufacturing, energy utilization, etc. The low porosity protective coating preparation system for bridge weathering steel refers to the combination of devices for automatic scheduling and parameter control of sandblasting roughening, plasma spraying, nitriding treatment, oxidation treatment, and vacuum sealing during the formation of a dense coating on the surface of weathering steel, covering substrate surface roughness control, powder feeding speed adjustment, spraying current and voltage control, atmosphere furnace temperature and gas flow control, cooling rate control, and vacuum environment sealing pressure and time control. Real-time acquisition is performed by configuring detection units such as temperature sensors, gas flow meters, pressure sensors, and thickness monitoring devices, and control signals are generated by the control unit after comparing with the preset values to drive the spraying device, atmosphere furnace heater, cooling system, and vacuum pump to complete the corresponding operation, achieving low porosity control of the entire coating preparation process.

[0003] In the traditional low porosity protective coating preparation technology for bridge weathering steel, parameter adjustment relies on preset value comparison and single-link correction, making it difficult to capture dynamic deviations between thickness growth and power output in a timely manner, leading to thickness uniformity being easily affected by delayed response. In the multi-link switching process, there is a lack of discrimination of parameter fluctuation direction and amplitude difference, and disturbance data is easily mixed with normal data, affecting process state judgment. When multiple devices run in parallel, it is difficult to correct time interval differences relying only on conventional feedback, causing rhythm mismatch and parameter instability. Under the condition of furnace temperature and gas flow fluctuation, effective compensation cannot be formed, resulting in uncontrollable deviation of heat treatment results. When multiple devices lose coordination, early warning and processing are not timely enough, affecting the density and overall consistency of the coating. SUMMARY

[0004] To solve the technical problems existing in the prior art, the present application provides a low porosity protective coating preparation system and method for bridge weathering steel. The technical solution is as follows: In one aspect, a low porosity protective coating preparation system for weathering steel for bridges is provided, the system comprising: The response offset adjustment module calls the spraying power output parameters, calculates the power transmission of the spraying current and voltage, judges the synchronization relationship between the thickness growth and the power output, detects the thickness response delay trend, adjusts the powder spraying speed and the spraying angle, and generates a thickness offset analysis result; The switching state determination module uses the thickness offset analysis result, collects multiple process parameter states, analyzes the fluctuation direction and amplitude difference, and matches the process completion characteristics corresponding to the stages, combines the stability of the parameter operation state, eliminates the disturbance period data, and generates stage state determination information; The linkage time coordination module judges the rhythm mismatching equipment according to the stage state determination information, compares the time interval of the operation response and the control instruction, combines the state synchronization degree between multiple process treatment equipment, adjusts the equipment control instruction output time, and generates rhythm mismatch correction data; The drift level linkage module uses the rhythm mismatch correction data to analyze the changes of furnace temperature and process gas flow rate, calculates the fluctuation intensity, judges the consistency of the data change direction, outputs the drift state level, and establishes a control compensation path to generate a heat treatment drift compensation configuration; The abnormal interlocking control module calls the heat treatment drift compensation configuration, analyzes the change direction of the spraying current, powder feeding speed, cooling air speed and furnace temperature in each cycle, judges the consistency of the parameter fluctuation between multiple equipment, identifies the cross-equipment miscoordination state, and sends abnormal alarm information to generate a linkage abnormality processing result.

[0005] As a further scheme of the present application, the thickness offset analysis result includes thickness response lag value, powder spraying speed correction amount, and spraying angle adjustment coefficient, the stage state determination information specifically includes stage switching verification identifier, process stability evaluation value, and disturbance period exclusion label, the rhythm mismatch correction data includes equipment response delay value, equipment start-up sequencing parameter, and handover timing adjustment amount, and the heat treatment drift compensation configuration specifically includes power correction gradient, gas flow rate ratio value, and drift level mapping section, and the linkage abnormality processing result includes trend miscoordination combination type, shutdown instruction trigger identifier, and interlocking abnormality identification label.

[0006] As a further scheme of the present application, the response offset adjustment module includes: The power transmission calculation submodule calls the spraying power output parameters, obtains the spraying current, spraying voltage, spraying gun displacement speed and spraying area coverage values, compares the changes of the spraying current and voltage, calculates the unit path power transmission, and establishes the path power transmission value; The thickness synchronous discrimination sub-module calls the path power transmission value, monitors the change of the spraying thickness, judges the synchronous relationship between the thickness growth and the power transmission, detects the thickness response delay trend and identifies as a state deviation area, and outputs the synchronous relationship information; The parameter adjustment compensation sub-module adjusts the spraying speed and spraying angle parameters according to the synchronous relationship information, and generates a thickness deviation analysis result.

[0007] As a further scheme of the present application, the process of detecting the thickness response delay trend and identifying as a state deviation area is specifically: collecting the spraying thickness change data in three continuous periods, and respectively calculating the difference value between the thickness growth value of each period and the thickness growth value of the previous period, if the absolute value of the thickness growth difference value in the three periods is less than the preset thickness change threshold value, it is determined that the thickness growth is not synchronized with the power transmission change; The setting basis of the preset thickness change threshold value is 0.85 times of the minimum response period average growth value of the spraying thickness change under the condition that the unit path power transmission value is unchanged; The minimum response period average growth value is obtained by piecewise linear fitting of the thickness data recorded continuously by the spraying thickness monitoring system, screening the time period with the most stable thickness change and calculating the average thickness increment per unit path in this period, and the stability judgment standard of the unit path power transmission value is that the fluctuation amplitudes of the spraying current and the spraying voltage in three continuous periods are less than 5% of the respective maximum allowable fluctuation range.

[0008] As a further scheme of the present application, the switching state determination module comprises: The process parameter acquisition sub-module obtains the thickness deviation analysis result, and acquires a plurality of process parameter states in each processing stage in real time, including current, process gas, furnace temperature, spraying thickness, and generates a multi-parameter acquisition data set; The fluctuation trend analysis sub-module analyzes the fluctuation direction and amplitude difference in each sampling period based on the multi-parameter acquisition data set, and matches with the process completion characteristics of the corresponding stage, and generates a process fluctuation trend matching value; The scheduling signal output sub-module calls the process fluctuation trend matching value, combines the parameter stable state, detects and eliminates the disturbance period parameters, outputs the process scheduling signal, and generates stage state determination information.

[0009] As a further scheme of the present application, the linkage time coordination module comprises: The response time comparison sub-module acquires the stage state determination information, acquires and compares the running response time and control instruction issuing time of a plurality of process equipment, including spraying equipment, atmosphere furnace, cooling fan, vacuum pump, judges the actual response deviation of each equipment, and generates an equipment response deviation value; The rhythm synchronization determination submodule determines the state synchronization degree among multiple devices based on the device response offset value, compares the rhythm matching conditions among the spraying device, the atmosphere furnace, the cooling fan and the vacuum pump, screens the rhythm mismatching devices and the start sequence differences, and generates a device synchronization determination coefficient; The instruction timing adjustment submodule calls the device synchronization determination coefficient, determines the influence of rhythm mismatching on stage handover, adjusts the control instruction output time of the corresponding device, and generates rhythm mismatching correction data.

[0010] As a further scheme of the present application, the drift level linkage module comprises: The heat treatment data identification submodule acquires the rhythm mismatching correction data, collects the furnace temperature and the process gas flow rate in the heat treatment stage, calculates the furnace temperature change amplitude and the gas flow rate change amplitude in each cycle, and obtains a heat treatment fluctuation amplitude value; The fluctuation state classification submodule compares the consistency of the data change direction in each cycle based on the heat treatment fluctuation amplitude value, including the same direction concentration state, the different direction concentration state and the trend dispersion state, classifies and outputs the drift state level, and generates a drift state classification result; The compensation path configuration submodule calls the drift state classification result, adjusts the output power and speed of the heating device and the gas supply device, establishes a control compensation path, and generates a heat treatment drift compensation configuration.

[0011] As a further scheme of the present application, the abnormal interlocking control module comprises: The cycle trend analysis submodule acquires the heat treatment drift compensation configuration, analyzes the change direction of the spraying current, the powder feeding speed, the cooling air speed and the furnace temperature in each cycle, and obtains a device parameter trend data group; The parameter consistency determination submodule calls the device parameter trend data group, determines the consistency of the parameter fluctuation among multiple devices, identifies the cycle synchronization characteristics, calculates the difference behavior between each parameter trend combination, and generates a cross-device consistency identification coefficient; The abnormal processing output submodule calls the cross-device consistency identification coefficient, identifies the cross-device miscoordination state, sends an abnormal alarm information and a shutdown signal according to the identification result, and generates a linkage abnormal processing result.

[0012] On the other hand, the method for preparing a low-porosity protective coating for a weathering steel for bridges is performed based on the system for preparing a low-porosity protective coating for a weathering steel for bridges described above, and comprises the following steps: S1: calling the spraying power output parameters, calculating the power transmission condition of the spraying current and voltage, determining the synchronization relationship between the thickness growth and the power output, detecting the thickness response delay trend, adjusting the powder spraying speed and the spraying angle, and generating a thickness offset analysis result; S2: Collect multiple process parameter states using the thickness offset analysis result, analyze the fluctuation direction and amplitude difference, and match with the process completion characteristics of the corresponding stage, combine the stability of the parameter running state, remove the disturbance period data, and generate stage state judgment information; S3: According to the stage state judgment information, by comparing the time interval of running response and control instruction, combining the state synchronization degree among multiple process equipment, judging the rhythm mismatch equipment, adjusting the equipment control instruction output time, generating rhythm mismatch correction data; S4: Using the rhythm mismatch correction data, analyze the changes of furnace temperature and process gas flow rate, calculate the fluctuation intensity, judge the consistency of data change direction, output the drift state level, and establish the control compensation path, generate the heat treatment drift compensation configuration; S5: Call the heat treatment drift compensation configuration, analyze the change direction of spraying current, powder feeding speed, cooling air speed and furnace temperature in each cycle, judge the consistency of parameter fluctuation among multiple equipment, identify the cross-equipment miscoordination state, and send abnormal alarm information, generate linkage abnormal processing result.

[0013] The technical scheme provided by the embodiment of the application has at least the following beneficial effects: Through dynamic matching of the spraying power and thickness growth relationship, the thickness uniformity and stability are enhanced, the state recognition and interference removal are realized by using the difference comparison of multiple process parameters, the reliability of the process is improved, the rhythm coordination of multiple processes is optimized by combining the time coordination and state synchronization among equipment, the fluctuation caused by running mismatch is reduced, the drift compensation of the consistency of furnace temperature and gas flow rate is adopted, the controllability of the heat treatment stage is improved, the abnormal state is identified and processed in time by using the parameter fluctuation correlation analysis among cross-equipment, and the coating density and protective performance are improved. BRIEF DESCRIPTION OF DRAWINGS

[0014] In order to more clearly illustrate the technical scheme in the embodiment of the application, the following will briefly introduce the drawings needed to be used in the embodiment description. Obviously, the drawings in the following description are only some embodiments of the application, and other drawings can be obtained by those skilled in the art without creative labor.

[0015] Figure 1 is a schematic diagram of a low-porosity protective coating preparation system for weathering steel for bridges provided by the embodiment of the application; Figure 2 is a system framework schematic diagram of the application; Figure 3 is a response offset adjustment module flow chart in the application; Figure 4Flow chart of the switching state determination module in the present application; Figure 5 Flow chart of the linkage time coordination module in the present application; Figure 6 Flow chart of the drift level linkage module in the present application; Figure 7 Flow chart of the abnormal interlocking control module in the present application; Figure 8 Flow chart of the method for preparing a low-porosity protective coating for weathering steel for bridges provided by an embodiment of the present application. DETAILED DESCRIPTION

[0016] The technical solutions in the present application will be described below with reference to the drawings.

[0017] In the embodiments of the present application, the words such as "example", "for example" and the like are used to represent as an example, illustration or description. Any embodiment or design scheme described as "example" in the present application should not be interpreted as more preferred or more advantageous than other embodiments or design schemes. Rather, the word "example" is intended to present the concept in a specific manner. In addition, in the embodiments of the present application, the meaning expressed by "and / or" can be both, or can be one of the two.

[0018] In the embodiments of the present application, "image" and "picture" can be used interchangeably at times, and it should be pointed out that the meanings expressed are consistent when the distinction is not emphasized. "Of", "corresponding" and "relevant" and "corresponding" can be used interchangeably at times, and it should be pointed out that the meanings expressed are consistent when the distinction is not emphasized.

[0019] In the embodiments of the present application, sometimes the subscript such as W1 can be written in the form of non-subscript such as W1, and the meanings expressed are consistent when the distinction is not emphasized.

[0020] To make the technical problems, technical solutions and advantages to be solved by the present application more clear, the following will be described in detail with reference to the drawings and specific embodiments.

[0021] The embodiments of the present application provide a low-porosity protective coating preparation system for weathering steel for bridges, as shown in Figures 1-2 The low-porosity protective coating preparation system for weathering steel for bridges shown in the schematic diagram of the system comprises: The response offset adjustment module calls the output parameters of the spraying power supply, calculates the power transmission of the spraying current and voltage, judges the synchronization relationship between the thickness growth and the power output, detects the thickness response delay trend, adjusts the powder spraying speed and the spraying angle, and generates a thickness offset analysis result. The switching state determination module utilizes the thickness offset analysis result, collects multiple process parameter states, analyzes the fluctuation direction and amplitude difference, and matches the process completion characteristics corresponding to the stages, combines the stability of the parameter running state, eliminates the disturbance period data, and generates stage state determination information; The linkage time coordination module generates rhythm mismatch correction data according to the stage state determination information, compares the time interval of the running response and the control instruction, combines the state synchronization degree between multiple process treatment equipment, judges the rhythm mismatch equipment, adjusts the equipment control instruction output time, and generates rhythm mismatch correction data; The drift level linkage module utilizes the rhythm mismatch correction data, analyzes the changes of the furnace temperature and the process gas flow rate, calculates the fluctuation intensity, judges the consistency of the data change direction, outputs the drift state level, establishes a control compensation path, and generates the heat treatment drift compensation configuration; The abnormal interlocking control module calls the heat treatment drift compensation configuration, analyzes the change direction of the spraying current, the powder feeding speed, the cooling air speed and the furnace temperature in each cycle, judges the consistency of the parameter fluctuation between multiple equipment, identifies the cross-equipment miscoordination state, and sends abnormal alarm information, and generates linkage abnormal processing result.

[0022] The thickness offset analysis result includes thickness response lag value, powder spraying speed correction amount, and spraying angle adjustment coefficient. The stage state determination information specifically includes stage switching verification identifier, process stability evaluation value, and disturbance period exclusion label. The rhythm mismatch correction data includes equipment response delay value, equipment start-up sequencing parameter, and handover timing adjustment amount. The heat treatment drift compensation configuration specifically includes power correction gradient, gas flow rate ratio value, and drift level mapping section. The linkage abnormal processing result includes trend miscoordination combination type, shutdown instruction trigger identifier, and interlocking abnormality identification label.

[0023] Specifically, as shown in Figure 2 , 3 The response offset adjustment module includes: The power transmission calculation sub-module calls the spraying power output parameter, obtains the spraying current, spraying voltage, spraying gun displacement speed and spraying area coverage value, compares the change of the spraying current and voltage, calculates the unit path power transmission, and establishes the path power transmission value; Firstly, in the process of spray power transmission calculation, the control system needs to call the spray power output parameters to obtain the key data such as spray current, spray voltage, etc., and combine the motion path information of the spray gun for comprehensive processing. The spray current and voltage are recorded in real time by the high-frequency acquisition system connected to the power module. For example, in the continuous operation state, the monitoring value of the spray current is maintained between 480 A and 500 A, and the spray voltage is maintained between 28 V and 30 V. The displacement speed of the spray gun is monitored by the arm load speed encoder, which is usually set to 250 mm / s. The spray area coverage value is calculated according to the nozzle spray width and the path length, for example, the spray width is 40 mm and the path length is 250 mm, then the spray area is 10000 mm². The construction of the unit path power transmission value is 10 mm per path, and the electric power value in a given period is 1420 W. This value will be used as representative data for subsequent synchronization analysis of spray heat input. The system will collect data for multiple cycles and compare the fluctuation amplitude to determine whether the power transmission is stable. When the unit path power fluctuation is within ± 15 W, it is determined to be in a stable state. The raw data collected in this process is shown in Table 1, and the parameters of each cycle are in normal working condition, forming a power stable control sample for subsequent matching with the thickness growth trend.

[0024] Table 1 Spray parameter and unit path power transmission data table

[0025] As shown in Table 1, the fluctuation of the unit path power value is small, which meets the stability judgment standard of spray heat input and is suitable for comparison and processing with the subsequent thickness response trend.

[0026] The thickness synchronization discrimination sub-module calls the path power transmission value, monitors the change of the spray thickness, judges the synchronization relationship between the thickness growth and the power transmission, detects the thickness response delay trend and identifies it as a state deviation area, and outputs the synchronization relationship information; Based on the above established unit path power transmission value, the real-time data of the spraying thickness monitoring system is called to judge whether the thickness change trend responds to the change of power input. In this system, the laser thickness gauge is used to collect the coating thickness growth value of three continuous cycles, the data record is cut into units of cycles, and the thickness growth data of unit path can be obtained combined with the movement path of the spray gun. For example, in a certain spraying operation, the power transmission value is maintained at 1420 W, the spraying thickness growth value is 48 μm in cycle 1, 47.5 μm in cycle 2, and 48.2 μm in cycle 3. The system preset synchronous identification standard is that the change direction of the thickness growth curve should be consistent with the trend of the power transmission curve, and the maximum offset should not exceed 0.5 seconds. In this case, the monitoring system synchronously collects the thickness growth response lagging behind the power peak value for 0.4 seconds, 0.6 seconds and 0.5 seconds respectively, and the average delay value is 0.5 seconds, which is close to the boundary range set by the system, so the system will mark this time period as a state offset area, and output it as synchronous relationship information for subsequent parameter compensation stage calling. If the delay is observed to be more than 1 second in other batches of operation, the system will record the abnormality and switch the spraying condition to the response adjustment state. Through this determination logic, the thickness response delay can be accurately identified, and the difference feature section is marked combined with the specific numerical interval, ensuring that the synchronism analysis has comparability and real-time performance.

[0027] The parameter adjustment compensation sub-module adjusts the powder spraying speed and spraying angle parameters according to the synchronous relationship information, and generates a thickness offset analysis result; Based on the synchronization relationship information of the pre-sequenced output, the output parameters of the key execution components are compensated by difference, and the main adjustment objects include the powder spraying speed and the spraying angle. In the actual spraying control, the powder spraying speed is executed by the screw powder feeder, and the standard set value is 2.5 g / s. When the average 0.5-second delay in the thickness response is identified, the system will automatically determine the compensation requirement, determine the incremental value based on the historical response data, and set the typical adjustment range to ±10% of the original speed. In this case, the system will increase the powder spraying speed to 2.75 g / s, and adjust the spraying angle from 85° to 88° to enhance the particle deposition density and cross-sectional coverage. The adjustment of the spraying angle is completed by the servo control component installed on the spray gun, and the accuracy can reach 0.5°. In the three cycles after the adjustment is completed, the thickness growth value recorded by the laser thickness gauge is increased to 50 μm, and the delay is reduced to 0.1 seconds, so the system determines that the compensation strategy is effective, and saves the current parameter configuration to the spraying database. If similar state offset areas appear again in the future, the system will preferentially call the current compensation parameters as the initial response strategy. In addition, the system determines the average reduction ratio of the parameter adjustment strategy to the response delay by clustering analysis on multiple historical samples, which is 76.4%, and the compensation response time is reduced to 24% of the original. These actual data provide effective support for the adjustment operation of the sub-module, so that the parameter adjustment has dynamic adaptive ability, and has multi-batch replicability and data traceability.

[0028] Specifically, as shown in Figure 2 、 4 The switching state determination module includes: The process parameter acquisition sub-module acquires the thickness offset analysis result, and acquires a plurality of process parameter states in each processing stage in real time, including current, process gas, furnace temperature, spraying thickness, to generate a multi-parameter acquisition data set; First, the thickness offset analysis results are obtained and used as the input for judgment data. During a continuous spraying cycle, the system collects multi-dimensional process parameters in real time, including current, process gas, furnace temperature, and spraying thickness, and establishes a timestamp sequence to ensure that data from different sources can be aligned under the same cycle benchmark. Taking a spraying test as an example, the system recorded the spraying current as 488 A, 491 A, and 490 A in three consecutive cycles, while the spraying voltage remained between 28.5 V and 29.5 V. Simultaneously, the oxygen-nitrogen mixture ratio in the atmosphere furnace was collected by a gas flow meter, with periodically recorded flow rates of 95 L / min, 96 L / min, and 94 L / min. The furnace temperature remained between 795 ℃ and 805 ℃ during this period, with real-time values ​​of 798 ℃, 800 ℃, and 803 ℃, respectively. The spraying thickness was monitored in real time by a laser thickness gauge, with periodic acquisition results of 47 μm, 48 μm, and 48.5 μm. After data acquisition, the system first calibrates the current, voltage, and coating thickness data using a stability reference system established by path power transfer values, eliminating anomalies caused by instantaneous power fluctuations. Subsequently, the system normalizes the atmosphere flow and furnace temperature data, enabling cross-comparison with the coating thickness data on a unified dimension, and generates a multi-parameter acquisition data set. This data set includes not only real-time acquired values ​​but also fluctuation amplitudes and relative offsets within each period, used as input for the subsequent trend matching module. The system also incorporates a stability check during the acquisition phase; if a parameter's fluctuation exceeds 5% of the maximum allowable range, it is marked as an anomaly in the multi-parameter acquisition data set for subsequent removal or separate analysis. This multi-parameter acquisition data set achieves unified acquisition and standardization of coating conditions across four dimensions: current, atmosphere, temperature, and thickness, providing a data foundation for trend analysis and judgment.

[0029] The fluctuation trend analysis submodule analyzes the differences in the direction and amplitude of fluctuations within each sampling period based on multi-parameter data sets, and matches them with the process completion characteristics of the corresponding stage to generate process fluctuation trend matching values. The specific formula for matching the process completion characteristics of the corresponding stage is as follows: ; Calculate the process trend matching coefficient and generate the process fluctuation trend matching value; in, For the first The coefficient of variation in the direction of fluctuation of the parameter. For the first The normalized value of the magnitude change of the term parameter, For the first The normalized value of the reference range for the corresponding stage target. For the first The weight value of the item parameter in the trend evaluation, The total number of process parameters in the sampling period, The serial number index of the parameter in the sampling period, The process trend matching coefficient.

[0030] In the above, the calculation formula of the process fluctuation trend matching value is: The formula first calculates the absolute value of the fluctuation direction difference of each parameter in the period, in order to quantify the consistency of the direction; then the square of the difference between the amplitude deviation and the reference amplitude is calculated to avoid the offset of positive and negative differences, and then the denominator is normalized and the square root is taken to ensure that the scale of the deviation value is comparable; finally, the weight product is introduced to adjust the importance of different parameters, and the sum of all parameters is divided by the number of parameters to obtain the overall trend matching coefficient. This process comprehensively utilizes absolute value, square, denominator normalization, square root and weighted average operations. Among them, : The fluctuation direction difference coefficient of the first dimension parameter, dimensionless, the quantification method is to calculate the cosine similarity value of the change direction angle of adjacent periods after collecting the parameter sequence, the range is . For example, when the spraying current changes in the same direction in two periods, the value is close to 0, and when it is completely opposite, the value is close to 1. The spraying current direction difference is set to 0.15, the atmosphere pressure direction difference is set to 0.10, and the furnace temperature direction difference is set to 0.20 in this embodiment. : The amplitude change normalization value of the first dimension parameter, the acquisition method is to collect the real-time amplitude change in each period (such as current fluctuation 4A) divided by the preset maximum allowable amplitude (such as 40A) to obtain a dimensionless ratio. For example, the current fluctuation amplitude in a certain period is 4A, and the maximum allowable amplitude is 40A, then . : The reference amplitude normalization value of the first dimension, the quantification method is to divide the target amplitude offset value of this process stage by the maximum allowable amplitude. For example, the target current fluctuation is controlled within 2A, and the maximum allowable amplitude is 40A, then . : The parameter weight value of the first dimension, dimensionless, determined by referring to the sensitivity of each parameter in the system to the coating density, and normalized to make the sum of all parameter weights equal to 1. For example, the current weight is 0.4, the furnace temperature weight is 0.35, and the atmosphere pressure weight is 0.25. : The number of parameters participating in the calculation in the sampling period, the embodiment sets , which are spraying current, furnace temperature and atmosphere pressure respectively.

[0031] Table 2 Process parameter normalization value and weight table

[0032] As shown in Table 2, the data are collected by the monitoring instrument and then calculated by normalization.

[0033] According to the formula, each term is calculated: Spraying current term: ; multiplied by the weight 0.40, 0.0795 is obtained.

[0034] Furnace temperature term: ; multiplied by the weight 0.35, 0.0768 is obtained.

[0035] Atmosphere pressure term: ; multiplied by the weight 0.25, 0.0446 is obtained.

[0036] Sum of the three: 0.0795+0.0768+0.0446=0.2009.

[0037] Divided by n=3 again: ; The final calculation result is the process fluctuation trend matching value 0.0670. The calculation result 0.0670 is in the preset matching interval [0, 0.10], which indicates that the periodic parameter fluctuation is highly close to the target stage process characteristics. The result shows that the generated process fluctuation trend matching value is consistent with the stage stable state, which can be used as a direct quantitative basis for subsequent process scheduling signals. The formula avoids the problem of incomparable between direction and amplitude by introducing the joint calculation of direction difference coefficient and amplitude offset normalization term, and through the combination of square, square root and normalization denominator, so that different physical quantities can be weighted and synthesized in a unified dimensionless scale, thereby comprehensively quantifying the process trend matching state.

[0038] The scheduling signal output submodule calls the process fluctuation trend matching value, combines the parameter stable state, detects and removes the disturbance periodic parameter, outputs the process scheduling signal, and generates the stage state judgment information; After calling the process fluctuation trend matching value, the scheduling signal output process needs to compare the matching value with the stable state in the multi-parameter acquisition data set and filter out the parameters belonging to the disturbance period. In actual operation, the system first sets the disturbance identification condition, for example, when the fluctuation directions of any two key parameters in the continuous period are opposite or the fluctuation amplitude exceeds 3% of the allowed interval, the period data is judged as a disturbance period and is excluded in the data marking. In a test process, the spraying current rises and falls in two periods, respectively, while the spraying thickness maintains a slow growth trend, the furnace temperature fluctuation is less than 3℃, and the atmosphere flow is stable. At this time, the system marks the reverse fluctuation of the current as a disturbance state and excludes it. Subsequently, the system comprehensively judges the remaining stable data and the aforementioned trend matching value to generate a process scheduling signal. The scheduling signal not only contains the time instruction of stage switching, but also clearly indicates the next operation sequence of the spraying power supply, the atmosphere furnace and the powder supply device, so as to avoid mutual interference between different devices. In a continuous spraying-cooling conversion experiment, the system outputs a scheduling signal according to the matching value, instructs the spraying power supply to be turned off when the thickness reaches 50 μm, sends a control signal to the atmosphere furnace to adjust the temperature to 780℃ and keep it for 5 minutes, and then starts the cooling fan to ensure smooth transition. The signal will be converted into stage state judgment information after generation, which contains the mark of whether the stage is completed, the stability index after the disturbance data is excluded, and the time stamp of device switching. Through this process, the system can realize closed-loop control from data trend analysis to scheduling signal output, ensure the generation of stage state judgment information to be traceable and stable, and form a logical connection with the subsequent linkage module.

[0039] Specifically, as shown in Figure 2 、 5 , the linkage time coordination module comprises: The response time comparison submodule acquires the stage state judgment information, acquires and compares the running response time and control instruction sending time of multiple process treatment devices, including spraying equipment, atmosphere furnace, cooling fan, vacuum pump, judges the actual response offset of each device, and generates a device response offset value; Based on the phase state judgment information, the actual running response time of the spraying equipment, the atmosphere furnace, the cooling fan and the vacuum pump in different process stages is collected and compared with the time of the control system to quantify the response deviation of each device. The system marks the time stamp at the time of issuing the control command, and records the completion time when the device performs the key state action (such as spraying power arc stabilization, atmosphere furnace heating power reaching the set value, cooling fan reaching the target wind speed, vacuum pump pressure stabilizing at the threshold value), and calculates the difference between the two as the response time. Taking a bridge weathering steel spraying experiment as an example, the spraying equipment command issuing time is 0.00 s, the arc stabilization time is 2.3 s, and the corresponding response deviation is 2.3 s; the atmosphere furnace heating command is issued at 5.00 s, and the temperature reaches 800 ℃ in 9.5 s, and the corresponding response deviation is 4.5 s; the cooling fan takes 3.8 s from starting to the wind speed reaching 12 m / s; the vacuum pump takes 6.1 s from starting to the cavity vacuum degree stabilizing at−0.09 MPa. The above deviation data is collected and arranged to generate a device response deviation value set. For easy statistics, the system samples three times independently at each stage, and takes the average value as the response deviation result of this stage. The deviation results of each device are listed in Table 3, which can reflect the response speed difference of different devices in the same stage.

[0040] Table 3 Process equipment response deviation data table

[0041] As shown in Table 3, the vacuum pump response deviation is obviously larger than that of other devices, indicating that it may become a key delay link in stage switching, and the system will focus on marking the device response deviation value when generating the device response deviation value.

[0042] The rhythm synchronization judgment submodule judges the state synchronization degree among multiple devices based on the device response deviation value, compares the rhythm matching situation among the spraying equipment, the atmosphere furnace, the cooling fan and the vacuum pump, selects the rhythm mismatching devices and the start sequence difference, and generates a device synchronization judgment coefficient; The running rhythm between the spraying equipment, the atmosphere furnace, the cooling fan and the vacuum pump is compared to determine the degree of state synchronization between the equipment, and the equipment with a large difference or offset in the starting sequence is screened out. First, the difference between the maximum and minimum values of the equipment response offset is taken as the rhythm difference benchmark. For example, when the vacuum pump is 6.1 s, the spraying equipment is 2.3 s, and the difference is 3.8 s, if it exceeds the preset 3.0 s synchronization difference threshold, it is determined that there is a rhythm mismatch. Then, the system determines the rhythm mismatch equipment by comparing the deviation of each equipment response offset and the overall average response offset. In this embodiment, the average response offset is 4.18 s, in which the vacuum pump deviates by +1.92 s and the spraying equipment deviates by -1.88 s, both of which exceed the set 1.5 s deviation standard, so they are identified as rhythm mismatch equipment. At the same time, the system also searches for the starting sequence of the equipment. If the starting delay of a certain equipment causes the next stage preparation signal to arrive in advance, it is determined that there is a difference in the starting sequence. In this case, the fast response of the spraying equipment causes its completion time to be significantly earlier than the stable points of the atmosphere furnace and the vacuum pump. The system marks this result as a sequence difference and generates a device synchronization determination coefficient for subsequent instruction timing adjustment. Through this sub-module, the system can establish quantitative data for rhythm coordination to ensure that the running states of different equipment have logical consistency.

[0043] The instruction timing adjustment submodule calls the device synchronization determination coefficient to determine the influence of rhythm mismatch on stage handover, adjusts the output time of the control instruction of the corresponding equipment, and generates rhythm mismatch correction data. After calling the device synchronization determination coefficient, the influence of rhythm mismatch on stage handover is quantified, and the output time of the control instruction is adjusted according to the response characteristics of different equipment. After identifying that the vacuum pump and the spraying equipment have rhythm deviation, the system will correct based on the average response offset. For example, if all equipment is required to complete stable operation within 15 s in the target stage, the control instruction of the vacuum pump is compensated by 6.1-4.18=1.92 s in advance, so that its starting signal is sent at 18.08 s; At the same time, the instruction of the spraying equipment is modified by 2.3-4.18=-1.88 s, that is, the system supplements the waiting logic by -1.88 s (i.e. the initial signal is not advanced) to avoid it entering the next stage too quickly. In multiple tests, this adjustment method reduces the equipment response time difference to 1.2 s, which is within the allowed range. Finally, the system establishes rhythm mismatch correction data based on the corrected instruction time as the input condition for subsequent stage process switching. Through this process, the linkage time coordination module can ensure that the running rhythm of multiple equipment remains consistent at stage handover, and avoid process interruption caused by the delay or advance of a single equipment.

[0044] Specifically, as Figure 2 ,6 The drift level linkage module includes: The thermal treatment data identification submodule acquires rhythm mismatch correction data, collects the furnace temperature and process gas flow rate in the thermal treatment stage, calculates the change amplitude of the furnace temperature and the change amplitude of the gas flow rate in each cycle, and obtains the thermal treatment fluctuation amplitude value; In the thermal treatment stage, the rhythm mismatch correction data is called as the input reference, the real-time values of the furnace temperature and the process gas flow rate are collected, and the periodic monitoring data sequence is established. The system calculates the change amplitude of the furnace temperature and the change amplitude of the gas flow rate in each 5-s sampling window to obtain the thermal treatment fluctuation amplitude value. Taking a nitriding treatment stage as an example, the furnace temperature rises from 790 ℃ to 798 ℃ in the first cycle, with a change amplitude of 8 ℃; rises from 798 ℃ to 805 ℃ in the second cycle, with an amplitude of 7 ℃; and drops from 805 ℃ to 802 ℃ in the third cycle, with an amplitude of 3 ℃. At the same time, the process gas flow rate rises from 95 L / min to 98 L / min in the first cycle, with an amplitude of 3 L / min; remains at 98 L / min to 99 L / min in the second cycle, with an amplitude of 1 L / min; and drops from 99 L / min to 96 L / min in the third cycle, with an amplitude of 3 L / min. After recording the periodic amplitudes of the furnace temperature and the gas flow rate, the system performs normalization processing to ensure that different parameters can be compared on a unified scale. For example, the maximum allowed amplitude of the furnace temperature is set to 20 ℃, and the maximum allowed amplitude of the gas flow rate is set to 10 L / min, and the normalization results are 0.40, 0.35, and 0.15 for the furnace temperature, and 0.30, 0.10, and 0.30 for the gas flow rate. The generated thermal treatment fluctuation amplitude value indicates the synchronization and offset of the furnace temperature and the gas flow rate in each cycle.

[0045] Table 4 Thermal treatment stage fluctuation amplitude normalization data table

[0046] As shown in Table 4, the system obtains the thermal treatment fluctuation amplitude value through collection and normalization processing, providing input conditions for subsequent drift state classification.

[0047] The fluctuation state classification submodule compares the consistency of the data change direction in each cycle based on the thermal treatment fluctuation amplitude value, including the same direction concentration state, the different direction concentration state, and the trend dispersion state, classifies and outputs the drift state level, and generates the drift state classification result. After obtaining the heat treatment fluctuation amplitude values, the change directions of the furnace temperature and gas flow rate in each cycle are compared and classified into the same direction concentration state, the opposite direction concentration state, or the trend dispersion state. The specific process is as follows: when the change directions of the furnace temperature and gas flow rate in a certain cycle are consistent, and the normalized value difference is less than 0.20, it is determined to be the same direction concentration state; when the change directions of the two are opposite, and the normalized value difference is more than 0.20, it is determined to be the opposite direction concentration state; when the change directions of the two are consistent but the difference is greater than 0.20, or the directions are different but the difference is less than 0.20, it is classified as the trend dispersion state. In the example data, the furnace temperature and gas flow rate in the first cycle both rise, the normalized difference is 0.10, and it is determined to be the same direction concentration state; the furnace temperature rises and the gas flow rate slightly decreases in the second cycle, the directions are inconsistent and the difference is 0.25, and it is determined to be the opposite direction concentration state; the directions of the two in the third cycle are consistent but the difference is 0.15, and it is determined to be the trend dispersion state. The system summarizes the classification results of each cycle, outputs the drift state level, and generates the drift state classification result. In this experiment, the results of the three cycles are the same direction concentration, the opposite direction concentration, and the trend dispersion, respectively. The system calculates the overall drift state level by setting the weights of the three states, and the specific value is marked as 2. The classification process ensures that different fluctuation characteristics can be distinguished and quantified, which is convenient for subsequent compensation steps.

[0048] The compensation path configuration submodule calls the drift state classification result, adjusts the output power and speed of the heating equipment and the gas supply equipment, establishes a control compensation path, and generates a heat treatment drift compensation configuration; After obtaining the drift state classification result, the output power and speed of the heating device and the gas supply device are adjusted according to different levels of drift, and a control compensation path is established. The system divides the drift state level into three intervals: 1 is low drift, maintaining the original parameters; 2 is medium drift, performing medium amplitude adjustment; 3 is high drift, performing large amplitude compensation. Taking the classification result of 2 in this example as an example, the system performs a small amplitude adjustment on the furnace temperature set value, increases the heating power by 3%, that is, from the rated 100 kW to 103 kW; at the same time, the gas flow rate is adjusted downward by 2%, from 96 L / min to 94 L / min, to offset the fluctuation offset. If the drift state classification result is 3, the system will increase the heating power to 105 kW, and adjust the gas flow rate downward by 5%, and at the same time, extend the atmosphere holding time by 5 minutes, to ensure that the fluctuation tends to be stable. All adjustment measures are recorded by the system as a control compensation path, and a heat treatment drift compensation configuration is generated in the monitoring interface. The compensation parameters, adjustment amplitude and execution time sequence are listed in detail in the configuration file, which serves as the basis for direct execution in subsequent operation. In this test, the heat treatment drift compensation configuration generated by the system finally shows that the furnace temperature power is adjusted to 103 kW, the gas flow rate is set to 94 L / min, and the atmosphere holding time is extended to 65 minutes of the original plan, thereby completing the establishment of the compensation path.

[0049] Specifically, as shown in Figure 2 、 7 , the abnormal interlocking control module comprises: The periodic trend analysis submodule obtains the heat treatment drift compensation configuration, analyzes the change direction of the spraying current, powder feeding speed, cooling air speed and furnace temperature in each cycle, and obtains a device parameter trend data set; Firstly, the heat treatment drift compensation configuration is called, and the furnace temperature and gas flow rate adjustment values therein are taken as the reference conditions, while the real-time data of the spraying current, powder feeding speed, cooling air speed and furnace temperature in the same period are collected. The system takes 1 second as a monitoring interval, and records the change direction and amplitude of each parameter in the continuous three periods. For example, in terms of the spraying current, the first period current rises from 480 A to 485 A, the second period falls from 485 A to 482 A, and the third period maintains 482 A to 483 A; the powder feeding speed is recorded as 30 g / min, 29 g / min and 31 g / min in the three periods respectively; the cooling air speed rises from 14.5 m / s to 15.0 m / s in the first period, maintains 15.0 m / s in the second period, and falls to 14.7 m / s in the third period; the furnace temperature rises from 800 ℃ to 805 ℃ in the first period, then falls to 798 ℃ in the second period, and maintains 799 ℃ in the third period. After these data are processed by the direction determination, the device parameter trend data set is formed, which not only marks the positive and negative directions of the value change, but also records the relative amplitude, so as to make consistency determination subsequently. During the monitoring process, if the sampling points of any parameter are lost or abnormal peaks appear, the system will automatically mark and exclude them, so as to ensure the integrity and reliability of the trend data set.

[0050] The parameter consistency determination submodule calls the device parameter trend data set, judges the consistency of the parameter fluctuations among multiple devices, identifies the period synchronization characteristics, calculates the difference behavior between each parameter trend combination, and generates a cross-device consistency identification coefficient; After obtaining the device parameter trend data set, the fluctuation directions and amplitudes among different devices need to be compared to determine the synchronization in the period. The system sets consistency determination conditions for each period: if at least three of the four parameters are consistent in direction, and the amplitude difference is less than 0.20, it is determined to be in synchronization; if the directions of two or more parameters are opposite, or the amplitude difference is greater than 0.20, it is determined to be out of coordination. In an experiment, the data set generated by the period trend analysis submodule shows that in the first period, the current and the furnace temperature direction are consistent and rise, while the powder feeding speed falls and the cooling air speed rises, only two parameters are consistent in direction, and the amplitude difference is 0.25, so it is determined to be out of coordination; in the second period, the current falls, the furnace temperature falls, the cooling air speed remains stable, and the powder feeding speed falls slightly, the trend directions of the four parameters are basically consistent, and the amplitude difference is 0.15, so it is determined to be in synchronization; in the third period, the current and the cooling air speed direction are consistent and rise, the furnace temperature and the powder feeding speed are different in direction, and the amplitude difference is 0.30, so it is determined to be out of coordination. The system calculates the cross-device consistency identification coefficient according to the determination results of the three periods, and the numerical interval is set to [0, 1], where 1 represents complete consistency and 0 represents complete loss of coordination. The identification coefficient obtained in this experiment is 0.42.

[0051] Table 5: Equipment parameter consistency determination example table

[0052] As shown in Table 5, the cross-equipment consistency identification coefficient is obtained by weighted average of the periodicity determination results, which facilitates subsequent abnormal processing output submodule calls.

[0053] The abnormal processing output submodule calls the cross-equipment consistency identification coefficient, identifies the cross-equipment miscoordination state, sends abnormal warning information and shutdown signals according to the identification results, and generates a linkage abnormal processing result; The cross-equipment consistency identification coefficient is called and compared with the preset control interval to determine whether to trigger abnormal warning information or shutdown signals. The system defines the consistency identification coefficient less than 0.50 as having a miscoordination risk, and immediately triggers a warning when two consecutive periods are determined to be miscoordinated. If two of the three periods are determined to be miscoordinated and the identification coefficient is less than 0.40, it is determined to be a serious miscoordination state, and the system performs a linkage shutdown. Taking the data of the present embodiment as an example, the identification coefficient is 0.42, which is in the risk interval, and two of the three periods are determined to be miscoordinated, which meets the shutdown condition. The system immediately sends abnormal warning information to the operation terminal and generates a shutdown signal, preferentially closes the spraying power supply and the powder feeding device, and then successively stops the cooling fan and the atmosphere furnace to avoid process out-of-control. The final linkage abnormal processing result is recorded in the log, including the trigger reason, the abnormal level, the shutdown sequence, and the parameter state snapshot. The record is used for subsequent analysis to ensure the transparency and traceability of the abnormal processing process.

[0054] Please refer to Figure 8 , a method for preparing a low-porosity protective coating for a bridge weathering steel is executed based on the above-mentioned low-porosity protective coating preparation system for a bridge weathering steel, comprising the following steps: S1: call the spraying power output parameter, calculate the power transmission of the spraying current and voltage, judge the synchronization relationship between thickness growth and power output, detect the thickness response delay trend, adjust the powder spraying speed and spraying angle, and generate a thickness deviation analysis result; S2: use the thickness deviation analysis result to collect multiple process parameter states, analyze the fluctuation direction and amplitude difference, and match with the process completion characteristics of the corresponding stage, combine the stability of the parameter running state, eliminate the disturbance period data, and generate stage state determination information; S3: according to the stage state determination information, by comparing the time interval of the running response and the control instruction, combining the state synchronization degree among multiple process equipment, judging the rhythm mismatch equipment, adjusting the equipment control instruction output time, generating the rhythm mismatch correction data; S4: using the rhythm mismatch correction data, analyzing the furnace temperature and the process gas flow rate change, calculating the fluctuation intensity, judging the consistency of the data change direction, outputting the drift state level, and establishing a control compensation path to generate a heat treatment drift compensation configuration; S5: calling the heat treatment drift compensation configuration, analyzing the change direction of the spraying current, the powder feeding speed, the cooling air speed and the furnace temperature in each cycle, judging the consistency of the parameter fluctuation among multiple devices, identifying the cross-device miscoordination state, and sending abnormal warning information to generate a linkage abnormality processing result.

[0055] The above is only a specific embodiment of the present application, but the protection scope of the present application is not limited thereto, any person skilled in the art can easily think of changes or replacements within the technical range disclosed by the present application, which should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A system for preparing a low-porosity protective coating for weathering steel used in bridges, characterized in that, The system includes: The response offset adjustment module calls the output parameters of the spraying power supply, calculates the power transfer of spraying current and voltage, determines the synchronous relationship between thickness growth and power output, detects the thickness response delay trend, adjusts the powder spraying speed and spraying angle, and generates thickness offset analysis results. The switching state determination module uses the thickness offset analysis results to collect the status of multiple process parameters, analyze the differences in fluctuation direction and amplitude, match them with the process completion characteristics of the corresponding stage, combine the stability of the parameter operation status, eliminate disturbance period data, and generate stage state determination information. The linkage time coordination module, based on the stage status determination information, compares the time interval between the running response and the control command, and combines the degree of state synchronization between multiple process equipment to determine the equipment with rhythm mismatch, adjust the output time of the equipment control command, and generate rhythm mismatch correction data. The drift level linkage module uses the rhythm mismatch correction data to analyze the changes in furnace temperature and process gas flow rate, calculate the fluctuation intensity, determine the consistency of the data change direction, output the drift state level, establish a control compensation path, and generate a heat treatment drift compensation configuration.

2. The low-porosity protective coating preparation system for weathering steel for bridges according to claim 1, characterized in that, The thickness offset analysis results include thickness response hysteresis value, powder spraying speed correction amount, and spraying angle adjustment coefficient. The stage state determination information specifically includes stage switching verification identifier, process stability assessment value, and disturbance cycle exclusion label. The rhythm mismatch correction data includes equipment response delay value, equipment start-up sequencing parameters, and handover timing adjustment amount. The heat treatment drift compensation configuration specifically includes power correction gradient, airflow rate ratio value, and drift level mapping section.

3. The low-porosity protective coating preparation system for weathering steel for bridges according to claim 1, characterized in that, The response offset adjustment module includes: The power transfer calculation submodule calls the output parameters of the spraying power supply to obtain the values ​​of spraying current, spraying voltage, spray gun displacement speed and spraying area coverage, compares the changes in spraying current and voltage, calculates the power transfer per unit path, and establishes the path power transfer value. The thickness synchronization discrimination submodule calls the path power transfer value, monitors the change in coating thickness, determines the synchronization relationship between thickness growth and power transfer, detects the thickness response delay trend and marks it as a state offset region, and outputs synchronization relationship information. The parameter adjustment and compensation submodule adjusts the powder spraying speed and spraying angle parameters according to the synchronization relationship information, and generates thickness offset analysis results.

4. The low-porosity protective coating preparation system for weathering steel for bridges according to claim 3, characterized in that, The process of detecting the thickness response delay trend and identifying it as a state offset region is as follows: collect coating thickness change data in three consecutive cycles, and calculate the difference between the thickness increase value in each cycle and the thickness increase value in the previous cycle. If the absolute value of the thickness increase difference in the three cycles is less than the preset thickness change threshold, it is determined that the thickness increase has not changed synchronously with the power transfer. The preset thickness change threshold is set based on 0.85 times the average increase in the minimum response period when the coating thickness change is constant under the condition that the power transfer value per unit path remains unchanged; The average growth value of the minimum response period is obtained by performing piecewise linear fitting on the thickness data continuously recorded by the coating thickness monitoring system, selecting the time period with the most stable thickness change, and calculating the average thickness increment per unit path within that period. The stability judgment criterion for the unit path power transfer value is that the fluctuation amplitude of the coating current and the coating voltage in three consecutive cycles is less than 5% of their respective maximum allowable fluctuation range.

5. The low-porosity protective coating preparation system for weathering steel for bridges according to claim 3, characterized in that, The switching state determination module includes: The process parameter acquisition submodule obtains the thickness offset analysis results and collects the status of multiple process parameters in each processing stage in real time, including current, process gas, furnace temperature, and coating thickness, and generates a multi-parameter acquisition data set. The fluctuation trend analysis submodule analyzes the differences in fluctuation direction and amplitude within each sampling period based on the multi-parameter data set, and matches them with the process completion characteristics of the corresponding stage to generate a process fluctuation trend matching value. The scheduling signal output submodule calls the process fluctuation trend matching value, combines it with the parameter stability state, detects and eliminates disturbance period parameters, outputs the process scheduling signal, and generates stage status judgment information.

6. The low-porosity protective coating preparation system for weathering steel for bridges according to claim 5, characterized in that, The linkage time coordination module includes: The response time comparison submodule obtains the stage status determination information, collects and compares the operating response time and control command issuance time of multiple process equipment, including spraying equipment, atmosphere furnace, cooling fan and vacuum pump, determines the actual response offset of each equipment, and generates equipment response offset value; The rhythm synchronization determination submodule determines the degree of state synchronization between multiple devices based on the device response offset value, compares the rhythm coordination between the spraying equipment, atmosphere furnace, cooling fan, and vacuum pump, filters out devices with rhythm mismatch and differences in start-up sequence, and generates device synchronization determination coefficients. The instruction timing adjustment submodule calls the device synchronization determination coefficient to determine the impact of rhythm mismatch on the stage handover, adjusts the control instruction output time of the corresponding device, and generates rhythm mismatch correction data.

7. The low-porosity protective coating preparation system for weathering steel for bridges according to claim 6, characterized in that, The drift level linkage module includes: The heat treatment data identification submodule acquires the rhythm mismatch correction data, collects the furnace temperature and process gas flow rate during the heat treatment stage, calculates the furnace temperature change amplitude and gas flow rate change amplitude for each cycle, and obtains the heat treatment fluctuation amplitude value. The fluctuation state classification submodule compares the consistency of the data change direction in each cycle based on the value of the heat treatment fluctuation amplitude, including the same-direction concentration state, opposite-direction concentration state, and trend dispersion state, classifies and outputs the drift state level, and generates the drift state classification result. The compensation path configuration submodule calls the drift state classification results, adjusts the output power and speed of the heating equipment and the gas supply equipment, establishes a control compensation path, and generates a heat treatment drift compensation configuration.

8. The low-porosity protective coating preparation system for weathering steel for bridges according to claim 1, characterized in that, The system also includes: The abnormal interlock control module calls the heat treatment drift compensation configuration, analyzes the direction of change of spraying current, powder feeding speed, cooling wind speed and furnace temperature in each cycle, judges the consistency of parameter fluctuations between multiple devices, identifies cross-device malfunctions, sends abnormal warning information, and generates linkage abnormal handling results. The results of the linkage anomaly handling include trend misalignment combination type, shutdown command trigger identifier, and interlock anomaly identification tag.

9. The low-porosity protective coating preparation system for weathering steel for bridges according to claim 8, characterized in that, The abnormal interlock control module includes: The cycle trend analysis submodule obtains the heat treatment drift compensation configuration, analyzes the changing direction of spraying current, powder feeding speed, cooling wind speed and furnace temperature in each cycle, and obtains the equipment parameter trend data group. The parameter consistency determination submodule calls the device parameter trend data group to determine the consistency of parameter fluctuations among multiple devices, identify periodic synchronization characteristics, calculate the difference behavior between each parameter trend combination, and generate cross-device consistency identification coefficients. The exception handling output submodule calls the cross-device consistency identification coefficient to identify cross-device inconsistency status, sends exception warning information and shutdown signal according to the identification result, and generates linkage exception handling result.

10. A method for preparing a low-porosity protective coating for weathering steel used in bridges, characterized in that, The low-porosity protective coating preparation system for weathering steel for bridges according to any one of claims 1-9 includes the following steps: S1: Call the output parameters of the spraying power supply, calculate the power transfer of spraying current and voltage, determine the synchronous relationship between thickness growth and power output, detect the thickness response delay trend, adjust the powder spraying speed and spraying angle, and generate thickness offset analysis results. S2: Using the thickness offset analysis results, collect the status of multiple process parameters, analyze the differences in fluctuation direction and amplitude, match them with the process completion characteristics of the corresponding stage, combine the stability of the parameter operation status, eliminate disturbance period data, and generate stage status judgment information. S3: Based on the stage status determination information, by comparing the time interval between the running response and the control command, and combining the degree of state synchronization between multiple process equipment, determine the equipment with rhythm mismatch, adjust the output time of the equipment control command, and generate rhythm mismatch correction data. S4: Using the rhythm mismatch correction data, analyze the changes in furnace temperature and process gas flow rate, calculate the fluctuation intensity, determine the consistency of the data change direction, output the drift state level, establish a control compensation path, and generate a heat treatment drift compensation configuration. S5: Invoke the heat treatment drift compensation configuration, analyze the direction of change of spraying current, powder feeding speed, cooling wind speed and furnace temperature in each cycle, determine the consistency of parameter fluctuations between multiple devices, identify cross-device malfunction status, send abnormal warning information, and generate linkage abnormal processing results.

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