Printer high-speed printing heat dissipation and dust suppression method

Abstract

The invention relates to the technical field of printers, in particular to a high-speed printing heat dissipation and dust suppression method for a printer, which comprises the following specific steps: firstly, collecting temperature and dust concentration data of multiple positions in equipment, then predicting hot dust distribution and pre-judging a printing head track based on printing task parameters, and then fusing the data to calculate an area processing priority; and planning a path of the movable electrostatic processing unit and generating a dynamic background airflow instruction, then driving the unit to move and switching modes as required, executing a composite sweeping program on a high-temperature and high-dust area, and finally comparing the processed data with predicted data, correcting a model and calibrating track pre-judgment of a printing head. According to the method, deep linkage of all links is achieved through full-process closed-loop design, high-speed printing dynamic working conditions are adapted, motion interference between a processing unit and a printing head is avoided, the precision and adaptability of heat dissipation and dust removal work are improved, the model precision is improved through feedback optimization, and stable operation and printing precision of high-speed printing equipment are guaranteed.

Description

Technical Field

[0001] This invention relates to the field of printer technology, and in particular to a method for heat dissipation and dust suppression during high-speed printing. Background Technology

[0002] The continuous development of high-speed printing technology has significantly improved printing efficiency. However, the high-frequency movement of the printhead and the rapid melting and ejection of consumables have also led to the rapid accumulation of heat and the large-scale dissipation of dust inside the equipment. Heat dissipation and dust removal have become key technical aspects to ensure the stable operation of high-speed printing equipment and maintain printing accuracy. In existing technologies, heat dissipation and dust removal for printers often adopt a structure of fixed heat dissipation modules combined with local dust removal devices, or only perform simple dynamic control on a single aspect. Although these technologies can achieve basic heat dissipation and dust removal, they have not built a complete technical chain from data acquisition and trend prediction to path planning and collaborative execution. The technologies of each aspect are independent of each other and it is difficult to adapt to the dynamic changes in heat and dust distribution and printhead movement during high-speed printing.

[0003] The existing design leads to a disconnect between heat dissipation and dust removal operations and the actual operating conditions of high-speed printing. It fails to achieve deep linkage between data monitoring, trend prediction, and execution control, which not only easily causes motion interference between the movable processing unit and the print head, but also makes it impossible for heat dissipation and dust removal operations to accurately match the dynamic distribution characteristics of hot dust. The accuracy of the operation and its adaptability to different printing conditions are significantly insufficient. This problem has become the core factor restricting the improvement of heat dissipation and dust removal effects of high-speed printing equipment. There is an urgent need to propose a heat dissipation and dust removal technology solution that can achieve closed-loop linkage throughout the entire process to adapt to the dynamic operating conditions of high-speed printing. Summary of the Invention

[0004] To overcome the above shortcomings, this invention provides a method for heat dissipation and dust suppression in high-speed printing of printers, aiming to improve the problems of existing technologies that cannot achieve closed-loop linkage throughout the entire process, the disconnect between heat dissipation and dust removal and the dynamic working conditions of high-speed printing, the easy occurrence of motion interference, and the lack of accuracy and adaptability.

[0005] In a first aspect, the present invention provides the following technical solution, comprising the following steps: S1. Real-time monitoring: Acquire temperature and dust concentration data from multiple locations inside the printer; S2. Prediction and Forecasting: Based on printing task parameters, predict the future heat and dust distribution inside the equipment, and forecast the future movement trajectory of the print head; S3. Dynamic Programming: Integrate the results of steps S1 and S2, calculate the overall processing priority of each region, and plan the movement path and work arrangement for the mobile electrostatic treatment unit accordingly, while generating corresponding dynamic background airflow control commands. S4. Cooperative Execution: Drive the movable electrostatic processing unit to move, and control the movable electrostatic processing unit to switch between electrostatic adsorption mode and ion wind cooling mode to perform processing according to the dominant working conditions at its position, the preset work arrangement and the printhead position; Among them, for high temperature and high dust areas, control the unit to execute a composite sweeping program that first starts the ion wind cooling mode, then switches to the electrostatic adsorption mode and performs associated movement. S5. Feedback Optimization: Based on the comparison between the processed regional data and the predicted data, the model on which the prediction is based is corrected.

[0006] Preferably, in step S1, acquiring temperature data and dust concentration data at multiple locations inside the printer specifically includes: collecting temperature data and dust concentration data in real time through a distributed sensor array inside the printer, and sending the collected data to the controller; The sensor array includes an infrared temperature sensor array for acquiring temperature data and a laser dust concentration sensor array for acquiring dust concentration data.

[0007] Preferably, in step S2, the prediction and forecasting based on the printing task parameters specifically includes: Obtain print job parameters from the printer's main control system. Print job parameters include at least page color distribution data, area coverage data, and print speed plan data. Based on the printing task parameters and the inherent physical characteristics of each functional module inside the printer, a prediction of the heat generation distribution and dust emission distribution inside the device in the future time period is generated by calculating through a preset heat and dust source prediction model. At the same time, based on the printing path planning data in the printing task parameters, the movement information of the print head within a preset time window is obtained to predict its future movement trajectory.

[0008] Preferably, in step S3, the calculation of the comprehensive processing priority of each region specifically involves: weighting and fusing real-time temperature data, real-time dust concentration data, predicted heat generation distribution, and dust emission distribution, and combining the region weights determined based on the predicted future movement trajectory information of the printhead, and calculating the comprehensive priority value representing the urgency of processing each region through an evaluation function.

[0009] Preferably, in step S3, the planning of the movement path and work arrangement for the movable electrostatic treatment unit specifically involves: within a preset time window, optimizing the path calculation by having the unit cover the target area with the shortest travel distance exceeding the threshold for comprehensive processing priority; and combining the printhead movement trajectory prediction information, marking the work mode switching points and path adjustment points associated with the printhead movement in the calculated path to form a work arrangement.

[0010] Preferably, in step S3, generating the corresponding dynamic background airflow control command specifically includes: calculating commands for controlling multiple independent adjustable airflow generators based on the real-time position of the movable electrostatic processing unit, the current working mode, the planned path, and the real-time position and future trajectory of the print head. The airflow generating device is installed on the equipment ventilation duct, and the command is used to control its start / stop, angle and flow rate to form a dynamic background airflow field that coordinates the flow of hot air and dust.

[0011] Preferably, in step S4, the control of the movable electrostatic treatment unit to switch between electrostatic adsorption mode and ion wind heat dissipation mode is as follows: when the dominant operating condition is high dust concentration, the high voltage electrostatic generator unit is controlled to output a high negative DC voltage to operate in electrostatic adsorption mode; when the dominant operating condition is high temperature, the high voltage electrostatic generator unit is controlled to output AC high voltage to operate in ion wind heat dissipation mode.

[0012] Preferably, in step S4, the composite sweeping procedure specifically includes: first, controlling the movable electrostatic treatment unit to start the ion wind cooling mode at the upstream position of the high temperature and high dust area to generate directional airflow; then controlling the unit to move along the direction of the directional airflow, and switching to electrostatic adsorption mode during the movement.

[0013] Preferably, during the execution of the composite sweeping procedure, the dynamic background airflow control command generated in step S3 is executed simultaneously, so that the formed dynamic background airflow field is coordinated with the direction of the ion wind generated by the movable electrostatic processing unit and the real-time movement direction of the printhead.

[0014] Preferably, in step S5, the model on which the corrected prediction is based specifically includes: calculating the deviation between the processed updated data and the predicted data, using the deviation to adjust the internal parameters of the thermal dust source prediction model through an iterative algorithm; at the same time, calibrating according to the difference between the actual movement trajectory of the print head and the predicted trajectory, and feeding back the calibration information for subsequent dynamic planning.

[0015] The present invention has the following beneficial effects: 1. In this invention, through a closed-loop design of the entire process and the collaboration of multiple technologies, a deep linkage of real-time monitoring, heat and dust prediction, dynamic planning, collaborative execution and feedback optimization is achieved. Relying on the data collected by the distributed sensor array and combined with the trend prediction model of heat and dust source, the path and mode are planned for the mobile electrostatic processing unit, which is adapted to the dynamic working conditions of high-speed printing, effectively avoids motion interference, and improves the accuracy and adaptability of heat dissipation and dust removal operations.

[0016] 2. In this invention, a composite sweeping procedure is performed for high-temperature and high-dust areas. First, an ion wind cooling mode is used to form a directional airflow, and then an electrostatic adsorption mode is switched to move along the airflow, synchronously linked with the dynamic background airflow field. The directional airflow guides the orderly diffusion of hot dust, and the subsequent adsorption accurately captures the dust, achieving synergistic effect of heat dissipation and dust removal, and solving the technical problem that a single mode cannot handle high-temperature and high-dust conditions.

[0017] 3. In this invention, based on a feedback optimization mechanism, the deviation between the processed data and the predicted data is calculated, and an iterative algorithm is used to correct the parameters of the thermal dust source prediction model, while simultaneously calibrating the printhead trajectory prediction coefficient. The corrected parameters are synchronously fed back to the prediction and planning module, continuously improving the prediction accuracy and path planning rationality of subsequent tasks, and adapting to the changing needs of different consumables and printing conditions.

[0018] 4. In this invention, priority calculation and path optimization technologies are used to determine the target area through multi-dimensional weighted fusion. An improved greedy algorithm is employed to plan the shortest path, and mode switching and path adjustment points are marked. This allows for concentrated resource processing of high-demand areas, shortens the travel distance of processing units, and efficiently covers the target area within a preset time window, thereby improving equipment operating efficiency.

[0019] 5. In this invention, by utilizing airflow coordinated control technology, the start / stop, angle, and flow rate of the airflow generator are dynamically adjusted according to the working mode, position, and printhead trajectory of the processing unit. The resulting background airflow field is adapted to the ion wind and the direction of printhead movement, which not only enhances the directional guidance effect of hot dust but also avoids airflow disturbance from affecting printing accuracy, ensuring high-speed printing quality. Attached Figure Description

[0020] Figure 1 This is a flowchart of a high-speed printing heat dissipation and dust suppression method for a printer proposed in this invention. Detailed Implementation

[0021] The technical solutions in 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.

[0022] This invention provides a method for heat dissipation and dust suppression during high-speed printing in a printer, such as... Figure 1 As shown, it includes the following steps: S1. Real-time monitoring: Acquire temperature and dust concentration data from multiple locations inside the printer; Furthermore, the acquisition of temperature data and dust concentration data at multiple locations inside the printer specifically includes: real-time collection of temperature data and dust concentration data through a distributed sensor array located inside the printer, and sending the collected data to the controller; The sensor array includes an infrared temperature sensor array for acquiring temperature data and a laser dust concentration sensor array for acquiring dust concentration data.

[0023] Specifically, a distributed array layout is adopted, with infrared temperature sensor arrays and laser dust concentration sensor arrays placed in key areas inside the printer to ensure coverage of the core heat generation area, high dust emission areas, and key airflow paths, eliminating monitoring blind spots. The infrared temperature sensor array is mainly deployed around the printhead nozzles, on the surface of the drive module, on the outer wall of the consumable melting chamber, and at the inlet and outlet of the ventilation duct, arranged in a ring or linear pattern. The sensor detection direction is perpendicular to the monitored target surface to avoid obstruction by the printhead movement trajectory. The laser dust concentration sensor array is correspondingly deployed on the working surface below the printhead, at the outlet of the consumable delivery channel, in the swirl / ventilation area, and at the corners of the equipment's inner wall. The detection port faces the direction in which dust tends to float and is rigidly connected to the sensor data acquisition module via shielded cables to reduce interference from printing vibrations on data acquisition.

[0024] Taking an industrial-grade high-speed laser printer as an example, six infrared temperature sensors are evenly arranged around the circumference of the printhead, with an angle of 60° between adjacent sensors. The detection distance is controlled within the rated effective range of the sensors to ensure that the temperature changes of the nozzle and surrounding area can still be accurately captured when the printhead moves at high speed. Two laser dust concentration sensors are symmetrically arranged on both sides of the consumable conveying channel outlet, and one is arranged at each corner of the inner wall of the equipment, forming a dust concentration monitoring network covering both local accumulation areas and the overall diffusion area.

[0025] The data acquisition is triggered in conjunction with the printer's main control system startup command. Once the print job begins, the sensor array synchronously enters working mode, continuously collecting temperature and dust concentration data at preset intervals. The acquisition cycle is dynamically matched to the printer's printing speed, with the main control system issuing adjustment commands in real time to ensure that the acquisition frequency can fully capture the thermal and dust changes within a single printhead movement cycle. The infrared temperature sensor converts infrared radiation signals into analog voltage signals via a thermoelectric conversion module, while the laser dust concentration sensor converts dust particle concentration into a corresponding current signal using the principle of light scattering. Both types of analog signals from the sensors are transmitted to the integrated data acquisition module.

[0026] The data acquisition module incorporates a signal conditioning circuit and an A / D converter. It first filters and amplifies the analog signal to eliminate signal noise caused by electromagnetic interference and vibration within the printer. Then, it converts the conditioned analog signal into a digital signal, which is transmitted to the controller via the CAN bus. During transmission, a data frame encryption format is used. Each data frame contains the sensor number, acquisition timestamp, monitored data value, and checksum. Upon receiving the data, the controller first verifies the checksum to ensure data transmission integrity and prevent monitoring deviations caused by packet loss or mistransmission.

[0027] To avoid the impact of sensor malfunctions and transient interference on the accuracy of subsequent analysis, the controller performs outlier removal processing on the received digital signals. An outlier detection model is constructed using the 3σ criterion, and anomaly identification and removal are achieved based on continuously collected datasets from the same sensor. First, statistical analysis is performed on N sets of data collected by a single sensor within a preset time window to calculate the mean and standard deviation of the dataset. Then, the normal range of data is determined according to the 3σ criterion; data exceeding this range are identified as outliers and removed. Simultaneously, linear interpolation of adjacent valid data is used to fill gaps, ensuring the continuity of the data sequence.

[0028] Suppose that the dataset collected by a certain sensor within a time window is X=[x1,x2,...,x...]. n ], where x i The original data from the i-th collection is calculated as follows: The first step is to calculate the mean μ of the dataset X, using the formula: ; In the formula, n is the number of data points collected within the time window, calculated from the collection period and the time window length, i.e., n = time window length / collection period, x i The digital signal values ​​acquired by the sensor in real time and converted by A / D are directly transmitted from the data acquisition module to the controller buffer.

[0029] The second step is to calculate the standard deviation σ of the dataset X, using the following formula: ; In the formula, μ is the mean of the dataset obtained in the first step, which is solved in real time by the built-in computing unit of the controller, and the standard deviation σ reflects the degree of data dispersion and is used to define the normal range of data fluctuation.

[0030] The third step is to identify outliers based on the 3σ criterion: when When, determine x i If the value is an outlier, the controller automatically removes the data; for the missing data positions after removing outliers, the two adjacent valid data points x are used. K and Perform linear interpolation supplementation, supplemented values The formula is: ; In the formula, t K t K+1 t K+2 These are the collection timestamps of the corresponding data. The data sequence extracted from the data frame and then interpolated is synchronously updated to the controller cache for subsequent data processing.

[0031] Due to the physical spacing between the sensors, to obtain data on the overall temperature and dust concentration distribution inside the printer, a Kriging interpolation algorithm is used for spatial completion based on the valid data after outlier removal. This generates a continuous two-dimensional distribution matrix, providing a complete data foundation for S2 predictive analysis. The Kriging interpolation algorithm quantifies the spatial correlation of data by constructing a semi-variogram model, achieving accurate estimation of data in areas without sensors while balancing spatial continuity and local fluctuations.

[0032] Let the internal monitoring area of ​​the printer be a planar region Ω, and the coordinates of the already deployed sensors be... The corresponding valid monitoring data is (j=1,2,...,m, where m is the total number of sensors), the coordinates of the point to be interpolated are (x0,y0), and the formula for the interpolation estimate ẑ(x0,y0) is: ; In the formula, Let be the weighting coefficients of the j-th sensor data, satisfying ∑λ j =1 (j=1,2,...,m), the weighting coefficients are obtained by solving the system of equations constructed by the semi-variogram function, reflecting the degree of influence of each sensor data on the interpolation point.

[0033] The semi-variogram γ(h) is used to describe the degree of variation in data between two points with a spatial distance of h, and the formula is: ; In the formula, h is the spatial distance between two points, and N(h) is the number of sample point pairs with a spatial distance equal to h. and The data represents monitoring data from two sample points with a distance h. The controller determines the optimal model parameters by fitting a semi-variogram function and then solves for the weighting coefficients. Then, the estimated values ​​of each interpolation point are calculated, and finally, the global temperature and dust concentration distribution matrix is ​​generated and transmitted to the subsequent prediction and analysis module.

[0034] The distributed arrangement of the sensor array achieves full coverage of key areas of thermal dust inside the printer, avoiding prediction deviations caused by missing local monitoring. The linkage mechanism of data acquisition and transmission, as well as signal conditioning and processing, ensures the real-time, completeness, and accuracy of the monitoring data, eliminating the impact of internal interference on the data. The outlier removal algorithm effectively filters out invalid data, and linear interpolation ensures the continuity of the data sequence. Kriging interpolation completes the discrete sensor data into continuously distributed data across the entire domain, providing a complete and reliable input data foundation for the thermal dust source prediction model in step S2, ensuring the accuracy of the prediction analysis.

[0035] Taking a high-speed inkjet printer as an example, the above monitoring scheme can capture the temperature changes of the printhead nozzles and the dust concentration distribution generated by ink evaporation in real time. After anomaly rejection and interpolation processing, the generated global data can accurately reflect the dynamic changes of heat and dust distribution during the movement of the printhead, providing accurate data support for subsequent path planning and airflow modulation command generation, and avoiding collaborative control failures caused by monitoring data defects.

[0036] S2. Prediction and Forecasting: Based on printing task parameters, predict the future heat and dust distribution inside the equipment, and forecast the future movement trajectory of the print head; Furthermore, the prediction and forecasting based on printing task parameters specifically include: Obtain print job parameters from the printer's main control system. Print job parameters include at least page color distribution data, area coverage data, and print speed plan data. Based on the printing task parameters and the inherent physical characteristics of each functional module inside the printer, a prediction of the heat generation distribution and dust emission distribution inside the device in the future time period is generated by calculating through a preset heat and dust source prediction model. At the same time, based on the printing path planning data in the printing task parameters, the movement information of the print head within a preset time window is obtained to predict its future movement trajectory.

[0037] Specifically, the controller establishes a communication link with the printer's main control system to read printing task parameters in real time. These parameters strictly cover page color distribution data, area coverage data, and print speed plan data. Simultaneously, it acquires the inherent physical characteristic parameters of each functional module within the printer, forming a complete input dataset. Page color distribution data is parsed in pixel matrix format and converted into filament ejection parameters for each area. Color areas correspond to the combined ejection volume of multi-color filaments, while monochrome areas correspond to the ejection volume of a single filament. Area coverage data is statistically analyzed by printing page partitions, calculating the filament coverage percentage for each partition and quantifying the total amount of filament melted / evaporated. Print speed plan data is broken down into time-specific speed parameters, clearly defining the printhead's movement speed, start / stop points, and acceleration / deceleration intervals in different page areas.

[0038] Inherent physical characteristic parameters are pre-stored in the controller's local database, including printhead nozzle heating power, filament specific heat capacity, filament volatility coefficient, drive module power consumption coefficient, and device housing thermal conductivity coefficient. These parameter values ​​are calibrated based on the printer's hardware specifications and can be manually updated according to the filament type. The parsed parameters are normalized to a model-recognizable format, eliminating interference from differences in parameter magnitudes on the prediction results. The pre-processed parameter set is transmitted to the thermal dust source prediction model input and simultaneously synchronized to the trajectory prediction module. Taking a high-speed laser printer as an example, after parsing the color distribution data of an A4 page, the page is divided into 10×10mm grid units. The filament ejection amount and coverage of each grid are statistically analyzed. Combined with preset laser heating power parameters, this provides a basis for subsequent heat generation calculations.

[0039] The heat and dust source prediction model adopts a "separate source superposition" approach, calculating three types of heat generation sources: consumable effects, drive module operation, and equipment heat dissipation loss, as well as two types of dust emission sources: consumable volatilization and mechanical friction. The model generates a global heat and dust distribution prediction result through spatial superposition, with the prediction period consistent with the S1 monitoring period, covering the next 1-2 printhead movement cycles. The model calculation is based on the global monitoring data generated by S1, combined with preprocessed task parameters and inherent characteristic parameters, to achieve dynamic prediction.

[0040] First, the heat generation distribution is predicted, with the total heat generation Q. total The formula for the sum of heat from all heat sources is: ; In the formula, (x,y) are the internal spatial coordinates of the printer, and t is the prediction time; Q consumable The heat generated by the melting / spraying of consumables is calculated from the spraying rate, specific heat capacity, and melting temperature; Q drive The heat generated during the operation of the drive module.

[0041] Next, the dust emission distribution is predicted, and the dust emission concentration C is calculated. total The formula for the sum of the concentrations of all dust sources is: ; In the formula, C volatilize C represents the dust concentration generated by the volatilization of consumables. friction The dust concentration generated by mechanical friction is positively correlated with the printhead moving speed.

[0042] After the model calculation is completed, the heat generation distribution matrix and dust emission distribution matrix for each time within the preset future time window are generated. The matrix dimension is consistent with the global data after S1 interpolation. The matrix is ​​synchronously stored in the controller cache to provide a basis for predicting heat and dust distribution for S3 dynamic planning.

[0043] Trajectory prediction is based on path planning data in the print task parameters, combined with the print speed plan. Through a path segmentation and parsing algorithm, it extracts the print head's motion information within a preset time window, including position coordinates, speed, turning angle, and dwell points, forming a trajectory prediction sequence. First, the path planning data is divided into continuous path segments according to page partitions. Each path segment corresponds to the print head's movement trajectory from one partition to another. The starting coordinates (x, y, z) of each path segment are then analyzed. s ,y s ), endpoint coordinates (x) e ,y e ) and the corresponding speed parameters.

[0044] Linear interpolation is used to supplement the coordinates of intermediate positions within the path segment, predicting the specific position of the print head at each prediction time step. The formula is as follows: ; In the formula, t seg The total time for the print head to traverse this path segment is given by t, where t is the time offset within the current path segment (0 ≤ t ≤ t). seg The angle between adjacent path segments is calculated to identify corner areas, providing a basis for marking key control areas in S3.

[0045] Taking a high-speed inkjet printer as an example, after analyzing its path planning data, the movement trajectory of the print head in the edge area of ​​the page is predicted. When the turning angle θ is greater than 90°, the corner is marked as a key area. The dwell time of the print head in the area is predicted simultaneously. Combined with the heat and dust source prediction results, the area is identified as a potential high-temperature and high-dust area, providing accurate trajectory information for subsequent dynamic planning.

[0046] The distribution matrix generated by the thermal dust source prediction model is spatiotemporally fused with the printhead motion sequence obtained from trajectory prediction to establish a "trajectory-thermal dust" correlation mapping table, which clarifies the heat generation and dust emission concentration corresponding to the printhead at different times and locations. During the fusion process, the trajectory information is associated with the corresponding spatial location thermal dust prediction data using the printhead position coordinates as an index. At the same time, high-temperature areas and high-dust areas within the coverage of the printhead motion trajectory, as well as the high-temperature and high-dust areas where the two overlap, are marked.

[0047] The fusion results are sorted by time series to generate a "trajectory-heat dust" collaborative data table for a future preset time window. The data table includes information such as time, printhead position, corresponding area heat value, dust concentration, and area type. This data is transmitted to the S3 dynamic planning module as the core basis for path planning and airflow modulation command generation. At the same time, the fusion results are synchronously fed back to the model calibration port, providing initial prediction data benchmarks for parameter correction in the S5 closed-loop feedback.

[0048] Refined analysis and preprocessing of printing task parameters ensured the accuracy and standardization of the input data for the prediction model, eliminating the interference of parameter differences on the prediction results. The heat and dust source prediction model adopted a source-by-source superposition approach, combining S1 monitoring data with the inherent characteristics of the equipment to achieve accurate dynamic prediction of heat and dust distribution, overcoming the limitations of traditional static prediction in adapting to the dynamic changes of high-speed printing. Trajectory prediction, through path segmentation analysis and interpolation calculation, completely extracted the future movement information of the print head, accurately locating key areas. The fusion of these two processes established a correlation between trajectory and heat and dust, providing complete "spatiotemporal coordination" data support for S3 dynamic planning, avoiding the disconnect between planning decisions and actual operating conditions.

[0049] Taking industrial-grade 3D printers as an example, this step predicts the trajectory of the print head during the printing process of complex models and the distribution of heat and dust in the corresponding areas. It identifies the risk of high temperature and high dust at the corners of the model in advance, providing a predictive basis for the path planning and mode switching of the S3 mobile processing unit. This ensures that the processing actions are accurately matched to changes in working conditions and avoids problems such as untimely heat dissipation or dust accumulation caused by passive responses.

[0050] S3. Dynamic Programming: Integrate the results of steps S1 and S2, calculate the overall processing priority of each region, and plan the movement path and work arrangement for the mobile electrostatic treatment unit accordingly, while generating corresponding dynamic background airflow control commands. Furthermore, the calculation of the comprehensive processing priority of each region specifically involves: weighting and fusing real-time temperature data, real-time dust concentration data, predicted heat generation distribution, and dust emission distribution, and combining the region weights determined based on the prediction information of the future movement trajectory of the printhead, and calculating the comprehensive priority value representing the urgency of processing each region through an evaluation function. Furthermore, the process of planning the movement path and work arrangement for the movable electrostatic treatment unit specifically involves: within a preset time window, optimizing the path calculation by having the unit cover the target area where the comprehensive processing priority exceeds a threshold with the shortest possible travel distance; and combining the printhead movement trajectory prediction information, marking the work mode switching points and path adjustment points associated with the printhead movement in the calculated path to form a work arrangement. Furthermore, the generation of the corresponding dynamic background airflow control command specifically includes: calculating commands for controlling multiple independent adjustable airflow generating devices based on the real-time position of the movable electrostatic processing unit, the current working mode, the planned path, and the real-time position and future trajectory of the print head; The airflow generating device is installed on the equipment ventilation duct, and the command is used to control its start / stop, angle and flow rate to form a dynamic background airflow field that coordinates the flow of hot air and dust. Specifically, the real-time monitoring data from S1 and the prediction and forecast results from S2 are first spatiotemporally aligned and fused to establish a unified internal spatial coordinate system and time axis for the equipment. This ensures consistent data dimensions and accurate correlation, providing an integrated data foundation for subsequent planning. The data fusion module imports the global real-time temperature matrix and real-time dust concentration matrix from S1 after anomaly removal and interpolation, as well as the future heat prediction matrix, dust emission prediction matrix, and printhead trajectory prediction sequence generated by S2. The former corresponds to the data at the current moment, and the latter corresponds to the data within the future prediction step. The fusion process uses spatial coordinates as an index to associate real-time data and predicted data according to the time series. At the same time, the printhead trajectory prediction information is mapped to the global space, marking the area and dwell time period that the printhead will cover within the future preset time window, achieving a synergistic consideration of real-time operating conditions and future trends. Taking a high-speed laser printer as an example, this fusion process can clearly identify the real-time high temperature data of the central area of ​​the page at the current moment, as well as the heat superposition prediction results when the printhead moves to that area within the future preset time period, providing comprehensive data support for priority determination.

[0051] A weighted fusion evaluation model is used to calculate the overall processing priority of each region. The higher the priority value, the more urgent the region's processing needs. The evaluation process takes into account the urgency of real-time operating conditions, future trend risks, and printhead trajectory correlation to ensure that resources are concentrated on core operating conditions. The evaluation is based on the fused full-domain data. First, weight coefficients for each input parameter are preset based on consumable type and printing condition. These coefficients can be dynamically corrected through the S5 closed-loop feedback loop. At the same time, the region weights are determined by combining the printhead trajectory prediction results. Regions that the printhead will cover in the future and whose dwell time exceeds the preset value have the highest weight, followed by regions that only pass through, and regions that are not covered have the lowest weight. By weighted fusion of five dimensions—real-time temperature, real-time dust concentration, predicted heat, predicted dust, and trajectory correlation region weights—the overall priority value of each region is obtained. Then, regions with priority exceeding the preset threshold are selected as target processing regions, and each target region type is simultaneously marked and transmitted to the path planning module.

[0052] The path planning aims to cover all target processing areas with the shortest possible distance within a preset time window. An improved greedy algorithm is used to calculate the path, while printhead trajectory prediction information is combined to avoid motion interference. Key nodes are marked to form a complete work schedule. Path calculation first connects target areas based on the shortest distance principle to generate an initial path. Then, based on the printhead trajectory prediction sequence, the initial path is optimized and adjusted to avoid the space and trajectory that the printhead will occupy in the future, ensuring no motion conflict between the processing unit and the printhead. The core of the work schedule is marking two types of key nodes: first, mode switching points, based on the target area type. High-temperature areas are marked as ion wind cooling mode start points, high-dust areas as electrostatic adsorption mode start points, and high-temperature, high-dust areas as composite mode switching points, strictly matching the switching sequence of the S4 composite sweep program; second, path adjustment points, based on printhead turning and start / stop actions. When the printhead is about to enter the processing unit's working area, adjustment points are marked on the path to preemptively drive the processing unit to avoid or pause, resuming operation after the printhead leaves. Taking a high-speed inkjet printer as an example, when planning the path, at the path adjustment point where the printhead turns, the preset processing unit pauses for two time steps and switches to low-speed ion wind mode. This avoids interference with the printhead and maintains the basic heat dissipation effect of the area, forming a coordinated work arrangement of "path-mode-timing".

[0053] Based on the integrated data fusion results, dynamic background airflow control commands are generated to regulate multiple independent adjustable airflow generators on the ventilation duct, forming a background airflow field that coordinates with the actions of the processing unit and printhead, enhancing the directional guidance effect of hot air and dust. Command generation uses the real-time position of the processing unit, current operating mode, planned path, and the real-time position and future trajectory prediction sequence of the printhead as core inputs. The start / stop status, outlet angle, and flow velocity parameters of each airflow generator are calculated through an airflow coordination model. The command generation logic is precisely adapted to the operating conditions: when the processing unit is in ion wind cooling mode, the corresponding area's airflow generator is activated, the outlet angle is directed towards the processing unit's working area, and the flow velocity is dynamically adjusted according to area priority, assisting the ion wind in guiding hot air to the ventilation opening; when in electrostatic adsorption mode, the outlet direction of the airflow generator is adjusted to form a directional airflow pointing towards the processing unit's adsorption port, guiding dust accumulation to improve adsorption efficiency; when the printhead moves at high speed, the airflow generators along the path are synchronously regulated to reduce the outlet flow velocity, avoiding airflow disturbances that could affect printing accuracy. All instructions are packaged and transmitted to the airflow generator controller in a time sequence, and the control parameters are updated in real time to ensure that the background airflow field is dynamically adapted to the actions of the processing unit and the print head.

[0054] Cross-step data fusion enables integrated consideration of real-time operating conditions and future trends, avoiding planning deviations caused by single data sources. Comprehensive priority determination, through multi-dimensional weighted fusion, accurately identifies high-demand processing areas, improving job targeting. The collaborative design of path planning and work arrangement ensures the efficiency of processing units while effectively avoiding interference with printhead movement, adapting to dynamic high-speed printing conditions. Dynamic background airflow commands, through deep coordination with the actions of processing units and printheads, enhance the effect of heat and dust guidance, providing a stable airflow environment for S4 collaborative execution. The overall process constructs a closed-loop logic of data fusion, priority determination, path planning, and airflow coordination, ensuring that the planning results match actual operational needs and achieving deep coordination between heat dissipation, dust removal, and printing actions.

[0055] S4. Cooperative Execution: Drive the movable electrostatic processing unit to move, and control the movable electrostatic processing unit to switch between electrostatic adsorption mode and ion wind cooling mode to perform processing according to the dominant working conditions at its position, the preset work arrangement and the printhead position; Among them, for high temperature and high dust areas, control the unit to execute a composite sweeping program that first starts the ion wind cooling mode, then switches to the electrostatic adsorption mode and performs associated movement. Furthermore, the control of the movable electrostatic treatment unit to switch between electrostatic adsorption mode and ion wind heat dissipation mode is as follows: when the dominant working condition is high dust concentration, the high voltage electrostatic generator unit is controlled to output a high negative DC voltage to work in electrostatic adsorption mode; when the dominant working condition is high temperature, the high voltage electrostatic generator unit is controlled to output AC high voltage to work in ion wind heat dissipation mode. Furthermore, the composite sweeping procedure specifically includes: firstly, controlling the movable electrostatic treatment unit to start the ion wind heat dissipation mode at the upstream position of the high temperature and high dust area to generate directional airflow; then controlling the unit to move along the direction of the directional airflow, and switching to electrostatic adsorption mode during the movement. Furthermore, during the execution of the composite sweeping procedure, the dynamic background airflow control command generated in step S3 is executed simultaneously, so that the formed dynamic background airflow field is coordinated with the direction of the ion wind generated by the movable electrostatic processing unit and the real-time movement direction of the printhead. Specifically, before driving the movable electrostatic treatment unit to perform operations, a triple matching verification of real-time operating conditions, preset arrangements, and position information is completed to ensure that the executed actions are accurately adapted to the actual operating conditions, while avoiding interference with the movement of the print head. The controller retrieves the global dust concentration matrix C obtained from real-time monitoring by S1. real (x,y,t), temperature matrix T real (x,y,t), extract the current position (x,y,t) of the movable electrostatic treatment unit. e ,y eReal-time operating data at location (x) is used to determine the dominant operating condition at that location; the work schedule, movement path, and real-time printhead position (x) planned by S3 are retrieved simultaneously. h ,y h,t The system verifies the node matching degree between the current position of the processing unit and the planned path, as well as whether the spatial distance between the processing unit and the printhead meets the safe operating threshold. If the dominant operating condition is consistent with the preset arrangement and there is no risk of printhead movement interference, the execution command is issued directly. If there is a deviation in the operating condition or an interference risk, the movement path and mode switching sequence of the processing unit are temporarily adjusted, and the execution process is restarted to ensure the rationality and safety of the execution action. Taking a high-speed inkjet printer as an example, if the processing unit reaches the preset high-dust area and real-time monitoring shows that the temperature in that area rises sharply due to printhead movement, the controller will temporarily adjust the mode switching sequence, first activating the short-term ion wind cooling mode and then switching to the electrostatic adsorption mode to adapt to the change in operating condition.

[0056] Based on the dominant operating conditions after matching and verification, the controller precisely regulates the voltage of the high-voltage electrostatic generator unit of the movable electrostatic treatment unit, realizing seamless switching between electrostatic adsorption mode and ion wind heat dissipation mode. The switching command and the movement of the treatment unit are synchronized and linked without execution delay.

[0057] Electrostatic adsorption mode activation: When the dominant operating condition at the processing unit location is high dust concentration, the real-time dust concentration C real ≥C th Temperature T real <T th At this time, the controller sends a command to control the high voltage electrostatic generator to output a high negative DC voltage, so that a stable electrostatic field is formed at the adsorption end of the processing unit. When dust particles that escape during the printing process pass through this area, they are adsorbed by the electrostatic field, realizing the fixed-point collection of dust. The adsorption efficiency is positively correlated with the amplitude of the negative DC voltage, and the voltage amplitude can be dynamically fine-tuned according to the real-time dust concentration. Ion wind cooling mode activated: When the dominant operating condition at the processing unit location is high temperature, the real-time temperature T... real ≥Tth, dust concentration C real <C th When the controller issues a command to control the high-voltage electrostatic generator unit to switch the output of AC high voltage, the high-voltage electric field ionizes the air to form a directional ion wind. The ion wind blows directly towards the high-temperature area and removes heat through forced convection heat exchange, achieving localized and precise heat dissipation. The wind speed of the ion wind is positively correlated with the frequency of the AC high voltage and can be dynamically adjusted according to the real-time temperature.

[0058] During mode switching, the voltage output type of the high-voltage electrostatic generator unit switches continuously, and the moving speed of the processing unit matches the operating efficiency corresponding to the mode, ensuring stable heat dissipation or dust removal operations are completed during the movement.

[0059] For Treal ≥T th And C real ≥C th In high-temperature and high-dust areas, a strict composite sweeping procedure is implemented, prioritizing ion wind cooling, followed by electrostatic adsorption, and then moving in conjunction with the surrounding environment. The procedure execution steps precisely correspond to the mode switching points and path adjustment points planned by S3, while the sweeping range and movement speed are determined based on the spatial morphology of the area. Upstream Positioning and Ionizing Wind Activation: Based on real-time airflow monitoring data (S1) and dynamic background airflow planning (S3), the controller determines the upstream position of the airflow in the high-temperature, high-dust area. This position is the source direction of the diffusion of hot air and dust. The controller drives the processing unit to move to this upstream position and accurately locates it. Then, it activates the ionizing wind cooling mode, outputting AC high voltage at a preset frequency to form a directional ionizing wind. The ionizing wind is blown along the main diffusion direction of the high-temperature, high-dust area, forcing convection heat exchange on the hot air in the area. At the same time, it pushes dust particles to move directionally downstream in the area, avoiding the irregular diffusion of hot dust. Movement along the flow and mode switching: After the ion wind forms a stable directional airflow, the controller drives the processing unit to move along the ion wind direction at a preset speed. The moving speed matches the ion wind speed to ensure that the ion wind always covers the untreated area. During the movement, the mode is seamlessly switched, and the high-voltage electrostatic generator is switched from AC high-voltage output to high negative DC voltage output to start the electrostatic adsorption mode. Mobile adsorption and full-area sweeping: In electrostatic adsorption mode, the processing unit continues to move along the flow direction, electrostatically adsorbing the dust particles pushed onto the path by the ion wind. At the same time, the heat exchange effect of the residual ion wind continues to dissipate heat to the area, achieving simultaneous heat dissipation and dust removal, until the processing unit moves to the downstream boundary of the high-temperature and high-dust area, completing a composite sweep.

[0060] Taking the high-temperature and high-dust corner area of ​​an industrial-grade laser printer as an example, the processing unit first starts the ion wind 5cm upstream of the corner to form a directional airflow to the downstream of the corner, and then moves along the airflow direction at a speed of 5mm / s. When it moves to the center of the corner, it switches to electrostatic adsorption mode until it moves to 5cm downstream of the corner, completing the composite sweep of the area. This achieves precise heat dissipation at the corner and avoids dust accumulation in the corner dead corner.

[0061] Throughout the entire process of executing the composite sweeping procedure, the controller synchronously retrieves the dynamic background airflow control command generated by S3 and sends it to multiple independent adjustable airflow generators on the printer ventilation duct. This achieves three-dimensional coordination between the dynamic background airflow field, the ion wind of the processing unit, and the real-time movement direction of the printhead, enhancing the heat and dust guidance and treatment effect without airflow collision or disturbance issues.

[0062] Directional Coordination: Adjust the air outlet angle of each airflow generating device to keep the main direction of the dynamic background airflow and the blowing direction of the ion wind of the processing unit in the same direction and collinear, while adapting to the real-time movement direction of the print head. If the print head moves into this area, the confluence direction of the background airflow and the ion wind avoids the print head's movement path to prevent airflow disturbance from affecting printing accuracy. If the print head leaves this area, the confluence direction of the background airflow and the ion wind points to the equipment vent, guiding hot air and dust to move towards the vent. Flow velocity coordination: Based on the wind speed of the ion wind in the processing unit, the outlet air velocity of the airflow generator is dynamically adjusted so that the background airflow velocity is slightly lower than the ion wind velocity, forming an airflow field guided by the main airflow and assisted by the secondary airflow. This not only enhances the directional movement effect of hot dust, but also avoids the high-velocity background airflow from dispersing the ion wind. Timing coordination: The start and stop, angle and velocity adjustment of the background airflow are completely synchronized with the execution timing of the composite sweeping program. When the processing unit starts the ion wind, the airflow generator in the corresponding area is turned on simultaneously; when the processing unit switches modes and adjusts its moving speed, the airflow generator adjusts its velocity and angle simultaneously; after the processing unit completes the composite sweeping, the airflow generator continues to run for a preset time to guide the residual hot air and dust in the area to the ventilation port or the adsorption end of the processing unit, and then gradually shuts down.

[0063] Throughout the collaborative execution process, the controller uses the monitoring frequency of S1 as a benchmark to collect updated temperature and dust concentration data of the processing unit's operating area in real time, as well as the real-time position and movement trajectory changes of the printhead. If a deviation is found between the actual operating conditions and the preset execution actions, the controller immediately makes dynamic fine adjustments to the processing unit's mode switching sequence, movement speed, and airflow parameters of the airflow generator to ensure that the collaborative execution effect always adapts to changes in operating conditions. For example, if real-time monitoring detects that the dust diffusion range in the high-temperature, high-dust area exceeds the preset sweeping range, the controller will immediately increase the ion wind speed of the processing unit and simultaneously expand the airflow angle of the corresponding airflow generator to widen the range of heat and dust guidance, ensuring full coverage without dead angles.

[0064] This step avoids the problems of mismatched operating conditions and printhead movement interference from the source, ensuring the accuracy and safety of the execution. Based on the precise voltage control of the high-voltage electrostatic generator, it achieves seamless switching between heat dissipation and dust removal modes, adapting to the operational needs of different dominant operating conditions. The composite sweeping program in high-temperature and high-dust areas solves the pain point that a single mode cannot handle high-temperature and high-dust conditions simultaneously through the logic of "ion wind first + electrostatic adsorption follow-up". The three-dimensional synergy between dynamic background airflow and composite sweeping not only enhances the directional guidance effect of hot dust, but also avoids the impact of airflow disturbance on printing accuracy, achieving deep synergy between heat dissipation, dust removal and printing operations. The overall execution process is based on the data analysis and planning of S1-S3, forming a closed loop of "planning-execution-feedback-fine-tuning", ensuring that the operation of the movable electrostatic treatment unit and the airflow generator always closely matches the dynamic operating conditions of high-speed printing, without lag, interference, or blind spots.

[0065] S5. Feedback Optimization: Based on the comparison between the processed regional data and the predicted data, the model on which the prediction is based is corrected.

[0066] Furthermore, the model upon which the corrected prediction is based specifically includes: calculating the deviation between the processed updated data and the predicted data, using this deviation to adjust the internal parameters of the thermal dust source prediction model through an iterative algorithm; simultaneously, calibrating based on the difference between the actual movement trajectory of the printhead and the predicted trajectory, and feeding back the calibration information for subsequent dynamic planning.

[0067] Specifically, after S4 completes its collaborative execution, the controller uses the sensor array deployed in S1 to collect updated data from each region at the original monitoring frequency. This includes overall temperature and dust concentration data, which, after anomaly removal, serves as the basis for feedback, ensuring data reliability. This updated data is then compared one by one with the corresponding region's predicted data generated by the S2 thermal dust source prediction model, using uniform spatial coordinates. Deviation is calculated on a region-by-region basis, eliminating extreme deviations caused by accidental factors such as sudden printhead movements or consumable malfunctions, retaining only valid deviation data for model correction. Deviation calculation employs a regional average deviation statistical method, mitigating the impact of individual monitoring point errors on overall correction and accurately reflecting regional prediction accuracy. Taking a high-speed laser printer as an example, the actual temperature and dust concentration of the high-temperature, high-dust area at the page corner are collected after processing and compared with the predicted data for that area from S2 to obtain the regional average deviation, which serves as the core input for model correction.

[0068] Based on data from multiple monitoring points in a single area, the average temperature deviation of the area is first calculated using the following formula: ; In the formula, n is the number of monitoring points in a single area, and T act,i To update the actual temperature data for the i-th monitoring point, Tpred,i The temperature prediction data for this monitoring point is provided by the S2 thermal dust source prediction model. Similarly, the average deviation of regional dust concentration is calculated using the same logic, and the two types of average deviation data are synchronously transmitted to the model correction module as the core basis for parameter adjustment.

[0069] Based on the calculated effective deviation data, the gradient descent iterative algorithm is used to adjust the internal parameters of the thermal dust source prediction model, aiming to optimize model accuracy by minimizing the deviation, while simultaneously correcting the parameter weights of the S3 priority determination. The iterative correction first extracts the core adjustable parameters of the model, including the correlation coefficient of consumable characteristics, the heat loss coefficient, and the dust emission coefficient, and constructs them into a parameter vector. Then, the parameter values ​​are dynamically updated through the gradient descent algorithm to ensure that the parameter adjustments fit the actual working conditions.

[0070] The parameter iterative update formula is: ; In the formula, θ k Let θ be the parameter vector for the k-th iteration. k+1 The updated parameter vector; α is the learning rate; The loss function J(θ) k ) at θ k The gradient at a given location is used, and the loss function takes the average deviation of the region as input. After each iteration, the model accuracy is verified using historical monitoring data. If the deviation is lower than a preset threshold, the iteration stops, the correction parameters are saved, and the S2 prediction module and S3 priority determination weights are updated synchronously as the basis for calculation in subsequent printing tasks.

[0071] The actual movement trajectory of the printhead is compared with the predicted trajectory of S2 simultaneously. Focusing on four dimensions—position, speed, turning angle, and dwell time—targeted calibration is performed to improve the accuracy of trajectory prediction and provide a precise basis for S3 dynamic planning. The trajectory difference calculation uses timestamps as an index to extract the actual and predicted positions of the printhead at each moment, and calculates the turning angle deviation $\Delta\theta(t)$ and speed deviation $\Deltav(t)$. Among these, the turning angle deviation has the greatest impact on path planning interference avoidance and is calibrated first.

[0072] To address steering angle deviation, a proportional calibration algorithm is used to adjust the prediction coefficient. The calibration formula is as follows: ; In the formula, θ k θ is the predicted steering angle value after calibration. pred (t) is the original predicted value of S2, k p θ is the proportionality constant. pred(t) represents the difference between the actual turning angle at the current moment and the original predicted value. During calibration, the focus is on optimizing the predicted parameters for cornering and start-stop phases, and correcting the trajectory prediction algorithm's consideration of motion inertia and speed adjustment lag. For example, if the actual turning angle of the high-speed inkjet printer printhead is consistently 5° smaller than the predicted value, this can be corrected by adjusting the proportional coefficient k. p This ensures that the predicted steering angle accurately matches the actual action, avoiding interference between the processing unit and the print head due to trajectory deviation.

[0073] The corrected parameters of the heat source prediction model, along with the printhead trajectory calibration information, are synchronously fed back to the S2 prediction module and the S3 dynamic programming module, forming a closed-loop process of execution-feedback-correction-optimization. The corrected model parameters are directly applied to the S2 heat source prediction for the next printing task, improving the prediction accuracy of heat generation and dust dispersion distribution. The trajectory calibration information is fed back to the S3 path planning stage, optimizing the setting logic of the processing unit path adjustment points and the prediction accuracy of mode switching timing, avoiding job interference or insufficient processing due to trajectory deviation. At the same time, the calibrated parameters and weights are stored in the controller's local database as the initial configuration for similar printing tasks, shortening the subsequent optimization cycle and improving job efficiency.

[0074] The S5 feedback optimization step, through the construction of a closed-loop adjustment mechanism, accurately identifies the deficiencies in the heat and dust source prediction model and the printhead trajectory prediction logic. Without additional hardware investment, prediction accuracy is gradually improved through iterative optimization of software algorithms. Model parameter optimization makes the S2 prediction results more closely match actual working conditions, providing reliable data support for S3 dynamic planning; trajectory calibration reduces printhead motion prediction deviations and minimizes the risk of motion interference between the processing unit and the printhead. The synergistic effect of these two processes makes subsequent dynamic planning and collaborative execution actions more adaptable to the dynamic changes of high-speed printing, continuously improving the stability and targeting of heat dissipation and dust removal, and flexibly adapting to diverse working conditions under different consumables and printing speeds.

[0075] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the 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 method for heat dissipation and dust suppression during high-speed printing in a printer, characterized in that, Includes the following steps: S1. Real-time monitoring: Acquire temperature and dust concentration data from multiple locations inside the printer; S2. Prediction and Forecasting: Based on printing task parameters, predict the future heat and dust distribution inside the equipment, and forecast the future movement trajectory of the print head; S3. Dynamic Programming: Integrate the results of steps S1 and S2, calculate the overall processing priority of each region, and plan the movement path and work arrangement for the mobile electrostatic treatment unit accordingly, while generating corresponding dynamic background airflow control commands. S4. Cooperative Execution: Drive the movable electrostatic processing unit to move, and control the movable electrostatic processing unit to switch between electrostatic adsorption mode and ion wind cooling mode to perform processing according to the dominant working conditions at its position, the preset work arrangement and the printhead position; Among them, for high temperature and high dust areas, control the unit to execute a composite sweeping program that first starts the ion wind cooling mode, then switches to the electrostatic adsorption mode and performs associated movement. S5. Feedback Optimization: Based on the comparison between the processed regional data and the predicted data, the model on which the prediction is based is corrected.

2. The method for heat dissipation and dust suppression in high-speed printing of a printer according to claim 1, characterized in that, In step S1, obtaining temperature data and dust concentration data at multiple locations inside the printer specifically includes: collecting temperature data and dust concentration data in real time through a distributed sensor array inside the printer, and sending the collected data to the controller; The sensor array includes an infrared temperature sensor array for acquiring temperature data and a laser dust concentration sensor array for acquiring dust concentration data.

3. The method for heat dissipation and dust suppression during high-speed printing of a printer according to claim 1, characterized in that, In step S2, the prediction and forecasting based on the printing task parameters specifically includes: Obtain print job parameters from the printer's main control system. Print job parameters include at least page color distribution data, area coverage data, and print speed plan data. Based on the printing task parameters and the inherent physical characteristics of each functional module inside the printer, a prediction of the heat generation distribution and dust emission distribution inside the device in the future time period is generated by calculating through a preset heat and dust source prediction model. At the same time, based on the printing path planning data in the printing task parameters, the movement information of the print head within a preset time window is obtained to predict its future movement trajectory.

4. The method for heat dissipation and dust suppression during high-speed printing of a printer according to claim 1, characterized in that, In step S3, the calculation of the comprehensive processing priority of each region specifically involves: weighting and fusing real-time temperature data, real-time dust concentration data, predicted heat generation distribution, and dust emission distribution, and combining the region weights determined based on the prediction information of the future movement trajectory of the printhead, and calculating the comprehensive priority value representing the urgency of each region to be processed through an evaluation function.

5. The method for heat dissipation and dust suppression in high-speed printing of a printer according to claim 1, characterized in that, In step S3, the process of planning the movement path and work arrangement for the movable electrostatic treatment unit is as follows: within a preset time window, the unit calculates the path with the shortest travel distance to cover the target area where the comprehensive processing priority exceeds the threshold as the optimization goal; and combined with the printhead movement trajectory prediction information, the work mode switching points and path adjustment points associated with the printhead movement are marked in the calculated path to form a work arrangement.

6. The method for heat dissipation and dust suppression during high-speed printing of a printer according to claim 1, characterized in that, In step S3, generating the corresponding dynamic background airflow control command specifically includes: calculating the command for controlling multiple independent adjustable airflow generating devices based on the real-time position of the movable electrostatic processing unit, the current working mode, the planned path, and the real-time position and future trajectory of the print head. The airflow generating device is installed on the equipment ventilation duct, and the command is used to control its start / stop, angle and flow rate to form a dynamic background airflow field that coordinates the flow of hot air and dust.

7. The method for heat dissipation and dust suppression in high-speed printing of a printer according to claim 1, characterized in that, In step S4, the control of the movable electrostatic treatment unit to switch between electrostatic adsorption mode and ion wind heat dissipation mode is as follows: when the dominant working condition is high dust concentration, the high voltage electrostatic generator unit is controlled to output a high negative DC voltage to work in electrostatic adsorption mode; when the dominant working condition is high temperature, the high voltage electrostatic generator unit is controlled to output AC high voltage to work in ion wind heat dissipation mode.

8. The method for heat dissipation and dust suppression in high-speed printing of a printer according to claim 1, characterized in that, In step S4, the composite sweeping procedure specifically includes: first, controlling the movable electrostatic treatment unit to start the ion wind heat dissipation mode at the upstream position of the high temperature and high dust area to generate directional airflow; then controlling the unit to move along the direction of the directional airflow and switching to electrostatic adsorption mode during the movement.

9. A method for heat dissipation and dust suppression during high-speed printing of a printer according to claim 8, characterized in that, During the execution of the composite sweeping procedure, the dynamic background airflow control command generated in step S3 is executed simultaneously, so that the formed dynamic background airflow field is coordinated with the direction of the ion wind generated by the movable electrostatic processing unit and the real-time movement direction of the printhead.

10. A method for heat dissipation and dust suppression during high-speed printing of a printer according to claim 1, characterized in that, In step S5, the model on which the corrected prediction is based specifically includes: calculating the deviation between the processed updated data and the predicted data, using the deviation to adjust the internal parameters of the thermal dust source prediction model through an iterative algorithm; at the same time, calibrating according to the difference between the actual movement trajectory of the print head and the predicted trajectory, and feeding back the calibration information for subsequent dynamic planning.

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