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CN-122018313-A - Automatic control system and control method for sunshade

CN122018313ACN 122018313 ACN122018313 ACN 122018313ACN-122018313-A

Abstract

The invention relates to the technical field of intelligent sunshade equipment control, in particular to an automatic sunshade control system and a control method, which are used for solving the problems that the conventional automatic sunshade control system is not always fully fused with multidimensional environment parameters and user intervention behaviors in terms of strategy generation, and is difficult to synchronously optimize energy consumption, comfort and illumination uniformity under dynamic weather conditions, so that a control strategy lacks individuation and prospective; according to the invention, the sun-shading strategy dynamic generation module is used for integrating multi-dimensional environment semantic modeling, short-term illumination trend prediction and user preference learning, a dynamic weighted multi-objective optimization mechanism is constructed, energy consumption, comfort and illumination uniformity are synchronously considered under the condition of meeting equipment constraint, and a control target and an evaluation standard are updated in real time based on user intervention records, so that accurate, prospective and highly personalized sun-shading strategy generation is realized, and the intelligent level and comprehensive performance of the system are remarkably improved.

Inventors

  • ZHANG AITAO

Assignees

  • 浙江赛欧遮阳科技有限公司

Dates

Publication Date
20260512
Application Date
20260122

Claims (10)

  1. 1. An automatic control system of sunshade is applied to sunshade control management platform, characterized by comprising: The sunshade environment data processing module is used for collecting sunshade environment parameters from the environment where the sunshade is positioned, preprocessing the collected sunshade environment parameters and outputting standardized sunshade environment parameters; the sunshade strategy dynamic generation module is used for carrying out multi-dimensional environment semantic scene modeling and short-term weather trend prediction based on standardized sunshade environment parameters and manual intervention records of a user, dynamically generating the sunshade strategy through multi-objective optimization, and updating the personalized control strategy according to user preference; The sunshade cooperative control module is used for decomposing a sunshade strategy into cooperative control commands of all the canopy sections, fusing manual instructions, app control and external control platform linkage signals, and performing uniform scheduling according to priority; The sunshade fault-tolerant execution module is used for executing a cooperative control command, starting a self-recovery mechanism when motor clamping stagnation, position deviation or communication interruption are detected, and executing forced folding, locking or rollback when wind speed exceeds limit, rainfall or movement resistance is abnormal; and the sunshade operation and maintenance early warning module is used for establishing a residual life prediction model of the motor, the transmission mechanism and the locking device based on standardized sunshade environment parameters and detection information of motor clamping stagnation and position deviation, and triggering maintenance early warning when the predicted life is lower than a set threshold value.
  2. 2. The automatic awning control system according to claim 1, wherein the process of modeling multi-dimensional environmental semantic scenario and predicting short-term weather trend based on standardized sunshade environment parameters and manual intervention records of a user in the sunshade strategy dynamic generation module comprises: The method comprises the steps of obtaining standardized sun-shading environment parameters at the current moment, generating heat induction intensity by the environment temperature and the relative humidity, generating humidity induction intensity by the relative humidity and the wind speed, generating wind induction intensity by the wind speed and the wind direction, forming current environment semantic description, obtaining environment semantic description at the previous moment, carrying out weighted average on the environment semantic description and the environment semantic description, and generating a current multi-dimensional environment scene; Acquiring a user manual intervention record with the time closest to the current moment and a multi-dimensional environment scene when the user manual intervention record occurs, calculating the maximum value of absolute differences of all components of the scene and the current multi-dimensional environment scene as a scene distance, taking a corresponding target opening as a user preference mark if the scene distance is smaller than a preset matching threshold value, otherwise, not setting the preference mark, and combining the user preference mark with the current multi-dimensional environment scene to generate the multi-dimensional environment scene containing user preference; Acquiring a horizontal plane illumination intensity sequence with a recently fixed length, calculating illumination change rates at adjacent moments from the tail to the front, distributing contribution weights according to signs and amplitudes of the change rates, combining illumination change trend characterization and illumination intensity at the latest moment, extrapolating according to trend directions to obtain a horizontal plane illumination intensity predicted value at the next moment, adding the predicted value as a newly added component into a multi-dimensional environment scene containing user preferences, and outputting a final multi-dimensional environment semantic scene.
  3. 3. The automatic awning control system according to claim 2, wherein the process of dynamically generating the sunshade strategy by multi-objective optimization in the sunshade strategy dynamic generation module and updating the personalized control strategy according to the user preference comprises: The method comprises the steps of obtaining an actual energy consumption value, an actual comfort level value and an actual illumination uniformity value under a current sunshade equipment control instruction, respectively obtaining corresponding ideal values, calculating absolute deviations, substituting the absolute energy consumption deviation, the absolute comfort level deviation and the absolute illumination uniformity deviation into a dynamic weight calculation expression to obtain an energy consumption weight, a comfort level weight and an illumination uniformity weight; Obtaining minimum opening and maximum opening constraint of the sunshade equipment, constructing a weighted objective function, solving an opening combination which enables the weighted objective function to be minimum under the condition that the opening is not smaller than a minimum value and not larger than a maximum value, and outputting an initial sunshade strategy; the method comprises the steps of obtaining a manual intervention record of a last user from an operation log, extracting the maximum tolerable illuminance, a comfortable temperature central value and an energy consumption sensitivity coefficient, setting a glare index upper limit threshold value by using the maximum tolerable illuminance, using the comfortable temperature central value as a reference temperature of a thermal discomfort index, and calculating an adjusted energy consumption ideal value by using the energy consumption sensitivity coefficient and the reference energy consumption value; Based on the adjusted ideal energy consumption value and the updated comfort level calculation mode, the actual value and the ideal value of the energy consumption, the comfort level and the illumination uniformity are re-acquired, corresponding absolute deviations are calculated, the deviations are substituted into the dynamic weight calculation expression again, the optimized weight based on the user preference is obtained, an updated weighted objective function is constructed, the optimal opening combination is solved under the same opening constraint, and the personalized sun-shading strategy is output.
  4. 4. The automated awning control system of claim 1, wherein the awning cooperative control module decomposes an awning strategy into cooperative control commands for each canopy segment comprising: The method comprises the steps of obtaining a sun shading strategy, extracting target physical quantity in the sun shading strategy, obtaining a sun azimuth angle, judging a sun area to which the sun azimuth angle belongs, obtaining a greenhouse segment list, and determining a sun shading task type of each segment based on a corresponding relation between the sun area and the segment orientation; calculating illumination deviation or temperature deviation according to the target physical quantity and the corresponding actual value in the shed, generating sunshade action intensity according to the illumination deviation or the temperature deviation, distributing control amplitude to each segment according to the sunshade task type, and mapping the control amplitude into an unfolding proportion or a blade angle according to the segment driving type to form a primary control quantity; And sequentially performing time coordination and space coordination on the preliminary control quantity of each section, and outputting cooperative control commands of all the canopy sections after finishing the processing of all the sections.
  5. 5. The automatic control system of sunshade of claim 4, wherein said sunshade cooperative control module incorporates manual command, app control and external control platform linkage signals, and the process of scheduling execution in priority order comprises: Acquiring a latest arriving control instruction and a current instruction queue to be executed, judging according to a fixed priority order if two instruction sources are different, taking the latest instruction as a standard if the sources are the same, and emptying the queue to be executed and setting a forced safety instruction as a unique item to be executed if a forced safety mark is valid; Analyzing the operation object and the operation type of the arbitrated instruction, checking whether the target state of each segment and the adjacent segment meets the mechanical motion continuity constraint in the generation process, and if not, adjusting the target state of the current segment to the adjacent value direction to be within the allowable deviation range to form a coordinated issuing command; And issuing the coordinated command to each segment execution mechanism, acquiring the actual state returned by the execution mechanism, simultaneously acquiring the instruction source, the time stamp, the arbitration result, the execution state and the feedback result, writing into a running log, and outputting a multi-source instruction fusion scheduling execution completion signal after all the segments are processed.
  6. 6. The automated sunshade control system of claim 1, wherein executing cooperative control commands in the sunshade fault tolerant execution module initiates a self-recovery mechanism upon detection of motor stuck, positional misalignment, or communication disruption comprising: Extracting a target position, a movement direction and an in-place judging strategy identifier from the cooperative control command, starting the motor to run in a specified direction, executing in-place judgment according to the strategy type, and stopping the motor when the judgment is satisfied; In the execution process, three types of anomalies are synchronously monitored, namely whether clamping stagnation occurs is judged through a motor drive enabling signal and a position feedback updating timestamp, whether position deviation occurs is judged through the validity of a position feedback original signal and the consistency of an actual motion direction and an instruction direction, whether communication interruption occurs is judged through a heartbeat signal receiving record, all motor drive outputs are immediately cleared once any abnormal event is triggered, and a recovery strategy is selected according to event combination; And executing the action sequence of the selected recovery strategy, collecting the current position of the awning, the state of the motor and the abnormal event mark, packaging the current position, the state and the abnormal event mark together with the recovery strategy identifier into a state report, and sending the state report to a monitoring end to complete the whole process of the self-recovery mechanism.
  7. 7. The automatic control system of sunshade according to claim 6, wherein said fault tolerant execution module performs the process of forced folding, locking or backing up when wind speed is over-limit, rainfall or movement resistance is abnormal, comprising: acquiring a wind speed overrun event mark, a rainfall event mark and a motion resistance abnormal event mark, when any event mark is effective, clearing all motion instructions, if the wind speed overrun event mark or the rainfall event mark is effective, executing a forced gathering action, and if only the motion resistance abnormal event mark is effective, executing a short-term backspacing action; Acquiring current position feedback and a completely folded position reference value of the awning, executing locking action when the current position feedback and the completely folded position reference value are consistent, then acquiring the states of all current event marks, and starting a stable timer when all the event marks are invalid; and acquiring the type of the triggering event of the safe standby, waiting for acquiring a manual reset confirmation signal if the triggering event is triggered by the movement resistance abnormal event mark, exiting the safe standby state after the automatic exit permission signal is valid or the manual reset confirmation signal arrives, and finally acquiring the type of the triggering event, the execution strategy identifier and the final position state of the awning, generating a safe event log and sending the safe event log to a monitoring end.
  8. 8. The automatic control system of a sunshade according to claim 1, wherein the process of establishing the residual life prediction model of the motor, the transmission mechanism and the locking device in the sunshade operation and maintenance early warning module based on the standardized sunshade environment parameters and the detection information of motor clamping stagnation and position deviation comprises the following steps: Acquiring a motor clamping stagnation coefficient, a position deviation normalization value and corresponding weights thereof, calculating a weighted fusion value after verifying that the sum of the weights is equal to one, subtracting the obtained fusion value from one to obtain a current comprehensive health index, acquiring a preset and fixed failure threshold value, a degradation nonlinear shape parameter and a reference degradation rate constant, terminating the flow if the degradation nonlinear shape parameter is equal to one, otherwise, continuing to execute the flow; Obtaining an environment sensitivity coefficient vector and a standardized sun-shading environment parameter vector, multiplying the environment sensitivity coefficient vector and the standardized sun-shading environment parameter vector item by item according to a corresponding relation, summing the two, then obtaining a natural index to obtain an environment stress acceleration factor, and substituting the current comprehensive health index, a failure threshold value, a degradation nonlinear shape parameter, a reference degradation rate constant and the environment stress acceleration factor into a formula to calculate the predicted residual service life; And acquiring a comprehensive health index sequence containing a plurality of time points and corresponding time stamps thereof, performing online fine adjustment on the degradation nonlinear shape parameters, the reference degradation rate constant and the environment sensitivity coefficient vector by using a recursive estimation algorithm, and outputting the updated degradation nonlinear shape parameters, the reference degradation rate constant and the environment sensitivity coefficient vector.
  9. 9. The automated control system of claim 8, wherein the process of triggering maintenance pre-warning in the sunshade operation and maintenance pre-warning module when the predicted lifetime is below a set threshold comprises: Obtaining a predicted remaining service life and an early warning time threshold, calculating a double early warning threshold, judging whether the predicted remaining service life is smaller than or equal to the early warning time threshold, obtaining a secondary early warning condition establishment mark, and judging whether the predicted remaining service life is larger than the early warning time threshold and smaller than or equal to the double early warning threshold, obtaining a primary early warning condition establishment mark; If the second-level early warning condition establishment mark is valid, performing audible and visual alarm, acquiring a device identifier, a predicted residual service life for the work order, a degradation reason identifier, a current clamping coefficient and a current position deviation state, inquiring a preset responsible person according to the device identifier, generating a maintenance work order, pushing the maintenance work order to the preset responsible person, and if the first-level early warning condition establishment mark is valid, recording maintenance prompts on an operation and maintenance platform; Acquiring early warning trigger time, prediction basis, associated state data and associated environment data, determining early warning level, reserving a treatment record field, and writing the early warning trigger time, the prediction basis, the associated state data, the associated environment data, the early warning level and the treatment record field into a log.
  10. 10. A sunshade automation control method applied to a sunshade automation control system as claimed in any one of claims 1 to 9, comprising the steps of: Collecting sun-shading environment parameters from the environment where the sun-shading shed is positioned, preprocessing the collected sun-shading environment parameters, and outputting standardized sun-shading environment parameters; secondly, modeling multi-dimensional environment semantic situations and predicting short-term weather trend based on standardized sun-shading environment parameters and manual intervention records of users, dynamically generating sun-shading strategies through multi-objective optimization, and updating personalized control strategies according to user preferences; decomposing the sunshade strategy into cooperative control commands of all canopy sections, and fusing manual commands, app control and external control platform linkage signals, and uniformly scheduling and executing according to priority; executing a cooperative control command, starting a self-recovery mechanism when motor clamping stagnation, position deviation or communication interruption are detected, and executing forced folding, locking or backing when wind speed exceeds limit, rainfall or movement resistance is abnormal; And fifthly, based on standardized sun-shading environment parameters and detection information of motor clamping stagnation and position deviation, establishing a residual life prediction model of the motor, the transmission mechanism and the locking device, and triggering maintenance early warning when the predicted life is lower than a set threshold value.

Description

Automatic control system and control method for sunshade Technical Field The invention relates to the technical field of intelligent sunshade equipment control, in particular to an automatic sunshade control system and an automatic sunshade control method. Background Along with the development of smart cities, green buildings and intelligent households, the importance of the building external sunshade system in the aspects of energy conservation, consumption reduction, comfort improvement and building service life extension is increasingly outstanding, the traditional sunshade is mostly dependent on manual operation or simple timing control, is difficult to respond to real-time weather changes, has the problems of lag in response, higher energy consumption, poor user experience and the like, is easy to cause equipment damage or potential safety hazard in severe weather, and simultaneously reduces natural lighting efficiency due to incapability of timely adjusting shielding states when illumination is insufficient. The patent application with the reference of publication number CN121325611A discloses a multi-input multi-output fuzzy neural network control method and a system for a pseudo-ginseng planting greenhouse, wherein the method comprises the steps of obtaining original parameters including greenhouse temperature, humidity, illumination, water fertilizer concentration, pseudo-ginseng growth state and water flow rate, obtaining input parameters after standardization, inputting the parameters into a three-layer counter-propagation neural network pre-training model, outputting preliminary adjustment coefficients of 6 control quantities such as the opening of the greenhouse, constructing a fuzzy rule base based on parameter coupling scenes, inputting the preliminary adjustment coefficients to obtain fuzzy output, obtaining corrected adjustment coefficients through a gravity center method, calculating control instructions by combining equipment rated range, realizing closed-loop control through dynamic adjustment, automatically operating the system through modules such as multi-parameter acquisition, equipment control output and the like, breaking through the traditional single-input single-output limitation, reducing the parameter fluctuation by more than 50%, adapting the pseudo-ginseng full-growth period, improving the water fertilizer utilization rate and the yield, reducing the labor cost and having obvious economic benefit; However, the conventional automatic control system for sunshades generally does not fully integrate multidimensional environment parameters and user intervention behaviors in terms of strategy generation, is difficult to synchronously optimize energy consumption, comfort and illumination uniformity under dynamic weather conditions, so that the control strategy lacks individuation and foresight, is generally lack of effective detection and autonomous recovery capability for motor clamping stagnation, position deviation, communication interruption and other anomalies in an execution link, cannot reliably trigger safety actions such as forced gathering, rollback or locking when the wind speed is over-limited, rainfall or movement resistance is abnormal and other working conditions, has the risk of insufficient equipment protection, adopts a fixed period overhaul or fault post-processing mechanism in an operation and maintenance level, fails to quantitatively model the degradation process of key components such as a motor, a transmission mechanism and a locking device based on the running state and the environment stress, is difficult to realize dynamic evaluation and grading early warning of the residual life, and the improvement of the reliability and maintenance efficiency of the system is restricted. To this end, the present invention proposes an automatic control system and control method for sunshades. Disclosure of Invention The invention aims to provide an automatic control system and a control method for a sunshade, which solve the problems that the conventional automatic control system for the sunshade generally fails to fully integrate multidimensional environment parameters and user intervention behaviors in terms of strategy generation, is difficult to synchronously optimize energy consumption, comfort and illumination uniformity under dynamic weather conditions, causes lack of individuation and forward-looking performance of a control strategy, generally lacks effective detection and autonomous recovery capability for motor clamping stagnation, position deviation, communication interruption and other anomalies in an execution link, cannot reliably trigger safety actions such as forced gathering, rollback or locking and the like when facing working conditions such as wind speed overrun, rainfall or abnormal movement resistance and the like, has insufficient equipment protection, and fails to quantitatively model degradation processes of key components such as a motor, a tr