Method for testing service life of fan of window cleaning robot and related device

Abstract

The embodiment of the invention provides a method for testing the service life of a fan of a window-cleaning robot and a related device, and relates to the technical field of cleaning. The method comprises the following steps: acquiring initial test parameters of a fan; under the condition that it is determined that the window cleaning robot is in the normal state, the pressure value of the draught fan is obtained; determining a first test parameter of the fan according to a pressure value and the initial test parameter, and controlling the fan to operate based on the first test parameter; and automatically updating the first test parameter according to a preset time period to obtain a second test parameter, and controlling the fan to operate according to the second test parameter. According to the scheme, the complex operation state of the window cleaning robot in actual operation can be comprehensively covered, the working condition covering capacity of the control system is remarkably improved, the test result is closer to a real use scene, and therefore the response speed and accuracy of fan service life testing are effectively improved.

Description

Technical Field

[0001] This application relates to the field of cleaning technology, and in particular to a method and related apparatus for testing the lifespan of a window cleaning robot fan. Background Technology

[0002] Window cleaning robots, as a typical example of cleaning tools, are widely used in homes, office buildings, shopping malls, and other scenarios. Their core function relies on a fan to generate negative pressure to adhere to the glass surface for stable cleaning. Therefore, the lifespan of the fan directly determines the product's reliability and user satisfaction.

[0003] Currently, the lifespan of window cleaning robots is mainly tested by running them at a fixed speed for an extended period. However, this testing method cannot fully cover the various operating conditions encountered by window cleaning robots in actual work, resulting in significant discrepancies between test results and actual usage, and also leads to long testing cycles. Summary of the Invention

[0004] This application provides a method and related apparatus for testing the lifespan of a window cleaning robot fan, which improves the efficiency and accuracy of fan lifespan testing.

[0005] In a first aspect, embodiments of this application provide a method for testing the lifespan of a window cleaning robot fan, including:

[0006] Obtain the initial test parameters of the wind turbine;

[0007] After confirming that the window cleaning robot is in normal working order, obtain the pressure value of the fan;

[0008] Based on the pressure value and the initial test parameters, the first test parameters of the fan are determined, and the operation of the fan is controlled based on the first test parameters;

[0009] Every preset time period, the first test parameter is automatically updated to obtain the second test parameter, and the operation of the fan is controlled by the second test parameter.

[0010] In some embodiments, the initial test parameter includes the pulse width modulation duty cycle; the automatic updating of the first test parameter at a preset time period includes:

[0011] The pulse width modulation duty cycle is updated with a preset step size;

[0012] After the pulse width modulation duty cycle reaches its maximum value, it is updated to its minimum value in the next time period.

[0013] In some embodiments, the method further includes:

[0014] During the operation of the fan, the performance parameters of the fan are recorded and saved at preset time intervals;

[0015] And / or,

[0016] The fan is controlled to run continuously for at least the first target duration using the second test parameters.

[0017] In some embodiments, the method further includes:

[0018] Based on the current of the fan, estimate the operating condition of the window cleaning robot;

[0019] Based on the working conditions of the window cleaning robot, the third test parameters corresponding to the target scene are obtained from the preset scene library;

[0020] Perform the third test parameters and record the performance parameters of the wind turbine under the third test parameters;

[0021] After the second target duration, the second test parameter is executed.

[0022] In some embodiments, the method further includes:

[0023] The performance parameters are processed in real time to predict the remaining lifespan of the wind turbine;

[0024] The second test parameter is adjusted according to the remaining lifespan, and the operation of the wind turbine is controlled based on the adjusted second test parameter;

[0025] In some embodiments, the method further includes:

[0026] Obtain the target operating environment of the window cleaning robot;

[0027] Control the operation of relevant equipment according to the target operating environment, and adjust the first test parameters;

[0028] The fan is controlled to operate based on the adjusted first test parameters, and the performance parameters of the fan are recorded.

[0029] In some embodiments, the method further includes:

[0030] If the window cleaning robot is found to be in an abnormal state during the operation of the fan, the testing of the fan shall be stopped.

[0031] And / or,

[0032] A life test report for the wind turbine is generated based on the performance parameters.

[0033] Secondly, embodiments of this application provide a window cleaning robot fan life test control device, comprising:

[0034] The first acquisition module is used to acquire the initial test parameters of the wind turbine.

[0035] The second acquisition module is used to acquire the pressure value of the fan when it is determined that the window cleaning robot is in normal condition.

[0036] The first control module is used to determine the first test parameters of the fan based on the pressure value and the initial test parameters, and to control the operation of the fan based on the first test parameters.

[0037] The second control module is used to automatically update the first test parameters at a preset time period to obtain the second test parameters, and control the operation of the fan with the second test parameters.

[0038] Thirdly, embodiments of this application provide an electronic device, including a processor, a transceiver, and a memory; the processor is communicatively connected to both the transceiver and the memory.

[0039] The memory stores computer-executed instructions;

[0040] The transceiver communicates and interacts with external devices.

[0041] The processor executes computer execution instructions stored in the memory, causing the processor to perform the first aspect and / or various possible implementations of the first aspect as described above.

[0042] Fourthly, this application provides a computer-readable storage medium having a computer program stored thereon, the computer program being executed by a processor to implement the method of any of the first aspects.

[0043] Fifthly, this application provides a computer program product, including a computer program that, when executed by a processor, implements the method of any one of the first aspects.

[0044] The window cleaning robot fan life testing method provided in this application includes acquiring initial test parameters of the fan; acquiring the fan pressure value when the window cleaning robot is in normal condition; determining first test parameters of the fan based on the pressure value and the initial test parameters, and controlling the fan operation based on the first test parameters; automatically updating the first test parameters at a preset time period to obtain second test parameters, and controlling the fan operation based on the second test parameters. In the above scheme, the rotational speed adjusted by the duty cycle can simulate the frequent speed changes in actual fan use. This comprehensively covers the complex operating states of the window cleaning robot in actual operation, significantly improving the operating condition coverage capability of the control system, making the test results closer to real-world usage scenarios, thereby effectively improving the response speed and accuracy of fan life testing, and requiring no manual intervention throughout the process, reducing labor costs. Attached Figure Description

[0045] Figure 1 A flowchart illustrating a method for testing the lifespan of a window cleaning robot fan, as provided in this application embodiment. Figure 1 ;

[0046] Figure 2 A flowchart illustrating a method for testing the lifespan of a window cleaning robot fan, as provided in this application embodiment. Figure 2 ;

[0047] Figure 3 A flowchart illustrating a method for testing the lifespan of a window cleaning robot fan, as provided in this application embodiment. Figure 3 ;

[0048] Figure 4 A flowchart illustrating a method for testing the lifespan of a window cleaning robot fan, as provided in this application embodiment. Figure 4 ;

[0049] Figure 5 A flowchart illustrating a method for testing the lifespan of a window cleaning robot fan, as provided in this application embodiment. Figure 5 ;

[0050] Figure 6 This is a schematic diagram of the structure of a window cleaning robot fan life testing device provided in an embodiment of this application;

[0051] Figure 7 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0052] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0053] In the embodiments of this application, the terms "first" and "second" are used to distinguish identical or similar items with essentially the same function and effect, without limiting their order. Those skilled in the art will understand that the terms "first" and "second" do not limit the quantity or execution order, and that the terms "first" and "second" do not necessarily imply that they are different.

[0054] It should be noted that, in the embodiments of this application, the terms "exemplary" or "for example" are used to indicate examples, illustrations, or descriptions. Any embodiment or design scheme described as "exemplary" or "for example" in this application should not be construed as being more preferred or advantageous than other embodiments or design schemes. Specifically, the use of terms such as "exemplary" or "for example" is intended to present the relevant concepts in a specific manner.

[0055] Window cleaning robots, as a typical example of cleaning tools, are widely used in homes, office buildings, shopping malls, and other scenarios. Their core function relies on a fan to generate negative pressure that adheres to the glass surface for stable cleaning; the lifespan of the fan directly determines the product's reliability and user satisfaction.

[0056] In existing technologies, the lifespan testing of window cleaning robot fans mainly involves running them at a fixed speed for extended periods. For example, testers set the fan to run continuously at a single speed for thousands of hours and assess its lifespan by observing whether it becomes damaged.

[0057] However, the above scheme only simulates operation at a fixed speed, which cannot cover various complex operating conditions in actual use, resulting in a significant deviation between the test results and real-world usage scenarios.

[0058] The problems are significant. Long-term fixed-speed testing cycles are lengthy and lack simulation of dynamic load changes, hindering the rapid exposure of potential defects and extending product development cycles. Furthermore, the reliance on manual adjustments to test parameters introduces human error and makes it difficult to achieve continuous and stable testing procedures, resulting in inconsistent and unreliable test results.

[0059] To address the aforementioned issues, this application provides a method and related apparatus for testing the lifespan of a window cleaning robot's fan. By constructing a hierarchical intelligent control system and combining dynamic working condition simulation with a multi-dimensional safety monitoring mechanism, it achieves efficient and accurate assessment of the lifespan of the window cleaning robot's fan, thereby covering the complex working conditions encountered in actual use of the window cleaning robot and improving testing efficiency and reliability.

[0060] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will be described below with reference to the accompanying drawings.

[0061] Figure 1 This is a flowchart illustrating a method for testing the lifespan of a window cleaning robot's fan, as provided in an embodiment of this application. The executing entity in this embodiment can be the control system of the window cleaning robot or a testing system mounted on the window cleaning robot. Taking the control system as an example... Figure 1 As shown in the embodiments of this application, the method for testing the lifespan of the window cleaning robot fan may include the following steps:

[0062] S101. Obtain the initial test parameters of the wind turbine.

[0063] In some embodiments, the initial test parameters may include the minimum and maximum values ​​of the Pulse-Width Modulation (PWM) duty cycle of the wind turbine, as well as the speed step size of the PWM duty cycle and the operating mode of the wind turbine.

[0064] For example, the minimum PWM duty cycle is 400, corresponding to a 40% duty cycle; the maximum PWM duty cycle is 1000, corresponding to a 100% duty cycle; the speed change step of the PWM duty cycle is 100, corresponding to a 10% speed change; the fan can operate in automatic mode.

[0065] It should be understood that the minimum and maximum values ​​of the PWM duty cycle, as well as the speed step size of the PWM duty cycle, can be set based on practical experience, and this application embodiment does not limit this.

[0066] In some embodiments, the control system may receive initial test parameters input by the user based on a parameter configuration interface, or read pre-written initial test parameters from an internal storage unit.

[0067] S102. After confirming that the window cleaning robot is in normal condition, obtain the pressure value of the fan.

[0068] In some embodiments, after obtaining the initial test parameters, the control system can perform a self-test. After the self-test passes, the initial test parameters can be initialized, and the fan can be controlled to run based on the initial test parameters.

[0069] For example, the PWM duty cycle can be set to the minimum duty cycle (e.g., 40%), and the operating mode can be set to automatic mode. The fan can then be controlled based on the minimum duty cycle and automatic mode.

[0070] During the operation of the fan, the control system can monitor whether the fan's temperature, current, vibration, and other parameters are within normal limits through the safety monitoring module. If these parameters are within normal limits, the window cleaning robot will operate normally; if any of these parameters are abnormal, the window cleaning robot will operate abnormally.

[0071] When the window cleaning robot is in normal operation, the control system can read the current actual pressure value of the fan through the pressure sensor.

[0072] In some embodiments, if the control system fails its self-test or the window cleaning robot is in an abnormal state, the fan can be stopped to exit the test.

[0073] S103. Determine the first test parameters of the fan based on the pressure value and initial test parameters, and control the operation of the fan based on the first test parameters.

[0074] In some embodiments, after reading the pressure value, the pressure difference between the pressure value and the ideal pressure value under the initial test parameters can be obtained, and the initial test parameters can be adjusted based on the difference so that the actual pressure value generated by the fan tends to the ideal pressure value.

[0075] For example, a PID algorithm can be used to adjust the current PWM duty cycle of the fan based on the pressure difference to obtain the first test parameter.

[0076] Optionally, the initial test parameters can be based on a predefined profile. The predefined profile can be a time-varying PWM sequence.

[0077] For example, a predefined profile might have a PWM duty cycle of 40% for 1-10 minutes, and a PWM duty cycle of 50% for 11-20 minutes, and so on. The corresponding PWM duty cycle can be determined from the predefined profile based on the current operating time of the fan, and then adjusted to obtain the first test parameter.

[0078] S104. The first test parameter is automatically updated at a preset time period to obtain the second test parameter, and the operation of the fan is controlled by the second test parameter and the feedback signal from the collision sensor.

[0079] In some embodiments, to simulate the different speeds of the window cleaning robot in actual work, the PWM duty cycle can be updated at preset time periods (such as 3 seconds, 5 seconds, etc.) during the control of the fan operation to adjust the fan speed.

[0080] For example, the pulse width modulation duty cycle is updated every preset time period with a preset step size; after the pulse width modulation duty cycle reaches its maximum value, it is updated to its minimum value in the next time period.

[0081] For example, the current PWM of the wind turbine is updated every 3 seconds in steps of 100 (10% duty cycle) until the maximum PWM duty cycle is reached. When the current PWM duty cycle is the maximum duty cycle, the PWM duty cycle is updated to the minimum PWM duty cycle in the next cycle.

[0082] For example, if the current PWM duty cycle is 40%, after 3 seconds, update the PWM duty cycle to 50%, and continue this update process until the PWM duty cycle reaches 100%. In the next update, the current PWM duty cycle can be updated back to 40%.

[0083] To better cover the test conditions, when updating the PWM duty cycle with a preset step size, after multiple rounds of updates, the current PWM duty cycle can also be updated randomly to cover any PWM duty cycles that may be missed when updating the PWM duty cycle with a preset step size, thereby improving the accuracy of the test.

[0084] In some embodiments, to ensure that the fan can run to a stable state after the fan speed is adjusted during the test, the fan can be controlled to run continuously for at least the first target duration with the second test parameters (updated test parameters) so that stable performance data of the fan can be collected.

[0085] For example, the duration of the first target can be 5 seconds, 10 seconds, etc., and this application embodiment does not limit this.

[0086] For example, after updating the PWM duty cycle of the fan from 40% to 50%, the fan should be controlled to run at 50% PWM duty cycle for 5 seconds before the next PWM duty cycle update can continue.

[0087] In some embodiments, to reduce the amount of data during testing, the performance parameters of the wind turbine can be recorded and saved at preset time intervals during wind turbine operation.

[0088] The performance parameters of the fan can include current, speed, temperature, vibration amplitude, etc.

[0089] For example, the performance parameters of the fan, such as temperature, current, and vibration amplitude, can be collected in real time using temperature sensors, current sensors, and vibration sensors, and the performance parameters can be saved to the storage medium every 3 seconds.

[0090] In some embodiments, if the window cleaning robot is found to be in an abnormal state during the operation of the fan, the fan is controlled to shut down in an emergency, and the testing of the fan is stopped; a life test report of the fan is generated based on the recorded performance parameters.

[0091] For example, the collected performance data can be analyzed and processed based on the constructed life prediction model to generate a life test report for the wind turbine. The life prediction model can be obtained by training a machine learning model based on the wind turbine's historical operating data.

[0092] The window cleaning robot fan life testing method provided in this application includes acquiring initial test parameters of the fan; acquiring the fan pressure value when the window cleaning robot is in normal condition; determining first test parameters of the fan based on the pressure value and the initial test parameters, and controlling the fan operation based on the first test parameters; automatically updating the first test parameters at a preset time period to obtain second test parameters, and controlling the fan operation based on the second test parameters. In the above scheme, the rotational speed adjusted by the duty cycle can simulate the frequent speed changes in actual fan use. This comprehensively covers the complex operating states of the window cleaning robot in actual operation, significantly improving the operating condition coverage capability of the control system, making the test results closer to real-world usage scenarios, thereby effectively improving the response speed and accuracy of fan life testing, and requiring no manual intervention throughout the process, reducing labor costs.

[0093] In some embodiments, during actual window cleaning, changes in the glass surface condition (such as wet, dry, dirty, oily, etc.), tilt angle, and adsorption force will cause dynamic changes in the fan load. To further simulate the working conditions of the window cleaning robot during use and improve test quality, the load can also be dynamically adjusted during the test.

[0094] Figure 2 A flowchart illustrating a method for testing the lifespan of a window cleaning robot fan provided in this application. Figure 2 ,like Figure 3 As shown, it includes:

[0095] S201. Estimate the working conditions of the window cleaning robot based on the performance parameters of the fan.

[0096] In some embodiments, the performance parameters of the wind turbine under different operating conditions can be collected during the calibration process. Based on the collected performance parameters and the corresponding operating conditions, a mapping relationship (mapping relationship table) or a simple regression model between the performance parameters and the operating conditions can be constructed.

[0097] During the operation of the wind turbine, after collecting the wind turbine's performance parameters, the collected performance parameters can be processed using the constructed mapping relationship or regression model to obtain the working conditions of the window cleaning robot.

[0098] For example, a high fan speed combined with a high current indicates an abnormal adsorption process in the window cleaning robot; a fan speed of approximately 0 combined with a high current indicates a stalled fan.

[0099] S202. Based on the working conditions of the window cleaning robot, obtain the third test parameters corresponding to the target scene from the preset scene library.

[0100] In some embodiments, the preset scenario library includes multiple scenarios, each corresponding to a test case strongly correlated with real-world failures. Each scenario is used to simulate extreme situations that may occur in actual use of the window cleaning robot.

[0101] During the initial calibration process, a mapping relationship can be established between various scenarios and the working conditions of the window cleaning robot.

[0102] After obtaining the working conditions of the window cleaning robot, the target scene can be obtained from the preset scene library based on the mapping relationship between the working conditions and the scene.

[0103] After obtaining the target scenario, the test case, including the third test parameter, can be obtained from the test case corresponding to the target scenario.

[0104] For example, the target scenario is to simulate filter clogging, and the corresponding second test parameter is that the PWM duty cycle of the fan is 80% for 20 minutes.

[0105] S203. Execute the third test parameters and record the performance parameters of the wind turbine under the third test parameters.

[0106] After obtaining the third test parameter, the system can switch from executing the second test parameter to executing the third test parameter, and record the performance parameters exhibited by the fan under the third test parameter to test the fan's performance under filter clogging.

[0107] Optionally, to further cover all scenarios and avoid omissions that could lead to biased test results, the control system can also randomly execute the corresponding test parameters for any scenario in the scenario library at preset intervals. This aims to cover as many extreme situations as possible that the window cleaning robot may encounter in actual use. For example, every 30 minutes, a scenario with corresponding test parameters can be randomly selected from the scenario library and executed.

[0108] S204. After the second target duration, execute the second test parameters.

[0109] In some embodiments, the second target duration can be a preset duration for executing the third test parameter (such as the default duration), or it can be the execution duration included in the third test parameter.

[0110] When executing the third test parameter, the control system can determine whether the third test parameter includes the corresponding execution duration. If it does, the duration is used as the second target duration; if it does not, the default duration is used as the second target duration.

[0111] After executing the second target duration of the second test parameter, the control system can switch to executing the second test parameter and perform the test with the original test logic.

[0112] The window cleaning robot fan life testing method provided in this application embodiment determines the high-damage working conditions associated with the window cleaning robot based on the estimated current working condition of the window cleaning robot, and strengthens the testing accordingly. This efficiently simulates the extreme situations that may occur in the actual use of the window cleaning robot, thereby verifying the life performance of the fan under various extreme conditions and effectively improving the accuracy of the fan life testing.

[0113] In some embodiments, during actual window cleaning, fan failure often stems from system coupling stress. For example, frequent motor starts and stops can cause the fan to drop or rise suddenly, leading to fan failure. To further simulate the working conditions of the window cleaning robot and improve the quality of fan life testing, the associated equipment of the fan can also be controlled during the test.

[0114] Figure 3 A flowchart illustrating a method for testing the lifespan of a window cleaning robot fan provided in this application. Figure 3 ,like Figure 3 As shown, it includes:

[0115] S301. Based on the test parameters of the wind turbine, obtain the test parameters of other equipment associated with the wind turbine; other equipment includes the wind turbine and / or servo motor.

[0116] In some embodiments, during the calibration process of the wind turbine, the allowable parameters corresponding to the wind turbine and / or servo motor when the wind turbine is running under different test parameters are defined, and a mapping relationship is established.

[0117] During wind turbine operation, based on the current test parameters of the wind turbine and this mapping relationship, the test parameters of other equipment associated with the wind turbine can be determined.

[0118] Optionally, the test cases corresponding to each scenario in the preset scenario library may include not only the test parameters of the wind turbine, but also the test parameters of other devices associated with the wind turbine.

[0119] After determining the working conditions of the window robot based on the performance parameters of the fan, the target scene can be determined from the preset scene library based on the working conditions, thereby obtaining the test parameters of other related equipment.

[0120] S302. Synchronously control the operation of other corresponding equipment with the test parameters of other equipment, and record the performance parameters of the fan during the operation of other equipment.

[0121] In some embodiments, when test parameters of other devices are obtained, the corresponding other devices can be controlled to operate synchronously with the wind turbine based on the test parameters.

[0122] During the operation of wind turbines and other equipment, the performance parameters of the wind turbines can be recorded and saved based on the aforementioned methods.

[0123] Optionally, after controlling other devices to run for a preset time, the control system can switch to controlling the fan to run only based on the first test parameters, and execute the test with the original test logic.

[0124] Optionally, during the synchronous operation of the fan and other equipment, the test parameters of the fan and / or other equipment can be randomized, thereby allowing the test parameters of the fan and other equipment to have various coupling possibilities. This allows for testing more unpredictable coupling situations, in order to discover various coupling faults that may affect the lifespan of the fan, thereby improving the accuracy of the fan lifespan test.

[0125] The window cleaning robot fan life testing method provided in this application changes the fan life testing process from the original single-axis independent testing mode to a multi-axis coupled testing mode, thereby better simulating the working conditions of the window cleaning robot in actual use and effectively improving the accuracy of fan life testing.

[0126] In some embodiments, window cleaning robots are typically semi-outdoor products. In real-world window cleaning processes, the operating environment of window cleaning robots is extremely complex, with the fans often directly exposed to the environment. To further simulate the working conditions of window cleaning robots during use and improve the quality of fan lifespan testing, tests can also be conducted in typical operating environments.

[0127] Figure 4 A flowchart illustrating a method for testing the lifespan of a window cleaning robot fan provided in this application. Figure 4 ,like Figure 4 As shown, it includes:

[0128] S401. Obtain the target operating environment for the window cleaning robot.

[0129] In some embodiments, the target operating environment can be the actual usage environment that the user needs to simulate. For example, a southern summer environment or a northern winter environment.

[0130] The target operating environment can be determined by the control system based on user input information obtained from the user interaction interface.

[0131] For example, different target operating environments have different identifiers, and users can input the target operating environment by entering it through the user interaction interface or by clicking the corresponding identifier.

[0132] S402. Control the operation of relevant equipment according to the target operating environment and adjust the first test parameters.

[0133] In some embodiments, the relevant equipment can be various devices in an environmental stress chamber used to simulate different operating environments for the window cleaning robot. Examples include light generators, sprayers, UV lamps, vibrators, and temperature and humidity controllers.

[0134] It should be understood that when testing the lifespan of the window cleaning robot's fan, the window cleaning robot needs to be placed on a test platform in an environmental stress chamber.

[0135] In some embodiments, different target operating environments have different environmental parameters. After the control system acquires the target environment, it can read the corresponding environmental parameters from a preset parameter library.

[0136] For example, the target operating environment is a southern summer environment, with corresponding environmental parameters of 40℃ and 90% humidity. The target operating environment is a northern winter environment, with corresponding environmental parameters of -10℃ and 20% humidity. The target operating environment is window cleaning on a rainy day, with corresponding environmental parameters of 25℃ and periodic spraying (spraying for 2 seconds every 10 seconds).

[0137] In some embodiments, after reading the corresponding environmental parameters, the corresponding equipment can be controlled to operate according to the environmental parameters in order to create the target operating environment for the window cleaning robot.

[0138] In some embodiments, after reading the corresponding environmental parameters, the first test parameter can be dynamically adjusted synchronously to match the first test parameter with the target operating environment. For example, in a low-temperature environment, the maximum PWM of the initial test parameter is limited; in a slippery environment, the PWM during initial operation is reduced.

[0139] When dynamically adjusting initial test parameters based on environmental parameters, adjustments can be made based on preset mapping relationships or models.

[0140] S403. Control the operation of the fan based on the adjusted first test parameters and record the performance parameters of the fan.

[0141] In some embodiments, when the adjusted first test parameter is obtained, the operation of the fan can be controlled based on the test parameter.

[0142] During the operation of the wind turbine, the performance parameters of the wind turbine can be recorded and saved based on the aforementioned method.

[0143] Optionally, after controlling the fan to run for a preset time, the control system can switch to controlling the fan to run only based on the second test parameters, and perform the test with the original test logic.

[0144] The window cleaning robot fan life testing method provided in this application places the window cleaning robot in a controllable environmental stress chamber and applies control simultaneously, thereby achieving dual accelerated aging of "environmental stress + working stress" to more realistically reproduce the failure mode in the field and further improve the accuracy of fan life testing.

[0145] In some embodiments, traditional life testing typically involves performing life analysis after the test to determine if the wind turbine has failed, making the entire testing process rather passive and delayed. To further improve the quality and efficiency of wind turbine life testing, test results can be analyzed in real time to estimate the remaining lifespan of the wind turbine, and test parameters can be adjusted based on the estimated remaining lifespan.

[0146] Figure 5 A flowchart illustrating a method for testing the lifespan of a window cleaning robot fan provided in this application. Figure 5 ,like Figure 5 As shown, it includes:

[0147] S501 processes performance parameters in real time and predicts the remaining lifespan of the wind turbine.

[0148] In some embodiments, edge devices can be used to process performance parameters in real time to improve the efficiency of data processing.

[0149] Edge devices can be devices deployed in the test site close to the window cleaning robot being tested. Examples include other window cleaning robots, servers, etc. Edge devices are equipped with lifetime prediction models that are updated and trained from the cloud.

[0150] The lifetime prediction model deployed on edge devices can be a lightweight lifetime prediction model, so as to quickly predict the remaining lifetime of the wind turbine based on the acquired performance data.

[0151] For example, lifetime prediction models can employ lightweight neural network models (TinyML) or degradation trajectory models (DTM).

[0152] In some embodiments, the cloud can periodically update the deployment model of edge devices via OTA.

[0153] It should be understood that the specific implementation methods for training and updating the lifespan prediction model in the cloud can refer to the implementation methods in existing technologies. These will not be elaborated upon here.

[0154] S502. Adjust the second test parameters according to the remaining lifespan, and control the operation of the fan based on the adjusted second test parameters.

[0155] After obtaining the predicted remaining lifespan of the wind turbine from the edge device, the control system can adjust the current first test parameters based on a preset adjustment strategy to dynamically adapt to the test process.

[0156] For example, when the remaining lifespan is greater than a certain preset value (indicating that the wind turbine's lifespan health is good), the testing intensity can be increased (e.g., reducing the frequency of PWM duty cycle changes or increasing the step size of updating the PWM duty cycle) to speed up the testing process and avoid long-term invalid testing.

[0157] When the remaining lifespan is less than a certain preset value (indicating severe wind turbine lifespan degradation), the upper limit of the maximum PWM duty cycle can be reduced, the PWM duty cycle update time can be extended, and the update step size of the PWM duty cycle can be reduced. This slows down the aging rate of the wind turbine and extends the observable degradation process of its lifespan.

[0158] S503. Stop testing the wind turbine when the remaining lifespan is less than the preset lifespan threshold.

[0159] In some embodiments, if the edge device predicts that the remaining lifespan of the wind turbine is less than a preset lifespan threshold, the control system may stop performing the wind turbine lifespan test to reduce the risk of sudden wind turbine failure.

[0160] In some embodiments, after each recording of wind turbine performance data, the edge device or control system can upload the recorded performance data to the cloud so that the cloud can iteratively train the life prediction model, thereby improving the accuracy of subsequent edge device predictions of wind turbine life.

[0161] The window cleaning robot fan life testing method provided in this application changes the original method of obtaining fan life test results only after the test is completed to a method of predicting the fan life while testing. This upgrades the traditional life testing from a "black box recording" to a "white box prediction + proactive optimization" model. It can obtain higher fan life failure rates with less testing time, effectively improving testing efficiency and accuracy.

[0162] In summary, the window cleaning robot fan life testing method provided in the embodiments of this application significantly improves the efficiency and reliability of window cleaning robot fan life testing through dynamic operating condition simulation and multi-dimensional safety monitoring mechanisms. Dynamic operating condition testing covers complex operating states in actual use, ensuring that test results are closer to real-world scenarios, thereby reducing early failures caused by insufficient testing. The safety monitoring module detects abnormal operating conditions in real time, reducing the risk of equipment damage through automatic protection mechanisms while ensuring the accuracy of test data.

[0163] Based on the above embodiments, this application also provides a window cleaning robot fan life testing device.

[0164] Figure 6 This is a schematic diagram of the structure of the window cleaning robot fan life testing device 70 provided in the embodiments of this application, as shown below. Figure 6 As shown, it includes:

[0165] The first acquisition module 601 is used to acquire the initial test parameters of the wind turbine.

[0166] The second acquisition module 602 is used to acquire the pressure value of the fan when it is determined that the window cleaning robot is in normal condition.

[0167] The first control module 603 is used to determine the first test parameters of the fan based on the pressure value and the initial test parameters, and to control the operation of the fan based on the first test parameters.

[0168] The second control module 604 is used to automatically update the first test parameters at a preset time period to obtain the second test parameters, and control the operation of the fan with the second test parameters.

[0169] In some embodiments, the initial test parameters include the pulse width modulation duty cycle. The second control module 604 is used to update the pulse width modulation duty cycle at preset time intervals with a preset step size. After the pulse width modulation duty cycle reaches its maximum value, it updates the pulse width modulation duty cycle to its minimum value in the next time interval.

[0170] In some embodiments, the second control module 604 is used to record and save the performance parameters of the wind turbine at preset time intervals during wind turbine operation; and / or control the wind turbine to run continuously for at least a first target duration with first test parameters.

[0171] In some embodiments, the second control module 604 is configured to estimate the working condition of the window cleaning robot based on the performance parameters of the fan; obtain the third test parameters corresponding to the target scene from a preset scene library based on the working condition of the window cleaning robot; execute the third test parameters and record the performance parameters of the fan under the third test parameters; and execute the second test parameters after the second target duration.

[0172] In some embodiments, the second control module 604 is used to process performance parameters in real time, predict the remaining lifespan of the wind turbine, adjust the second test parameters according to the remaining lifespan, and control the operation of the wind turbine based on the adjusted second test parameters; and stop testing the wind turbine when the remaining lifespan is less than a preset lifespan threshold.

[0173] In some embodiments, the second control module 604 is configured to acquire test parameters of other devices associated with the wind turbine based on the test parameters of the wind turbine; the other devices include the wind turbine and / or servo motors; synchronously control the operation of the corresponding other devices with the test parameters of the other devices, and record the performance parameters of the wind turbine during the operation of the other devices.

[0174] In some embodiments, the second control module 604 is used to acquire the target operating environment of the window cleaning robot; control the operation of relevant equipment according to the target operating environment and adjust the first test parameters; control the fan to operate based on the adjusted first test parameters and record the performance parameters of the fan.

[0175] In some embodiments, the second control module 604 is used to stop testing the fan if it is determined that the window cleaning robot is in an abnormal state during the operation of the fan; and to generate a life test report of the fan based on performance parameters.

[0176] The window cleaning robot fan life testing device provided in this application embodiment can perform the window cleaning robot fan life testing method shown in any of the above embodiments. Its principle and technical effect are similar, and will not be described again here.

[0177] This application also provides an electronic device.

[0178] Figure 7 This is a schematic diagram of the structure of the electronic device 70 provided in the embodiments of this application, such as... Figure 7 As shown, the electronic device may include: a transceiver 701, a processor 702, and a memory 703. The electronic device may be a control system as described in any of the above embodiments.

[0179] Processor 702 executes computer execution instructions stored in memory, causing processor 702 to perform the scheme in the above embodiments. Processor 702 can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0180] The memory 703 is connected to the processor 702 via the system bus and completes communication between them. The memory 703 is used to store computer program instructions.

[0181] The transceiver 701 can receive and send data and instructions.

[0182] Optionally, the electronic device 70 may also include a communication interface 704, which allows communication and interaction with external or internal devices via the communication interface 703. External devices may be, for example, client devices (e.g., mobile phones, tablets). In specific implementations, if the communication interface 704, memory 703, and processor 702 are implemented independently, they can be interconnected via a bus to complete communication with each other.

[0183] The system bus can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. The system bus can be divided into address bus, data bus, control bus, etc. For ease of representation, only one thick line is used in the diagram, but this does not indicate that there is only one bus or one type of bus. Transceivers are used to enable communication between database access devices and other computers (e.g., clients, read-write libraries, and read-only libraries). Memory may include random access memory (RAM) and may also include non-volatile memory.

[0184] Optionally, in a specific implementation, if the communication interface 704, memory 703, and processor 702 are integrated on a single chip, then the communication interface 704, memory 703, and processor 702 can communicate through an internal interface.

[0185] This application also provides a chip for executing instructions, which is used to execute the technical solutions of the methods described in the above embodiments.

[0186] This application also provides a computer-readable storage medium storing a computer program thereon. When the computer program is executed by a processor, it implements the technical solution of the above method embodiment. Its implementation principle and technical effect are similar, and will not be repeated here.

[0187] In one possible implementation, a computer-readable medium may include random access memory (RAM), read-only memory (ROM), compact discread-only memory (CD-ROM) or other optical disc storage, disk storage or other magnetic storage devices, or any other medium targeted to carry or to store the required program code in the form of instructions or data structures, and accessible by a computer. Furthermore, any connection is appropriately referred to as a computer-readable medium. For example, if software is transmitted from a website, server, or other remote source using coaxial cable, fiber optic cable, twisted pair, Digital Subscriber Line (DSL), or wireless technologies such as infrared, radio, and microwave, then coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwave are included in the definition of medium. As used herein, disks and optical discs include optical discs, laser discs, optical discs, Digital Versatile Discs (DVDs), floppy disks, and Blu-ray discs, where disks typically reproduce data magnetically, while optical discs optically reproduce data using lasers. Combinations of the above should also be included within the scope of computer-readable media.

[0188] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the technical solution of the above method embodiments. Its implementation principle and technical effects are similar, and will not be repeated here.

[0189] In the specific implementation of the aforementioned terminal device or server, it should be understood that the processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. A general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in the embodiments of this application can be directly manifested as execution by a hardware processor, or execution by a combination of hardware and software modules within the processor.

[0190] Those skilled in the art will understand that all or part of the steps in any of the above method embodiments can be implemented by hardware associated with program instructions. The aforementioned program can be stored in a computer-readable storage medium, and when the program is executed, all or part of the steps in the above method embodiments are performed.

[0191] If the technical solution of this application is implemented in software form and sold or used as a product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the technical solution of this application can be embodied in the form of a software product, which is stored in a storage medium and includes a computer program or several instructions. This computer software product enables a computer device (which may be a personal computer, server, network device, or similar electronic device) to execute all or part of the steps of the methods in the embodiments of this application.

[0192] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily essential to this application.

[0193] It should be further noted that although the steps in the flowchart are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowchart may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the sub-steps or stages of other steps.

[0194] It should be understood that the above-described device embodiments are merely illustrative, and the device of this application can also be implemented in other ways. For example, the division of units / modules in the above embodiments is only a logical functional division, and there may be other division methods in actual implementation. For example, multiple units, modules, or components may be combined, or integrated into another system, or some features may be ignored or not executed.

[0195] Furthermore, unless otherwise specified, the functional units / modules in the various embodiments of this application can be integrated into one unit / module, or each unit / module can exist physically separately, or two or more units / modules can be integrated together. The integrated units / modules described above can be implemented in hardware or as software program modules.

[0196] When integrated units / modules are implemented in hardware, the hardware can be digital circuits, analog circuits, etc. The physical implementation of the hardware structure includes, but is not limited to, transistors, memristors, etc. Unless otherwise specified, the processor can be any suitable hardware processor, such as a CPU, GPU, FPGA, DSP, and ASIC, etc. Unless otherwise specified, the storage unit can be any suitable magnetic or magneto-optical storage medium, such as Resistive Random Access Memory (RRAM), Dynamic Random Access Memory (DRAM), Static Random Access Memory (SRAM), Enhanced Dynamic Random Access Memory (EDRAM), High-Bandwidth Memory (HBM), Hybrid Memory Cube (HMC), etc.

[0197] If the integrated unit / module is implemented as a software program module and sold or used as an independent product, it can be stored in a computer-readable storage device (CMD). Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned memory includes various media capable of storing program code, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard drive, magnetic disk, or optical disk.

[0198] In the above embodiments, the descriptions of each embodiment have their own emphasis. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments. The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as the combination of these technical features does not contradict each other, it should be considered within the scope of this specification.

[0199] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

Claims

1. A method for testing the lifespan of a window cleaning robot's fan, characterized in that, include: Obtain the initial test parameters of the wind turbine; After confirming that the window cleaning robot is in normal working order, obtain the pressure value of the fan; Based on the pressure value and the initial test parameters, the first test parameters of the fan are determined, and the operation of the fan is controlled based on the first test parameters; The first test parameter is automatically updated at a preset time period to obtain the second test parameter, and the operation of the fan is controlled by the second test parameter.

2. The method according to claim 1, characterized in that, The initial test parameters include the pulse width modulation duty cycle; the automatic updating of the first test parameters at a preset time period includes: The pulse width modulation duty cycle is updated every preset time period with a preset step size; After the pulse width modulation duty cycle reaches its maximum value, it is updated to its minimum value in the next time period.

3. The method according to claim 2, characterized in that, The method further includes: During the operation of the fan, the performance parameters of the fan are recorded and maintained at preset time intervals; And / or, The fan is controlled to run continuously for at least the first target duration using the second test parameters.

4. The method according to claim 3, characterized in that, The method further includes: Based on the current of the fan, estimate the operating condition of the window cleaning robot; Based on the working conditions of the window cleaning robot, the third test parameters corresponding to the target scene are obtained from the preset scene library; Perform the third test parameters and record the performance parameters of the wind turbine under the third test parameters; After the second target duration, the second test parameter is executed.

5. The method according to claim 3, characterized in that, The method further includes: The performance parameters are processed in real time to predict the remaining lifespan of the wind turbine; The second test parameter is adjusted according to the remaining lifespan, and the operation of the wind turbine is controlled based on the adjusted second test parameter; When the remaining lifespan is less than a preset lifespan threshold, the testing of the wind turbine is stopped.

6. The method according to claim 3, characterized in that, The method further includes: Based on the test parameters of the wind turbine, obtain the operating parameters of other equipment associated with the wind turbine; the other equipment includes motors and / or servo motors; The operation of other corresponding equipment is controlled synchronously using the aforementioned operating parameters, and the performance parameters of the fan are recorded during the operation of the other equipment.

7. The method according to any one of claims 1-6, characterized in that, The method further includes: Obtain the target operating environment of the window cleaning robot; Control the operation of relevant equipment according to the target operating environment, and adjust the first test parameters; The fan is controlled to operate based on the adjusted first test parameters, and the performance parameters of the fan are recorded.

8. The method according to claim 7, characterized in that, The method further includes: If the window cleaning robot is found to be in an abnormal state during the operation of the fan, the testing of the fan shall be stopped. And / or, A life test report for the wind turbine is generated based on the performance parameters.

9. A window cleaning robot fan life testing and control device, characterized in that, include: The first acquisition module is used to acquire the initial test parameters of the wind turbine; The second acquisition module is used to acquire the pressure value of the fan when it is determined that the window cleaning robot is in normal condition; The first control module is used to determine the first test parameters of the fan based on the pressure value and the initial test parameters, and to control the operation of the fan based on the first test parameters; The second control module is used to automatically update the first test parameters at a preset time period to obtain the second test parameters, and control the operation of the fan with the second test parameters.

10. An electronic device, characterized in that, include: The processor, transceiver, and memory are provided; the processor is communicatively connected to both the transceiver and the memory. The memory stores computer-executed instructions; The transceiver communicates and interacts with external devices. The processor executes computer execution instructions stored in the memory to implement the method as described in any one of claims 1-8.

11. A computer-readable storage medium, characterized in that, It stores a computer program, which is executed by a processor to implement the method of any one of claims 1-8.

12. A computer program product, characterized in that, Includes a computer program that, when executed by a controller, implements the method of any one of claims 1-8.

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