Cleaning equipment rolling brush detection method and device, computer equipment and cleaning equipment

Abstract

The invention relates to a cleaning equipment rolling brush detection method and device, computer equipment, a storage medium, a computer program product and cleaning equipment. The method comprises the following steps: acquiring an echo signal measured for a rolling brush in the cleaning equipment; and performing signal analysis on the echo signal, and determining a target roughness level of the rolling brush. By adopting the method, the roughness of the surface of the rolling brush can be accurately judged through the echo signal returned from the surface of the rolling brush.

Description

Technical Field

[0001] The present application relates to the technical field of cleaning equipment detection, and in particular to a cleaning equipment roller brush detection method, device, computer equipment, storage medium, computer program product and cleaning equipment. Background Art

[0002] Currently, the cleaning equipment used for cleaning the floor on the market mainly relies on roller brushes to clean the floor. However, the roughness of the roller brush surface will decrease due to friction with the floor during use, causing the cleaning effect of the roller brush to decrease continuously with the increase in usage time.

[0003] To ensure the cleaning effect, in traditional technology, the main control chip can be used to record the working time of the cleaning equipment to determine the roughness of the roller brush according to the working time. However, the roughness of the roller brush surface is affected by many factors, such as the roughness of the cleaned ground, the maintenance frequency of the roller brush, etc., resulting in the inability to accurately determine the roughness of the roller brush surface only by the working time. Summary of the invention

[0004] Based on this, it is necessary to provide a cleaning equipment roller brush detection method, device, computer equipment, computer readable storage medium, computer program product and cleaning equipment to address the above-mentioned technical problem of being unable to accurately judge the roughness of the roller brush surface.

[0005] In a first aspect, the present application provides a method for detecting a roller brush of a cleaning device, comprising: acquiring an echo signal measured for a roller brush in the cleaning device; performing signal analysis on the echo signal to determine a target roughness level of the roller brush.

[0006] In one of the embodiments, performing signal analysis on the echo signal to determine the target roughness level of the roller brush includes: performing signal analysis on the echo signal to extract signal regularity analysis parameters from the echo signal; and determining the target roughness level of the roller brush based on the signal regularity analysis parameters.

[0007] In one of the embodiments, the signal regularity analysis parameter is the target amplitude change data of the echo signal; based on the signal regularity analysis parameter, the target roughness level of the roller brush is determined, including: obtaining the initial amplitude change data configured for the roller brush; and determining the target roughness level of the roller brush by comparing the initial amplitude change data and the target amplitude change data.

[0008] In one of the embodiments, the signal regularity analysis parameter is the target signal strength of the echo signal in multiple directions; based on the signal regularity analysis parameter, the target roughness level of the roller brush is determined, including: obtaining the initial signal strength in multiple directions configured for the roller brush; and determining the target roughness level of the roller brush by comparing the target signal strength in multiple directions with the initial signal strength.

[0009] In one of the embodiments, the cleaning device roller brush detection method further includes: determining a target rotation speed that matches a target roughness level of the roller brush; and controlling the roller brush to rotate at the target rotation speed during operation of the cleaning device.

[0010] In one embodiment, determining a target rotation speed that matches a target roughness level of the roller brush includes: acquiring a first mapping rule between the roughness level and the rotation speed; and determining the target rotation speed of the roller brush according to the target roughness level and the first mapping rule.

[0011] In one of the embodiments, the first mapping rule is constructed in the following manner: obtaining the roughness level of each of a plurality of test roller brushes, and the cleanliness score of each test roller brush at different rotational speeds; for each test roller brush, taking the minimum rotational speed that makes the cleanliness score of the test roller brush greater than or equal to the cleanliness score threshold as the expected rotational speed of the test roller brush; respectively constructing a mapping relationship between the roughness level and the expected rotational speed of each test roller brush to obtain the first mapping rule.

[0012] In one of the embodiments, the cleaning equipment roller brush detection method further includes: obtaining a second mapping rule between the roughness level and the remaining service life; and determining the remaining service life of the roller brush according to the target roughness level and the second mapping rule.

[0013] In one of the embodiments, the second mapping rule is constructed in the following manner: obtaining the roughness level of each of a plurality of test roller brushes and the cleanliness score of each test roller brush under a rotation speed threshold; for each test roller brush, configuring a remaining service life for the test roller brush according to the cleanliness score of the test roller brush, and constructing a mapping relationship between the roughness level of the test roller brush and the remaining service life to obtain the second mapping rule.

[0014] In the second aspect, the present application also provides a cleaning equipment roller brush detection device, including: an echo signal acquisition module, used to obtain the echo signal measured for the roller brush in the cleaning equipment; a roughness level determination module, used to perform signal analysis on the echo signal to determine the target roughness level of the roller brush.

[0015] In a third aspect, the present application also provides a computer device. The computer device includes a memory and a processor, the memory stores a computer program, and the processor implements the following steps when executing the computer program: obtaining an echo signal measured for a roller brush in a cleaning device; performing signal analysis on the echo signal to determine a target roughness level of the roller brush.

[0016] In a fourth aspect, the present application further provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented: obtaining an echo signal measured for a roller brush in a cleaning device; performing signal analysis on the echo signal to determine a target roughness level of the roller brush.

[0017] In a fifth aspect, the present application also provides a computer program product. The computer program product includes a computer program, which implements the following steps when executed by a processor: obtaining an echo signal measured for a roller brush in a cleaning device; performing signal analysis on the echo signal to determine a target roughness level of the roller brush.

[0018] The above-mentioned cleaning equipment roller brush detection method, device, computer equipment, storage medium and computer program product obtain the echo signal measured for the roller brush in the cleaning equipment, thereby performing signal analysis on the echo signal to determine the target roughness level of the roller brush. That is, instead of judging the roughness of the roller brush surface based on the working time as in the traditional technology, the roughness of the roller brush surface can be accurately judged by the echo signal returned from the roller brush surface.

[0019] In the sixth aspect, the present application also provides a cleaning device, including: a roller brush; a signal processor for transmitting a signal to the roller brush and receiving an echo signal measured for the roller brush; and a controller for obtaining the echo signal from the signal processor, performing signal analysis on the echo signal, and determining the target roughness level of the roller brush.

[0020] In one embodiment, the cleaning device also includes: a motor for driving the roller brush to rotate; a controller for determining a target rotational speed that matches the target roughness level of the roller brush, and sending the target rotational speed to the motor during the operation of the cleaning device, so that the motor drives the roller brush to rotate at the target rotational speed.

[0021] The above-mentioned cleaning device can transmit a signal to the roller brush through the signal processor, and receive an echo signal returned from the surface of the roller brush and measured for the roller brush. Based on this, the controller can obtain the echo signal from the signal processor, and accurately determine the target roughness level of the roller brush by performing signal analysis on the echo signal. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] FIG1 is a diagram showing an application environment of a method for detecting a roller brush of a cleaning device according to an embodiment;

[0023] FIG2 is a schematic diagram of a flow chart of a method for detecting a roller brush of a cleaning device in one embodiment;

[0024] FIG3 is a schematic diagram of a process for determining a target roughness level of a roller brush based on a signal regularity analysis parameter in an echo signal in one embodiment;

[0025] FIG4 is a schematic diagram of a flow chart of controlling the rotation speed of a roller brush in a cleaning device based on the amplitude change of an echo signal in one embodiment;

[0026] FIG5 is a schematic diagram of a flow chart of controlling the rotation speed of a roller brush in a cleaning device based on the signal strength of an echo signal in multiple directions in one embodiment;

[0027] FIG6 is a schematic diagram of a flow chart of controlling the roller brush to rotate at a target speed based on a target roughness level in one embodiment;

[0028] 7 is a schematic diagram of a process of determining a target rotation speed based on a first mapping relationship to control the rotation of a roller brush in a cleaning device in one embodiment;

[0029] FIG8 is a schematic diagram of a process of constructing a first mapping rule in one embodiment;

[0030] FIG9 is a schematic diagram of a process for determining the remaining service life of a roller brush according to a target roughness level in one embodiment;

[0031] FIG10 is a schematic diagram of a process for constructing a second mapping rule in one embodiment;

[0032] FIG11 is a schematic diagram of a flow chart of controlling the rotation speed of a roller brush and monitoring the remaining service life of the roller brush based on an echo signal measured for the roller brush in one embodiment;

[0033] FIG12 is a schematic diagram of a module of a cleaning device in one embodiment;

[0034] FIG13 is a schematic diagram of a module of a cleaning device including a motor in one embodiment;

[0035] FIG14 is a schematic structural diagram of a floor scrubber in one embodiment;

[0036] FIG15 is a block diagram of a cleaning equipment roller brush detection device according to an embodiment;

[0037] FIG. 16 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0038] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0039] The cleaning device roller brush detection method provided in the embodiment of the present application can be applied in the application environment shown in FIG1 . The cleaning device 100 may include: a signal processor 102, a roller brush 104, and a controller 106. The signal processor 102 may be provided separately or integrated on the controller 104, and it is ensured that the signal processor 102 can transmit a signal to the surface of the roller brush 104, and can receive an echo signal returned from the surface of the roller brush 104, and feed the echo signal back to the controller 106.

[0040] Specifically, the controller 106 in the cleaning device 100 can obtain the echo signal measured for the roller brush 104 in the cleaning device 100 through the signal processor 102, and determine the target roughness level of the roller brush 104 by performing signal analysis on the echo signal. Among them, the cleaning device 100 can be a floor scrubber, a sweeper, a cleaner, a multifunctional cleaning robot, professional cleaning equipment, etc. equipped with a roller brush. The signal processor 102 can be: a device with both signal transmission and signal receiving functions, for example, an ultrasonic sensor that can emit ultrasonic waves and receive echo signals, or a pulse sensor that can emit pulse signals to the surface of an object and then receive echo signals. The roller brush 104 can roll to clean the ground and is made of various materials. The roller brush 104 in the cleaning device 100 usually has high durability and wear resistance. The controller 106 can specifically be the main control chip of the cleaning device 100, which can control the operation of the cleaning device 100 according to instructions triggered by the user or according to the acquired data. In this embodiment, the controller 106 can intelligently adjust the rotation speed of the roller brush 104 in the cleaning device 100 according to the echo signal received by the signal processor 102 to ensure the cleaning effect of the cleaning device 100.

[0041] In one embodiment, as shown in FIG. 2 , a method for detecting a roller brush of a cleaning device is provided, and the method is applied to the controller 106 in FIG. 1 as an example for description, including the following steps:

[0042] Step 202: Acquire an echo signal measured for a roller brush in a cleaning device.

[0043] The generation principle of the echo signal is mainly based on the reflection phenomenon in the propagation medium. When the signal encounters an obstacle, part of the energy will be reflected back to form an echo signal. In this embodiment, the roughness of the roller brush surface can be analyzed by sending a signal to the roller brush surface and receiving the reflected signal.

[0044] It should be noted that in the cleaning device of this embodiment, the signal processor is installed near the roller brush so that the direction of the signal processor sending the signal is facing the roller brush in the cleaning device, so that the roughness of the roller brush surface can be measured. For example, a signal processor can be installed at a position facing the central axis of the roller brush, but the number of signal processors can also be multiple, and they can be installed in positions close to the roller brush to measure the roughness of the roller brush surface. If multiple signal processors are installed, there will be intervals between the time when different signal processors send signals to avoid mutual interference between signal processors.

[0045] Based on this, the signal processor in the cleaning device can automatically send a signal, such as an ultrasonic wave, to the roller brush facing the signal processor at a preset time interval. Furthermore, when the signal processor in the cleaning device receives the echo signal measured for the roller brush in the cleaning device, the controller can obtain the echo signal from the signal processor regardless of whether the signal processor is set separately or integrated in the controller.

[0046] Step 204: perform signal analysis on the echo signal to determine the target roughness level of the roller brush.

[0047] Optionally, when the surface roughness of the roller brush in the cleaning device is high, the signal sent by the signal processor may be reflected in large quantities on the surface of the roller brush. However, as the roller brush is used, the roughness of the surface of the roller brush will gradually decrease, and the echo signal generated by the reflection will be significantly different from that of a roller brush with a high roughness. Based on this, the controller can perform signal analysis on the echo signal based on a preset signal analysis rule to determine the target roughness level of the roller brush.

[0048] The above-mentioned cleaning equipment roller brush detection method, device, computer equipment, storage medium and computer program product obtain the echo signal measured for the roller brush in the cleaning equipment, thereby performing signal analysis on the echo signal to determine the target roughness level of the roller brush. That is, instead of judging the roughness of the roller brush surface based on the working time as in the traditional technology, the roughness of the roller brush surface can be accurately judged by the echo signal returned from the roller brush surface.

[0049] In one embodiment, as shown in FIG3 , a flow chart of determining a target roughness level of a roller brush based on a signal regularity analysis parameter in an echo signal is provided, which mainly includes the following steps:

[0050] Step 302: perform signal analysis on the echo signal and extract signal regularity analysis parameters from the echo signal.

[0051] Among them, for roller brushes with high surface roughness, due to the complex surface shape, the signal regularity analysis parameters carried in the echo signal generated by reflection will show irregular characteristics. The higher the roughness, the higher the irregularity of the signal regularity analysis parameters. For roller brushes with relatively smooth surfaces, due to the smooth surface, the signal regularity analysis parameters carried in the echo signal generated by reflection will show partially regular characteristics. The smoother the surface, the higher the regularity of the echo signal. The signal regularity analysis parameters include but are not limited to any of the following: amplitude change data of the echo signal, signal strength of the echo signal in multiple directions, and the signal regularity analysis parameters can characterize the regularity or irregularity of the echo signal.

[0052] Based on this, the controller can perform signal analysis on the echo signal through the digital signal processing program integrated in the controller, determine the amplitude data in the echo signal, the signal strength data in each direction, etc., so that the signal law analysis parameters can be extracted from the echo signal based on the preset signal law analysis parameter extraction rules.

[0053] Step 304, analyzing parameters according to the signal rules to determine the target roughness level of the roller brush.

[0054] Optionally, for each signal regularity analysis parameter, the controller may store initial signal regularity analysis parameters of the same type measured for the roller brush when the roller brush is not in use. Among them, the initial signal regularity analysis parameters can reflect the roughness of the roller brush when it is not in use (no wear and tear occurs), and the signal regularity analysis parameters extracted by the controller can reflect the real-time roughness of the roller brush (when wear and tear occurs). The same type of initial signal regularity analysis parameters will show more obvious irregular characteristics than the same type of signal regularity analysis parameters. Furthermore, after the controller extracts a certain signal regularity analysis parameter, the controller can analyze and determine the real-time roughness of the roller brush by comparing the signal regularity analysis parameter and the initial signal regularity analysis parameter of the same type as the signal regularity analysis parameter, that is, determine the target roughness level of the roller brush.

[0055] In this embodiment, the roughness of the roller brush surface can be accurately identified by performing signal analysis on the echo signal reflected from the roller brush surface, that is, the target roughness level of the roller brush can be accurately determined.

[0056] In one embodiment, the signal regularity analysis parameter may be target amplitude change data of the echo signal. Based on this, as shown in FIG4 , a flow chart of controlling the rotation speed of the roller brush in the cleaning device based on the amplitude change of the echo signal is provided, which mainly includes the following steps:

[0057] Step 402: Perform signal analysis on the echo signal to obtain target amplitude change data of the echo signal.

[0058] Optionally, after obtaining the echo signal from the signal processor, the controller may first perform denoising on the echo signal, and may also amplify the denoised signal to obtain a preprocessed echo signal, wherein the denoising process includes but is not limited to: any one of low-pass filtering, band-pass filtering, and wavelet transform denoising, and signal amplification can improve the signal-to-noise ratio of the signal to facilitate subsequent analysis.

[0059] Furthermore, the controller can convert the echo signal into waveform data in the time domain based on digital signal processing technology (DSP, Digital Signal Processing Technology), and calculate the peak and valley values ​​of the waveform data, so as to calculate the amplitude data of each segment from the peak to the valley value in the waveform data (amplitude = peak value - valley value), and then obtain multiple segments of amplitude data from the peak to the valley value, and use the collected amplitude data as the target amplitude change data. Among them, for roller brushes with high surface roughness, due to the complex surface shape, the amplitude of the echo signal generated by reflection will have irregular changes. The higher the roughness, the more complex the amplitude change. For roller brushes with smoother surfaces, there will be regular amplitudes in the echo signal generated by reflection. Based on this, the roughness of the roller brush surface can be analyzed based on the target amplitude change data extracted from the echo signal.

[0060] Step 404, obtaining initial amplitude change data configured for the roller brush.

[0061] Among them, each model of cleaning equipment has its own matching roller brush model. For various commonly used models of roller brushes, testers can pre-test to obtain the initial amplitude change data generated by the reflection on the roller brush surface when no loss occurs, and import the initial amplitude change data of various models of roller brushes into the controller, so that the controller can use the initial amplitude change data as baseline data for subsequent analysis reference.

[0062] Optionally, the controller may obtain the initial amplitude change data configured for the roller brush from the stored data according to the model of the roller brush.

[0063] Step 406 , determining the target roughness level of the roller brush by comparing the initial amplitude change data with the target amplitude change data.

[0064] Optionally, the controller can first determine the model of the cleaning device and the roller brush model that matches the model of the cleaning device, and then obtain the initial amplitude change data corresponding to the matched roller brush model from the stored data. Based on this, the controller can determine the frequency of occurrence of regular amplitudes in the target amplitude change data by comparing the initial amplitude change data with the target amplitude change data, and determine the target roughness level of the roller brush according to the frequency of occurrence of regular amplitudes. Among them, the higher the frequency of occurrence of regular amplitudes, the more serious the loss of the roller brush surface, the lower the roughness level, and the higher the speed required to control the roller brush to ensure the cleaning effect of the roller brush.

[0065] Exemplarily, taking the four frequency intervals set in the controller: [first frequency, second frequency), [second frequency, third frequency), [third frequency, fourth frequency), [fourth frequency, +∞) as an example, if the frequency of occurrence of the regular amplitude in the target amplitude change data belongs to [first frequency, second frequency), the controller can determine that the target roughness level of the roller brush is the highest first roughness level, indicating that the surface loss of the roller brush is small and the roughness is high; if the frequency of occurrence of the regular amplitude belongs to [second frequency, third frequency), the controller can determine that the target roughness level of the roller brush is the second roughness level, indicating that there is a certain loss on the surface of the roller brush and the roughness is reduced; if the frequency of occurrence of the regular amplitude belongs to [third frequency, fourth frequency), the controller can determine that the target roughness level of the roller brush is the third roughness level, that is, the loss of the surface of the roller brush is aggravated and the roughness is further reduced; if the frequency of occurrence of the regular amplitude belongs to [fourth frequency, +∞), the controller can determine that the target roughness level of the roller brush is the fourth roughness level, indicating that the surface loss of the roller brush is serious and the roughness is low. It should be noted that the above target roughness level classification rules are only examples, and the roughness levels that can be classified in this embodiment are not limited to the above ones.

[0066] In this embodiment, the target amplitude change data can be determined by performing signal analysis on the echo signal reflected from the roller brush surface, and the roughness of the roller brush surface can be accurately identified based on the difference in regularity between the target amplitude change data and the initial amplitude change data, that is, the target roughness level of the roller brush can be accurately determined.

[0067] In one embodiment, the signal regularity analysis parameter may be the target signal strength of the echo signal in multiple directions. Based on FIG. 2 , as shown in FIG. 5 , a flow chart of controlling the rotation speed of the roller brush in the cleaning device based on the signal strength of the echo signal in multiple directions is provided, which mainly includes the following steps:

[0068] Step 502: Perform signal analysis on the echo signal to determine the target signal strength of the echo signal in multiple directions.

[0069] Optionally, when the roller brush surface is rough, if the signal processor transmits a signal to the roller brush surface, the roller brush surface will reflect the signal reaching the surface in different directions, so that the signal processor receives echo signals from different directions, and the strength of the echo signals in different directions will be different. When the roller brush surface is relatively smooth, the direction of the reflected signal is relatively uniform, so that the direction of the echo signal received by the signal processor is reduced, and the strength of the received echo signal is uniform. Based on this, after obtaining the echo signal from the signal processor, the controller can first perform signal analysis on the echo signal to determine the target signal strength of the echo signal in multiple directions. Among them, when the signal processor receives echo signals from different directions, it can mark the direction of the received echo signal and mark the signal strength of the echo signal in different directions for subsequent analysis by the controller.

[0070] Step 504, obtaining initial signal strengths in multiple directions configured for the roller brush.

[0071] Among them, each model of cleaning equipment has its own matching roller brush model. For various commonly used models of roller brushes, testers can pre-test to obtain the initial signal strength in multiple directions generated by the reflection generated by the roller brush surface when no loss occurs, and import the initial signal strength of various models of roller brushes into the controller, so that the controller can use the initial signal strength as baseline data for subsequent analysis reference.

[0072] Optionally, the controller may obtain the initial signal strengths in multiple directions configured for the roller brush from the stored data according to the model of the roller brush.

[0073] Step 506 , determining the target roughness level of the roller brush by comparing the target signal strengths and the initial signal strengths in multiple directions.

[0074] Optionally, the controller may first determine the model of the cleaning device and the roller brush model that matches the model of the cleaning device, and then obtain the initial signal strength in multiple directions corresponding to the matched roller brush model from the stored data. Furthermore, the controller may determine the target roughness level of the roller brush by comparing the target signal strength and the initial signal strength in multiple directions. Among them, from the perspective of the signal receiving direction, the fewer / more uniform the signal receiving directions, the smoother the surface of the roller brush; from the perspective of signal strength, the more uniform the target signal strength of the echo signal in the same direction, the smoother the surface of the roller brush.

[0075] For example, if the controller stores data with initial signal strengths in n directions configured for the roller brush, and the received echo data contains target signal strengths in k directions, in theory, n is greater than k. If k is close to n, and compared with the irregularity of the initial signal strengths in n directions, the target signal strengths in k directions are also significantly irregular, the controller can determine that the target roughness level of the roller brush is the highest first roughness level, indicating that the roller brush surface has less loss and a high degree of roughness; if k is less than n, but compared with the irregularity of the initial signal strengths in n directions, the target signal strengths in k directions are also significantly irregular, the controller can determine that the target roughness level of the roller brush is the second roughness level, indicating that there is loss on the roller brush surface and the roughness decreases; if k is much less than n, and compared with the irregularity of the initial signal strengths in n directions, the target signal strengths in k directions are relatively uniform, the controller can determine that the target roughness level of the roller brush is the third roughness level, indicating that the roller brush surface has serious loss and a low degree of roughness. It should be noted that the above target roughness level division rules are only examples, and the roughness levels that can be divided in this embodiment are not limited to the above types.

[0076] In this embodiment, by performing signal analysis on the echo signal reflected from the surface of the roller brush, the target signal strength of the echo signal in multiple directions can be determined, and based on the difference in regularity between the target signal strength and the initial signal strength in multiple directions, the roughness of the roller brush surface can be accurately identified, that is, the target roughness level of the roller brush can be accurately determined.

[0077] In one embodiment, based on FIG. 2 , as shown in FIG. 6 , the cleaning device roller brush detection method further includes:

[0078] Step 602, determining a target rotation speed that matches the target roughness level of the roller brush.

[0079] The target rotation speed that matches the target roughness level of the roller brush means that when the roughness of the surface of the roller brush is the target roughness level, if the roller brush rotates at the target rotation speed, the desired cleaning effect can be achieved.

[0080] Optionally, the controller may determine a target rotational speed that matches a target roughness level of the roller brush based on a preset rotational speed determination rule.

[0081] Step 604, during the operation of the cleaning device, control the roller brush to rotate at a target speed.

[0082] The cleaning device may further include a motor, and the shaft of the motor may be connected to the shaft of the roller brush.

[0083] Optionally, during the operation of the cleaning device, the controller can send an operating instruction to the motor, and the motor can control its own shaft to rotate at a target speed according to the target speed carried in the operating instruction sent by the controller, thereby controlling the shaft of the roller brush to rotate at the target speed.

[0084] For example, when the user replaces the roller brush with a new one, the roughness level of the roller brush surface is relatively high, and the roller brush can achieve the desired cleaning effect without running at an excessively high speed. Based on this, the controller can intelligently reduce the speed of the roller brush, that is, select a target speed that matches the current target roughness level of the roller brush, and control the roller brush to rotate at the target speed. As the roller brush is used, the surface of the roller brush will gradually become smoother, and the roller brush speed needs to be increased to ensure the cleaning effect of the roller brush. Based on this, the controller can increase the speed of the roller brush based on the newly acquired target roughness level, for example, determine a target speed that matches the newly acquired target roughness level, and control the roller brush to rotate at the newly determined target speed to ensure the cleaning effect of the roller brush.

[0085] In this embodiment, before the roller brush is replaced, the rotation speed of the roller brush can be intelligently adjusted according to the roughness of the roller brush surface to ensure the cleaning effect of the cleaning device.

[0086] In an exemplary embodiment, as shown in FIG. 7 , a flow chart of determining a target rotation speed based on a first mapping relationship to control the rotation of a roller brush in a cleaning device is provided, which mainly includes the following steps:

[0087] Step 702: Obtain a first mapping rule between the roughness level and the rotation speed.

[0088] Optionally, a first mapping rule between the roughness level and the rotation speed may be pre-stored in the controller.

[0089] Exemplarily, taking the example of dividing the roughness level into 4 levels and setting 4 speed gears in the cleaning equipment, the first mapping rule can be specifically as follows: the first roughness level, which indicates that the roller brush surface has less loss, corresponds to a rpm; the second roughness level, which indicates that the roller brush surface has a certain loss and the roughness is reduced, can correspond to b rpm; the third roughness level, which indicates that the loss of the roller brush surface is aggravated and the roughness is further reduced, can correspond to c rpm; the fourth roughness level, which indicates that the loss of the roller brush surface is serious and the roughness is low, can correspond to d rpm. Among them, d>c>b>a, that is, the greater the loss of the roller brush surface, the higher the speed, so as to ensure the cleaning effect of the roller brush. It should be noted that the roughness levels and speed gears that can be set in the cleaning equipment include but are not limited to the above ones, and the above are only examples.

[0090] Step 704: Determine the target rotation speed of the roller brush according to the target roughness level and the first mapping rule.

[0091] Optionally, the controller may determine a target rotation speed that matches a target roughness level of the roller brush by querying a first mapping rule.

[0092] Step 706, during the operation of the cleaning device, control the roller brush to rotate at a target speed.

[0093] Optionally, during the operation of the cleaning device, the controller may transmit the determined target rotational speed to the motor in the cleaning device, so that the motor drives the roller brush to rotate at the target rotational speed.

[0094] In this embodiment, a suitable target rotation speed can be intelligently selected according to the state of the roller brush surface, so as to ensure the cleaning effect of the cleaning device before replacing the roller brush as the roller brush surface gradually wears out.

[0095] In one embodiment, as shown in FIG8 , a flow chart of constructing a first mapping rule is provided, which mainly includes the following steps:

[0096] Step 802, obtaining the roughness levels of the plurality of test roller brushes and the cleanliness scores of each test roller brush at different rotation speeds.

[0097] The roller brush models of the multiple test roller brushes are the same as the roller brush models of the cleaning device to which the controller belongs. The roughness levels of the multiple test roller brushes and the cleanliness scores of each test roller brush at different speeds can be obtained by pre-testing and evaluation by the tester and imported into the controller.

[0098] Optionally, the controller may obtain, from the stored data, the roughness levels of each of the plurality of test roller brushes and the cleanliness scores of each of the test roller brushes at different rotation speeds.

[0099] Step 804 : For each test roller brush, the minimum rotation speed that makes the cleanliness score of the test roller brush greater than or equal to the cleanliness score threshold is used as the expected rotation speed of the test roller brush.

[0100] Among them, the cleanliness score threshold can be flexibly configured according to actual needs.

[0101] Optionally, for each test roller brush, the controller may use the minimum rotation speed that makes the cleanliness score of the test roller brush greater than or equal to the cleanliness score threshold as the expected rotation speed of the test roller brush. The smaller the rotation speed, the less energy is consumed during operation. Therefore, even if a test roller brush can achieve the desired cleaning effect at multiple rotation speeds, the minimum rotation speed that can achieve the cleaning effect is selected as the expected rotation speed of the test roller brush.

[0102] Step 806 : construct a mapping relationship between the roughness level and the expected rotation speed of each test roller brush to obtain a first mapping rule.

[0103] Optionally, after determining the expected rotation speeds corresponding to each of the multiple test roller brushes, the controller can further determine the roughness level of each test roller brush and construct a mapping relationship between the roughness level and the expected rotation speed of each test roller brush. If there is a mapping relationship between a certain roughness level and multiple expected rotation speeds, the controller can use the minimum expected rotation speed with a mapping relationship with the roughness level as the expected rotation speed for the final mapping of the roughness level, or use the average of multiple expected rotation speeds with a mapping relationship with the roughness level as the expected rotation speed for the final mapping of the roughness level. Finally, the final mapping relationships of all the roughness levels are collected to obtain the first mapping rule.

[0104] In this embodiment, a first mapping rule between the roughness level and the expected rotational speed can be constructed and stored based on the test data pre-tested and evaluated by the tester, so that the controller of the subsequent cleaning device can easily refer to the first mapping rule during operation to accurately select the target rotational speed that matches the wear state of the roller brush surface in the cleaning device, thereby ensuring the cleaning effect of the cleaning device.

[0105] In a possible implementation, based on FIG. 2 , as shown in FIG. 9 , a flow chart of determining the remaining service life of the roller brush according to the target roughness level is also provided, wherein:

[0106] Step 902: Obtain a second mapping rule between the roughness level and the remaining useful life.

[0107] Optionally, a second mapping rule between the roughness level and the remaining service life may be pre-stored in the controller, wherein the higher the roughness of the roller brush surface (the higher the roughness level), the longer the remaining service life of the roller brush.

[0108] Exemplarily, taking the classification of the roughness level into 4 levels as an example, the second mapping rule may specifically be: the first roughness level, which indicates that the roller brush surface has less wear and tear, may correspond to A hours of remaining service life; the second roughness level, which indicates that the roller brush surface has certain wear and tear and the roughness level is reduced, may correspond to B hours; the third roughness level, which indicates that the wear and tear of the roller brush surface is aggravated and the roughness level is further reduced, may correspond to C hours; the fourth roughness level, which indicates that the wear and tear of the roller brush surface is serious and the roughness level is low, may correspond to D hours. Among them, A>B>C>D, that is, the greater the wear and tear of the roller brush surface, the shorter the remaining service life, so that when the wear and tear of the roller brush surface is large, a prompt reminder can be given to replace the roller brush to ensure the cleaning effect of the roller brush. It should be noted that the roughness level and remaining service life that can be set in the cleaning device include but are not limited to the above types, and the above are only examples.

[0109] Step 904: Determine the remaining service life of the roller brush according to the target roughness level and the second mapping rule.

[0110] Optionally, the controller may determine the remaining service life that matches the target roughness level of the roller brush by querying the second mapping rule.

[0111] For example, if the remaining service life of the roller brush is less than or equal to the life threshold of the roller brush, the controller can automatically feedback a reminder to replace the roller brush. If the remaining service life of the roller brush is greater than the life threshold of the roller brush, the controller continues to monitor the target roughness level of the roller brush to continue to monitor the remaining service life of the roller brush. The life threshold can be flexibly configured according to actual needs.

[0112] For example, if a warning light is provided on the cleaning device, the controller can control the warning light to be always on or flash to provide feedback on the roller brush replacement prompt to remind the user to replace the roller brush. The controller can also provide feedback on the roller brush replacement prompt to the terminal device through pop-up reminders, reminders in the mini program, etc. In addition, the user can independently and conveniently choose whether to ignore or close the roller brush replacement prompt.

[0113] In this embodiment, the remaining service life of the roller brush can be determined based on the wear state of the roller brush surface (target roughness level), and a roller brush replacement reminder can be fed back in time to ensure the cleaning effect of the cleaning equipment.

[0114] In some embodiments, as shown in FIG10 , a flow chart of constructing a second mapping rule is provided, which mainly includes the following steps:

[0115] Step 1002, obtaining the roughness level of each of the plurality of test roller brushes and the cleanliness score of each of the test roller brushes at a rotation speed threshold.

[0116] The roller brush models of the multiple test roller brushes are the same as the roller brush models of the cleaning device to which the controller belongs. The roughness levels of the multiple test roller brushes and the cleanliness scores of each test roller brush under the speed threshold can be obtained by pre-testing and evaluation by the tester and imported into the controller. The speed threshold refers to: the maximum speed of the cleaning device to which the controller belongs.

[0117] Optionally, the controller may obtain, from the stored data, the roughness levels of each of the plurality of test roller brushes and the cleanliness score of each of the test roller brushes at a rotation speed threshold.

[0118] Step 1004 , for each test roller brush, a remaining service life is configured for the test roller brush according to the cleanliness score of the test roller brush, and a mapping relationship between the roughness level of the test roller brush and the remaining service life is constructed to obtain a second mapping rule.

[0119] Among them, the higher the cleanliness score, the longer the remaining service life.

[0120] Optionally, for each test roller brush, the controller may configure a remaining service life for the test roller brush according to the cleanliness score of the test roller brush. For example, for a test roller brush with a cleanliness score greater than a cleanliness score threshold, the controller may configure a remaining service life greater than the life threshold. For a test roller brush with a cleanliness score less than or equal to the cleanliness score threshold, the controller may configure a remaining service life less than or equal to the life threshold. Further, the controller may construct a mapping relationship between the roughness level and the remaining service life of each test roller brush, thereby obtaining a second mapping rule.

[0121] Exemplarily, taking the four cleanliness score intervals set in the controller: [first score, second score], (second score, cleanliness score threshold], (cleanliness score threshold, third score], (third score, +∞) as an example, the second mapping rule can be specifically: if the cleanliness score of the test roller brush belongs to [first score, second score], the controller can determine that the remaining service life of the test roller brush is D; if the cleanliness score of the test roller brush belongs to (second score, cleanliness score threshold], the controller can determine that the remaining service life of the test roller brush is C; if the cleanliness score of the test roller brush belongs to (cleanliness score threshold, third score], the controller can determine that the remaining service life of the test roller brush is B; if the cleanliness score of the test roller brush belongs to (third score, +∞), the controller can determine that the remaining service life of the test roller brush is A. Among them, A>B>life threshold≥C>D, the higher the cleanliness score, the longer the remaining service life. It should be noted that the above remaining service life determination rules are only examples.

[0122] In this embodiment, a second mapping rule between the roughness level and the remaining service life can be constructed and stored based on the test data pre-tested and evaluated by the tester, so that the controller of the subsequent cleaning device can easily refer to the second mapping rule during operation, accurately select the remaining service life that matches the wear state of the roller brush surface in the cleaning device, and promptly remind the user to replace the roller brush to ensure the cleaning effect of the cleaning device.

[0123] In an exemplary embodiment, as shown in FIG11 , a flow chart of controlling the rotation speed of the roller brush and monitoring the remaining service life of the roller brush based on the echo signal measured for the roller brush is provided, wherein:

[0124] Step 1102, obtaining an echo signal measured for a roller brush in a cleaning device;

[0125] Step 1104, performing signal analysis on the echo signal to determine the target roughness level of the roller brush;

[0126] Step 1106, obtaining a first mapping rule between the roughness level and the rotation speed;

[0127] Step 1108, determining a target rotation speed of the roller brush according to the target roughness level and the first mapping rule;

[0128] Step 1110, during the operation of the cleaning device, controlling the roller brush to rotate at a target speed;

[0129] Step 1112, obtaining a second mapping rule between the roughness level and the remaining service life;

[0130] Step 1114, determining the remaining service life of the roller brush according to the target roughness level and the second mapping rule;

[0131] If the remaining service life of the roller brush is less than or equal to the life threshold of the roller brush, execute step 1116 and provide a roller brush replacement prompt; otherwise, return to step 1102.

[0132] It should be understood that, although the steps in the flowcharts involved in the above embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps is not strictly limited in order, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above embodiments may include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0133] Based on the application environment shown in FIG1 , a cleaning device 100 is provided in an embodiment of the present application, including:

[0134] Roller brush 104;

[0135] The signal processor 102 is used to transmit a signal to the roller brush 104 and receive an echo signal measured for the roller brush 104;

[0136] The controller 106 is used to obtain the echo signal from the signal processor 102 , perform signal analysis on the echo signal, and determine the target roughness level of the roller brush 104 .

[0137] The above-mentioned cleaning device 100 can transmit a signal to the roller brush 104 through the signal processor 102, and receive an echo signal returned from the surface of the roller brush 104 and measured for the roller brush 104. Based on this, the controller 106 can obtain the echo signal from the signal processor 102, and accurately determine the target roughness level of the roller brush 104 by performing signal analysis on the echo signal.

[0138] In one embodiment, as shown in FIG. 12 , the cleaning device 100 further includes:

[0139] The motor 108 is used to drive the roller brush 104 to rotate;

[0140] The controller 106 is also used to determine a target rotation speed that matches the target roughness level of the roller brush 104, and send the target rotation speed to the motor 108 during the operation of the cleaning device 100, so that the motor 108 drives the roller brush 104 to rotate at the target rotation speed.

[0141] The motor 108 can convert electrical energy into mechanical energy. In this embodiment, the motor 108 can convert the electrical energy provided by the storage battery or the power connection device of the cleaning device 100 into mechanical energy to drive the roller brush 104 to rotate at a desired speed.

[0142] In this embodiment, before replacing the roller brush 104, the controller 106 can select a target rotation speed that matches the roughness of the surface of the roller brush 104 according to the target roughness level of the roller brush 104, and send instructions to the motor 108 so that the motor 108 controls the roller brush 104 to run at the target rotation speed, thereby improving the cleaning effect of the cleaning device 100. Therefore, by using the above cleaning device 100, it is possible to accurately determine the roughness of the surface of the roller brush 104, and improve the cleaning effect of the cleaning device 100 before replacing the roller brush 104 according to the roughness of the surface of the roller brush 104.

[0143] Optionally, as shown in FIG13 , the cleaning device may further include: a roller brush shaft 110, a roller 112, a handle assembly 114, and a movable housing 116. The roller brush shaft 110 is used to install the roller brush 104, and the roller brush shaft 110 is connected to the motor 108. When the motor 108 runs according to the target speed, the motor 108 can drive the roller brush shaft 110 to rotate at the target speed, so that the roller brush 104 rotates at the target speed. The roller 112 allows the cleaning device 100 to move flexibly, the handle assembly 114 can be installed with a long handle, which is convenient for the user to push the cleaning device 100, and the movable housing 116 can protect the motor 108 and the roller brush shaft 110 in the cleaning device 100 when it is closed, and it is convenient for the user to replace the roller brush 104 and overhaul the motor 108 when the movable housing 116 is opened.

[0144] For example, as shown in FIG14, taking the cleaning device as a floor scrubber as an example, a schematic diagram of the structure of the floor scrubber is provided, wherein: a roller brush can be installed on a roller brush shaft 1402 of the floor scrubber (the roller brush is not shown in FIG14, and FIG14 shows a schematic diagram of the roller brush shaft 1402 exposed after the user removes the roller brush); a signal processor 1404 can be installed at a position directly opposite to the roller brush shaft 1402, so that the signal sent by the signal processor 1404 can reach the surface of the roller brush; the motor 1406 can drive the roller brush shaft 1402 to rotate at a target speed based on the target speed transmitted by the controller of the floor scrubber (not shown in FIG14), so that the roller brush rotates at the target speed. The floor scrubber may also include: a roller 1406, so that the floor scrubber can be flexibly moved; a handle assembly 1408, so that a long handle can be installed to facilitate the user to push the floor scrubber; and a movable housing 1410, which can protect the motor 1406 and the roller brush shaft 1402 when closed, and facilitate the maintenance of the motor 1406 or the replacement of the roller brush when opened.

[0145] Based on the same inventive concept, the embodiment of the present application also provides a cleaning equipment roller brush detection device for implementing the cleaning equipment roller brush detection method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more cleaning equipment roller brush detection device embodiments provided below can refer to the limitations of the cleaning equipment roller brush detection method above, and will not be repeated here.

[0146] In one embodiment, as shown in FIG. 15 , a cleaning equipment roller brush detection device is provided, comprising: an echo signal acquisition module 1502 and a roughness level determination module 1506 , wherein:

[0147] An echo signal acquisition module is used to acquire an echo signal measured for a roller brush in a cleaning device;

[0148] The roughness level determination module is used to perform signal analysis on the echo signal to determine the target roughness level of the roller brush.

[0149] The above-mentioned cleaning equipment roller brush detection device obtains the echo signal measured for the roller brush in the cleaning equipment, and then performs signal analysis on the echo signal to determine the target roughness level of the roller brush. That is, instead of judging the roughness of the roller brush surface based on the working time as in the traditional technology, the roughness of the roller brush surface can be accurately judged by the echo signal returned from the roller brush surface.

[0150] In one of the embodiments, the roughness level determination module also includes: a parameter extraction unit for performing signal analysis on the echo signal and extracting signal law analysis parameters from the echo signal; a roughness level determination unit for determining the target roughness level of the roller brush based on the signal law analysis parameters.

[0151] In one of the embodiments, the signal regularity analysis parameter is the target amplitude change data of the echo signal, and the roughness level determination unit is also used to: obtain the initial amplitude change data configured for the roller brush; and determine the target roughness level of the roller brush by comparing the initial amplitude change data and the target amplitude change data.

[0152] In one of the embodiments, the signal regularity analysis parameter is the target signal strength of the echo signal in multiple directions, and the roughness level determination unit is also used to: obtain the initial signal strength in multiple directions configured for the roller brush; and determine the target roughness level of the roller brush by comparing the target signal strength and the initial signal strength in multiple directions.

[0153] In one of the embodiments, the roller brush detection device for cleaning equipment further includes a rotation speed control module, which is used to: determine a target rotation speed that matches a target roughness level of the roller brush; and control the roller brush to rotate at the target rotation speed during operation of the cleaning equipment.

[0154] In one of the embodiments, the rotation speed control module is further used to: obtain a first mapping rule between the roughness level and the rotation speed; and determine the target rotation speed of the roller brush according to the target roughness level and the first mapping rule.

[0155] In one of the embodiments, the cleaning equipment roller brush detection device also includes a first mapping rule construction module, which is used to: obtain the roughness level of each of a plurality of test roller brushes, and the cleanliness score of each test roller brush at different rotation speeds; for each test roller brush, use the minimum rotation speed that makes the cleanliness score of the test roller brush greater than or equal to the cleanliness score threshold as the expected rotation speed of the test roller brush; respectively construct a mapping relationship between the roughness level and the expected rotation speed of each test roller brush to obtain a first mapping rule.

[0156] In one of the embodiments, the cleaning equipment roller brush detection device also includes a service life determination module, which is further used to: obtain a second mapping rule between the roughness level and the remaining service life; and determine the remaining service life of the roller brush according to the target roughness level and the second mapping rule.

[0157] In one of the embodiments, the cleaning equipment roller brush detection device also includes a second mapping rule construction module, which is further used to: obtain the roughness level of each of a plurality of test roller brushes, and the cleanliness score of each test roller brush under a rotation speed threshold; for each test roller brush, configure a remaining service life for the test roller brush according to the cleanliness score of the test roller brush, and construct a mapping relationship between the roughness level and the remaining service life of the test roller brush to obtain a second mapping rule.

[0158] Each module in the above-mentioned cleaning equipment roller brush detection device can be implemented in whole or in part by software, hardware and their combination. Each of the above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the corresponding operations of each of the above modules.

[0159] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be shown in FIG16. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. The processor, the memory and the input / output interface are connected via a system bus, and the communication interface is connected to the system bus via the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store cleaning equipment roller brush detection data. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, a cleaning equipment roller brush detection method is implemented.

[0160] Those skilled in the art will understand that the structure shown in FIG. 16 is merely a block diagram of a partial structure related to the scheme of the present application, and does not constitute a limitation on the computer device to which the scheme of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different arrangement of components.

[0161] In one embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above-mentioned method embodiments when executing the computer program.

[0162] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0163] In one embodiment, a computer program product is provided, including a computer program, which implements the steps in the above method embodiments when executed by a processor.

[0164] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant laws, regulations and standards of relevant countries and regions.

[0165] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0166] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0167] The above embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A method for detecting a roller brush of a cleaning device, characterized in that: The method comprises: Acquire an echo signal measured for a roller brush in a cleaning device; Signal analysis is performed on the echo signal to determine the target roughness level of the roller brush.

2. The method according to claim 1, characterized in that The performing signal analysis on the echo signal to determine the target roughness level of the roller brush includes: Performing signal analysis on the echo signal, and extracting signal regularity analysis parameters from the echo signal; The target roughness level of the roller brush is determined according to the signal regularity analysis parameters.

3. The method according to claim 2, characterized in that The signal regularity analysis parameter is target amplitude variation data of the echo signal; The step of analyzing parameters according to the signal rule to determine the target roughness level of the roller brush includes: Acquiring initial amplitude change data configured for the roller brush; By comparing the initial amplitude change data with the target amplitude change data, the target roughness level of the roller brush is determined.

4. The method according to claim 2, characterized in that: The signal regularity analysis parameter is the target signal strength of the echo signal in multiple directions; The step of analyzing parameters according to the signal rule to determine the target roughness level of the roller brush includes: Acquire initial signal strengths in multiple directions configured for the roller brush; The target roughness level of the roller brush is determined by comparing the target signal strengths and the initial signal strengths in the multiple directions.

5. The method according to claim 1, characterized in that The method further comprises: determining a target rotation speed that matches a target roughness level of the roller brush; During the operation of the cleaning device, the roller brush is controlled to rotate at the target rotation speed.

6. The method according to claim 5, characterized in that The determining of a target rotation speed matching a target roughness level of the roller brush comprises: Obtaining a first mapping rule between the roughness level and the rotation speed; The target rotation speed of the roller brush is determined according to the target roughness level and the first mapping rule.

7. The method according to claim 6, characterized in that The first mapping rule is constructed in the following manner: Obtaining the roughness level of each of the plurality of test roller brushes and the cleanliness score of each of the test roller brushes at different rotation speeds; For each of the test roller brushes, the minimum rotation speed that makes the cleanliness score of the test roller brush greater than or equal to the cleanliness score threshold is used as the expected rotation speed of the test roller brush; A mapping relationship between the roughness level and the expected rotation speed of each of the test roller brushes is respectively constructed to obtain a first mapping rule.

8. The method according to claim 1, characterized in that The method further comprises: obtaining a second mapping rule between the roughness level and the remaining service life; The remaining service life of the roller brush is determined according to the target roughness level and the second mapping rule.

9. The method according to claim 8, characterized in that The second mapping rule is constructed in the following manner: Obtaining the roughness level of each of the plurality of test roller brushes and the cleanliness score of each of the test roller brushes at a rotation speed threshold; For each of the test roller brushes, a remaining service life is configured for the test roller brush according to the cleanliness score of the test roller brush, and a mapping relationship between the roughness level of the test roller brush and the remaining service life is constructed to obtain a second mapping rule.

10. A cleaning device, characterized in that: The cleaning equipment comprises: Roller brush; A signal processor, used for transmitting a signal to the roller brush and receiving an echo signal measured for the roller brush; The controller is used to obtain the echo signal from the signal processor, perform signal analysis on the echo signal, and determine the target roughness level of the roller brush.

11. The cleaning device according to claim 10, characterized in that The cleaning device also includes: A motor, used for driving the roller brush to rotate; The controller is further used to determine a target rotation speed that matches a target roughness level of the roller brush, and to send the target rotation speed to the motor during the operation of the cleaning device, so that the motor drives the roller brush to rotate at the target rotation speed.

12. A cleaning equipment roller brush detection device, characterized in that: The device comprises: An echo signal acquisition module is used to acquire an echo signal measured for a roller brush in a cleaning device; The roughness level determination module is used to perform signal analysis on the echo signal to determine the target roughness level of the roller brush.

13. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 9 are implemented.

14. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 9 are implemented.

15. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 9 are implemented.

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