Cleaning machine control method and device based on garbage detection, cleaning machine and medium

Abstract

The invention relates to the technical field of cleaning machines, and discloses a cleaning machine control method and device based on garbage detection, a cleaning machine and a medium, and the method comprises the steps that first airflow detection data are obtained in real time, and the first airflow detection data are detection data of airflow entering a dust box of the cleaning machine; performing garbage particle analysis according to the first airflow detection data to obtain a first analysis result; according to the first analysis result, target cleaning control parameters of the cleaning machine are determined; and controlling the cleaning machine to clean according to the target cleaning control parameter. The cleaning control parameters are dynamically determined on the basis of the garbage particle analysis result, cleaning of the cleaning machine is matched with cleaning needed by garbage on the ground, and therefore the cleanliness of the ground is guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of cleaning machines, and in particular to a cleaning machine control method and device based on garbage detection, a cleaning machine and a medium. Background Art

[0002] A cleaning machine, also known as a sweeping robot, automatic sweeper, smart vacuum cleaner, robot vacuum cleaner, etc., is a type of smart home appliance that can automatically complete floor cleaning in a room with the help of artificial intelligence. Cleaning machines generally use brushing and vacuuming to absorb dust and debris on the floor into their own dust box (also known as a garbage collection box), thereby completing the function of floor cleaning. However, the suction force of existing cleaning machines is constant. When encountering a floor with a lot of dust or slightly larger debris, it still uses conventional suction force for cleaning, and the cleanliness of the floor cannot be guaranteed. Summary of the invention

[0003] Based on this, it is necessary to propose a cleaning machine control method, device, cleaning machine and medium based on garbage detection to address the technical problem that the existing cleaning machines in the prior art have constant suction force, and when encountering a ground with a lot of dust and a slightly larger volume of debris, they still use conventional suction force for cleaning, and the cleanliness of the ground cannot be guaranteed.

[0004] In a first aspect, a cleaning machine control method based on garbage detection is provided, the method comprising:

[0005] Acquire first airflow detection data in real time, where the first airflow detection data is detection data of the airflow entering the dust box of the cleaning machine;

[0006] Performing garbage particle analysis according to the first airflow detection data to obtain a first analysis result;

[0007] Determining target cleaning control parameters of the cleaning machine according to the first analysis result;

[0008] The cleaning machine is controlled to clean according to the target cleaning control parameter.

[0009] Furthermore, the step of controlling the cleaning machine to clean according to the target cleaning control parameter includes:

[0010] Determining fan power data and roller brush motor parameters according to the target cleaning control parameters;

[0011] The operation of the fan of the cleaning machine is controlled according to the fan power data, and the operation of the roller brush motor of the cleaning machine is controlled according to the roller brush motor parameters.

[0012] Furthermore, the method further comprises:

[0013] Acquire second airflow detection data, wherein the second airflow detection data is detection data of airflow passing through the filter of the cleaning machine, and the airflow passes through the dust box and enters the filter;

[0014] Performing garbage particle analysis according to the second airflow detection data to obtain a second analysis result;

[0015] Determine the filtering level according to the second analysis result;

[0016] If the filtering level is within the first level range, a filter replacement reminder signal is generated and sent according to a first sending method.

[0017] Furthermore, the step of acquiring the second airflow detection data includes:

[0018] Obtaining a cleaning start signal of the cleaning machine;

[0019] In response to the cleaning start signal, a first time period is waited after the generation time of the cleaning start signal to obtain the second airflow detection data.

[0020] Furthermore, the method further comprises:

[0021] Obtaining a preparation signal of the cleaning machine;

[0022] In response to the preparation signal, acquiring each of the first analysis results as a data packet at a first time interval and a preset time window;

[0023] Performing garbage particle trend prediction according to the data packet to obtain a trend prediction result;

[0024] Determining cleaning control parameter compensation data according to the trend prediction result;

[0025] The step of determining the target cleaning control parameter of the cleaning machine according to the first analysis result comprises:

[0026] Determining initial cleaning control parameters of the cleaning machine according to the first analysis result;

[0027] The initial cleaning control parameters are corrected according to the cleaning control parameter compensation data to obtain the target cleaning control parameters of the cleaning machine.

[0028] Furthermore, the method further comprises:

[0029] Obtaining dirt detection data of the target area;

[0030] Performing cleaning control parameter distribution prediction based on the dirt detection data to obtain distribution prediction data;

[0031] The step of controlling the cleaning machine to clean according to the target cleaning control parameter comprises:

[0032] According to the distribution prediction data, the target cleaning control parameter is adjusted to obtain an adjusted cleaning control parameter;

[0033] According to the adjusted cleaning control parameters, the cleaning machine is controlled to clean the target area.

[0034] Furthermore, in the process of controlling the cleaning machine to clean the target area according to the adjusted cleaning control parameter, the method further includes:

[0035] Predicting garbage particle data of the airflow entering the dust box according to the dirt detection data to obtain first data;

[0036] Acquire the first analysis result corresponding to the target area as second data;

[0037] Determine the cleaning level of the roller brush according to the first data and the second data;

[0038] If the roller brush cleaning level is within the second level range, a roller brush replacement reminder signal is generated and sent according to a second sending method.

[0039] In a second aspect, a cleaning machine control device based on garbage detection is provided, the device comprising:

[0040] A real-time data acquisition module, used for acquiring first airflow detection data in real time, wherein the first airflow detection data is detection data of the airflow entering the dust box of the cleaning machine;

[0041] An analysis module, configured to perform garbage particle analysis based on the first airflow detection data to obtain a first analysis result;

[0042] a cleaning control parameter determination module, configured to determine a target cleaning control parameter of the cleaning machine according to the first analysis result;

[0043] The cleaning control module is used to control the cleaning machine to clean according to the target cleaning control parameter.

[0044] In a third aspect, a cleaning machine is provided, comprising a first detector, a cleaning component, a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the first detector is used to detect the airflow entering a dust box of the cleaning machine, the processor is electrically connected to the first detector and the cleaning component, and the processor implements the steps of the above-mentioned cleaning machine control method based on garbage detection when executing the computer program.

[0045] In a fourth aspect, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the above-mentioned cleaning machine control method based on garbage detection are implemented.

[0046] The garbage detection-based cleaning machine control method, device, cleaning machine and medium of the present application obtain first airflow detection data in real time, the first airflow detection data is the detection data of the airflow entering the dust box of the cleaning machine, performs garbage particle analysis based on the first airflow detection data, obtains a first analysis result, determines the target cleaning control parameter of the cleaning machine based on the first analysis result, and controls the cleaning of the cleaning machine based on the target cleaning control parameter. The cleaning control parameter is dynamically determined based on the result of the garbage particle analysis, so that the cleaning of the cleaning machine matches the cleaning required for the garbage on the ground, thereby ensuring the cleanliness of the ground. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0048] in:

[0049] Figure 1 is an application environment diagram of a cleaning machine control method based on garbage detection in one embodiment;

[0050] Figure 2 is a flow chart of a cleaning machine control method based on garbage detection in one embodiment;

[0051] Figure 3 is a flow chart of a cleaning machine control method based on garbage detection in one embodiment;

[0052] Figure 4 is a structural block diagram of a cleaning machine control device based on garbage detection in one embodiment;

[0053] Figure 5 is a structural diagram of a cleaning machine in one embodiment;

[0054] Figure 6 1 is a structural diagram of a cleaning machine in one embodiment. DETAILED DESCRIPTION

[0055] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0056] The cleaning machine control method based on garbage detection provided by the embodiment of the present invention can be applied in Figure 1 In the application environment, Figure 1 The application environment includes a cleaning machine 1, a server 2, and a client 3. The client 3 communicates with the server 2 through a network, and the cleaning machine 1 communicates with the server 2 and the client 3 respectively.

[0057] Optionally, the cleaning machine 1 is configured to implement the cleaning machine control method based on garbage detection of the present application, which specifically includes: acquiring first airflow detection data in real time, the first airflow detection data being detection data of the airflow entering the dust box of the cleaning machine; performing garbage particle analysis according to the first airflow detection data to obtain a first analysis result; determining the target cleaning control parameter of the cleaning machine according to the first analysis result; and controlling the cleaning of the cleaning machine according to the target cleaning control parameter. The cleaning control parameter is dynamically determined based on the result of the garbage particle analysis, so that the cleaning of the cleaning machine matches the cleaning required for the garbage on the ground, thereby ensuring the cleanliness of the ground.

[0058] Optionally, the server 2 obtains first airflow detection data in real time from the client 3 or the cleaning machine 1, and the first airflow detection data is the detection data of the airflow entering the dust box of the cleaning machine. The server 2 is configured to implement the following steps: perform garbage particle analysis according to the first airflow detection data to obtain a first analysis result; determine the target cleaning control parameter of the cleaning machine according to the first analysis result; send a signal to the cleaning machine 1 according to the target cleaning control parameter, and control the cleaning machine to clean by the signal.

[0059] Optionally, the client 3 obtains first airflow detection data from the cleaning machine in real time, and the first airflow detection data is the detection data of the airflow entering the dust box of the cleaning machine. The client 3 is configured to implement the following steps: perform garbage particle analysis according to the first airflow detection data to obtain a first analysis result; determine the target cleaning control parameter of the cleaning machine according to the first analysis result; send a signal to the cleaning machine 1 according to the target cleaning control parameter, and control the cleaning machine to clean by the signal.

[0060] See also Figure 6 Optionally, the cleaning machine 1 includes a first detector ( Figure 6), cleaning components (including but not limited to roller brush 11, dust box 12, filter 13, fan), storage device ( Figure 6 Not shown), processor ( Figure 6 The present invention relates to a computer program stored in the memory and executable on the processor, wherein the first detector is used to detect the airflow entering the dust box 12 of the cleaning machine 1, and the processor is electrically connected to the first detector and the cleaning component. When the processor executes the computer program, the steps of the cleaning machine control method based on garbage detection are implemented.

[0061] The first detector uses a light sensor. The first detector is arranged near the garbage inlet 14 of the dust box 12. Optionally, the first detector includes a transmitter and a receiver. The transmitter emits light, and the light emitted by the transmitter passes through the airflow entering the dust box of the cleaning machine. The receiver receives the light passing through the airflow entering the dust box of the cleaning machine, and analyzes and processes the light received by the receiver, converting it into data with practical significance (that is, light state parameters), and the light state parameters are called first airflow detection data.

[0062] Optionally, the light sensing state parameters include: light intensity, light change frequency, light attenuation, light wavelength change and light signal duration. Light intensity: indicates the intensity of the received light. Light change frequency: reflects how fast the light changes over time. Light attenuation: reflects the degree of light loss in the process of passing through the airflow. Light wavelength change: if there is detection of light of different wavelengths, it may include the change of the relevant wavelength. Light signal duration: the duration of the light being received, etc.

[0063] It is understandable that the rotation of the roller brush 11 drives the garbage on the ground to mix with the air to form an airflow carrying the garbage on the ground. The airflow carrying the garbage on the ground enters the garbage storage chamber 15 in the dust box 12 from the garbage inlet 14 of the dust box 12 of the cleaning machine 1 through the suction force of the fan. The airflow passes from the garbage storage chamber 15 through the cleaning outlet of the dust box 12 through the filter 13, and is filtered by the filter 13. The airflow filtered by the filter 13 is cleaner than the airflow entering the dust box. During the whole process, the garbage brought into the garbage storage chamber 15 by the airflow is deposited in the garbage storage chamber 15. The air filtered by the filter 13 is discharged into the external environment.

[0064] The client may be, but is not limited to, various personal computers, laptops, smart phones, tablet computers, and portable wearable devices. The server may be implemented as an independent server or a server cluster consisting of multiple servers.

[0065] The present invention is described in detail below through specific embodiments.

[0066] See also Figure 2 As shown, Figure 2 A flow chart of a cleaning machine control method based on garbage detection provided by an embodiment of the present invention includes the following steps:

[0067] S1: acquiring first airflow detection data in real time, where the first airflow detection data is detection data of the airflow entering the dust box of the cleaning machine;

[0068] Specifically, the first detector of the cleaning machine detects the airflow entering the dust box of the cleaning machine, and uses the detection data (also called light sensing state parameters) obtained as the first airflow detection data. The execution end of this method obtains the first airflow detection data obtained by the first detector in real time.

[0069] S2: performing garbage particle analysis according to the first airflow detection data to obtain a first analysis result;

[0070] Establish a relationship model between light-sensing state parameters and particle characteristics. Through a large number of experiments and data analysis, determine the change pattern of light-sensing state parameters caused by the influence of different particle numbers and sizes on light scattering, absorption, etc.

[0071] Specifically, based on the relationship model between the light sensing state parameters and the particle characteristics, the number and size of the garbage particles are calculated according to the first airflow detection data, and the calculated data is used as the first analysis result.

[0072] S3: determining a target cleaning control parameter of the cleaning machine according to the first analysis result;

[0073] Specifically, according to the first analysis result, a cleaning control parameter is determined by using a table lookup method, and the cleaning control parameter is used as a target cleaning control parameter of the cleaning machine.

[0074] Cleaning control parameters include suction parameters. Suction parameters include maximum suction, continuous suction, static pressure value and air volume. Maximum suction: indicates the strongest suction value that the sweeper can generate, generally in Pascals (Pa), which is an important indicator to measure the suction size. Continuous suction: reflects the suction level that the sweeper can maintain for a long time under normal working conditions. Static pressure value: reflects the pressure generated by the sweeper on the air under specific conditions, and is also a reference for suction performance. Air volume: that is, the volume of air passing through the sweeper per unit time, which is also related to suction.

[0075] S4: Controlling the cleaning machine to clean according to the target cleaning control parameter.

[0076] Specifically, a control signal is generated according to the target cleaning control parameter, and the cleaning machine is controlled to clean according to the control signal.

[0077] This embodiment acquires first airflow detection data in real time, the first airflow detection data is the detection data of the airflow entering the dust box of the cleaning machine, performs garbage particle analysis based on the first airflow detection data, obtains a first analysis result, determines the target cleaning control parameter of the cleaning machine based on the first analysis result, and controls the cleaning of the cleaning machine based on the target cleaning control parameter. The cleaning control parameter is dynamically determined based on the result of the garbage particle analysis, so that the cleaning of the cleaning machine matches the cleaning required for the garbage on the ground, thereby ensuring the cleanliness of the ground.

[0078] In one embodiment, the step of controlling the cleaning machine to clean according to the target cleaning control parameter comprises:

[0079] S41: Determine fan power data and roller brush motor parameters according to the target cleaning control parameters;

[0080] Specifically, according to the suction force parameter in the target cleaning control parameter, the fan power data is determined by using a table lookup method, and according to the roller brush speed parameter in the target cleaning control parameter, the roller brush motor parameter is determined by using a table lookup method.

[0081] The roller brush speed parameter is a parameter that describes the speed of the roller brush.

[0082] The fan power data is the power data of the fan of the sweeper. The fan draws air from the garbage inlet of the dust box into the garbage collection chamber in the dust box, and then sucks the garbage out of the garbage collection chamber from the clean outlet of the dust box through the filter.

[0083] The roller brush motor parameters are the sweeping parameters of the roller brush of the sweeper.

[0084] S42: controlling the operation of the fan of the cleaning machine according to the fan power data, and controlling the operation of the roller brush motor of the cleaning machine according to the roller brush motor parameters.

[0085] Specifically, a first signal in the control signal is generated according to the fan power data, and the operation of the fan of the cleaning machine is controlled by the first signal, so that the airflow is sucked from the garbage inlet of the dust box into the garbage storage chamber in the dust box through the operation of the fan; a second signal in the control signal is generated according to the roller brush motor parameters, and the operation of the roller brush motor of the cleaning machine is controlled by the second signal, so that the roller brush is driven to rotate through the operation of the roller brush motor.

[0086] This embodiment realizes dynamic determination of fan power data and roller brush motor parameters based on the results of garbage particle analysis, so that the suction force of the cleaning machine matches the suction force required for the garbage on the ground, and the rotation of the roller brush matches the brushing movement required for the garbage on the ground, thereby ensuring the cleanliness of the ground.

[0087] See also Figure 3As shown, in one embodiment, the method further includes:

[0088] S51: Acquire second airflow detection data, wherein the second airflow detection data is detection data of airflow passing through the filter of the cleaning machine, and the airflow passes through the dust box and enters the filter;

[0089] Specifically, the second detector of the cleaning machine detects the airflow passing through the filter of the cleaning machine, and uses the detection data (also called light sensing state parameter) obtained by the detection as the second airflow detection data. The execution end of this method obtains the second airflow detection data obtained by the second detector.

[0090] The second detector uses a light sensor. The second detector is installed on the side of the filter away from the cleaning outlet of the dust box. Optionally, the second detector includes a transmitting end and a receiving end. The transmitting end emits light, and the light emitted by the transmitting end passes through the airflow entering the dust box of the cleaning machine. The receiving end receives the light passing through the airflow entering the dust box of the cleaning machine, and analyzes and processes the light received by the receiving end, converting it into data with practical significance (that is, light state parameters), and the light state parameters are used as second airflow detection data.

[0091] S52: performing garbage particle analysis according to the second airflow detection data to obtain a second analysis result;

[0092] Specifically, based on the relationship model between the light sensing state parameters and the particle characteristics, the number and size of the garbage particles are calculated according to the second airflow detection data, and the calculated data is used as the second analysis result.

[0093] S53: Determine the filtering level according to the second analysis result;

[0094] Specifically, according to the second analysis result, a table lookup method is used to determine the filtering level.

[0095] S54: If the filtering level is within the first level range, a filter replacement reminder signal is generated, and the filter replacement reminder signal is sent according to a first sending method.

[0096] Specifically, if the filtering level is within the first level range, it means that the filter filtering does not meet the requirements and the filter needs to be replaced as soon as possible. Therefore, a filter replacement reminder signal is generated and sent according to the first sending method to realize the filter replacement reminder.

[0097] The first sending method may be one or more of a signal light reminder, a cleaning pause reminder, a voice reminder, and sending a signal reminder to the client.

[0098] It is understandable that if the filtering level is outside the first level range, it means that the filter filtering meets the requirements, there is no need to replace the filter, and there is no need to be reminded to replace the filter.

[0099] This embodiment analyzes whether to replace the filter based on the detection data of the airflow passing through the filter of the cleaning machine, and when it is analyzed that the filtering of the filter does not meet the requirements, the filter replacement reminder signal is sent according to the first sending method, thereby facilitating the user to replace the filter in time.

[0100] In one embodiment, the step of acquiring the second airflow detection data includes:

[0101] S511: Acquire a cleaning start signal of the cleaning machine;

[0102] Specifically, the cleaning start signal is generated according to a preset condition. For example, the preset condition is that when it is detected that the cleaning machine is about to enter an area that needs to be cleaned, the cleaning start signal is actively generated.

[0103] S511: responding to the cleaning start signal, waiting for a first time period after the generation time of the cleaning start signal, and acquiring the second airflow detection data.

[0104] Specifically, when the cleaning start signal is obtained, a first time period is waited after the generation time of the cleaning start signal to obtain the second airflow detection data.

[0105] This embodiment waits for a first period of time after the generation time of the cleaning start signal to obtain the second airflow detection data, so that after each cleaning is started, only one filter replacement evaluation needs to be performed, reducing the consumption of computing resources.

[0106] In one embodiment, the method further comprises:

[0107] S61: Acquire a preparation signal of the cleaning machine;

[0108] The preparation signal is a start signal for preparing for cleaning work. For example, the cleaning machine generates the preparation signal when it enters the startup state from shutdown.

[0109] S62: In response to the preparation signal, obtaining each of the first analysis results as a data packet according to a first time interval and a preset time window;

[0110] Specifically, when the preparation signal is obtained, at the start time of each cycle corresponding to the first time interval, the start time is used as the end time, and each of the first analysis results of the preset time window is obtained, and each of the first analysis results obtained is used as a data packet. It can be understood that the generation time of the first analysis results in the data packet is after the generation time of the current preparation signal.

[0111] S63: performing junk particle trend prediction according to the data packet to obtain a trend prediction result;

[0112] Specifically, the data packet is input into a pre-trained garbage particle trend prediction model to perform garbage particle trend prediction, and the predicted data is used as a trend prediction result.

[0113] Optionally, the pre-trained garbage particle trend prediction model is a model obtained by training based on a time series model, wherein the time series model includes: an autoregressive moving average model (ARMA) and an autoregressive integrated moving average model (ARIMA).

[0114] The trend prediction results are time and garbage particle prediction results. The garbage particle prediction results describe the number and size of garbage particles.

[0115] S64: determining cleaning control parameter compensation data according to the trend prediction result;

[0116] Specifically, according to the trend prediction result, the cleaning control parameter compensation data is determined by using a table lookup method.

[0117] The step of determining the target cleaning control parameter of the cleaning machine according to the first analysis result comprises:

[0118] S31: Determine initial cleaning control parameters of the cleaning machine according to the first analysis result;

[0119] Specifically, according to the first analysis result, a table lookup method is used to determine the cleaning control parameters, and the determined cleaning control parameters are used as the initial cleaning control parameters of the cleaning machine.

[0120] S32: Correcting the initial cleaning control parameters according to the cleaning control parameter compensation data to obtain the target cleaning control parameters of the cleaning machine.

[0121] Specifically, the cleaning control parameter compensation data and the initial cleaning control parameters are substituted into a first correction function for calculation, and the calculated data is used as the target cleaning control parameter of the cleaning machine.

[0122] The first correction function can be obtained by fitting multiple sets of experimental data.

[0123] This embodiment first determines the cleaning control parameter compensation data through the garbage particle trend prediction data, and then uses the cleaning control parameter compensation data to correct the initial cleaning control parameters, thereby improving the accuracy of the determined target cleaning control parameters, further improving the matching degree between the cleaning of the cleaning machine and the cleaning requirements of the garbage on the ground, and further ensuring the cleanliness of the ground.

[0124] In one embodiment, the method further comprises:

[0125] S71: Obtaining dirt detection data of the target area;

[0126] The dirt detection data includes one or more of images and videos.

[0127] The target area is the area you want to clean.

[0128] Specifically, the dirt detection data of the target area can be obtained from the cleaning machine, and the dirt detection data sent to the target area by the monitoring device can also be obtained through the Internet of Things.

[0129] S72: Predicting the distribution of cleaning control parameters according to the dirt detection data to obtain distribution prediction data;

[0130] Specifically, the dirt detection data is input into the pre-trained dirt classification model to perform classification prediction for each pixel point, and the vector element corresponding to the maximum prediction value among the prediction values ​​(which are probability values) corresponding to the designated pixel point in the predicted vector is used as the target element, and the classification category corresponding to the target element (the classification category expresses the associated data of the dirt type and dirt level) is used as the classification result corresponding to the designated pixel point to obtain the classification distribution result; the region is divided according to the classification distribution result, wherein, in a divided region, the dirt type of each pixel point is the same, the dirt level is within the same preset level range, and the position is close, that is, the divided region is a connected region; according to the classification distribution result, the cleaning control parameter of each region is determined by the table lookup method, and the cleaning control parameters corresponding to all regions are used as distribution prediction data. The designated pixel point is any one of the pixel points corresponding to the dirt detection data.

[0131] The pre-trained dirt classification model is a pre-trained multi-classification model.

[0132] The step of controlling the cleaning machine to clean according to the target cleaning control parameter comprises:

[0133] S41: adjusting the target cleaning control parameter according to the distribution prediction data to obtain an adjusted cleaning control parameter;

[0134] Specifically, the distribution prediction data and the target cleaning control parameter are substituted into the second correction function for calculation, and the calculated data is used as the adjusted cleaning control parameter.

[0135] The second correction function can be obtained by fitting multiple sets of experimental data.

[0136] S42: Controlling the cleaning machine to clean the target area according to the adjusted cleaning control parameters.

[0137] Specifically, a control signal is generated according to the adjustment of the cleaning control parameter, and the cleaning machine is controlled to clean according to the control signal.

[0138] This embodiment further improves the matching degree between the cleaning of the cleaning machine and the cleaning requirements of the garbage on the ground by predicting the distribution of the cleaning control parameters according to the dirt detection data to adjust the target cleaning control parameters, thereby further ensuring the cleanliness of the ground.

[0139] In one embodiment, in the process of controlling the cleaning machine to clean the target area according to the adjusted cleaning control parameter, the method further includes:

[0140] S421: predicting the garbage particle data of the airflow entering the dust box according to the dirt detection data to obtain first data;

[0141] Specifically, the dirt detection data is input into a pre-trained garbage particle trend prediction model to predict the garbage particle data of the airflow entering the dust box, and the predicted data is used as the first data.

[0142] Optionally, the pre-trained garbage particle trend prediction model is a model obtained by training based on a time series model, wherein the time series model includes: an autoregressive moving average model (ARMA) and an autoregressive integrated moving average model (ARIMA).

[0143] S422: Acquire the first analysis result corresponding to the target area as second data;

[0144] It can be understood that any first analysis result among all the first analysis results corresponding to the target area can be obtained as the second data.

[0145] S423: Determine the cleaning level of the roller brush according to the first data and the second data;

[0146] Specifically, a table lookup method is used to determine the roller brush cleaning level based on the data in the first data corresponding to the second data and the second data.

[0147] S424: If the roller brush cleaning level is within the second level range, a roller brush replacement reminder signal is generated, and the roller brush replacement reminder signal is sent according to the second sending method.

[0148] Specifically, if the roller brush cleaning level is within the second level range, it means that the rotation of the roller brush and the mixing of garbage and air on the ground have not achieved the expected effect, and the roller brush needs to be replaced. Therefore, a roller brush replacement reminder signal is generated and sent according to the second sending method to realize the reminder to replace the roller brush.

[0149] The second sending method may be one or more of a signal light reminder, a cleaning pause reminder, a voice reminder, and sending a signal reminder to the client.

[0150] This embodiment predicts the garbage particle data of the airflow entering the dust box based on the dirt detection data corresponding to the target area and the first analysis result corresponding to the target area to analyze whether to replace the roller brush, and if it is analyzed that the roller brush does not meet the requirements, the roller brush replacement reminder signal is sent according to the second sending method, thereby facilitating the user to replace the roller brush in time and ensuring the cleanliness of the floor.

[0151] See also Figure 4 As shown, in one embodiment, a cleaning machine control device based on garbage detection is provided, the device comprising:

[0152] A real-time data acquisition module 801 is used to acquire first airflow detection data in real time, where the first airflow detection data is detection data of the airflow entering the dust box of the cleaning machine;

[0153] An analysis module 802 is used to perform garbage particle analysis based on the first airflow detection data to obtain a first analysis result;

[0154] A cleaning control parameter determination module 803, used to determine a target cleaning control parameter of the cleaning machine according to the first analysis result;

[0155] The cleaning control module 804 is used to control the cleaning machine to clean according to the target cleaning control parameters.

[0156] This embodiment acquires first airflow detection data in real time, the first airflow detection data is the detection data of the airflow entering the dust box of the cleaning machine, performs garbage particle analysis based on the first airflow detection data, obtains a first analysis result, determines the target cleaning control parameter of the cleaning machine based on the first analysis result, and controls the cleaning of the cleaning machine based on the target cleaning control parameter. The cleaning control parameter is dynamically determined based on the result of the garbage particle analysis, so that the cleaning of the cleaning machine matches the cleaning required for the garbage on the ground, thereby ensuring the cleanliness of the ground.

[0157] In one embodiment, the step of controlling the cleaning machine to clean according to the target cleaning control parameter in the cleaning control module 804 includes:

[0158] Determining fan power data and roller brush motor parameters according to the target cleaning control parameters;

[0159] The operation of the fan of the cleaning machine is controlled according to the fan power data, and the operation of the roller brush motor of the cleaning machine is controlled according to the roller brush motor parameters.

[0160] In one embodiment, the device further includes: a first reminder module, wherein the first reminder module is configured to:

[0161] Acquire second airflow detection data, wherein the second airflow detection data is detection data of airflow passing through the filter of the cleaning machine, and the airflow passes through the dust box and enters the filter;

[0162] Performing garbage particle analysis according to the second airflow detection data to obtain a second analysis result;

[0163] Determine the filtering level according to the second analysis result;

[0164] If the filtering level is within the first level range, a filter replacement reminder signal is generated and sent according to a first sending method.

[0165] In one embodiment, the step of obtaining the second airflow detection data in the first reminder module includes:

[0166] Obtaining a cleaning start signal of the cleaning machine;

[0167] In response to the cleaning start signal, a first time period is waited after the generation time of the cleaning start signal to obtain the second airflow detection data.

[0168] In one embodiment, the device further comprises: a trend prediction module, wherein the trend prediction module is configured to:

[0169] Obtaining a preparation signal of the cleaning machine;

[0170] In response to the preparation signal, acquiring each of the first analysis results as a data packet at a first time interval and a preset time window;

[0171] Performing garbage particle trend prediction according to the data packet to obtain a trend prediction result;

[0172] Determining cleaning control parameter compensation data according to the trend prediction result;

[0173] The step of determining the target cleaning control parameter of the cleaning machine according to the first analysis result in the cleaning control parameter determination module 803 includes:

[0174] Determining initial cleaning control parameters of the cleaning machine according to the first analysis result;

[0175] The initial cleaning control parameters are corrected according to the cleaning control parameter compensation data to obtain the target cleaning control parameters of the cleaning machine.

[0176] In one embodiment, the device further comprises: a suction prediction module, wherein the suction prediction module is used to:

[0177] Obtaining dirt detection data of the target area;

[0178] Performing cleaning control parameter distribution prediction based on the dirt detection data to obtain distribution prediction data;

[0179] The step of controlling the cleaning machine to clean according to the target cleaning control parameter in the cleaning control module 804 includes:

[0180] According to the distribution prediction data, the target cleaning control parameter is adjusted to obtain an adjusted cleaning control parameter;

[0181] According to the adjusted cleaning control parameters, the cleaning machine is controlled to clean the target area.

[0182] In one embodiment, the cleaning control module 804 is further configured to:

[0183] Predicting garbage particle data of the airflow entering the dust box according to the dirt detection data to obtain first data;

[0184] Acquire the first analysis result corresponding to the target area as second data;

[0185] Determine the cleaning level of the roller brush according to the first data and the second data;

[0186] If the roller brush cleaning level is within the second level range, a roller brush replacement reminder signal is generated and sent according to a second sending method.

[0187] See also Figure 5 and Figure 6 As shown, in one embodiment, a cleaning machine is proposed, wherein the cleaning machine 1 includes a first detector ( Figure 6 ), cleaning components (including but not limited to a roller brush 11, a dust box 12, a filter 13), a storage device ( Figure 6 Not shown), processor ( Figure 6The first detector is used to detect the airflow entering the dust box of the cleaning machine, the processor is electrically connected to the first detector and the cleaning component, and the processor implements the following steps when executing the computer program:

[0188] Acquire first airflow detection data in real time, where the first airflow detection data is detection data of the airflow entering the dust box of the cleaning machine;

[0189] Performing garbage particle analysis according to the first airflow detection data to obtain a first analysis result;

[0190] Determining target cleaning control parameters of the cleaning machine according to the first analysis result;

[0191] The cleaning machine is controlled to clean according to the target cleaning control parameter.

[0192] This embodiment acquires first airflow detection data in real time, the first airflow detection data is the detection data of the airflow entering the dust box of the cleaning machine, performs garbage particle analysis based on the first airflow detection data, obtains a first analysis result, determines the target cleaning control parameter of the cleaning machine based on the first analysis result, and controls the cleaning of the cleaning machine based on the target cleaning control parameter. The cleaning control parameter is dynamically determined based on the result of the garbage particle analysis, so that the cleaning of the cleaning machine matches the cleaning required for the garbage on the ground, thereby ensuring the cleanliness of the ground.

[0193] In one embodiment, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the following steps are implemented:

[0194] Acquire first airflow detection data in real time, where the first airflow detection data is detection data of the airflow entering the dust box of the cleaning machine;

[0195] Performing garbage particle analysis according to the first airflow detection data to obtain a first analysis result;

[0196] Determining target cleaning control parameters of the cleaning machine according to the first analysis result;

[0197] The cleaning machine is controlled to clean according to the target cleaning control parameter.

[0198] This embodiment acquires first airflow detection data in real time, the first airflow detection data is the detection data of the airflow entering the dust box of the cleaning machine, performs garbage particle analysis based on the first airflow detection data, obtains a first analysis result, determines the target cleaning control parameter of the cleaning machine based on the first analysis result, and controls the cleaning of the cleaning machine based on the target cleaning control parameter. The cleaning control parameter is dynamically determined based on the result of the garbage particle analysis, so that the cleaning of the cleaning machine matches the cleaning required for the garbage on the ground, thereby ensuring the cleanliness of the ground.

[0199] It should be noted that the above functions or steps that can be implemented by the computer-readable storage medium or computer device can refer to the relevant descriptions on the server side and the client side in the aforementioned method embodiment. To avoid repetition, they will not be described one by one here.

[0200] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing related 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 memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct RAMbus dynamic RAM (DRDRAM), and RAMbus dynamic RAM (RDRAM), etc.

[0201] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0202] The embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. A cleaning machine control method based on garbage detection, characterized in that: The method comprises: Acquire first airflow detection data in real time, where the first airflow detection data is detection data of the airflow entering the dust box of the cleaning machine; Performing garbage particle analysis according to the first airflow detection data to obtain a first analysis result; Determining target cleaning control parameters of the cleaning machine according to the first analysis result; The cleaning machine is controlled to clean according to the target cleaning control parameter.

2. The cleaning machine control method based on garbage detection according to claim 1 is characterized in that: The step of controlling the cleaning machine to clean according to the target cleaning control parameter comprises: Determining fan power data and roller brush motor parameters according to the target cleaning control parameters; The operation of the fan of the cleaning machine is controlled according to the fan power data, and the operation of the roller brush motor of the cleaning machine is controlled according to the roller brush motor parameters.

3. The cleaning machine control method based on garbage detection according to claim 1, characterized in that: The method further comprises: Acquire second airflow detection data, wherein the second airflow detection data is detection data of airflow passing through the filter of the cleaning machine, and the airflow passes through the dust box and enters the filter; Performing garbage particle analysis according to the second airflow detection data to obtain a second analysis result; Determine the filtering level according to the second analysis result; If the filtering level is within the first level range, a filter replacement reminder signal is generated and sent according to a first sending method.

4. The cleaning machine control method based on garbage detection according to claim 3 is characterized in that: The step of acquiring the second airflow detection data comprises: Obtaining a cleaning start signal of the cleaning machine; In response to the cleaning start signal, a first time period is waited after the generation time of the cleaning start signal to obtain the second airflow detection data.

5. The cleaning machine control method based on garbage detection according to claim 1, characterized in that: The method further comprises: Obtaining a preparation signal of the cleaning machine; In response to the preparation signal, acquiring each of the first analysis results as a data packet at a first time interval and a preset time window; Performing garbage particle trend prediction according to the data packet to obtain a trend prediction result; Determining cleaning control parameter compensation data according to the trend prediction result; The step of determining the target cleaning control parameter of the cleaning machine according to the first analysis result comprises: Determining initial cleaning control parameters of the cleaning machine according to the first analysis result; The initial cleaning control parameters are corrected according to the cleaning control parameter compensation data to obtain the target cleaning control parameters of the cleaning machine.

6. The cleaning machine control method based on garbage detection according to claim 1, characterized in that: The method further comprises: Obtaining dirt detection data of the target area; Performing cleaning control parameter distribution prediction based on the dirt detection data to obtain distribution prediction data; The step of controlling the cleaning machine to clean according to the target cleaning control parameter comprises: According to the distribution prediction data, the target cleaning control parameter is adjusted to obtain an adjusted cleaning control parameter; According to the adjusted cleaning control parameters, the cleaning machine is controlled to clean the target area.

7. The cleaning machine control method based on garbage detection according to claim 6 is characterized in that: In the process of controlling the cleaning machine to clean the target area according to the adjusted cleaning control parameters, the method further includes: Predicting garbage particle data of the airflow entering the dust box according to the dirt detection data to obtain first data; Acquire the first analysis result corresponding to the target area as second data; Determine the cleaning level of the roller brush according to the first data and the second data; If the roller brush cleaning level is within the second level range, a roller brush replacement reminder signal is generated and sent according to a second sending method.

8. A cleaning machine control device based on garbage detection, characterized in that: The device comprises: A real-time data acquisition module, used for acquiring first airflow detection data in real time, wherein the first airflow detection data is detection data of the airflow entering the dust box of the cleaning machine; An analysis module, configured to perform garbage particle analysis based on the first airflow detection data to obtain a first analysis result; a cleaning control parameter determination module, configured to determine a target cleaning control parameter of the cleaning machine according to the first analysis result; The cleaning control module is used to control the cleaning machine to clean according to the target cleaning control parameter.

9. A cleaning machine, characterized in that: The cleaning machine includes a first detector, a cleaning component, a memory, a processor, and a computer program stored in the memory and executable on the processor. The first detector is used to detect the airflow entering the dust box of the cleaning machine. The processor is electrically connected to the first detector and the cleaning component. When the processor executes the computer program, the steps of the cleaning machine control method based on garbage detection as described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the cleaning machine control method based on garbage detection as claimed in any one of claims 1 to 7 are implemented.

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