WO2022179237A1 - 拖擦组件清洁程度检测方法、检测电路及相关设备 - Google Patents

拖擦组件清洁程度检测方法、检测电路及相关设备 Download PDF

Info

Publication number
WO2022179237A1
WO2022179237A1 PCT/CN2021/135579 CN2021135579W WO2022179237A1 WO 2022179237 A1 WO2022179237 A1 WO 2022179237A1 CN 2021135579 W CN2021135579 W CN 2021135579W WO 2022179237 A1 WO2022179237 A1 WO 2022179237A1
Authority
WO
WIPO (PCT)
Prior art keywords
sewage
base station
cleanliness
cleaning
detection
Prior art date
Application number
PCT/CN2021/135579
Other languages
English (en)
French (fr)
Inventor
袁健
Original Assignee
深圳市银星智能科技股份有限公司
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 深圳市银星智能科技股份有限公司 filed Critical 深圳市银星智能科技股份有限公司
Publication of WO2022179237A1 publication Critical patent/WO2022179237A1/zh

Links

Images

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume, or surface-area of porous materials
    • G01N15/06—Investigating concentration of particle suspensions
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84—Systems specially adapted for particular applications
    • G01N21/88—Investigating the presence of flaws or contamination
    • G01N21/94—Investigating contamination, e.g. dust
    • G01N15/075—

Definitions

  • the present application relates to the field of smart home technology, and in particular, to a method for detecting the cleanliness of a mopping component, a detecting circuit and related equipment.
  • the base station can automatically clean the mopping components.
  • the base station of the existing cleaning robot only uses the same cleaning process to clean the mopping components. When it is high, cleaning water will be wasted; when the cleanliness of the mopping components is low, the mopping components will not be cleaned cleanly; some base stations of cleaning robots support different cleaning modes, but manual settings are required, and the intelligence is insufficient. Or because the method of judging the cleanliness of the cleaning components is inaccurate, it is easy to cause insufficient cleaning or over-cleaning of the cleaning components.
  • the main purpose of the present application is to solve the existing technical problems that the cleanliness detection of the cleaning components of the cleaning robot is not intelligent enough and the accuracy of the detection results is low.
  • a first aspect of the present application provides a method for detecting the cleanliness of a mopping component.
  • the method for detecting the cleanliness of a mopping component is applied to a base station, where the base station is used to clean a mopping component of a cleaning robot, and the base station includes sewage
  • the detection device, the method for detecting the cleanliness of the mopping component comprises:
  • the base station When the base station cleans the mopping component once and performs sewage pumping, the base station detects the sewage currently pumped by the sewage detection device arranged on the sewage passage of the base station, get test data;
  • the base station calculates the suspended particulate matter concentration of the currently pumped sewage according to the detection data
  • the base station determines the cleanliness of the currently pumped sewage according to the suspended particulate matter concentration.
  • the sewage detection device includes several optical components, and the optical components include a light emitting element and a light receiving element.
  • the base station detects the sewage currently pumped by the sewage detection device arranged on the sewage passage of the base station, and the obtained detection data includes:
  • the base station When the base station cleans the mopping assembly once and performs sewage pumping, the base station controls the light emitting element disposed on the sewage passage of the base station to emit light, and passes through the light emitting element disposed on the base station.
  • the light-receiving tube on the sewage passage performs light sampling at least twice to obtain detection data of the currently pumped sewage, wherein the detection data includes light reflection intensity or light absorption intensity.
  • the light emitting element and the light receiving element are disposed on one side of the sewage passage of the base station and form a set angle, or the light
  • the transmitting element and the light receiving element are arranged on different sides of the sewage passage of the base station and face oppositely.
  • the sewage detection device further includes: a sewage sampling pipe and a sewage sampling tank, wherein two ends of the sewage sampling pipe are respectively connected to the sewage passage. Connected to the sewage sampling tank, the light emitting element and the light receiving element are oppositely arranged on both sides of the sewage sampling tank.
  • the sewage detection device includes a photographing device, and when the base station cleans the mopping component once and performs sewage pumping, The base station detects the sewage currently pumped by the sewage detection device arranged on the sewage passage of the base station, and the obtained detection data includes:
  • the base station When the base station cleans the mopping component once and performs sewage pumping, the base station controls the photographing device disposed on the sewage passage of the base station to photograph the sewage in the sewage passage, The detection data of the currently pumped sewage is obtained, and the detection data includes a sewage image.
  • the calculation by the base station of the suspended particulate matter concentration of the currently pumped sewage according to the detection data includes:
  • the base station performs segmentation and recognition on the sewage image, and intercepts an effective image in the sewage image according to the segmentation and recognition result;
  • the base station performs particle feature point extraction on the effective image, obtains a plurality of particle feature points, and performs statistics on the number of particles and the area of the particles;
  • the base station calculates the amount of suspended particles in an equivalent unit area according to the number of particles and the area of particles obtained by statistics, and obtains the concentration of suspended particles in the currently pumped sewage.
  • calculating, by the base station according to the detection data, the suspended particulate matter concentration of the currently pumped sewage includes:
  • the base station performs analog-to-digital conversion on the light reflection intensity or light absorption intensity to obtain a corresponding light intensity value
  • the base station converts the light intensity value into the suspended particulate matter concentration of the currently pumped sewage according to a pre-replacement calculation formula.
  • the method further includes:
  • the base station determines whether the current cleaning robot meets the preset cleaning exit condition according to the cleanliness of the currently pumped sewage;
  • the base station sets the next round of cleaning strategy according to the cleanliness of the currently pumped sewage, and performs the next round of cleanliness detection on the cleaning robot, wherein the cleaning strategy includes: cleaning mode, At least one of sewage circulation speed and clean water circulation speed.
  • a second aspect of the present application provides a detection circuit, the detection circuit includes: a first detection circuit, a second detection circuit, and a voltage comparison circuit;
  • the first detection circuit includes a light-emitting diode and a first triode, the anode of the light-emitting diode is connected to the reference voltage, the cathode of the light-emitting diode is connected to the collector of the first triode, and the first triode The emitter of the tube is grounded, and the base of the first triode is connected to the microprocessor of the base station;
  • the second detection circuit includes a photosensitive element, one end of the photosensitive element is connected to the reference voltage, and the other end is grounded;
  • the voltage comparison circuit includes an operational amplifier and a second transistor, the inverting input terminal of the operational amplifier is connected to the photosensitive element in the second detection circuit, and the non-inverting input terminal of the operational amplifier is connected to the reference voltage , the output of the operational amplifier is connected to the base of the second triode, the collector of the second triode is connected to the microprocessor of the base station, and the emitter of the second triode is grounded ;
  • the light emitting diode and the photosensitive element are arranged on one side of the sewage passage of the base station and form a set angle, or the light emitting diode and the photosensitive element are arranged on different sides of the sewage passage of the base station and face opposite. .
  • a third aspect of the present application provides a base station, the base station is used for cleaning a mopping component of a cleaning robot, the base station includes a sewage detection device, and the base station further includes:
  • the detection module is used to detect the currently pumped sewage through the sewage detection device disposed on the sewage passage of the base station when the sewage is pumped after the first cleaning of the mopping component is completed, and the detection is obtained. data;
  • a calculation module configured to calculate the suspended particulate matter concentration of the currently pumped sewage according to the detection data
  • a determination module configured to determine the cleanliness of the currently pumped sewage according to the suspended particulate matter concentration.
  • the sewage detection device includes several optical components, the optical components include a light emitting element and a light receiving element, and the detection module is further configured to:
  • the light emitting element disposed on the sewage passage of the base station is controlled to emit light
  • the light emitting element disposed on the sewage passage of the base station is controlled to emit light.
  • the light-receiving tube performs at least two light samplings to obtain detection data of the currently pumped sewage, wherein the detection data includes light reflection intensity or light absorption intensity.
  • the light emitting element and the light receiving element are arranged on one side of the sewage passage of the base station and form a set angle, or the light
  • the transmitting element and the light receiving element are arranged on different sides of the sewage passage of the base station and face oppositely.
  • the sewage detection device further includes: a sewage sampling pipe and a sewage sampling tank, wherein two ends of the sewage sampling pipe are respectively connected to the sewage passage. Connected to the sewage sampling tank, the light emitting element and the light receiving element are oppositely arranged on both sides of the sewage sampling tank.
  • the sewage detection device includes a photographing device, and the detection module is further configured to:
  • the photographing device disposed on the sewage passage of the base station is controlled to photograph the sewage in the sewage passage, and the current pump is obtained. Detection data of sucked sewage, the detection data including sewage images.
  • the computing module includes:
  • an identification unit for segmenting and identifying the sewage image, and intercepting an effective image in the sewage image according to the segmentation and identification result
  • an extraction unit configured to perform particle feature point extraction on the effective image, obtain a plurality of particle feature points, and perform statistics on the number of particles and the area of the particles;
  • the calculation unit is used to calculate the amount of suspended particles in the equivalent unit area according to the number of particles and the area of particles obtained by statistics, and obtain the concentration of suspended particles in the currently pumped sewage.
  • the base station computing module further includes:
  • a conversion unit configured to perform analog-to-digital conversion on the light reflection intensity or light absorption intensity to obtain a corresponding light intensity value
  • the conversion unit is configured to convert the light intensity value into the suspended particulate matter concentration of the currently pumped sewage according to the pre-replacement calculation formula.
  • the base station further includes a cleaning control module, where the cleaning control module is configured to:
  • the cleaning strategy includes at least one of: cleaning mode, sewage circulation speed, and clean water circulation speed.
  • a fourth aspect of the present application provides a base station, comprising: a memory and at least one processor, where instructions are stored in the memory; the at least one processor invokes the instructions in the memory to cause the base station to execute The above-mentioned method for detecting the cleanliness of the mopping component.
  • a fifth aspect of the present application provides a computer-readable storage medium, where instructions are stored in the computer-readable storage medium, when the computer-readable storage medium runs on a computer, the computer executes the above-mentioned method for detecting the cleanliness of a mopping component.
  • a sewage detection device is arranged on the sewage passage of the base station.
  • the sewage detection device detects the concentration of suspended particles in the sewage, and uses the sewage to detect the concentration of suspended particles in the sewage.
  • the concentration of suspended particles is used to measure the cleanliness of the currently pumped sewage. In general, the higher the concentration of suspended particles in the sewage, the lower the cleanliness of the sewage. After the concentration of suspended particles in the sewage, the cleanliness of the sewage is detected, which is used for subsequent cleaning control of the mopping components, improving the cleaning efficiency of the mopping components, and reducing the waste of cleaning water.
  • FIG. 1 is a schematic diagram of an embodiment of a method for detecting the cleanliness of a mopping component in an embodiment of the present application
  • FIG. 2 is a schematic diagram of a first installation embodiment of the detection device in the embodiment of the application.
  • FIG. 3 is a schematic diagram of a second installation embodiment of the detection device in the embodiment of the application.
  • FIG. 4 is a schematic diagram of a third installation embodiment of the detection device in the embodiment of the application.
  • FIG. 5 is a schematic diagram of an embodiment of a detection circuit in an embodiment of the present application.
  • FIG. 6 is a schematic diagram of a circuit design of a preferred embodiment of the detection circuit in the embodiment of the present application.
  • FIG. 7 is a schematic diagram of a modular embodiment of a base station in an embodiment of the present application.
  • FIG. 8 is a schematic diagram of another modular embodiment of a base station in an embodiment of the present application.
  • FIG. 9 is a schematic diagram of an embodiment of a hardware device of a base station in an embodiment of the present application.
  • Embodiments of the present application provide a method for detecting the cleanliness of a mopping assembly and related equipment, including: when the base station performs sewage pumping after cleaning the mopping assembly once, the base station passes through a sewage path disposed on the base station.
  • the sewage detection device detects the currently pumped sewage to obtain the detection data; the base station calculates the suspended particulate matter concentration of the currently pumped sewage according to the detection data; the base station determines the cleanliness of the currently pumped sewage according to the suspended particulate matter concentration.
  • the present application realizes the detection of the cleanliness of sewage, so as to determine the cleanliness of the mopping components, so as to improve the cleaning efficiency of the mopping components and save water.
  • the first embodiment of the method for detecting the cleanliness of the mopping component in the embodiment of the present application includes:
  • the base station cleans the mopping component once and performs sewage pumping
  • the base station performs the sewage pumping operation on the sewage currently pumped through the sewage detection device arranged on the sewage passage of the base station. Detect, get the detection data;
  • the base station can use the preset detection method through the sewage detection device installed on the sewage channel. Detect the cleaned sewage, such as an optical detection method, an image detection method, etc., wherein the sewage detection device may include several optical components, or a photographing device, that is, for example, the sewage is detected by an optical component, or a photographing device is used to detect the sewage. Detection, corresponding to the detection data of light intensity data and sewage images.
  • the cleaning degree detection method of the mopping component of the cleaning robot is as follows:
  • the base station When the base station cleans the mopping assembly once and performs sewage pumping, the base station controls the light emitting element disposed on the sewage passage of the base station to emit light, and passes through the light emitting element disposed on the base station.
  • the light-receiving tube on the sewage passage performs optical sampling at least twice to obtain detection data of the currently pumped sewage, wherein the detection data includes light reflection intensity or light absorption intensity;
  • the sewage detection device includes several optical components, and the optical components include a light emitting element and a light receiving element.
  • the base station uses the reflection or transmission of suspended particles in the sewage to emit light through the light-emitting element.
  • the concentration of suspended particles in the sewage is large, the reflection of the light is enhanced, and the light intensity received by the light-receiving element is enhanced or transmitted.
  • the effect is weakened, the light intensity received by the light receiving element is weakened, and the intensity of the reflected light or refracted light is converted into an electrical signal, which is sent to the controller for processing. .
  • the light emitting element 202 and the light receiving element 203 are disposed on one side of the sewage passage 201 of the base station and form a set angle.
  • the reflection effect of light is used, and the concentration of suspended particles in the subsequent sewage is calculated by the reflection intensity of light received by the light receiving element.
  • the light emitting element 202 and the light receiving element 203 are disposed on different sides of the sewage passage 201 of the base station and face opposite.
  • the placement positions of the light-emitting element and the light-receiving element form a placement angle.
  • the reflection of light is mainly used to suspend the subsequent sewage by the reflection intensity of the light received by the light-receiving element.
  • Calculation of particle concentration when the placement angle is greater than 90°, the transmission of light is mainly used to calculate the concentration of suspended particles in subsequent sewage through the transmission intensity of light received by the light-receiving element.
  • the sewage detection device may further include: a sewage sampling pipe 204 and a sewage sampling tank 205 , wherein the two ends of the sewage sampling pipe 204 are respectively connected with the sewage passage 201 and the sewage The sampling tank 205 is connected, and the light-emitting element 202 and the light-receiving element 203 are oppositely arranged on both sides of the sewage sampling tank 205 .
  • the light-emitting element and the light-receiving element may be disposed on the upper and lower sides, the left and right sides, or the front and rear sides of the sewage sampling tank, which are not specifically limited here. Among them, the transmission effect of light is mainly used here, and what the light receiving element receives is the light transmission intensity.
  • sewage detection starts after the sewage sampling tank is filled with water, and during the sewage detection period, the sewage in the sewage passage is continuously introduced into the sewage sampling tank through the sewage sampling pipe, so that the total amount of sewage in the sewage sampling tank is reduced. It is full of sewage; and the sewage drainage pipe is installed on the upper side of the sewage sampling tank.
  • the sewage is introduced into the sewage sampling tank through the sewage sampling pipe, the original sewage in the sewage sampling tank is discharged from the sewage sampling tank through the sewage drainage pipe.
  • the cleaning degree detection method of the mopping component of the cleaning robot is as follows:
  • the base station When the base station cleans the mopping component once and performs sewage pumping, the base station controls the photographing device disposed on the sewage passage of the base station to photograph the sewage in the sewage passage, Obtain the detection data of the sewage currently pumped, and the detection data includes a sewage image;
  • the sewage image is taken by a photographing device, and the concentration of suspended particulate matter in the sewage is predicted by a statistical counting method, and the photographing device can be installed inside or outside the sewage passage.
  • the sewage image of a fixed area is mainly used to count the suspended particulate matter in the sewage, so as to predict the suspended particulate matter concentration of the sewage.
  • the base station calculates, according to the detection data, the suspended particulate matter concentration of the currently pumped sewage;
  • the detection data and the sewage can be collected according to the detection data.
  • the relationship between the concentration of suspended particulate matter, for different types of detection data, the concentration of suspended particulate matter in sewage is calculated in a corresponding way.
  • the higher the light refraction intensity of the sewage the smaller the light transmission intensity; for the collected detection data of the sewage image, when the characteristics of the suspended particles in the sewage image are The denser the dots, the higher the concentration of suspended particulate matter.
  • the suspended particulate matter concentration of sewage can be calculated in the following ways:
  • the base station performs analog-to-digital conversion on the light reflection intensity or light absorption intensity to obtain a corresponding light intensity value
  • the base station converts the light intensity value into the suspended particulate matter concentration of the currently pumped sewage according to the pre-replacement calculation formula.
  • the light reflection intensity or light absorption intensity received by the light receiving element is converted into an electrical signal of equivalent value, which is used as the light intensity value, and the electrical signal is sent to the controller in the base station.
  • the empirical light absorption coefficient can be calculated from the light reflection intensity or the light transmission intensity.
  • the suspended particle concentration of the sewage can be calculated in the following ways:
  • the base station performs segmentation and identification on the sewage image, and intercepts an effective image in the sewage image according to the segmentation and identification result;
  • the base station performs particle feature point extraction on the effective image to obtain a plurality of particle feature points, and performs statistics on the number of particles and the area of particles;
  • the base station calculates the amount of suspended particles in the equivalent unit area according to the number of particles and the area of the particles obtained by statistics, and obtains the concentration of suspended particles in the currently pumped sewage.
  • the effective image in the sewage image refers to the part of the sewage pipeline. If the calculation accuracy is to be further improved, the central part of the sewage pipeline can be selected as the effective image; after the part of the sewage pipeline is determined, the edge of the sewage pipeline can be intercepted. , obtain an effective image in the sewage image, or further extend a preset distance to the inside of the edge of the sewage pipe as the center edge of the pipe, and intercept through the center edge of the pipe to obtain an effective image in the sewage image.
  • the color difference between the particles and the water can be used to extract the feature points of the particles captured in the effective image obtained by intercepting. Convert it into a feature map, such as a color histogram, color matrix or color set, and then extract the particle feature points in the effective image through the feature map.
  • a feature map such as a color histogram, color matrix or color set
  • the number of particles is calculated through the feature points of particles extracted in the effective image, and the area of each particle is calculated separately.
  • the concentration of particles is relatively high, the particles will overlap, and the overlapping part will be automatically carried out according to the contour characteristics of the particles. Contour correction and quantity calculation, and further calculate the area of particles after contour correction.
  • the base station determines, according to the suspended particulate matter concentration, the cleanliness of the currently pumped sewage.
  • the concentration of suspended particulate matter there is an empirical coefficient K between the concentration of suspended particulate matter and the cleanliness of sewage
  • the cleanliness of the sewage can represent the cleanliness of the mopping components of the cleaning robot after cleaning. The lower the cleanliness of the mopping components, the lower the cleanliness of the sewage after cleaning the mopping components, and vice versa.
  • the base station judges whether the current cleaning robot meets the preset cleaning exit conditions according to the cleanliness of the currently pumped sewage;
  • the base station sets the next round of cleaning strategy according to the cleanliness of the currently pumped sewage, and performs the next round of cleanliness detection on the cleaning robot, wherein the cleaning strategy includes: cleaning At least one of mode, sewage circulation speed, and clean water circulation speed.
  • the cleaning exit condition can be preset, for example, the cleanliness threshold of the cleaning robot is set to a percentage value between 85% and 99%. If the cleanliness threshold is set to 95%, when the cleanliness of the current sewage is greater than When it is equal to or equal to 95%, it is determined that the current cleaning robot meets the cleaning exit conditions, and the base station can exit the cleaning of the cleaning robot without performing the next round of cleaning; if the current cleanliness of sewage is less than 95%, it is determined If the robot is still "dirty" and does not meet the cleaning exit conditions, the cleaning robot needs to be cleaned again, then the base station resets the cleaning strategy according to the cleanliness of the sewage to perform the next round of cleaning for the cleaning robot.
  • the cleaning mode, sewage circulation speed, and clean water circulation speed corresponding to the cleaning degree interval can be set, for example:
  • the cleaning degree is between (Ai, Ai+1], the cleaning mode Bi, the sewage circulating speed Ci and the sewage circulating speed Di are adopted.
  • a sewage detection device is provided on the sewage passage of the base station.
  • the sewage detection device detects the concentration of suspended particles in the sewage, and uses the suspended particles to detect the concentration of suspended particles in the sewage. Concentration to measure the cleanliness of the currently pumped sewage, wherein, under normal circumstances, the higher the concentration of suspended particles in the sewage, the lower the cleanliness of the sewage. After the concentration of suspended particles, the detection of the cleanliness of the sewage is realized, which is used for subsequent cleaning control of the mopping components, improving the cleaning efficiency of the mopping components, and reducing the waste of cleaning water.
  • the detection circuit in the embodiment of the present application includes: a first detection circuit 501, a second detection circuit a detection circuit 502 and a voltage comparison circuit 503;
  • the first detection circuit 501 includes a light-emitting diode 5011 and a first triode 5012, the anode of the light-emitting diode 5012 is connected to the reference voltage, the cathode of the light-emitting diode 5011 is connected to the collector of the first triode 5012, and the emission of the first triode 5012 is The pole is grounded, and the base of the first transistor 5012 is connected to the microprocessor of the base station;
  • the second detection circuit 502 includes a photosensitive element 5021, one end of the photosensitive element 5021 is connected to the reference voltage, and the other end is grounded;
  • the voltage comparison circuit 503 includes an operational amplifier 5031 and a second transistor 5032.
  • the inverting input terminal of the operational amplifier 5031 is connected to the photosensitive element 5021 in the second detection circuit, and the non-inverting input terminal of the operational amplifier 5031 is connected to the reference voltage.
  • the operational amplifier 5031 The output is connected to the base of the second triode 5032, the collector of the second triode 5032 is connected to the microprocessor of the base station, and the emitter of the second triode 5032 is grounded;
  • the light emitting diode 5011 and the photosensitive element 5021 are arranged on one side of the sewage passage of the base station and form a set angle, or the light emitting diode 5011 and the photosensitive element 5021 are arranged on different sides of the sewage passage of the base station and face opposite.
  • the first detection circuit 501 is used to: when performing sewage pumping, receive a detection signal sent by a microprocessor (Microcontroller Unit, MCU, hereinafter referred to as MCU), if the voltage of the detection signal is greater than the preset first voltage threshold, the first transistor 5012 is turned on and the light-emitting diode 5011 is energized to emit light; when the voltage of the detection signal is greater than the first voltage threshold, the first transistor 5012 is turned on, forming a loop with the grounded emitter, so that The light emitting diode 5011 is energized and emits light. When the voltage of the detection signal is less than the first voltage threshold, the first transistor 5012 is not turned on, and the light emitting diode 5011 is not energized and does not emit light.
  • MCU Microcontroller Unit
  • the second detection circuit 502 is used for: when the light-emitting diode 5011 is powered on and emits light, the photosensitive element 5021 changes the resistance value according to the change of the received light intensity, and causes the voltage input to the inverting input terminal of the operational amplifier 5031 to correspondingly generate Variation; among them, the photosensitive element can include all light-sensitive electronic elements such as photoresistor, phototransistor, etc.
  • the voltage comparison circuit 503 is used for: comparing the voltage difference between the non-inverting input terminal and the inverting input terminal of the operational amplifier 5031, and making the second transistor 5032 conduct or non-conducting according to the voltage difference, wherein , when the second transistor 5032 is turned on, if the output voltage of the operational amplifier 5031 is greater than the preset second voltage threshold, the MCU performs cleaning control on the cleaning robot.
  • a complete detection circuit is formed by the first detection circuit, the second detection circuit and the voltage comparison circuit.
  • the first triode of the first detection circuit is turned on, and the light-emitting diode is controlled to emit light.
  • the photosensitive element of the second detection circuit receives the light intensity after the light transmits through the sewage, obtains the corresponding resistance value, measures the concentration of suspended particles in the sewage according to the resistance value, and finally outputs the corresponding voltage value; the voltage comparison circuit passes through the second detection circuit. The input voltage value is compared with the reference voltage value.
  • the cleanliness of the mopping component is high enough, and the second diode is turned on, so that the MCU exits the cleaning of the cleaning robot.
  • the difference is negative, the cleaning degree of the mopping component is not high enough, and the second diode is not conducting, so that the MCU controls the cleaning robot to perform the next round of cleaning, realizes the detection of the cleaning degree of the cleaning robot, and realizes the cleaning robot. cleaning control.
  • FIG. 6 A schematic diagram of circuit design of a preferred embodiment of the detection circuit is shown in FIG. 6 .
  • An IO (Input/Output, input/output) port of the MCU is connected to the transistor Q1 through the base resistor R1, the bias resistor R2 is connected to the transistor Q1 to ground, and the collector of the transistor Q1 is connected to the resistor R3 and the light-emitting diode D1, and is connected to the reference.
  • Voltage Volt Current Condenser, VCC, hereinafter referred to as VCC
  • VCC Voltage
  • the other end of the resistor R5 is connected in series with the photoresistor R4, one end of the photoresistor R4 is grounded, and the other end is connected to the inverting input end of the operational amplifier OA, which finally constitutes a second detection circuit.
  • the non-inverting input terminal of operational amplifier OA is connected to VCC through resistor R6, and is connected to ground through resistor R7.
  • the output terminal of operational amplifier OA is connected to transistor Q2 in series with resistor R8, and the collector of transistor Q2 is connected to another IO port of MCU.
  • the bias resistor R9 is connected to ground, which ultimately constitutes the op amp.
  • the base station when the base station cleans the mopping component once, it will pump sewage, and the MCU sends a voltage detection signal higher than the preset voltage threshold, so that the transistor Q1 is turned on, the bias resistor R2, the resistor R3 and the luminous
  • the diode D1 is connected to the ground in series to form a loop, and the light-emitting diode D1 emits light; the light is projected onto the photoresistor R4 through the sewage.
  • the voltage output from the photoresistor R4 to the operational amplifier OA is reduced, indicating that the concentration of suspended particles in the sewage is lower.
  • the light intensity projected to the photoresistor R4 is the largest.
  • the photoresistor R4 and the resistor R5 are divided, and a voltage value V - is input to the inverting input terminal of the operational amplifier OA:
  • a reference voltage V + is input to the non-inverting input of the operational amplifier OA:
  • the reference voltage V + can be set by developers according to experience, indicating the preset cleaning exit condition.
  • V + is compared with V - . If V + is less than V - , the operational amplifier OA outputs a low level, the transistor Q2 is not conducting, and the other IO port of the MCU outputs a high voltage. The resulting effect needs to be set by the base station.
  • the cleaning strategy continues to clean the cleaning robot; if V + is greater than V - , the operational amplifier OA outputs a high level, the transistor Q2 is turned on, and the other IO port of the MCU outputs a low voltage. The effect is that the base station exits the cleaning robot. cleaning.
  • the transistor Q1 is turned on when pumping sewage, so as to control the light-emitting diode D1 to emit light; the photoresistor R4 receives the light after the light-emitting diode D1 emits light and transmits the sewage to obtain the corresponding resistance value to measure the amount of water in the sewage.
  • the concentration of suspended particulate matter is adjusted, and the voltage value of the reverse input terminal of the input operational amplifier OA is adjusted; the voltage value input by the operational amplifier OA through the photoresistor R4 is compared with the reference voltage value of the input terminal in the same direction.
  • the cleanliness of the mopping component is high enough, and the diode Q2 is turned on, so that the MCU quits cleaning the cleaning robot.
  • the output terminal of the operational amplifier OA outputs a negative value, the cleanliness of the mopping component is not high enough, and the diode Q2 is not conductive, making the The MCU controls the cleaning robot to perform the next round of cleaning, realizes the detection of the cleaning degree of the cleaning robot, and realizes the cleaning control of the cleaning robot.
  • An embodiment of the base station in the embodiment of the present application includes:
  • the detection module 701 is used to detect the currently pumped sewage through the sewage detection device arranged on the sewage passage of the base station when the sewage is pumped after the first cleaning of the mopping component is completed, and obtain Test data;
  • a calculation module 702 configured to calculate the suspended particulate matter concentration of the currently pumped sewage according to the detection data
  • a determination module 703 is configured to determine the cleanliness of the currently pumped sewage according to the suspended particulate matter concentration.
  • a sewage detection device is provided on the sewage passage of the base station.
  • the sewage detection device detects the concentration of suspended particles in the sewage, and uses the suspended particles to detect the concentration of suspended particles in the sewage.
  • the concentration is used to measure the cleanliness of the currently pumped sewage. Generally, the higher the concentration of suspended particles in the sewage, the lower the cleanliness of the sewage. After the concentration of suspended particles, the detection of the cleanliness of the sewage is realized, which is used for subsequent cleaning control of the mopping components, improving the cleaning efficiency of the mopping components, and reducing the waste of cleaning water.
  • another embodiment of the base station in the embodiment of the present application includes:
  • the detection module 701 is used to detect the currently pumped sewage through the sewage detection device arranged on the sewage passage of the base station when the sewage is pumped after the first cleaning of the mopping component is completed, and obtain Test data;
  • a calculation module 702 configured to calculate the suspended particulate matter concentration of the currently pumped sewage according to the detection data
  • a determination module 703 is configured to determine the cleanliness of the currently pumped sewage according to the suspended particulate matter concentration.
  • the sewage detection device includes several optical components, and the optical components include a light emitting element and a light receiving element, and the detection module 701 is further used for:
  • the light emitting element disposed on the sewage passage of the base station is controlled to emit light
  • the light emitting element disposed on the sewage passage of the base station is controlled to emit light.
  • the light-receiving tube performs at least two light samplings to obtain detection data of the currently pumped sewage, wherein the detection data includes light reflection intensity or light absorption intensity.
  • the light emitting element and the light receiving element are arranged on one side of the sewage passage of the base station and form a set angle, or the light emitting element and the light receiving element are arranged in the sewage of the base station. Different sides of the passageway and facing opposite.
  • the sewage detection device further includes: a sewage sampling pipe and a sewage sampling tank, wherein two ends of the sewage sampling pipe are respectively connected to the sewage passage and the sewage sampling tank, and the light emitting element is connected to the sewage sampling tank.
  • the light-receiving elements are oppositely arranged on both sides of the sewage sampling tank.
  • the sewage detection device includes a photographing device, and the detection module 701 is further used for:
  • the photographing device disposed on the sewage passage of the base station is controlled to photograph the sewage in the sewage passage, and the current pump is obtained. Detection data of sucked sewage, the detection data including sewage images.
  • the computing module 702 includes:
  • the identification unit 7021 is used for segmenting and identifying the sewage image, and intercepting valid images in the sewage image according to the segmentation and identification result;
  • An extraction unit 7022 configured to extract feature points of particles from the effective image, obtain a plurality of feature points of particles, and perform statistics on the number of particles and the area of particles;
  • the calculation unit 7023 is configured to calculate the number of suspended particles in the equivalent unit area according to the number of particles and the area of the particles obtained by statistics, and obtain the concentration of suspended particles of the currently pumped sewage.
  • the base station computing module 702 further includes:
  • a conversion unit 7024 configured to perform analog-to-digital conversion on the light reflection intensity or light absorption intensity to obtain a corresponding light intensity value
  • the conversion unit 7025 is configured to convert the light intensity value into the suspended particulate matter concentration of the currently pumped sewage according to a pre-replacement calculation formula.
  • the base station further includes a cleaning control module 704, and the cleaning control module 704 is used for:
  • the cleaning strategy includes at least one of: cleaning mode, sewage circulation speed, and clean water circulation speed.
  • a sewage detection device is provided on the sewage passage of the base station.
  • the sewage detection device detects the concentration of suspended particles in the sewage, and uses the suspended particles to detect the concentration of suspended particles in the sewage. Concentration to measure the cleanliness of the currently pumped sewage, wherein, under normal circumstances, the higher the concentration of suspended particles in the sewage, the lower the cleanliness of the sewage. After the concentration of suspended particles, the detection of the cleanliness of the sewage is realized, which is used for subsequent cleaning control of the mopping components, improving the cleaning efficiency of the mopping components, and reducing the waste of cleaning water.
  • FIG. 9 is a schematic structural diagram of a base station provided by an embodiment of the present application.
  • the base station 900 may vary greatly due to different configurations or performance, and may include one or more processors (central processing units, CPU) 910 (for example, , one or more processors) and memory 920, one or more storage media 930 (eg, one or more mass storage devices) that store applications 933 or data 932.
  • the memory 920 and the storage medium 930 may be short-term storage or persistent storage.
  • the program stored in the storage medium 930 may include one or more modules (not shown in the figure), and each module may include a series of instructions to operate in the base station 900 .
  • the processor 910 may be configured to communicate with the storage medium 930 to execute a series of instruction operations in the storage medium 930 on the base station 900 .
  • the base station 900 may also include one or more power supplies 940, one or more wired or wireless network interfaces 950, one or more input and output interfaces 960, and/or, one or more operating systems 931, such as Windows Server, Mac OS X, Unix, Linux, FreeBSD, and more.
  • operating systems 931 such as Windows Server, Mac OS X, Unix, Linux, FreeBSD, and more.
  • the present application further provides a base station, the base station includes a memory and a processor, the memory stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, causes the processor to perform the dragging in the foregoing embodiments The steps of the component cleanliness detection method.
  • the present application also provides a computer-readable storage medium.
  • the computer-readable storage medium may be a non-volatile computer-readable storage medium.
  • the computer-readable storage medium may also be a volatile computer-readable storage medium.
  • the computer-readable storage medium stores instructions that, when executed on a computer, cause the computer to execute the steps of the method for detecting the degree of cleanliness of the mopping component.
  • the integrated unit if implemented in the form of a software functional unit and sold or used as an independent product, may be stored in a computer-readable storage medium.
  • the technical solutions of the present application can be embodied in the form of software products in essence, or the parts that contribute to the prior art, or all or part of the technical solutions, and the computer software products are stored in a storage medium , including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present application.
  • the aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), magnetic disk or optical disk and other media that can store program codes .

Abstract

本申请涉及智能家居技术领域，公开了一种拖擦组件清洁程度检测方法、检测电路及相关设备，该方法应用于基站（900），该基站（900）用于对清洁机器人的拖擦组件进行清洁，该基站（900）包括污水检测装置。其中，该方法包括：当基站（900）对拖擦组件一次清洁完成之后，进行污水泵吸时，基站（900）通过设置在基站的污水通路（201）上的污水检测装置，对当前泵吸的污水进行检测，得到检测数据；基站（900）根据检测数据，计算当前泵吸的污水的悬浮颗粒物浓度；基站（900）根据悬浮颗粒物浓度，确定当前泵吸的污水的洁净程度。本申请实现了对污水洁净程度的检测，以判别拖擦组件的洁净程度，达到提升拖擦组件的清洁效率，并节约用水。

Description

拖擦组件清洁程度检测方法、检测电路及相关设备
本申请要求2021年2月25日向中国国家知识产权局递交的申请号为202110210483.8，申请名称为“拖擦组件清洁程度检测方法、检测电路及相关设备”的在先申请的优先权，上述在先申请的内容以引入的方式并入本文本中。
技术领域
本申请涉及智能家居技术领域，尤其涉及一种拖擦组件清洁程度检测方法、检测电路及相关设备。
背景技术
随着清洁机器人的日渐普及和技术研发发展，要求基站可以对拖擦组件自动进行清洗，而现有清洁机器人的基站对拖擦组件的清洗仅采用同一种清洗流程，在拖擦组件洁净程度较高时，会造成清洁用水浪费；而在拖擦组件洁净程度较低时，会使得拖擦组件清洗不干净；部分清洁机器人的基站支持采用不同的清洁模式，但需要人工设置，智能化不足，或者由于清洁组件洁净程度的判断方式不准确，容易导致对清洁组件的清洁存在不足或者过清洗情况。
申请内容
本申请的主要目的在于解决现有对清洁机器人清洁组件的洁净程度检测不够智能化且检测结果准确度较低的技术问题。
本申请第一方面提供了一种拖擦组件清洁程度检测方法，所述拖擦组件清洁程度检测方法应用于基站，所述基站用于对清洁机器人的拖擦组件进行清洁，所述基站包括污水检测装置，所述拖擦组件清洁程度检测方法包括：
当所述基站对所述拖擦组件一次清洁完成之后，进行污水泵吸时，所述基站通过设置在所述基站的污水通路上的所述污水检测装置，对当前泵吸的污水进行检测，得到检测数据；
所述基站根据所述检测数据，计算当前泵吸的污水的悬浮颗粒物浓度；
所述基站根据所述悬浮颗粒物浓度，确定当前泵吸的污水的洁净程度。
可选的，在本申请第一方面的第一种实现方式中，所述污水检测装置包括若干光学组件，所述光学组件包含光发射元件和光接收元件，所述当所述基站对所述拖擦组件一次清洁完成之后，进行污水泵吸时，所述基站通过设置在所述基站的污水通路上的所述污水检测装置，对当前泵吸的污水进行检测，得到检测数据包括：
当所述基站对所述拖擦组件一次清洁完成之后，进行污水泵吸时，所述基站控制设置在所述基站的污水通路上的所述光发射元件发光，并通过设置在所述基站的污水通路上的所述光接收管进行至少两次光采样，得到当前泵 吸的污水的检测数据，其中，所述检测数据包括光反射强度或光吸收强度。
可选的，在本申请第一方面的第二种实现方式中，所述光发射元件和所述光接收元件设置于所述基站的污水通路的一侧且形成设定角度，或所述光发射元件和所述光接收元件设置于所述基站的污水通路的不同侧且朝向相对。
可选的，在本申请第一方面的第三种实现方式中，所述污水检测装置还包括：污水采样管和污水采样槽，其中，所述污水采样管的两端分别与所述污水通路和所述污水采样槽连接，所述光发射元件和所述光接收元件相对设置在所述污水采样槽的两侧。
可选的，在本申请第一方面的第四种实现方式中，所述污水检测装置包括拍摄装置，所述当所述基站对所述拖擦组件一次清洁完成之后，进行污水泵吸时，所述基站通过设置在所述基站的污水通路上的所述污水检测装置，对当前泵吸的污水进行检测，得到检测数据包括：
当所述基站对所述拖擦组件一次清洁完成之后，进行污水泵吸时，所述基站控制设置在所述基站的污水通路上的所述拍摄装置对所述污水通路中的污水进行拍摄，得到当前泵吸的污水的检测数据，所述检测数据包括污水图像。
可选的，在本申请第一方面的第五种实现方式中，所述基站根据所述检测数据，计算当前泵吸的污水的悬浮颗粒物浓度包括：
所述基站对所述污水图像进行分割识别，并根据分割识别结果，截取所述污水图像中的有效图像；
所述基站对所述有效图像进行颗粒物特征点提取，得到多个颗粒物特征点，并进行颗粒物数量和颗粒物面积统计；
所述基站根据统计得到的颗粒物数量和颗粒物面积，计算等效单位面积内悬浮颗粒物数量，得到当前泵吸的污水的悬浮颗粒物浓度。
可选的，在本申请第一方面的第六种实现方式中，所述基站根据所述检测数据，计算当前泵吸的污水的悬浮颗粒物浓度包括：
所述基站对所述光反射强度或光吸收强度进行模数转换，得到对应的光强度值；
所述基站根据预置换算公式，将所述光强度值换算为当前泵吸的污水的悬浮颗粒物浓度。
可选的，在本申请第一方面的第七种实现方式中，在所述基站根据所述悬浮颗粒物浓度，确定当前泵吸的污水的洁净程度之后，还包括：
所述基站根据当前泵吸的污水的洁净程度，判断当前清洁机器人是否满足预置清洁退出条件；
若满足，则所述基站退出清洁；
若不满足，则所述基站根据当前泵吸的污水的洁净程度，设置下一轮清洗策略，并对所述清洁机器人进行下一轮清洁程度检测，其中，所述清洁策略包括：清洁模式、污水循环速度、清水循环速度中的至少一项。
本申请第二方面提供了一种检测电路，所述检测电路包括：第一检测电路、第二检测电路和电压比较电路；
所述第一检测电路包括发光二极管、第一三极管，所述发光二极管的阳极连接基准电压，所述发光二极管的阴极连接所述第一三极管的集电极，所述第一三极管的发射极接地，所述第一三极管的基极连接所述基站的微处理器；
所述第二检测电路包括光敏元件，所述光敏元件一端连接所述基准电压，另一端接地；
所述电压比较电路包括运算放大器、第二三极管，所述运算放大器的反相输入端与所述第二检测电路中光敏元件相连，所述运算放大器的同相输入端与所述基准电压相连，所述运算放大器的输出与所述第二三极管的基极相连，所述第二三极管的集电极连接所述基站的微处理器，所述第二三极管的发射极接地；
所述发光二极管与所述光敏元件设置于所述基站的污水通路的一侧且形成设定角度，或所述发光二极管与所述光敏元件设置于所述基站的污水通路的不同侧且朝向相对。
本申请第三方面提供了一种基站，所述基站用于对清洁机器人的拖擦组件进行清洁，所述基站包括污水检测装置，所述基站还包括：
检测模块，用于当对所述拖擦组件一次清洁完成之后，进行污水泵吸时，通过设置在所述基站的污水通路上的所述污水检测装置对当前泵吸的污水进行检测，得到检测数据；
计算模块，用于根据所述检测数据，计算当前泵吸的污水的悬浮颗粒物浓度；
确定模块，用于根据所述悬浮颗粒物浓度，确定当前泵吸的污水的洁净程度。
可选的，在本申请第三方面的第一种实现方式中，所述污水检测装置包括若干光学组件，所述光学组件包含光发射元件和光接收元件，所述检测模块还用于：
当所述基站对所述拖擦组件一次清洁完成之后，进行污水泵吸时，控制设置在所述基站的污水通路上的所述光发射元件发光，并通过设置在所述基站的污水通路上的所述光接收管进行至少两次光采样，得到当前泵吸的污水 的检测数据，其中，所述检测数据包括光反射强度或光吸收强度。
可选的，在本申请第三方面的第二种实现方式中，所述光发射元件和所述光接收元件设置于所述基站的污水通路的一侧且形成设定角度，或所述光发射元件和所述光接收元件设置于所述基站的污水通路的不同侧且朝向相对。
可选的，在本申请第三方面的第三种实现方式中，所述污水检测装置还包括：污水采样管和污水采样槽，其中，所述污水采样管的两端分别与所述污水通路和所述污水采样槽连接，所述光发射元件和所述光接收元件相对设置在所述污水采样槽的两侧。
可选的，在本申请第三方面的第四种实现方式中，所述污水检测装置包括拍摄装置，所述检测模块还用于：
当所述基站对所述拖擦组件一次清洁完成之后，进行污水泵吸时，控制设置在所述基站的污水通路上的所述拍摄装置对所述污水通路中的污水进行拍摄，得到当前泵吸的污水的检测数据，所述检测数据包括污水图像。
可选的，在本申请第三方面的第五种实现方式中，所述计算模块包括：
识别单元，用于对所述污水图像进行分割识别，并根据分割识别结果，截取所述污水图像中的有效图像；
提取单元，用于对所述有效图像进行颗粒物特征点提取，得到多个颗粒物特征点，并进行颗粒物数量和颗粒物面积统计；
计算单元，用于根据统计得到的颗粒物数量和颗粒物面积，计算等效单位面积内悬浮颗粒物数量，得到当前泵吸的污水的悬浮颗粒物浓度。
可选的，在本申请第三方面的第六种实现方式中，所述基站计算模块还包括：
转换单元，用于对所述光反射强度或光吸收强度进行模数转换，得到对应的光强度值；
换算单元，用于根据预置换算公式，将所述光强度值换算为当前泵吸的污水的悬浮颗粒物浓度。
可选的，在本申请第三方面的第七种实现方式中，所述基站还包括清洁控制模块，所述清洁控制模块用于：
根据当前泵吸的污水的洁净程度，判断当前清洁机器人是否满足预置清洁退出条件；若满足，则退出清洁；若不满足，则根据当前泵吸的污水的洁净程度，设置下一轮清洗策略，并对所述清洁机器人进行下一轮清洁程度检测，其中，所述清洁策略包括：清洁模式、污水循环速度、清水循环速度中的至少一项。
本申请第四方面提供了一种基站，包括：存储器和至少一个处理器，所 述存储器中存储有指令；所述至少一个处理器调用所述存储器中的所述指令，以使得所述基站执行上述的拖擦组件清洁程度检测方法。
本申请的第五方面提供了一种计算机可读存储介质，所述计算机可读存储介质中存储有指令，当其在计算机上运行时，使得计算机执行上述的拖擦组件清洁程度检测方法。
本申请提供的技术方案中，基站的污水通路上设置有污水检测装置，当基站对拖擦组件完成一次清洁后，进行污水泵吸时，通过污水检测装置检测污水中的悬浮颗粒浓度，并以悬浮颗粒浓度来衡量当前泵吸的污水的洁净程度，其中，通常情况下，当污水中的悬浮颗粒浓度越高，则污水的洁净程度越低，故本申请实施例在通过污水检测装置检测到污水的悬浮颗粒浓度后，实现了对污水洁净程度的检测，以用于后续对拖擦组件进行清洁控制，提升拖擦组件的清洁效率，降低清洁用水的浪费。
附图说明
图1为本申请实施例中拖擦组件清洁程度检测方法的一个实施例示意图；
图2为本申请实施例中检测装置的第一个安装实施例示意图；
图3为本申请实施例中检测装置的第二个安装实施例示意图；
图4为本申请实施例中检测装置的第三个安装实施例示意图；
图5为本申请实施例中检测电路的一个实施例示意图；
图6为本申请实施例中检测电路的一个较佳实施例电路设计示意图；
图7为本申请实施例中基站的一个模块化实施例示意图；
图8为本申请实施例中基站的另一个模块化实施例示意图；
图9为本申请实施例中基站的一个硬件设备实施例示意图。
具体实施方式
本申请实施例提供了一种拖擦组件清洁程度检测方法及相关设备，包括：当基站对拖擦组件一次清洁完成之后，进行污水泵吸时，基站通过设置在所述基站的污水通路上的污水检测装置，对当前泵吸的污水进行检测，得到检测数据；基站根据检测数据，计算当前泵吸的污水的悬浮颗粒物浓度；基站根据悬浮颗粒物浓度，确定当前泵吸的污水的洁净程度。本申请实现了对污水洁净程度的检测，以判别拖擦组件的洁净程度，达到提升拖擦组件的清洁效率，并节约用水。
本申请的说明书和权利要求书及上述附图中的术语“第一”、“第二”、“第三”、“第四”等(如果存在)是用于区别类似的对象，而不必用于描述特定的顺序或先后次序。应该理解这样使用的数据在适当情况下可以互换，以便这里描述的实施例能够以除了在这里图示或描述的内容以外的顺序实施。此外，术语“包括”或“具有”及其任何变形，意图在于覆盖不排他的包含，例如，包含 了一系列步骤或单元的过程、方法、系统、产品或设备不必限于清楚地列出的那些步骤或单元，而是可包括没有清楚地列出的或对于这些过程、方法、产品或设备固有的其它步骤或单元。
为便于理解，下面对本申请实施例的具体流程进行描述，请参阅图1，本申请实施例中拖擦组件清洁程度检测方法的第一个实施例包括：
101、当所述基站对所述拖擦组件一次清洁完成之后，进行污水泵吸时，所述基站通过设置在所述基站的污水通路上的所述污水检测装置，对当前泵吸的污水进行检测，得到检测数据；
本实施例中，基站在完成一次拖擦组件的清洗后，粘附在拖擦组件上的污渍会被洗脱至污水之中，故可以通过检测污水的洁净程度来间接衡量拖擦组件的洁净程度。在每次完成拖擦组件的依次清洗后，污水均会通过污水通道泵吸至污水箱中，在泵吸过程中，基站可以通过安装在污水通路上的污水检测装置，采用预先设置的检测方法对清洁后的污水进行检测，比如光学检测方法、图像检测方法等，其中，污水检测装置可以包括若干光学组件、或者拍摄装置，即比如通过光学组件对污水进行检测、或者通过拍摄装置对污水进行检测，对应得到光强度数据、污水图像的检测数据。
可选的，在一实施例中，当采用光学组件对污水进行检测时，清洁机器人的拖擦组件的清洁程度检测方式为：
当所述基站对所述拖擦组件一次清洁完成之后，进行污水泵吸时，所述基站控制设置在所述基站的污水通路上的所述光发射元件发光，并通过设置在所述基站的污水通路上的所述光接收管进行至少两次光采样，得到当前泵吸的污水的检测数据，其中，所述检测数据包括光反射强度或光吸收强度；
本实施例中，所述污水检测装置包括若干光学组件，所述光学组件包含光发射元件和光接收元件。基站利用污水中悬浮颗粒物对光线的反射作用或者透射作用，通过光发射元件发射光线，当污水悬浮颗粒物浓度较大时，对光线的反射作用增强，光接收元件接收到的光强度增强，或者透射作用减弱，光接收元件接收到的光强度减弱，并把反射光或者折射光的强度转换成电信号，发送给控制器处理，控制器通过对数据处理和运算进而换算得到污水中悬浮颗粒的浓度。
进一步的，如图2所示，所述光发射元件202和所述光接收元件203设置于所述基站的污水通路201的一侧且形成设定角度。
本实施例利用光线的反射作用，通过光接收元件接收到的光反射强度进行后续污水中悬浮颗粒的浓度计算。
进一步的，如图3所示，所述光发射元件202和所述光接收元件203设置于所述基站的污水通路201的不同侧且朝向相对。
本实施例中，光发射元件和光接收元件的放置位置形成一个放置角度， 当放置角度小于90°时，则主要利用光线的反射作用，通过光接收元件接收到的光反射强度进行后续污水的悬浮颗粒物浓度计算；当放置角度大于90°时，则主要利用光线的透射作用，通过光接收元件接收到的光透射强度进行后续污水的悬浮颗粒物浓度计算。
进一步的，如图4所示，所述污水检测装置还可以包括：污水采样管204和污水采样槽205，其中，所述污水采样管204的两端分别与所述污水通路201和所述污水采样槽205连接，所述光发射元件202和所述光接收元件203相对设置在所述污水采样槽205的两侧。
本实施例中，当污水通过污水通路时，污水的一部分通过污水采样管进入污水采样槽中，在污水采样槽中进行污水检测。光发射元件和光接收元件可相对设置在污水采样槽的上下侧、左右侧、或者前后侧均可，此处不作具体限定。其中，此处主要利用光线的透射作用，光接收元件接收到的是光透射强度。
另外，为降低污水检测的误差，污水采样槽内在充满水后开始进行污水检测，并且在污水检测期间，污水通路中的污水通过污水采样管不断引入污水采样槽内，使得污水采样槽内总是充满污水；而污水采样槽上侧安装有污水引流管，在污水通过污水采样管引入污水采样槽时，污水采样槽内原本的污水通过污水引流管排出污水采样槽。
可选的，在一实施例中，当采用拍摄装置对污水进行检测时，清洁机器人的拖擦组件的清洁程度检测方式为：
当所述基站对所述拖擦组件一次清洁完成之后，进行污水泵吸时，所述基站控制设置在所述基站的污水通路上的所述拍摄装置对所述污水通路中的污水进行拍摄，得到当前泵吸的污水的检测数据，所述检测数据包括污水图像；
本实施例中，通过拍摄装置拍摄污水图像，利用统计学计数方式预测污水中的悬浮颗粒物浓度，拍摄装置可以安装在污水通路的内侧或者外侧。此处主要利用采集固定面积的污水图像，用于后续对污水中的悬浮颗粒物进行计数，以此预测污水的悬浮颗粒物浓度。
102、所述基站根据所述检测数据，计算当前泵吸的污水的悬浮颗粒物浓度；
本实施例中，在采集到污水对应的检测数据后，包括采用光学组件采集到的污水的光折射强度、光吸收强度、和采用拍摄装置采集到的污水图像，则可以根据检测数据与污水中悬浮颗粒物浓度的关系，对不同检测数据的类型，采用对应的方式计算污水的悬浮颗粒物浓度，比如对于采集到的污水的光折射强度、光透射强度的检测数据，当污水中悬浮颗粒物浓度越高时，由于悬浮颗粒物会对光线产生折射，阻挡光线的透射，故此时污水的光折射强 度越大、光透射强度越小；对于采集到的污水图像的检测数据，当污水图像中的悬浮颗粒物特征点越密集，表示悬浮颗粒物浓度越高。
具体的，当检测数据为光折射强度或者光吸收强度时，可通过以下方式计算污水的悬浮颗粒物浓度：
1.1)所述基站对所述光反射强度或光吸收强度进行模数转换，得到对应的光强度值；
1.2)所述基站根据预置换算公式，将所述光强度值换算为当前泵吸的污水的悬浮颗粒物浓度。
本实施例中，将光接收元件接收到的光反射强度或者光吸收强度转化为等值的电信号，以作为光强度值，电信号发送给基站中的控制器，通过预先设置的换算公式，将光强度值换算成悬浮颗粒物浓度。具体可通过郎伯-比尔定律进行换算：a＝b*c，其中，a为吸光系数，单位是L/(g·cm)，b为污水通路厚度或者污水采样池的厚度单位为cm，c为污水悬浮颗粒物浓度。其中，可通过光反射强度或者光透射强度计算经验性的光吸收系数。
具体的，当检测数据为污水图像时，可通过以下方式计算污水的悬浮颗粒物浓度：
2.1)所述基站对所述污水图像进行分割识别，并根据分割识别结果，截取所述污水图像中的有效图像；
2.2)所述基站对所述有效图像进行颗粒物特征点提取，得到多个颗粒物特征点，并进行颗粒物数量和颗粒物面积统计；
2.3)所述基站根据统计得到的颗粒物数量和颗粒物面积，计算等效单位面积内悬浮颗粒物数量，得到当前泵吸的污水的悬浮颗粒物浓度。
本实施例中，污水图像中的有效图像指的是污水管道部分，若欲进一步提升计算精度，可选取污水管道的中心部分作为有效图像；在确定污水管道部分后，可通过污水管道边缘进行截取，得到污水图像中的有效图像，或者进一步向污水管道边缘内侧延伸预设距离作为管道中心边缘，并通过管道中心边缘进行截取，得到污水图像中的有效图像。
然后，由于污水中水呈透明，而颗粒物颜色一般较深，故可利用颗粒物与水的颜色差，对截取得到的有效图像中拍摄到的颗粒物进行特征点提取，可通过有效图像中的颜色分布转化为特征图，比如颜色直方图、颜色矩阵或者颜色集，然后通过特征图提取有效图像中的颗粒物特征点。
接着，通过有效图像内提取到的颗粒物特征点，计算颗粒物的数量，并分别计算各颗粒物的面积，其中，当颗粒物浓度比较高时，颗粒物会产生重叠，根据颗粒物的轮廓特征，自动进行重叠部分的轮廓补正和数量计算，并进一步计算轮廓补正后颗粒物的面积。
最后，将截取到的不同面积的有效图像计算得到的颗粒物数量和颗粒物 面积，转化为相同有效面积面积的颗粒物数量，其中，颗粒物面积转化为等效的颗粒物数量，然后可以通过数量与相同的等效单位计算污水的悬浮颗粒物浓度：悬浮颗粒物数量/等效单位面积＝悬浮颗粒物浓度。
103、所述基站根据所述悬浮颗粒物浓度，确定当前泵吸的污水的洁净程度。
本实施例中，悬浮颗粒物浓度和污水的洁净程度之间存在一个经验系数K，通过经验系数K构建悬浮颗粒物浓度和洁净程度的转换公式：洁净程度＝K*悬浮颗粒物浓度，其中，洁净程度以一个百分比值进行表示。另外，污水的洁净程度可侧面表示清洗后清洁机器人的拖擦组件的洁净程度，拖擦组件的洁净程度越低，则清洗拖擦组件后的污水洁净程度自然越低，反之则越高。
进一步的，在确定污水的洁净程度后，可以此衡量拖擦组件的洁净程度，并确定是否对拖擦组件进行下一轮清洁；若进行下一轮清洁，则根据洁净程度筛选适当的清洁策略进行清洁，具体流程如下所示：
3.1)所述基站根据当前泵吸的污水的洁净程度，判断当前清洁机器人是否满足预置清洁退出条件；
3.2)若满足，则所述基站退出清洁；
3.3)若不满足，则所述基站根据当前泵吸的污水的洁净程度，设置下一轮清洗策略，并对所述清洁机器人进行下一轮清洁程度检测，其中，所述清洁策略包括：清洁模式、污水循环速度、清水循环速度中的至少一项。
本实施例中，可预先设置清洁退出条件，比如设置清洁机器人的洁净程度阈值为85％-99％之间的一个百分比值，若设置洁净程度阈值为95％，则当当前污水的洁净程度大于或等于95％时，则确定当前清洁机器人满足清洁退出条件，无需对清洁机器人进行下一轮的清洁，基站即可退出对清洁机器人的清洁；若当前污水的洁净程度小于95％，则确定当前机器人还“较脏”，不满足清洁退出条件，需要再对清洁机器人进行清洁，则基站根据污水的洁净程度重新设置清洁策略对清洁机器人进行下一轮的清洁。
其中，污水的洁净程度越高，则选择更强力的清洁模式，对拖擦组件进行更强劲的清洁，并选择更快的污水循环速度、更快的清水循环速度，使得等同清洁时间内采用更多的清水对拖擦组件进行清洁。
具体的，可设置清洁程度区间对应的清洁模式、污水循环速度、清水循环速度，例如：
当清洁程度在(A1，A2]之间时，采用清洁模式B1、污水循环速度C1和污水循环速度D1；
当清洁程度在(A2，A3]之间时，采用清洁模式B2、污水循环速度C2和污水循环速度D2；
……
当清洁程度在(Ai，Ai+1]之间时，采用清洁模式Bi、污水循环速度Ci和污水循环速度Di。
本申请实施例中，基站的污水通路上设置有污水检测装置，当基站对拖擦组件完成一次清洁后，进行污水泵吸时，通过污水检测装置检测污水中的悬浮颗粒浓度，并以悬浮颗粒浓度来衡量当前泵吸的污水的洁净程度，其中，通常情况下，当污水中的悬浮颗粒浓度越高，则污水的洁净程度越低，故本申请实施例在通过污水检测装置检测到污水的悬浮颗粒浓度后，实现了对污水洁净程度的检测，以用于后续对拖擦组件进行清洁控制，提升拖擦组件的清洁效率，降低清洁用水的浪费。
上面对本申请实施例中拖擦组件清洁程度检测方法进行了描述，下面对本申请实施例中检测电路进行描述，请参阅图5，本申请实施例中检测电路包括：第一检测电路501、第二检测电路502和电压比较电路503；
第一检测电路501包括发光二极管5011、第一三极管5012，发光二极管5012的阳极连接基准电压，发光二极管5011的阴极连接第一三极管5012的集电极，第一三极管5012的发射极接地，第一三极管5012的基极连接基站的微处理器；
第二检测电路502包括光敏元件5021，光敏元件5021一端连接基准电压，另一端接地；
电压比较电路503包括运算放大器5031、第二三极管5032，运算放大器5031的反相输入端与第二检测电路中光敏元件5021相连，运算放大器5031的同相输入端与基准电压相连，运算放大器5031的输出与第二三极管5032的基极相连，第二三极管5032的集电极连接基站的微处理器，第二三极管5032的发射极接地；
发光二极管5011与光敏元件5021设置于基站的污水通路的一侧且形成设定角度，或发光二极管5011与光敏元件5021设置于基站的污水通路的不同侧且朝向相对。
本实施例中，第一检测电路501用于：当进行污水泵吸时，接收微处理器(Microcontroller Unit，MCU，下称MCU，)发送的检测信号，若检测信号的电压大于预置第一电压阈值，则使第一三极管5012导通并使发光二极管5011通电发光；当检测信号的电压大于第一电压阈值时，第一三极管5012导通，与接地发射极构成回路，使得发光二极管5011通电发光，当检测信号的电压小于第一电压阈值时，第一三极管5012不导通，则发光二极管5011不通电而不发光。
另外，第二检测电路502用于：当发光二极管5011通电发出光时，光敏元件5021根据接收到的光强度的变化而使电阻值发生变化，并使输入运算放 大器5031反相输入端的电压相应发生变化；其中，光敏元件可以包括光敏电阻、光敏三极管等一切对光敏感的电子元件。
另外，电压比较电路503用于：比较运算放大器5031的正相输入端与反相输入端之间的电压差值，并根据电压差值使第二三极管5032导通或不导通，其中，当第二三极管5032导通时，若运算放大器5031的输出电压大于预置第二电压阈值，则MCU对清洁机器人进行清洁控制。
本申请实施例中，通过第一检测电路、第二检测电路和电压比较电路构成一个完整的检测电路，在对泵吸污水时第一检测电路的第一三极管导通，控制发光二极管发光；第二检测电路的光敏元件接收光线透射过污水后的光强度，得到对应的阻值，根据阻值衡量污水中的悬浮颗粒物浓度，最后输出对应的电压值；电压比较电路通过第二检测电路输入的电压值与基准电压值作比较，当两者电压差为正值时，拖擦组件洁净程度足够高，第二二极管导通，使得MCU退出对清洁机器人的清洗，当两者电压差为负值时，拖擦组件洁净程度不够高，第二二极管不导通，使得MCU控制对清洁机器人进行下一轮的清洗，实现对清洁机器人的清洁程度检测，并实现对清洁机器人的清洁控制。
如图6所示的检测电路一较佳实施例的电路设计示意图。MCU的一个IO(Input/Output，输入/输出)口通过基极电阻R1与三极管Q1相连，偏置电阻R2与三极管Q1连接接地，三极管Q1的集电极连接电阻R3与发光二极管D1，并与基准电压(Volt Current Condenser，VCC，下称VCC)连接，最终构成第一检测电路。
另一端电阻R5与光敏电阻R4串联，光敏电阻R4的一端接地，另一端接运算放大器OA的反相输入端，最终构成第二检测电路。
而运算放大器OA的同相输入端通过电阻R6接VCC，之间通过电阻R7接地，运算放大器OA的输出端串联电阻R8接三极管Q2，三极管Q2的集电极连接MCU的另一个IO口，三极管Q2与偏置电阻R9连接接地，最终构成运算放大器。
本实施例中，当基站对拖擦组件完成一次清洁时，会进行污水泵吸，MCU发出高于预置电压阈值的电压检测信号，使得三极管Q1导通，偏置电阻R2、电阻R3和发光二极管D1串联接地，构成回路，发光二极管D1发光；光透过污水投射到光敏电阻R4上，投射到光敏电阻R4的光强度越高，光敏电阻R4的阻值越低，压降会发生降低，使得光敏电阻R4输出到运算放大器OA的电压降低，表示污水中的悬浮颗粒浓度越低，当污水管道中为清水时，投射到光敏电阻R4的光强度最大。
光敏电阻R4与电阻R5进行分压，向运算放大器OA的反向输入端输入一个电压值V -：
Figure PCTCN2021135579-appb-000001
运算放大器OA的同向输入端输入一个基准电压V +：
Figure PCTCN2021135579-appb-000002
其中，基准电压V +可开发人员根据经验进行设置，表示预置清洁退出条件。
V +与V -进行比较，若V +小于V -时，运算放大器OA输出低电平，三极管Q2不导通，MCU的另一个IO口输出高电压，所产生的效果基站需设定新的清洁策略对清洁机器人继续清洗；若V +大于V -时，运算放大器OA输出高电平，三极管Q2导通作，MCU的另一个IO口输出低电压，产生的效果是基站退出对清洁机器人的清洗。
本申请实施例中，在对泵吸污水时三极管Q1导通，以控制发光二极管D1发光；光敏电阻R4接收发光二极管D1发光并透射过污水后的光线，得到对应的阻值，以衡量污水中的悬浮颗粒物浓度，调整输入运算放大器OA反向输入端的电压值；运算放大器OA通过光敏电阻R4输入的电压值与同向输入端的基准电压值作比较，当运算放大器OA的输出端输出正值时，拖擦组件洁净程度足够高，二极管Q2导通，使得MCU退出对清洁机器人的清洗，当运算放大器OA的输出端输出负值时，拖擦组件洁净程度不够高，二极管Q2不导通，使得MCU控制对清洁机器人进行下一轮的清洗，实现对清洁机器人的清洁程度检测，并实现对清洁机器人的清洁控制。
上面对本申请实施例中检测电路进行了描述，下面对本申请实施例中基站进行描述，请参阅图7，本申请实施例中基站一个实施例包括：
检测模块701，用于当对所述拖擦组件一次清洁完成之后，进行污水泵吸时，通过设置在所述基站的污水通路上的所述污水检测装置对当前泵吸的污水进行检测，得到检测数据；
计算模块702，用于根据所述检测数据，计算当前泵吸的污水的悬浮颗粒物浓度；
确定模块703，用于根据所述悬浮颗粒物浓度，确定当前泵吸的污水的洁净程度。
本申请实施例中，基站的污水通路上设置有污水检测装置，当基站对拖擦组件完成一次清洁后，进行污水泵吸时，通过污水检测装置检测污水中的悬浮颗粒浓度，并以悬浮颗粒浓度来衡量当前泵吸的污水的洁净程度，其中， 通常情况下，当污水中的悬浮颗粒浓度越高，则污水的洁净程度越低，故本申请实施例在通过污水检测装置检测到污水的悬浮颗粒浓度后，实现了对污水洁净程度的检测，以用于后续对拖擦组件进行清洁控制，提升拖擦组件的清洁效率，降低清洁用水的浪费。
请参阅图8，本申请实施例中基站的另一个实施例包括：
检测模块701，用于当对所述拖擦组件一次清洁完成之后，进行污水泵吸时，通过设置在所述基站的污水通路上的所述污水检测装置对当前泵吸的污水进行检测，得到检测数据；
计算模块702，用于根据所述检测数据，计算当前泵吸的污水的悬浮颗粒物浓度；
确定模块703，用于根据所述悬浮颗粒物浓度，确定当前泵吸的污水的洁净程度。
具体的，所述污水检测装置包括若干光学组件，所述光学组件包含光发射元件和光接收元件，所述检测模块701还用于：
当所述基站对所述拖擦组件一次清洁完成之后，进行污水泵吸时，控制设置在所述基站的污水通路上的所述光发射元件发光，并通过设置在所述基站的污水通路上的所述光接收管进行至少两次光采样，得到当前泵吸的污水的检测数据，其中，所述检测数据包括光反射强度或光吸收强度。
具体的，所述光发射元件和所述光接收元件设置于所述基站的污水通路的一侧且形成设定角度，或所述光发射元件和所述光接收元件设置于所述基站的污水通路的不同侧且朝向相对。
具体的，所述污水检测装置还包括：污水采样管和污水采样槽，其中，所述污水采样管的两端分别与所述污水通路和所述污水采样槽连接，所述光发射元件和所述光接收元件相对设置在所述污水采样槽的两侧。
具体的，所述污水检测装置包括拍摄装置，所述检测模块701还用于：
当所述基站对所述拖擦组件一次清洁完成之后，进行污水泵吸时，控制设置在所述基站的污水通路上的所述拍摄装置对所述污水通路中的污水进行拍摄，得到当前泵吸的污水的检测数据，所述检测数据包括污水图像。
具体的，所述计算模块702包括：
识别单元7021，用于对所述污水图像进行分割识别，并根据分割识别结果，截取所述污水图像中的有效图像；
提取单元7022，用于对所述有效图像进行颗粒物特征点提取，得到多个颗粒物特征点，并进行颗粒物数量和颗粒物面积统计；
计算单元7023，用于根据统计得到的颗粒物数量和颗粒物面积，计算等效单位面积内悬浮颗粒物数量，得到当前泵吸的污水的悬浮颗粒物浓度。
具体的，所述基站计算模块702还包括：
转换单元7024，用于对所述光反射强度或光吸收强度进行模数转换，得到对应的光强度值；
换算单元7025，用于根据预置换算公式，将所述光强度值换算为当前泵吸的污水的悬浮颗粒物浓度。
具体的，所述基站还包括清洁控制模块704，所述清洁控制模块704用于：
根据当前泵吸的污水的洁净程度，判断当前清洁机器人是否满足预置清洁退出条件；若满足，则退出清洁；若不满足，则根据当前泵吸的污水的洁净程度，设置下一轮清洗策略，并对所述清洁机器人进行下一轮清洁程度检测，其中，所述清洁策略包括：清洁模式、污水循环速度、清水循环速度中的至少一项。
本申请实施例中，基站的污水通路上设置有污水检测装置，当基站对拖擦组件完成一次清洁后，进行污水泵吸时，通过污水检测装置检测污水中的悬浮颗粒浓度，并以悬浮颗粒浓度来衡量当前泵吸的污水的洁净程度，其中，通常情况下，当污水中的悬浮颗粒浓度越高，则污水的洁净程度越低，故本申请实施例在通过污水检测装置检测到污水的悬浮颗粒浓度后，实现了对污水洁净程度的检测，以用于后续对拖擦组件进行清洁控制，提升拖擦组件的清洁效率，降低清洁用水的浪费。
上面图7和图8从模块化功能实体的角度对本申请实施例中的基站进行详细描述，下面从硬件处理的角度对本申请实施例中基站进行详细描述。
图9是本申请实施例提供的一种基站的结构示意图，该基站900可因配置或性能不同而产生比较大的差异，可以包括一个或一个以上处理器(central processing units，CPU)910(例如，一个或一个以上处理器)和存储器920，一个或一个以上存储应用程序933或数据932的存储介质930(例如一个或一个以上海量存储设备)。其中，存储器920和存储介质930可以是短暂存储或持久存储。存储在存储介质930的程序可以包括一个或一个以上模块(图示没标出)，每个模块可以包括对基站900中的一系列指令操作。更进一步地，处理器910可以设置为与存储介质930通信，在基站900上执行存储介质930中的一系列指令操作。
基站900还可以包括一个或一个以上电源940，一个或一个以上有线或无线网络接口950，一个或一个以上输入输出接口960，和/或，一个或一个以上操作系统931，例如Windows Serve，Mac OS X，Unix，Linux，FreeBSD等等。本领域技术人员可以理解，图9示出的基站结构并不构成对基站的限定，可以包括比图示更多或更少的部件，或者组合某些部件，或者不同的部件布置。
本申请还提供一种基站，所述基站包括存储器和处理器，存储器中存储有计算机可读指令，计算机可读指令被处理器执行时，使得处理器执行上述各实施例中的所述拖擦组件清洁程度检测方法的步骤。
本申请还提供一种计算机可读存储介质，该计算机可读存储介质可以为非易失性计算机可读存储介质，该计算机可读存储介质也可以为易失性计算机可读存储介质，所述计算机可读存储介质中存储有指令，当所述指令在计算机上运行时，使得计算机执行所述拖擦组件清洁程度检测方法的步骤。
所属领域的技术人员可以清楚地了解到，为描述的方便和简洁，上述描述的系统，装置和单元的具体工作过程，可以参考前述方法实施例中的对应过程，在此不再赘述。
所述集成的单元如果以软件功能单元的形式实现并作为独立的产品销售或使用时，可以存储在一个计算机可读取存储介质中。基于这样的理解，本申请的技术方案本质上或者说对现有技术做出贡献的部分或者该技术方案的全部或部分可以以软件产品的形式体现出来，该计算机软件产品存储在一个存储介质中，包括若干指令用以使得一台计算机设备(可以是个人计算机，服务器，或者网络设备等)执行本申请各个实施例所述方法的全部或部分步骤。而前述的存储介质包括：U盘、移动硬盘、只读存储器(read-only memory，ROM)、随机存取存储器(random access memory，RAM)、磁碟或者光盘等各种可以存储程序代码的介质。
以上所述，以上实施例仅用以说明本申请的技术方案，而非对其限制；尽管参照前述实施例对本申请进行了详细的说明，本领域的普通技术人员应当理解：其依然可以对前述各实施例所记载的技术方案进行修改，或者对其中部分技术特征进行等同替换；而这些修改或者替换，并不使相应技术方案的本质脱离本申请各实施例技术方案的精神和范围。

Claims (18)

  1. 一种拖擦组件清洁程度检测方法，其中，所述拖擦组件清洁程度检测方法应用于基站，所述基站用于对清洁机器人的拖擦组件进行清洁，所述基站包括污水检测装置，所述拖擦组件清洁程度检测方法包括：
    当所述基站对所述拖擦组件一次清洁完成之后，进行污水泵吸时，所述基站通过设置在所述基站的污水通路上的所述污水检测装置，对当前泵吸的污水进行检测，得到检测数据；
    所述基站根据所述检测数据，计算当前泵吸的污水的悬浮颗粒物浓度；
    所述基站根据所述悬浮颗粒物浓度，确定当前泵吸的污水的洁净程度。
  2. 根据权利要求1所述的拖擦组件清洁程度检测方法，其中，所述污水检测装置包括若干光学组件，所述光学组件包含光发射元件和光接收元件，所述当所述基站对所述拖擦组件一次清洁完成之后，进行污水泵吸时，所述基站通过设置在所述基站的污水通路上的所述污水检测装置，对当前泵吸的污水进行检测，得到检测数据包括：
    当所述基站对所述拖擦组件一次清洁完成之后，进行污水泵吸时，所述基站控制设置在所述基站的污水通路上的所述光发射元件发光，并通过设置在所述基站的污水通路上的所述光接收管进行至少两次光采样，得到当前泵吸的污水的检测数据，其中，所述检测数据包括光反射强度或光吸收强度。
  3. 根据权利要求2所述的拖擦组件清洁程度检测方法，其中，所述光发射元件和所述光接收元件设置于所述基站的污水通路的一侧且形成设定角度，或所述光发射元件和所述光接收元件设置于所述基站的污水通路的不同侧且朝向相对。
  4. 根据权利要求2所述的拖擦组件清洁程度检测方法，其中，所述污水检测装置还包括：污水采样管和污水采样槽，其中，所述污水采样管的两端分别与所述污水通路和所述污水采样槽连接，所述光发射元件和所述光接收元件相对设置在所述污水采样槽的两侧。
  5. 根据权利要求1所述的拖擦组件清洁程度检测方法，其中，所述污水检测装置包括拍摄装置，所述当所述基站对所述拖擦组件一次清洁完成之后，进行污水泵吸时，所述基站通过设置在所述基站的污水通路上的所述污水检测装置，对当前泵吸的污水进行检测，得到检测数据包括：
    当所述基站对所述拖擦组件一次清洁完成之后，进行污水泵吸时，所述基站控制设置在所述基站的污水通路上的所述拍摄装置对所述污水通路中的污水进行拍摄，得到当前泵吸的污水的检测数据，所述检测数据包括污水图像。
  6. 根据权利要求5所述的拖擦组件清洁程度检测方法，其中，所述基站根据所述检测数据，计算当前泵吸的污水的悬浮颗粒物浓度包括：
    所述基站对所述污水图像进行分割识别，并根据分割识别结果，截取所述污水图像中的有效图像；
    所述基站对所述有效图像进行颗粒物特征点提取，得到多个颗粒物特征点，并进行颗粒物数量和颗粒物面积统计；
    所述基站根据统计得到的颗粒物数量和颗粒物面积，计算等效单位面积内悬浮颗粒物数量，得到当前泵吸的污水的悬浮颗粒物浓度。
  7. 根据权利要求2所述的拖擦组件清洁程度检测方法，其中，所述基站根据所述检测数据，计算当前泵吸的污水的悬浮颗粒物浓度包括：
    所述基站对所述光反射强度或光吸收强度进行模数转换，得到对应的光强度值；
    所述基站根据预置换算公式，将所述光强度值换算为当前泵吸的污水的悬浮颗粒物浓度。
  8. 根据权利要求1中任一项所述的拖擦组件清洁程度检测方法，其中，在所述基站根据所述悬浮颗粒物浓度，确定当前泵吸的污水的洁净程度之后，还包括：
    所述基站根据当前泵吸的污水的洁净程度，判断当前清洁机器人是否满足预置清洁退出条件；
    若满足，则所述基站退出清洁；
    若不满足，则所述基站根据当前泵吸的污水的洁净程度，设置下一轮清洗策略，并对所述清洁机器人进行下一轮清洁程度检测，其中，所述清洁策略包括：清洁模式、污水循环速度、清水循环速度中的至少一项。
  9. 根据权利要求2中任一项所述的拖擦组件清洁程度检测方法，其中，在所述基站根据所述悬浮颗粒物浓度，确定当前泵吸的污水的洁净程度之后，还包括：
    所述基站根据当前泵吸的污水的洁净程度，判断当前清洁机器人是否满 足预置清洁退出条件；
    若满足，则所述基站退出清洁；
    若不满足，则所述基站根据当前泵吸的污水的洁净程度，设置下一轮清洗策略，并对所述清洁机器人进行下一轮清洁程度检测，其中，所述清洁策略包括：清洁模式、污水循环速度、清水循环速度中的至少一项。
  10. 根据权利要求3中任一项所述的拖擦组件清洁程度检测方法，其中，在所述基站根据所述悬浮颗粒物浓度，确定当前泵吸的污水的洁净程度之后，还包括：
    所述基站根据当前泵吸的污水的洁净程度，判断当前清洁机器人是否满足预置清洁退出条件；
    若满足，则所述基站退出清洁；
    若不满足，则所述基站根据当前泵吸的污水的洁净程度，设置下一轮清洗策略，并对所述清洁机器人进行下一轮清洁程度检测，其中，所述清洁策略包括：清洁模式、污水循环速度、清水循环速度中的至少一项。
  11. 根据权利要求4中任一项所述的拖擦组件清洁程度检测方法，其中，在所述基站根据所述悬浮颗粒物浓度，确定当前泵吸的污水的洁净程度之后，还包括：
    所述基站根据当前泵吸的污水的洁净程度，判断当前清洁机器人是否满足预置清洁退出条件；
    若满足，则所述基站退出清洁；
    若不满足，则所述基站根据当前泵吸的污水的洁净程度，设置下一轮清洗策略，并对所述清洁机器人进行下一轮清洁程度检测，其中，所述清洁策略包括：清洁模式、污水循环速度、清水循环速度中的至少一项。
  12. 根据权利要求5中任一项所述的拖擦组件清洁程度检测方法，其中，在所述基站根据所述悬浮颗粒物浓度，确定当前泵吸的污水的洁净程度之后，还包括：
    所述基站根据当前泵吸的污水的洁净程度，判断当前清洁机器人是否满足预置清洁退出条件；
    若满足，则所述基站退出清洁；
    若不满足，则所述基站根据当前泵吸的污水的洁净程度，设置下一轮清洗策略，并对所述清洁机器人进行下一轮清洁程度检测，其中，所述清洁策 略包括：清洁模式、污水循环速度、清水循环速度中的至少一项。
  13. 根据权利要求6中任一项所述的拖擦组件清洁程度检测方法，其中，在所述基站根据所述悬浮颗粒物浓度，确定当前泵吸的污水的洁净程度之后，还包括：
    所述基站根据当前泵吸的污水的洁净程度，判断当前清洁机器人是否满足预置清洁退出条件；
    若满足，则所述基站退出清洁；
    若不满足，则所述基站根据当前泵吸的污水的洁净程度，设置下一轮清洗策略，并对所述清洁机器人进行下一轮清洁程度检测，其中，所述清洁策略包括：清洁模式、污水循环速度、清水循环速度中的至少一项。
  14. 根据权利要求7中任一项所述的拖擦组件清洁程度检测方法，其中，在所述基站根据所述悬浮颗粒物浓度，确定当前泵吸的污水的洁净程度之后，还包括：
    所述基站根据当前泵吸的污水的洁净程度，判断当前清洁机器人是否满足预置清洁退出条件；
    若满足，则所述基站退出清洁；
    若不满足，则所述基站根据当前泵吸的污水的洁净程度，设置下一轮清洗策略，并对所述清洁机器人进行下一轮清洁程度检测，其中，所述清洁策略包括：清洁模式、污水循环速度、清水循环速度中的至少一项。
  15. 一种检测电路，应用于清洁机器人对应的基站，其中，所述检测电路包括：第一检测电路、第二检测电路和电压比较电路；
    所述第一检测电路包括发光二极管、第一三极管，所述发光二极管的阳极连接基准电压，所述发光二极管的阴极连接所述第一三极管的集电极，所述第一三极管的发射极接地，所述第一三极管的基极连接所述基站的微处理器；
    所述第二检测电路包括光敏元件，所述光敏元件一端连接所述基准电压，另一端接地；
    所述电压比较电路包括运算放大器、第二三极管，所述运算放大器的反相输入端与所述第二检测电路中光敏元件相连，所述运算放大器的同相输入端与所述基准电压相连，所述运算放大器的输出与所述第二三极管的基极相连，所述第二三极管的集电极连接所述基站的微处理器，所述第二三极管的 发射极接地；
    所述发光二极管与所述光敏元件设置于所述基站的污水通路的一侧且形成设定角度，或所述发光二极管与所述光敏元件设置于所述基站的污水通路的不同侧且朝向相对。
  16. 一种基站，其中，所述基站用于对清洁机器人的拖擦组件进行清洁，所述基站包括污水检测装置，所述基站还包括：
    检测模块，用于当对所述拖擦组件一次清洁完成之后，进行污水泵吸时，通过设置在所述基站的污水通路上的所述污水检测装置对当前泵吸的污水进行检测，得到检测数据；
    计算模块，用于根据所述检测数据，计算当前泵吸的污水的悬浮颗粒物浓度；
    确定模块，用于根据所述悬浮颗粒物浓度，确定当前泵吸的污水的洁净程度。
  17. 一种基站，其中，所述基站包括：存储器和至少一个处理器，所述存储器中存储有指令；
    所述至少一个处理器调用所述存储器中的所述指令，以使得所述基站执行如权利要求1中任一项所述的拖擦组件清洁程度检测方法。
  18. 一种计算机可读存储介质，所述计算机可读存储介质上存储有计算机程序，其中，所述计算机程序被处理器执行时实现如权利要求1中任一项所述的拖擦组件清洁程度检测方法。
PCT/CN2021/135579 2021-02-25 2021-12-05 拖擦组件清洁程度检测方法、检测电路及相关设备 WO2022179237A1 (zh)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CN202110210483.8 2021-02-25
CN202110210483.8A CN112986079B (zh) 2021-02-25 2021-02-25 拖擦组件清洁程度检测方法、检测电路及相关设备

Publications (1)

Publication Number Publication Date
WO2022179237A1 true WO2022179237A1 (zh) 2022-09-01

Family

ID=76350551

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2021/135579 WO2022179237A1 (zh) 2021-02-25 2021-12-05 拖擦组件清洁程度检测方法、检测电路及相关设备

Country Status (2)

Country Link
CN (1) CN112986079B (zh)
WO (1) WO2022179237A1 (zh)

Families Citing this family (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112986079B (zh) * 2021-02-25 2022-10-28 深圳银星智能集团股份有限公司 拖擦组件清洁程度检测方法、检测电路及相关设备
CN114875500B (zh) * 2022-04-30 2023-08-11 江苏阿代尔新材料科技有限公司 一种废丝再生涤纶长丝生产工艺
WO2024020882A1 (zh) * 2022-07-27 2024-02-01 云鲸智能(深圳)有限公司 清洁机器人的控制、清洁方法、装置、系统及存储介质

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN2738332Y (zh) * 2004-03-29 2005-11-02 天津市凯瑟戴克环保科技有限公司 自动售货机的出货装置
CN107340724A (zh) * 2017-03-29 2017-11-10 宁波方太厨具有限公司 一种清洗机的清洗控制方法
CN109620064A (zh) * 2016-12-16 2019-04-16 云鲸智能科技（东莞）有限公司 用于清洁机器人系统的基站
US20190143481A1 (en) * 2017-11-14 2019-05-16 Taiwan Semiconductor Manufacturing Co., Ltd. Method and apparatus for cleaning process monitoring
CN112043217A (zh) * 2020-09-29 2020-12-08 珠海市一微半导体有限公司 全自动清洁机器人系统及控制方法
CN112986079A (zh) * 2021-02-25 2021-06-18 深圳市银星智能科技股份有限公司 拖擦组件清洁程度检测方法、检测电路及相关设备

Family Cites Families (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5331177A (en) * 1993-04-26 1994-07-19 Honeywell Inc. Turbidity sensor with analog to digital conversion capability
CN205250236U (zh) * 2015-12-27 2016-05-25 浙江机电职业技术学院 一种鸭胗清洗装置
CN205436462U (zh) * 2015-12-27 2016-08-10 浙江机电职业技术学院 一种小麦自动清洗装置
CN207627192U (zh) * 2017-06-30 2018-07-20 佛山市顺德区美的电热电器制造有限公司 烹饪器具
CN207574428U (zh) * 2017-10-12 2018-07-06 襄阳富襄现代农业开发有限公司 一种鸭胗清洗装置
CN108992013B (zh) * 2018-09-07 2020-12-29 浙江欧琳生活健康科技有限公司 一种洗碗机智能洗涤的方法及系统
CN209252750U (zh) * 2018-11-30 2019-08-16 东莞图境机电科技有限公司 一种自动拖把清洁装置的控制装置
CN110051285B (zh) * 2019-04-18 2021-12-24 云鲸智能科技（东莞）有限公司 一种检测方法、装置及存储介质

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN2738332Y (zh) * 2004-03-29 2005-11-02 天津市凯瑟戴克环保科技有限公司 自动售货机的出货装置
CN109620064A (zh) * 2016-12-16 2019-04-16 云鲸智能科技（东莞）有限公司 用于清洁机器人系统的基站
CN107340724A (zh) * 2017-03-29 2017-11-10 宁波方太厨具有限公司 一种清洗机的清洗控制方法
US20190143481A1 (en) * 2017-11-14 2019-05-16 Taiwan Semiconductor Manufacturing Co., Ltd. Method and apparatus for cleaning process monitoring
CN112043217A (zh) * 2020-09-29 2020-12-08 珠海市一微半导体有限公司 全自动清洁机器人系统及控制方法
CN112986079A (zh) * 2021-02-25 2021-06-18 深圳市银星智能科技股份有限公司 拖擦组件清洁程度检测方法、检测电路及相关设备

Also Published As

Publication number Publication date
CN112986079A (zh) 2021-06-18
CN112986079B (zh) 2022-10-28

Similar Documents

Publication Publication Date Title
WO2022179237A1 (zh) 拖擦组件清洁程度检测方法、检测电路及相关设备
WO2022002039A1 (zh) 一种基于视觉地图的视觉定位方法、装置
WO2019128636A1 (zh) 一种清扫方法及清洁机器人
CN107137026A (zh) 一种扫地机器人及其摄像头补光系统、方法
CN112826383A (zh) 清洁机器人清洁控制方法、装置、基站及存储介质
US10293489B1 (en) Control method and system, and cleaning robot using the same
US8013841B2 (en) Enhanced lift detection technique for a laser illuminated optical mouse sensor
CN106485729A (zh) 一种基于混合高斯模型的运动目标检测方法
CN113524265B (zh) 机器人防跌落方法、机器人及可读存储介质
CN109876569A (zh) 一种布袋除尘器净化气体指标在线检测装置、系统及方法
CN111311927A (zh) 车流量检测方法、装置、计算机设备及存储介质
Chen et al. Feature extraction using a portable vision system
Zhang et al. Dynamic fry counting based on multi-object tracking and one-stage detection
CN104457911B (zh) 一种液位检测系统及液位检测方法
US11234571B2 (en) Cleaning robot and material identification method thereof
WO2024060637A1 (zh) 一种洗地机控制系统、洗地机及控制方法
CN113104945A (zh) 一种基于絮团特性反馈的煤泥水智能加药方法及系统
WO2024045659A1 (zh) 一种hepa网脏污检测方法和装置
CN111493741B (zh) 尘盒检测方法、装置、电子设备及计算机可读存储介质
CN114451831B (zh) 清洁机器人清理垃圾的处理方法、存储介质及清洁机器人
CN205416748U (zh) 一种全自动视觉印刷机清洗纸用量检测系统
CN117015699A (zh) 污浊度检测方法及清洁设备
US20240049938A1 (en) Washing control method and apparatus, computer readable storage medium, and electronic device
WO2021147364A1 (zh) 图像曝光调整方法、装置、设备和介质
CN111429487B (zh) 一种深度图像的黏连前景分割方法及装置

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 21927661

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE