Method and system for self-adjusting windscreen wiper based on fuzzy degree of automobile windscreen

Abstract

The invention provides a method and system for self-adjusting a windscreen wiper based on the fuzzy degree of an automobile windscreen, and relates to the technical field of intelligent control over vehicle-mounted windscreen wipers. The method comprises the following steps: S1, acquiring video data of an automobile windshield in real time through a camera and transmitting the video data to a controller; s2, the controller performs frame sampling on the video data based on a preset sampling frequency to obtain real-time state image data of the windshield; s3, based on the real-time state image data of the windshield, evaluating the real-time state image data by adopting a Brenner algorithm to obtain a fuzzy state of the windshield; s4, whether the windscreen wiper needs to be controlled to start working or not is judged based on the fuzzy state of the windscreen; s5, the working frequency of the windscreen wiper is obtained based on a preset windscreen wiper working frequency calculation formula; and S6, controlling the vehicle machine system to output PWM waves with the frequency being the working frequency of the windscreen wiper to drive a motor of the windscreen wiper to work. The defects that an existing windscreen wiper is low in detection precision and high in false alarm rate, and the speed of the windscreen wiper cannot be adjusted in a stepless mode are overcome.

Description

Technical Field

[0001] The invention relates to the technical field of intelligent control of vehicle-mounted wipers, and in particular to a method and system for self-regulating wipers based on the blur degree of a vehicle windshield. Background Art

[0002] Car wipers are an indispensable part of cars. Their working principle is to use a motor to drive, reduce speed and increase torque through a worm gear mechanism, and then convert the rotational motion into a reciprocating swing of the wiper arm through a four-bar linkage to achieve the wiping action. The wiper blade rubber strip is a tool to directly remove rain and dirt from the glass. It is pressed against the glass surface by a spring bar to ensure that it is in line with the glass angle to achieve a good wiping effect.

[0003] With the development of intelligence, modern wipers also have intelligent sensing functions, which can automatically adjust the speed of wiper swing according to the amount of rain, improving driving safety and convenience. In addition, some high-end models are also equipped with water-spraying wiper blades, which spray glass water evenly on the glass through the small holes designed on the wiper blades to achieve better cleaning effects. With the continuous development of the automotive industry, the technology of wipers will continue to improve, providing drivers with a safer and more comfortable driving experience.

[0004] The working principle and defects of existing inductive wipers: There are two main working principles of inductive wipers: speed-sensitive and rain-sensitive.

[0005] Speed-sensing type: The oscillation frequency of the wipers is controlled by the vehicle speed signal. When the vehicle is moving, the higher the speed, the faster the wipers move. At the same time, during driving, the force of the wipers is proportional to the amount of rainfall. The greater the rainfall, the greater the force of the wipers; the higher the speed, the faster the frequency.

[0006] Rain sensor: The rain sensor on the windshield detects the amount and intensity of rain, and then the computer controller adjusts the frequency and strength of the wipers. The rain sensor can sense the size of raindrops and automatically adjust the speed of the wipers to provide the driver with a good view.

[0007] Existing inductive wipers have the advantages of improved safety, energy saving, extended life and improved intelligent experience. However, they also have the disadvantage of insufficient sensitivity: although inductive automatic wipers can automatically adjust according to external conditions, false alarms or missed alarms may still occur. For example, in light rain or when there are no water droplets around the sensor, the automatic wipers may not start; and in the case of mud, dirt, fog and other non-rain water, the automatic wipers may start by mistake.

[0008] Therefore, it is urgent to design a method and system for self-adjusting wipers based on the blur level of the automobile windshield to solve the defects in the prior art. Summary of the invention

[0009] The present invention aims to provide a method and system for self-adjusting wipers based on the blur degree of automobile windshield, aiming to solve the shortcomings of wipers in the prior art, such as low detection accuracy, high false alarm rate, and inability to adjust wiper speed infinitely.

[0010] On the one hand, the present application provides a method for self-adjusting wipers based on the blur degree of a car windshield, wherein a camera and a controller are integrated in the car, the controller is integrated in the vehicle system, the camera is electrically connected to the controller, and the method comprises: S1: acquiring video data of the car windshield in real time through the camera and transmitting it to the controller; S2: the controller samples the video data based on a preset sampling frequency to obtain real-time state image data of the windshield; S3: the controller uses the Brenner algorithm to evaluate the real-time state image data of the windshield to obtain to the blurred state of the windshield; S4: the controller determines whether it is necessary to control the wiper to start working based on the blurred state of the windshield; S5: in response to the need to control the wiper to start working, the controller obtains the working frequency of the wiper based on a preset wiper working frequency calculation formula; S6: based on the working frequency of the wiper, the controller controls the vehicle system to output a PWM wave with a frequency equal to the working frequency of the wiper to drive the wiper motor to work; S7: the wiper is controlled by the motor connected thereto to work based on the working frequency; S8: in response to the need not to control the wiper to start working, go to step S1.

[0011] Furthermore, the step S1: acquiring the video data of the car windshield in real time through the camera and transmitting it to the controller includes: S110: acquiring the video data of the car windshield in real time through the camera during the car startup process and transmitting it to the controller via Ethernet.

[0012] Furthermore, the step S2: the controller performs frame sampling on the video data based on a preset sampling frequency to obtain real-time status image data of the windshield, including: S210: when the controller receives the video data of the car windshield, it uses python and its image library to load the acquired car windshield video data and pre-process it; S220: frame sampling the pre-processed video data at a preset sampling frequency to obtain N real-time status image data of the windshield.

[0013] Furthermore, the preprocessing in step S210 includes compressing each frame of the image in the collected video data of the automobile windshield.

[0014] Further, the step S3: the controller uses the Brenner algorithm to evaluate the real-time state image data of the windshield to obtain the blur state of the windshield, including: S310: using the Brenner algorithm to calculate the square of the grayscale difference between adjacent pixels in the real-time state image data of the automobile windshield to obtain a blur index; S320: evaluating the blur state of the automobile windshield based on the blur index; the Brenner algorithm includes:

[0015]

[0016] Where FBrenner is the blur index, f(x+2,y) and f(x,y) represent the grayscale values ​​of the image at pixel points (x+2,y) and (x,y), respectively, and m and n are the width and height of the real-time state image of the windshield, respectively.

[0017] Furthermore, the step S4: the controller determines whether it is necessary to control the wiper to start working based on the blur state of the windshield, including: S410: based on comparing the blur index of the car windshield with a preset blur threshold, when the blur index of the car windshield is greater than or equal to the blur threshold, it is determined that the wiper needs to be controlled to start working; when the blur index of the car windshield is less than the blur threshold, it is determined that it is not necessary to control the wiper to start working.

[0018] Further, the step S5: in response to the need to control the wiper to start working, the controller obtains the working frequency of the wiper based on a preset wiper working frequency calculation formula, including: the preset wiper working frequency calculation formula is: f=k×FBrenner+b;

[0019] Where f is the operating frequency of the wiper, FBrenner is the windshield blur index, k is the frequency scaling factor, and b is a constant.

[0020] Furthermore, the step S6: the controller controls the vehicle system to output a PWM wave with a frequency equal to the working frequency of the wiper based on the working frequency of the wiper to drive the motor of the wiper to work, including: S610: when the controller determines that the wiper needs to be controlled to work, the working frequency is converted into an electrical signal by digital modulation and sent to the vehicle system; S620: the vehicle system sends a PWM wave to the motor based on the electrical signal to drive the motor to drive the wiper to work at the working frequency.

[0021] Furthermore, the motor in step S6 is a stepper motor, and the stepper motor is connected to the wiper to control the operating frequency of the wiper.

[0022] In the second aspect, the present application provides a system for self-adjusting wipers based on the blur degree of a car windshield, the system is implemented by the method for self-adjusting wipers based on the blur degree of a car windshield as described above, the wiper self-adjusting system includes a camera, a controller, a vehicle computer system and a wiper, the camera is placed at the car windshield, the controller is integrated in the vehicle computer system, the camera communicates with the controller via Ethernet; the camera is used to acquire video data of the car windshield in real time and transmit it to the controller; the controller is integrated with a real-time state image data acquisition module, a blur state evaluation module, a judgment module, a wiper operating frequency calculation module and a drive module; the real-time state image data acquisition module is suitable for sampling the video data based on a preset The frame sampling is performed at a frequency to obtain real-time state image data of the windshield; the fuzzy state evaluation module is suitable for evaluating the real-time state image data of the windshield using the Brenner algorithm to obtain the fuzzy state of the windshield; the judgment module is suitable for judging whether it is necessary to control the wiper to start working based on the fuzzy state of the windshield; the wiper working frequency calculation module is suitable for responding to the need to control the wiper to start working, and obtaining the working frequency of the wiper based on a preset wiper working frequency calculation formula; the driving module is suitable for controlling the vehicle system to output a PWM wave with a frequency of the working frequency of the wiper based on the working frequency of the wiper to drive the motor of the wiper to work; the wiper is suitable for controlling it to work based on the working frequency through the motor connected thereto.

[0023] In a third aspect, an embodiment of the present invention further provides an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the computer program is executed by the processor, the method for self-adjusting the wiper based on the blur degree of the automobile windshield is implemented.

[0024] In a fourth aspect, an embodiment of the present invention further provides a readable storage medium, which, when the instructions in the storage medium are executed by a processor of an electronic device, enables the electronic device to execute the above-mentioned method of self-adjusting the wiper based on the blur degree of the automobile windshield.

[0025] The beneficial effects of the present invention are:

[0026] The embodiment of the present application provides a method and system for self-adjusting a wiper based on the blur degree of a car windshield. By evaluating the blur degree of the car windshield, determining whether to turn on the wiper based on the blur degree evaluation result, and calculating the working frequency of the wiper based on the blur degree evaluation result, the working frequency of the wiper can be self-adjusted based on the blur degree of the car windshield, that is, the higher the blur degree of the car windshield, the higher the working frequency of the wiper. It is only necessary to collect the video of the windshield as input through a camera, and then combine the corresponding video image processing method and signal analysis processing method, so that the blur degree of the windshield can be conveniently and accurately calculated, and then the wiper can be controlled to work matching the blur degree. It makes up for the shortcomings of the traditional wiper, such as low degree of automation, not simple operation, and inaccurate adjustment of the wiper working frequency. It can achieve a relatively accurate determination of the cleanliness of the windshield without manual intervention, and automatically and infinitely control the work of the wiper. It is suitable for target groups in complex environments or with high requirements for automation and ease of operation. The present invention has the advantages of high accuracy, convenience, no need for manual intervention, and infinitely variable speed regulation. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0028] Figure 1 This is a flow chart of a method for self-adjusting wipers based on the blur level of a car windshield provided in Example 1 of the present invention.

[0029] Figure 2 This is a schematic diagram of the overall structure of a car provided in Example 1 of the present invention.

[0030] Figure 3 It is a schematic diagram of the structure of a system for self-adjusting wipers based on the blur level of a car windshield provided in Example 2 of the present invention.

[0031] Figure 4 This is a partial block diagram of an electronic device provided in Embodiment 3 of the present invention. DETAILED DESCRIPTION

[0032] It should be mentioned before discussing the exemplary embodiments in more detail that some exemplary embodiments are described as processes or methods depicted as flow charts. Although the flow charts describe the operations as sequential processes, many of the operations therein can be implemented in parallel, concurrently or simultaneously. In addition, the order of the operations can be rearranged. The process can be terminated when its operation is completed, but can also have additional steps not included in the accompanying drawings. The process can correspond to a method, function, procedure, subroutine, subprogram, etc.

[0033] It should be understood that, although the terms "first", "second", etc. may be used herein to describe various units, these units should not be limited by these terms. These terms are used only to distinguish one unit from another unit. For example, without departing from the scope of the exemplary embodiments, the first unit may be referred to as the second unit, and similarly the second unit may be referred to as the first unit. The term "and / or" used herein includes any and all combinations of one or more of the listed associated items.

[0034] The present invention will now be described in detail with reference to the accompanying drawings. This figure is a simplified schematic diagram, which only illustrates the basic structure of the present invention in a schematic manner, and therefore only shows the components related to the present invention.

[0035] Example 1

[0036] For ease of understanding, the inventive concept is generally described below before describing the embodiments of the present invention in detail:

[0037] This embodiment provides a method and system for self-adjusting the wiper based on the blur degree of the automobile windshield. The image data of the automobile windshield is obtained by a camera, the blur degree of the automobile windshield is evaluated based on the Brenner algorithm, whether the wiper needs to be turned on is determined based on the blur degree evaluation result, and the working frequency of the wiper is calculated based on the blur degree evaluation result, so that the working frequency of the wiper can be self-adjusted based on the blur degree of the automobile windshield, that is, the higher the blur degree of the automobile windshield, the higher the working frequency of the wiper. It is only necessary to collect the video of the windshield as input through the camera, and then combine the corresponding video image processing method and signal analysis processing method, so that the blur degree of the windshield can be conveniently and accurately calculated, and then the wiper can be controlled to work matching the blur degree. It makes up for the shortcomings of the traditional wiper, such as low working automation, not simple operation, and inaccurate adjustment of the wiper working frequency, and can achieve more accurate determination of the cleanliness of the windshield without manual intervention, and automatically and infinitely control the work of the wiper. It is suitable for target groups in complex environments or with high requirements for automation and ease of operation. The invention has the advantages of high accuracy, convenience, speed, no need for manual intervention, and stepless speed regulation.

[0038] The specific implementation is as follows:

[0039] like Figure 1 As shown, it is a flow chart of a method for self-adjusting wipers based on the blur level of the automobile windshield provided by this embodiment.

[0040] As an example, the car is integrated with a camera 1 and a controller, the controller is integrated in a vehicle system, the camera is electrically connected to the controller, and the method includes:

[0041] S1: Acquire video data of the automobile windshield in real time through the camera and transmit it to the controller.

[0042] S2: The controller performs frame sampling on the video data based on a preset sampling frequency to obtain real-time status image data of the windshield.

[0043] S3: The controller uses the Brenner algorithm to evaluate the real-time state image data of the windshield to obtain the blur state of the windshield.

[0044] S4: The controller determines whether it is necessary to control the wiper to start working based on the blurry state of the windshield.

[0045] S5: In response to the need to control the wiper to start working, the controller obtains the operating frequency of the wiper based on a preset wiper operating frequency calculation formula.

[0046] S6: The controller controls the vehicle computer system to output a PWM wave having a frequency equal to the working frequency of the wiper based on the working frequency of the wiper to drive the motor of the wiper to work.

[0047] S7: The wiper is controlled by a motor connected thereto to operate based on the operating frequency;

[0048] S8: In response to the fact that there is no need to control the wiper to start working, go to step S1.

[0049] In some feasible embodiments, combined with Figure 2 As shown, the camera 1 is installed on the automobile workbench in a semi-buried oblique installation manner near the windshield. The camera 1 is used to obtain the video image of the windshield in real time and transmit it to the vehicle system. The step S1: obtaining the video data of the automobile windshield in real time through the camera and transmitting it to the controller includes: S110: during the automobile startup process, the video data of the automobile windshield is collected in real time through the camera and transmitted to the controller via Ethernet. The video stream uses Gigabit Ethernet as the transmission medium to ensure the transmission speed and transmission stability of the video stream.

[0050] In some feasible implementations, the step S2: the controller performs frame sampling on the video data based on a preset sampling frequency, and obtains the real-time state image data of the windshield, including: S210: after the controller receives the video data of the automobile windshield, it uses python and its image library to load the obtained automobile windshield video data and preprocess it; S220: the preprocessed video data is frame sampled according to the preset sampling frequency to obtain N real-time state image data of the windshield. Among them, the preprocessing in the step S210 includes compressing each frame of the collected automobile windshield video data, and the system extracts a frame of video image every period of time (for example, 1 second). Specifically, by using python and its image library to load the acquired video for subsequent processing, 30 frames of images will be read in each second. In order to speed up the image processing speed and reduce the memory consumption, each frame of the video can be compressed. It should be noted that the method used to process the video data is not limited here, that is, other languages ​​that can load and process videos can be used instead of being limited to python.

[0051] In some feasible implementations, the step S3: the controller uses the Brenner algorithm to evaluate the real-time state image data of the windshield to obtain the blur state of the windshield, including: S310: using the Brenner algorithm to calculate the square of the grayscale difference between adjacent pixels in the real-time state image data of the automobile windshield to obtain a blur index; S320: evaluating the blur state of the automobile windshield based on the blur index; the Brenner algorithm includes: In the formula, FBrenner is the blur index, f(x+2,y) and f(x,y) represent the grayscale values ​​of the image at the pixel points (x+2,y) and (x,y), respectively, and m and n are the width and height of the real-time state image of the windshield. The Brenner function has a small amount of calculation and can quickly evaluate the clarity of the image by calculating the square of the grayscale difference between two pixels. This method is very useful for real-time autofocus systems, as it can quickly provide an indicator of image clarity. It not only ensures the accuracy of the evaluation, but also ensures that the system calculation is small, ensuring that the on-board equipment can bear the calculation pressure.

[0052] In some feasible implementations, the step S4: the controller determines whether it is necessary to control the wiper to start working based on the blur state of the windshield, including: S410: based on the comparison of the blur index of the automobile windshield with a preset blur threshold, when the blur index of the automobile windshield is greater than or equal to the blur threshold, it is determined that the wiper needs to be controlled to start working; when the blur index of the automobile windshield is less than the blur threshold, it is determined that it is not necessary to control the wiper to start working. Specifically, the preset blur threshold is determined through experiments, and is not limited here. Relevant technicians can set it based on actual needs during actual application.

[0053] In some feasible implementations, the step S5: in response to the need to control the wiper to start working, the controller obtains the operating frequency of the wiper based on a preset wiper operating frequency calculation formula, including:

[0054] The preset wiper operating frequency calculation formula is:

[0055] f=k×FBrenner+b; where f is the operating frequency of the wiper, FBrenner is the windshield blur index, k is the frequency scaling factor, and b is a constant. The higher the calculated image blur index, the greater the PWM wave frequency output to the stepper motor, and the frequency is proportional to the blur value, thus realizing stepless control of the wiper operating frequency.

[0056] In some feasible implementations, the step S6: the controller controls the vehicle system to output a PWM wave with a frequency equal to the working frequency of the wiper based on the working frequency of the wiper to drive the motor of the wiper to work, including: S610: when the controller determines that the wiper needs to be controlled to work, the working frequency is converted into an electrical signal by digital modulation and sent to the vehicle system; S620: the vehicle system sends a PWM wave to the motor based on the electrical signal to drive the motor to drive the wiper to work at the working frequency.

[0057] In some feasible implementations, the motor in step S6 is a stepper motor, which is connected to the wiper and used to control the operating frequency of the wiper. Using a stepper motor to drive the wiper has the advantages of high control accuracy, fast response speed, low operating noise and high reliability, and can achieve stepless control of the operating frequency of the wiper.

[0058] In the above-mentioned embodiment, it is only necessary to collect the video of the windshield as input through the camera, and then combine it with the corresponding video image processing method and signal analysis processing method, so as to conveniently and accurately calculate the blur degree of the windshield, and then control the wiper to work in accordance with the blur degree. It makes up for the shortcomings of traditional wipers, such as low automation, not simple operation, and inaccurate adjustment of wiper working frequency. It can achieve more accurate determination of windshield cleanliness without manual intervention, and automatically and infinitely control the operation of the wiper. It is suitable for target groups in complex environments or with high requirements for automation and ease of operation. The present invention has the advantages of high accuracy, convenience, no need for manual intervention, and infinitely variable speed regulation.

[0059] Example 2

[0060] See also Figure 3 , is a schematic diagram of the structure of a system for self-adjusting wipers based on the blur level of a car windshield provided in this embodiment.

[0061] As a strength, the system adopts the method of self-adjusting wipers based on the blur degree of the car windshield as described in Example 1. The wiper self-adjusting system includes a camera 1, a controller 2, a vehicle system 3 and a wiper 4. The camera 1 is placed at the car windshield, the controller 2 is integrated in the vehicle system 3, and the camera 1 communicates with the controller 2 via Ethernet.

[0062] The camera 1 is used to obtain video data of the automobile windshield in real time and transmit it to the controller;

[0063] The controller 2 integrates a real-time state image data acquisition module 210 , a fuzzy state evaluation module 220 , a judgment module 230 , a wiper operating frequency calculation module 240 and a driving module 250 .

[0064] The real-time state image data acquisition module 210 is adapted to perform frame sampling on the video data based on a preset sampling frequency to acquire the real-time state image data of the windshield.

[0065] The blur state evaluation module 220 is adapted to evaluate the real-time state image data of the windshield using the Brenner algorithm to obtain the blur state of the windshield.

[0066] The determination module 230 is adapted to determine whether the wiper needs to be controlled to start working based on the blur state of the windshield.

[0067] The wiper operating frequency calculation module 240 is adapted to obtain the wiper operating frequency based on a preset wiper operating frequency calculation formula in response to a need to control the wiper to start operating.

[0068] The driving module 250 is suitable for controlling the vehicle system 3 to output a PWM wave with a frequency equal to the working frequency of the wiper based on the working frequency of the wiper to drive the motor of the wiper to work.

[0069] The wiper 4 is adapted to be controlled by a motor connected thereto to operate based on the operating frequency.

[0070] It is not difficult to find that this embodiment is a system embodiment corresponding to the first embodiment, and this embodiment can be implemented in conjunction with the first embodiment. The relevant technical details mentioned in the first embodiment are still valid in this embodiment, and in order to reduce repetition, they are not repeated here. Accordingly, the relevant technical details mentioned in this embodiment can also be applied in the first embodiment.

[0071] It is worth mentioning that all modules involved in this embodiment are logical units. In practical applications, a logical unit can be a physical unit, a part of a physical unit, or a combination of multiple physical units. In addition, in order to highlight the innovative part of the present invention, this embodiment does not introduce units that are not closely related to solving the technical problem proposed by the present invention, but this does not mean that there are no other units in this embodiment.

[0072] Example 3

[0073] See also Figure 4 An embodiment of the present invention further provides an electronic device, comprising: a memory and a processor; the memory stores at least one program instruction; the processor loads and executes the at least one program instruction to implement the method for self-adjusting the wiper based on the blur degree of the automobile windshield provided in Example 1.

[0074] The memory 702 and the processor 701 are connected in a bus manner, and the bus may include any number of interconnected buses and bridges, and the bus connects various circuits of one or more processors 701 and the memory 702 together. The bus can also connect various other circuits such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art and are therefore not further described herein. The bus interface provides an interface between the bus and the transceiver. The transceiver can be one element or multiple elements, such as multiple receivers and transmitters, providing a unit for communicating with various other devices on a transmission medium. The data processed by the processor 701 is transmitted on a wireless medium via an antenna, and further, the antenna also receives data and transmits the data to the processor 701.

[0075] The processor 701 is responsible for managing the bus and general processing, and can also provide various functions, including timing, peripheral interfaces, voltage regulation, power management and other control functions. The memory 702 can be used to store data used by the processor 701 when performing operations.

[0076] Example 4

[0077] The embodiment of the present invention further provides a storage medium, on which is stored a method for self-adjusting a wiper based on the blur level of a car windshield, wherein when the program for self-adjusting a wiper based on the blur level of a car windshield is executed, the steps of the method for self-adjusting a wiper based on the blur level of a car windshield as described above are implemented. Since the storage medium adopts all the technical solutions of all the above embodiments, it has at least all the beneficial effects brought by the technical solutions of the above embodiments, which will not be described one by one here.

[0078] The above is only an embodiment of the present invention. The common sense such as the known specific structure and characteristics in the scheme is not described in detail here. The ordinary technicians in the relevant field know all the common technical knowledge in the technical field of the invention before the application date or priority date, can know all the existing technologies in the field, and have the ability to apply the conventional experimental means before that date. The ordinary technicians in the relevant field can improve and implement this scheme in combination with their own abilities under the enlightenment given by this application. Some typical known structures or known methods should not become obstacles for ordinary technicians in the relevant field to implement this application. It should be pointed out that for those skilled in the art, without departing from the structure of the present invention, several deformations and improvements can be made, which should also be regarded as the scope of protection of the present invention, which will not affect the effect of the implementation of the present invention and the practicality of the patent. The scope of protection required by this application shall be based on the content of its claims, and the specific implementation methods and other records in the specification can be used to interpret the content of the claims.

Claims

1. A method for self-adjusting wipers based on the blur level of a car windshield, characterized in that: The vehicle is integrated with a camera and a controller, the controller is integrated in a vehicle system, the camera is electrically connected to the controller, and the method includes: S1: acquiring video data of the automobile windshield in real time through the camera and transmitting the data to the controller; S2: the controller performs frame sampling on the video data based on a preset sampling frequency to obtain real-time state image data of the windshield; S3: the controller uses the Brenner algorithm to evaluate the real-time state image data of the windshield to obtain the blur state of the windshield; S4: the controller determines whether it is necessary to control the wiper to start working based on the blur state of the windshield; S5: In response to the need to control the wiper to start working, the controller obtains the operating frequency of the wiper based on a preset wiper operating frequency calculation formula; S6: The controller controls the vehicle computer system to output a PWM wave with a frequency equal to the working frequency of the wiper based on the working frequency of the wiper to drive the motor of the wiper to work; S7: The wiper is controlled by a motor connected thereto to operate based on the operating frequency; S8: In response to the fact that there is no need to control the wiper to start working, go to step S1.

2. The method for self-adjusting wipers based on the blur level of the automobile windshield according to claim 1, characterized in that: The step S1: acquiring video data of the automobile windshield in real time through the camera and transmitting the video data to the controller comprises: S110: During the process of starting the car, the video data of the car windshield is collected in real time by the camera and transmitted to the controller via Ethernet.

3. The method for self-adjusting wipers based on the blur level of automobile windshield according to claim 1, characterized in that: The step S2: the controller performs frame sampling on the video data based on a preset sampling frequency to obtain real-time state image data of the windshield, including: S210: After receiving the video data of the automobile windshield, the controller uses Python and its image library to load the acquired video data of the automobile windshield and pre-process the data; S220: Frame sampling is performed on the preprocessed video data at a preset sampling frequency to obtain N pieces of real-time status image data of the windshield.

4. The method for self-adjusting wipers based on the blur level of automobile windshield according to claim 3, characterized in that: The preprocessing in step S210 includes compressing each frame of the image in the collected video data of the automobile windshield.

5. The method for self-adjusting wipers based on the blur level of automobile windshield according to claim 1, characterized in that: The step S3: the controller uses the Brenner algorithm to evaluate the real-time state image data of the windshield to obtain the blur state of the windshield, including: S310: Calculating the square of the grayscale difference between adjacent pixels in the real-time state image data of the automobile windshield by using the Brenner algorithm to obtain a blur index; S320: Evaluate the blur state of the automobile windshield based on the blur index; The Brenner algorithm includes: Where FBrenner is the blur index, f(x+2,y) and f(x,y) represent the grayscale values ​​of the image at pixel points (x+2,y) and (x,y), respectively, and m and n are the width and height of the real-time state image of the windshield, respectively.

6. The method for self-adjusting wipers based on the blur level of the automobile windshield according to claim 5, characterized in that: The step S4: the controller determines whether to control the wiper to start working based on the blur state of the windshield, including: S410: Based on the comparison between the blur index of the automobile windshield and a preset blur threshold, when the blur index of the automobile windshield is greater than or equal to the blur threshold, it is determined that the wiper needs to be controlled to start working; when the blur index of the automobile windshield is less than the blur threshold, it is determined that the wiper does not need to be controlled to start working.

7. The method for self-adjusting wipers based on the blur level of automobile windshield according to claim 1, characterized in that: The step S5: in response to the need to control the wiper to start working, the controller obtains the working frequency of the wiper based on a preset wiper working frequency calculation formula, including: The preset wiper operating frequency calculation formula is: f = k × Fbrener + b; Where f is the operating frequency of the wiper, FBrenner is the windshield blur index, k is the frequency scaling factor, and b is a constant.

8. The method for self-adjusting wipers based on the blur level of automobile windshield according to claim 1, characterized in that: The step S6: the controller controls the vehicle system to output a PWM wave with a frequency equal to the working frequency of the wiper based on the working frequency of the wiper to drive the motor of the wiper to work, including: S610: When the controller determines that the wiper needs to be controlled to work, the controller converts the working frequency into an electrical signal by digital modulation and sends the signal to the vehicle computer system; S620: The vehicle system sends a PWM wave to the motor based on the electrical signal to drive the motor to drive the wiper to work at the working frequency.

9. The method for self-adjusting wipers based on the blur level of automobile windshield according to claim 1, characterized in that: The motor in step S6 is a stepper motor, which is connected to the wiper and is used to control the operating frequency of the wiper.

10. A system for self-adjusting wipers based on the degree of blurring of a car windshield, characterized in that: The system is implemented by the method for self-adjusting the wiper based on the blur degree of the automobile windshield as claimed in any one of claims 1 to 9, wherein the wiper self-adjusting system comprises a camera, a controller, a vehicle computer system and a wiper, wherein the camera is placed at the automobile windshield, the controller is integrated into the vehicle computer system, and the camera communicates with the controller via Ethernet; The camera is used to obtain video data of the automobile windshield in real time and transmit it to the controller; The controller is integrated with a real-time state image data acquisition module, a fuzzy state evaluation module, a judgment module, a wiper operating frequency calculation module and a driving module; The real-time state image data acquisition module is adapted to perform frame sampling on the video data based on a preset sampling frequency to acquire real-time state image data of the windshield; The fuzzy state evaluation module is adapted to evaluate the real-time state image data of the windshield using the Brenner algorithm to obtain the fuzzy state of the windshield; The judgment module is adapted to judge whether it is necessary to control the wiper to start working based on the fuzzy state of the windshield; The wiper operating frequency calculation module is adapted to, in response to a need to control the wiper to start operating, obtain the wiper operating frequency based on a preset wiper operating frequency calculation formula; The driving module is adapted to control the vehicle computer system to output a PWM wave with a frequency equal to the working frequency of the wiper based on the working frequency of the wiper to drive the motor of the wiper to work; The wiper is adapted to be controlled by a motor connected thereto to operate based on the operating frequency.

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