A method and system for detecting the state of a self-powered flower drum

Abstract

The application relates to a self-generating flower drum state detection method and system, and relates to the field of flower drum use detection, which comprises the following steps: step 100: collecting a driving state of a vehicle, and determining a vehicle-mounted battery power based on the driving state; step 101: when the vehicle-mounted battery power is less than a preset power threshold value, determining a wheel rotating speed based on the driving state; step 102: determining a flower drum power generation amount according to the wheel rotating speed; step 103: when the flower drum power generation amount is greater than a preset power generation threshold value, determining a charging power amount according to the flower drum power generation amount; and step 104: if the charging power amount is not greater than a preset power supply threshold value, generating and sending a flower drum direct power supply instruction, and generating and displaying a use state detection report in response to the flower drum power generation amount. The application has the effects of improving the precision of self-generating flower drum use state detection and accurately detecting the flower drum use state.

Description

Technical Field

[0001] This invention relates to the field of hub usage testing, and in particular to a method and system for testing the condition of self-generating hubs. Background Technology

[0002] A self-generating hub is a device that converts the mechanical energy of a rotating wheel into electrical energy.

[0003] In the existing technology, self-generating hubs are generally installed on vehicles. They convert the kinetic energy of the wheel rotation into electrical energy to charge the vehicle battery. The generated electricity can power the vehicle's electrical appliances, such as headlights. However, the power generated by the hub to charge the vehicle battery will result in losses.

[0004] When the remaining power after the power loss is small, it may not be able to support the normal operation of the headlights. In this case, the hub status may be misjudged based on the headlight display status. Summary of the Invention

[0005] To improve the accuracy of detecting the usage status of self-generating hubs and to accurately detect the usage status of hubs, this invention provides a method and system for detecting the status of self-generating hubs.

[0006] In a first aspect, the present invention provides a method for detecting the state of a self-generating hub, employing the following technical solution:

[0007] This invention provides a method for detecting the state of a self-generating flower drum, comprising:

[0008] Step 100: Collect the vehicle's driving status and determine the vehicle battery level based on the driving status;

[0009] Step 101: When the vehicle battery charge is less than a preset charge threshold, determine the wheel speed based on the driving state;

[0010] Step 102: Determine the power generation of the hub based on the wheel speed;

[0011] Step 103: When the power generation of the hub is greater than the preset power generation threshold, determine based on the power generation of the hub.

[0012] Charging capacity;

[0013] Step 104: If the charging power is not greater than the preset power supply threshold, generate and send a hub direct supply command, and respond to the hub power generation by generating and displaying a usage status detection report.

[0014] By adopting the above technical solution, the vehicle battery power is extracted, and when the vehicle battery power is too low, the wheel speed is extracted from the driving state. The hub power generation is calculated based on the wheel speed. If the hub power generation is sufficient to power the headlights, it is determined whether the loss caused by sending the power generated by the hub to the vehicle battery can power the headlights. When the hub power generation is insufficient to power the headlights, the hub power generation is directly supplied to the vehicle headlights and the power supply status of the hub is displayed, thereby improving the accuracy of hub usage status recognition.

[0015] Optionally, it also includes a display state determination method, the display state determination method comprising:

[0016] Step 105: If the charging power is not greater than the preset power supply threshold, acquire driving images;

[0017] Step 106: Extract the left and right view images from the driving image, and identify the two maximum brightness values ​​and brightness value locations based on the left and right view images;

[0018] Step 107: Calculate the brightness difference based on the two maximum brightness values, and determine the brightness distance according to the position of the brightness values;

[0019] Step 108: Calculate the quotient of the brightness difference and the brightness distance as the attenuation coefficient;

[0020] Step 109: Determine the headlight brightness based on the attenuation coefficient, and generate a brightness time correspondence table based on the headlight brightness;

[0021] Step 110: Generate and display a display status report of the vehicle lights in response to the brightness time correspondence table.

[0022] By adopting the above technical solution, when the power generated by the hub is delivered to the vehicle battery and the resulting loss is insufficient to power the headlights, driving images during the driving process are collected, the headlight brightness is extracted from the images, and a brightness time correspondence table is generated based on the headlight brightness. Thus, by detecting the headlight display status, the stability of the hub's direct power supply is indirectly verified, making the hub's usage status detection more accurate.

[0023] Optionally, the display state determination method further includes:

[0024] Step 111: When the attenuation coefficient is greater than the preset attenuation threshold, select the larger image with the larger brightness value from the left and right view images based on the two maximum brightness values;

[0025] Step 112: Determine the relative position of the larger brightness value based on the larger image;

[0026] Step 113: Determine the mirror position based on the relative position, and extract the smaller brightness value from the driving image based on the mirror position;

[0027] Step 114: Update the headlight brightness in response to the lower brightness value.

[0028] By adopting the above technical solution, when the headlights malfunction, the brightness of the headlight with the larger brightness value is used as the reference brightness. The position of the axis symmetry of the reference brightness is determined from the driving image as the position of the smaller brightness value. The brightness of this position is identified as the smaller brightness value and defined as the headlight brightness. The headlight brightness can be calibrated when the brightness of two headlights is abnormal, thereby improving the accuracy of headlight display status recognition.

[0029] Optionally, the display state determination method further includes:

[0030] Step 115: When the attenuation coefficient is greater than the preset attenuation threshold, determine the larger brightness value based on the larger image;

[0031] Step 116: Determine the brightness distribution map based on the larger brightness value;

[0032] Step 117: Determine smaller images based on the larger images, and identify smaller distribution maps from the smaller images;

[0033] Step 118: Calculate the difference between the smaller distribution map and the brightness distribution map, and define it as the difference distribution map;

[0034] Step 119: In response to the difference distribution map, identify the difference brightness and update the smaller brightness value.

[0035] By adopting the above technical solution, when a single headlight malfunctions, the brightness of the malfunctioning headlight is easily affected by the normal headlights, which can lead to errors in brightness recognition. In this case, the influence of the normal headlights on the malfunctioning headlights can be estimated based on the brightness of the normal headlights, thereby reducing the influence of higher brightness on lower brightness, accurately adjusting the lower brightness value, and further improving the detection accuracy of headlight display status.

[0036] Optionally, it also includes a method for determining flicker anomalies, the method comprising:

[0037] Step 200: Extract the on / off time correspondence tables for each of the two vehicle lights from the brightness time correspondence table;

[0038] Step 201: Determine the flicker frequency of the vehicle lights based on the corresponding table of on / off times;

[0039] Step 202: When the flicker frequency is greater than a preset frequency threshold, determine the anomaly probability based on the flicker frequency;

[0040] Step 203: In response to the anomaly probability generation, display a flashing anomaly warning.

[0041] By adopting the above technical solution, the on / off time correspondence table of different vehicle lights is extracted from the brightness time correspondence table. The frequency of on / off is determined according to the on / off time correspondence table. When the frequency of on / off is high, the vehicle light display is judged to be abnormal. The probability of flickering is determined according to the number of on / off frequencies, and a flickering abnormality warning is generated according to the abnormality probability. This indirectly judges the stability of hub power generation and further improves the detection dimension of hub usage status.

[0042] Optionally, the flicker anomaly determination method further includes:

[0043] Step 204: Based on the flickering abnormality warning, acquire an interface image of the hub and determine the wire characteristics from the interface image;

[0044] Step 205: Determine the interface length from the interface image based on the cable characteristics;

[0045] Step 206: Determine the loosening distance based on the interface length;

[0046] Step 207: If the loosening distance is greater than a preset distance threshold, determine the loosening probability based on the loosening distance;

[0047] Step 208: In response to the loosening probability generation, display an interface loosening warning.

[0048] By adopting the above technical solution, when the headlights flicker abnormally, the hub interface image is collected, the loosening distance of the connector is determined from the interface image, if the loosening distance is large, the loosening probability is determined according to the loosening distance, and an interface loosening warning is generated according to the loosening probability. The abnormal headlight flickering is associated with the hub interface loosening, and the cause of the flickering abnormality is further determined.

[0049] Optionally, the flicker anomaly determination method further includes:

[0050] Step 209: If the detachment distance is greater than a preset distance threshold, identify the actual height of the vehicle from the driving image;

[0051] Step 210: Compare the preset reference height with the actual height to determine the degree of bumpiness;

[0052] Step 211: Calculate the correlation coefficient by combining the degree of bumpiness and the flicker frequency;

[0053] Step 212: If the correlation coefficient is greater than the preset correlation threshold, update the loosening probability based on the loosening distance and the correlation coefficient.

[0054] By adopting the above technical solution, when the loosening distance is large, the degree of vehicle bumpiness is determined by comparing the actual height of the vehicle with the reference height. Then, the correlation coefficient is calculated by the degree of bumpiness and the flicker frequency. If the correlation coefficient is large, it is determined that the degree of bumpiness has a greater impact on the flicker, further verifying the causal relationship between the flicker abnormality and the interface loosening, and improving the accuracy of the cause of the flicker abnormality.

[0055] Optionally, it also includes an aging determination method, the aging determination method comprising:

[0056] Step 300: If the loosening distance is not greater than a preset distance threshold, determine the increase brightness value based on the headlight brightness, and determine the acceleration speed based on the increase brightness value;

[0057] Step 301: Calculate the expected rotational speed by combining the wheel rotational speed and acceleration speed;

[0058] Step 302: When the wheel speed matches the expected speed, update the headlight brightness based on the expected speed;

[0059] Step 303: Compare the brightness of the headlights to determine the increase in brightness;

[0060] Step 304: If the growth rate is lower than the growth brightness value, determine the aging probability based on the growth rate;

[0061] Step 305: In response to the aging probability generation, an aging warning is displayed.

[0062] By adopting the above technical solution, when there is no risk of the interface becoming loose, there is a certain increase in brightness from the current brightness value to the point where the headlight becomes bright enough to be clearly detected. Reaching this increase in brightness value requires a certain acceleration. Based on the wheel speed at the current brightness value, the wheel speed after acceleration is estimated. When the estimated wheel speed is reached, the headlight brightness is identified. If the increase in headlight brightness between the previous brightness value and the previous brightness value is less than the increase in brightness value before reaching the previous value, the hub is judged to be aging. This eliminates the influence of interface loosening on hub status detection and improves the accuracy of hub aging status judgment.

[0063] Optionally, the aging determination method further includes:

[0064] Step 306: Identify the water accumulation area from the driving image, extract the water-filled road section from the driving image based on the water accumulation area, and retrieve the vehicle position from the driving status;

[0065] Step 307: Determine the duration of wading by comparing the waterlogged sections and vehicle locations;

[0066] Step 308: Determine the degree of aging by combining the immersion time and the rate of increase;

[0067] Step 309: Generate and display an aging status report in response to the aging level.

[0068] By adopting the above technical solution, road sections with water accumulation are extracted from driving images, and the total time the vehicle spends in the water-filled road section is calculated and defined as the wading time. The longer the wading time, the more serious the aging. Thus, the aging degree is quantified by analyzing the impact of wading time on hub aging, making hub aging detection more consistent with the actual working environment of sanitation vehicles.

[0069] Secondly, this application provides a condition detection system for self-generating hubs, employing the following technical solution:

[0070] A condition detection system for self-generating hubs includes:

[0071] The data acquisition module is used to collect driving status data.

[0072] A memory for storing the program for any of the above-mentioned methods for detecting the state of a self-generating flower drum;

[0073] The processor is the unit of memory that allows programs to be loaded and executed by the processor.

[0074] By adopting the above technical solution, the vehicle battery power is extracted, and when the vehicle battery power is too low, the wheel speed is extracted from the driving state. The hub power generation is calculated based on the wheel speed. If the hub power generation is sufficient to power the headlights, it is determined whether the loss caused by sending the power generated by the hub to the vehicle battery can power the headlights. When the hub power generation is insufficient to power the headlights, the hub power generation is directly supplied to the vehicle headlights and the power supply status of the hub is displayed, thereby improving the accuracy of hub usage status recognition.

[0075] In summary, this application includes at least one of the following beneficial technical effects:

[0076] 1. Extract the vehicle battery power and extract the wheel speed from the driving status when the vehicle battery power is too low. Calculate the hub power generation based on the wheel speed. If the hub power generation is sufficient to power the headlights, determine whether the loss caused by sending the power generated by the hub to the vehicle battery can power the headlights. When the hub power generation is insufficient to power the headlights, directly power the vehicle headlights with the hub power generation and display the hub power supply status to improve the accuracy of hub usage status recognition.

[0077] 2. When the remaining power after the power generated by the hub is delivered to the vehicle battery is insufficient to power the headlights, the driving images during the driving process are captured, the headlight brightness is extracted from the images, and a brightness time correspondence table is generated based on the headlight brightness. By detecting the headlight display status, the stability of the hub's direct power supply is indirectly verified, making the hub's usage status detection more accurate.

[0078] 3. When a headlight malfunctions, the brightness of the headlight with the higher brightness value is used as the reference brightness. The position of the axis symmetry of the reference brightness is determined from the driving image as the position of the smaller brightness value. The brightness of this position is identified as the smaller brightness value and defined as the headlight brightness. This can be used to calibrate the headlight brightness when the brightness of two headlights is abnormal, thereby improving the accuracy of headlight display status recognition. Attached Figure Description

[0079] Figure 1 This is a flowchart of a method for detecting the condition of a self-generating hub.

[0080] Figure 2 This is a flowchart of the method for determining strobe;

[0081] Figure 3 This is a flowchart of the aging determination method. Detailed Implementation

[0082] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0083] Reference Figure 1 A method for detecting the condition of a self-generating hub, comprising:

[0084] Step 100: Collect the vehicle's driving status and determine the vehicle battery power based on the driving status.

[0085] Driving status refers to the performance status of various parameters of the vehicle during driving. Driving status includes information such as wheel speed, on-board battery charge, vehicle position, and driving time. Driving status can be retrieved from the vehicle's infotainment system, and the method of collecting driving status is selected by the staff according to the actual situation.

[0086] Vehicle battery power refers to the remaining amount of electricity that the vehicle battery can supply for vehicle operation. The vehicle battery power can be extracted while the vehicle is in motion. The method for extracting vehicle battery power is selected by the staff based on the actual situation.

[0087] Step 101: When the vehicle battery charge is less than a preset charge threshold, determine the wheel speed based on the driving state.

[0088] The battery power threshold refers to the minimum remaining battery power required for the vehicle to operate normally. This threshold is selected by the staff based on the actual situation. A battery power level below the threshold indicates insufficient battery power for normal vehicle operation. Wheel speed refers to the number of revolutions a wheel makes around its axle per unit time. Wheel speed can be extracted from the driving status, and the extraction method is selected by the staff based on the actual situation.

[0089] Step 102: Determine the power generation of the hub based on the wheel speed.

[0090] Hub power generation refers to the amount of electrical energy converted from the kinetic energy of the rotating wheel. The higher the wheel speed, the higher the hub power generation. You can look up the hub power generation corresponding to different wheel speeds in the hub power generation correspondence table. The hub power generation correspondence table is a data table that records different wheel speeds and their corresponding hub power generation.

[0091] Step 103: When the power generation of the hub is greater than the preset power generation threshold, the charging power is determined based on the power generation of the hub.

[0092] The power generation threshold refers to the minimum amount of power generated by the hub that is sufficient to power the vehicle's lights. This threshold is selected by the operator based on the actual situation. A hub power generation exceeding the threshold indicates that the hub's power generation is sufficient to power the vehicle's lights. The charging capacity refers to the amount of electricity generated by the hub that powers the vehicle's battery. The charging capacity can be found in the charging capacity correspondence table, which records the charging capacity of different hubs and their corresponding charging capacities.

[0093] Step 104: If the charging power is not greater than the preset power supply threshold, generate and send a hub direct supply command, and respond to the hub power generation by generating and displaying a usage status detection report.

[0094] The power supply threshold refers to the minimum amount of electricity remaining after losses incurred by the battery during charging, which is sufficient to power the vehicle lights. This threshold is selected by the operator based on the actual situation. A charging quantity not exceeding the power supply threshold means that the remaining electricity after losses incurred by the battery is insufficient to power the vehicle lights. The hub direct supply command refers to the command that directly supplies the generated electricity from the hub to the vehicle lights to power them. This command is also selected by the operator based on the actual situation.

[0095] The usage status test report is used to show the staff the connection status between the hub and the headlight, that is, whether the hub directly supplies power to the headlight. After the usage status test report is generated, it is sent to the staff's terminal for the staff to view. The method of generating the usage status test report is common knowledge to those in the field.

[0096] The system extracts the vehicle battery power and, when the battery power is low, extracts the wheel speed from the driving status. It calculates the hub power generation based on the wheel speed. If the hub power generation is sufficient to power the headlights, it determines whether the loss caused by sending the power generated by the hub to the vehicle battery is enough to power the headlights. When the hub power generation is insufficient to power the headlights, it directly supplies the vehicle headlights with the hub power generation and displays the hub's power supply status, thus improving the accuracy of hub usage status recognition.

[0097] It also includes a method for determining the display status:

[0098] Step 105: If the charging power is not greater than the preset power supply threshold, acquire driving images.

[0099] Driving images refer to images of the road conditions in front of a vehicle while it is in motion. These images are typically captured by a camera fixed to the front of the vehicle, and a vehicle driving recorder can be used as the camera. The method of capturing driving images is selected by the staff based on the actual situation.

[0100] Step 106: Extract the left and right view images from the driving image, and identify the two maximum brightness values ​​and brightness value locations based on the left and right view images.

[0101] The left and right view images refer to the two images obtained by dividing the driving image in half. The driving image is divided into several images according to the setting of the headlights. In this embodiment, the headlights are set symmetrically on the left and right sides of the front of the vehicle as an example. The left and right view images can be extracted from the driving image by image processing technology. The extraction methods of the left and right view images are common knowledge known to those in the art.

[0102] The maximum brightness value refers to the two largest brightness values ​​in the left and right view images. This maximum brightness value can be identified from the left and right view images using image processing techniques, and the method for identifying the maximum brightness value is common knowledge to those skilled in the art. The brightness value position refers to the location of the maximum brightness value within the left and right view images. This brightness value position can be identified from the left and right view images using image processing techniques, and the method for identifying the brightness value position is common knowledge to those skilled in the art.

[0103] Step 107: Calculate the brightness difference based on the two maximum brightness values, and determine the brightness distance according to the position of the brightness values.

[0104] The brightness difference refers to the difference between two maximum brightness values. The difference between the two maximum brightness values ​​can be calculated as the brightness difference. The calculation method for the brightness difference is selected by the staff based on the actual situation.

[0105] Brightness distance refers to the distance between two brightness value positions. The difference between the two brightness value positions is calculated as the brightness distance. The calculation method for brightness distance is selected by the staff based on the actual situation.

[0106] Step 108: Calculate the quotient of the brightness difference and the brightness distance as the attenuation coefficient.

[0107] The attenuation coefficient is a quantitative indicator of how much brightness decreases with distance. It can be calculated as the quotient of the brightness difference and the brightness distance. The calculation method for the attenuation coefficient is selected by the staff based on the actual situation.

[0108] Step 109: Determine the headlight brightness based on the attenuation coefficient, and generate a brightness time correspondence table based on the headlight brightness.

[0109] Headlight brightness refers to an optical indicator that measures the intensity of light emitted by a headlight. When multiple headlights are emitting light normally at the same time, the superposition of the light causes the attenuation coefficient to decrease. If a headlight malfunctions, the attenuation coefficient is likely to increase. The larger the attenuation coefficient, the dimmer the headlight brightness. You can look up the headlight brightness corresponding to different attenuation coefficients in the headlight brightness correspondence table. The headlight brightness correspondence table is a data table that records different attenuation coefficients and their corresponding headlight brightness.

[0110] A brightness time correspondence table is a data table that records different times and their corresponding headlight brightness. When a headlight malfunctions and causes the attenuation coefficient to increase, the brightness at the position corresponding to the larger maximum brightness value is defined as 100, and the headlight brightness is defined as the brightness of the headlight on the other side. A brightness time correspondence table can be generated from the headlight brightness.

[0111] Step 110: Generate and display a display status report of the vehicle lights in response to the brightness time correspondence table.

[0112] The display status report refers to the information displayed to the staff regarding the brightness of the vehicle lights, and the method for generating the display status report is common knowledge to those in the field.

[0113] When the remaining power after the hub delivers electricity to the vehicle battery is insufficient to power the headlights, driving images are captured during the journey. The headlight brightness is extracted from the images, and a brightness time correspondence table is generated based on the headlight brightness. By detecting the headlight display status, the stability of the hub's direct power supply is indirectly verified, making the hub's usage status detection more accurate.

[0114] The methods for determining the display status also include:

[0115] Step 111: When the attenuation coefficient is greater than the preset attenuation threshold, select the larger image with the larger brightness value from the left and right view images based on the two maximum brightness values.

[0116] The attenuation threshold refers to the minimum value at which the brightness of a headlight normally decreases. The attenuation threshold is selected by the staff based on the actual situation. An attenuation coefficient greater than the attenuation threshold indicates that a headlight has malfunctioned. A larger image refers to the image containing the largest maximum brightness value. The method for selecting a larger image is also selected by the staff based on the actual situation.

[0117] Step 112: Determine the relative position of the larger brightness value based on the larger image.

[0118] Relative position refers to the position of brightness value in a larger image. The method for identifying relative position is selected by the staff based on the actual situation.

[0119] Step 113: Determine the mirror position based on the relative position, and extract the smaller brightness value from the driving image based on the mirror position.

[0120] A mirror position refers to the corresponding spatial position in another image that is symmetrical about the relative position. A mirror position can be obtained by flipping the relative position symmetrically.

[0121] The smaller brightness value refers to the maximum brightness value in a smaller image. The smaller brightness value can be extracted from a driving image using image processing techniques. The method for extracting the smaller brightness value is common knowledge to those in the field.

[0122] Step 114: Update the headlight brightness in response to the lower brightness value.

[0123] The brightness value corresponding to the larger maximum brightness value is defined as 100, and the smaller brightness value is defined as the brightness of the headlight on the other side.

[0124] When a headlight malfunctions, the brightness of the headlight with the higher brightness value is used as the reference brightness. The position of the smaller brightness value is determined from the position of the reference brightness in the driving image. The brightness of this position is identified as the smaller brightness value and defined as the headlight brightness. This allows for the calibration of headlight brightness when the brightness of two headlights is abnormal, improving the accuracy of headlight display status recognition.

[0125] The methods for determining the display status also include:

[0126] Step 115: When the attenuation coefficient is greater than the preset attenuation threshold, determine the larger brightness value based on the larger image.

[0127] The larger brightness value refers to the maximum brightness value in a larger image. The larger brightness value can be retrieved from the maximum brightness value. The method for retrieving the larger brightness value is selected by the staff according to the actual situation.

[0128] Step 116: Determine the brightness distribution map based on the larger brightness value.

[0129] A brightness distribution map refers to the area affected by larger brightness values ​​in a larger image. The influence range corresponding to different brightness values ​​can be found in an influence range mapping table, which records different brightness values ​​and their corresponding influence ranges. The brightness distribution map is obtained by mapping the locations of larger brightness values ​​to the brightness values ​​in the influence range mapping table.

[0130] Step 117: Determine a smaller image based on the larger image, and identify a smaller distribution map from the smaller image.

[0131] A smaller image refers to the image containing the smaller maximum brightness value. The smaller image is the image in the driving image excluding the larger image.

[0132] A smaller distribution map refers to the brightness value of each location in a smaller image. The smaller distribution map can be extracted from a smaller image using image processing techniques. The extraction method of the smaller distribution map is common knowledge to those in the field.

[0133] Step 118: Calculate the difference between the smaller distribution map and the brightness distribution map, and define it as the difference distribution map.

[0134] The difference distribution map refers to the brightness of the light emitted by a single faulty headlight at each position in the image. Brighter headlights tend to illuminate dimmer headlights, leading to inaccurate brightness of dimmer headlights. The difference distribution map can be calculated by comparing the smaller distribution map and the brightness distribution map. The calculation method for the difference distribution map is selected by the staff based on the actual situation.

[0135] Step 119: In response to the difference distribution map, identify the difference brightness and update the smaller brightness value.

[0136] Difference brightness refers to the maximum brightness of the faulty vehicle light. The maximum brightness can be extracted from the difference distribution map as the difference brightness. The method for extracting difference brightness is selected by the staff based on the actual situation.

[0137] The brightness at the position corresponding to the difference brightness is defined as the smaller brightness value.

[0138] When a single headlight malfunctions, its brightness is easily affected by the normal headlights, leading to errors in brightness recognition. In this case, the impact of the normal headlights on the malfunctioning headlights can be estimated based on their brightness, thereby reducing the influence of higher brightness on lower brightness, accurately adjusting the lower brightness value, and further improving the accuracy of headlight status detection.

[0139] Reference Figure 2 Methods for determining flicker include:

[0140] Step 200: Extract the on / off time correspondence tables for each of the two vehicle lights from the brightness time correspondence table.

[0141] The on / off time correspondence table is a data table that records different times and their corresponding on / off states of the vehicle lights. The on / off time correspondence table can be extracted from the brightness time correspondence table. That is, when the brightness is not 0, it means that the vehicle light display state is on, and when the brightness is 0, it means that the vehicle light display state is off.

[0142] Step 201: Determine the flicker frequency of the vehicle lights based on the corresponding table of on / off times.

[0143] The flicker frequency refers to the number of times the headlights turn on and off within the update cycle. The flicker frequency can be found by looking up the table corresponding to the on / off times. The update cycle refers to the time interval between updates to the table corresponding to the on / off times.

[0144] Step 202: When the flicker frequency is greater than the preset frequency threshold, determine the abnormal probability based on the flicker frequency.

[0145] The frequency threshold refers to the maximum normal number of headlight flashes within the update cycle. The frequency threshold is selected by staff based on actual conditions. A flash frequency greater than the frequency threshold indicates an abnormal number of headlight on / off cycles within the update cycle. The anomaly probability is a numerical value used to display abnormal headlight on / off cycles; the higher the flash frequency, the greater the anomaly probability. The anomaly probability can be found in the anomaly probability correspondence table, which records different flash frequencies and their corresponding anomaly probabilities.

[0146] Step 203: In response to the anomaly probability generation, display a flashing anomaly warning.

[0147] A strobe abnormality warning is a message used to notify staff of abnormal flashing of vehicle lights. The method for generating a strobe abnormality warning is common knowledge to those in the field.

[0148] Extract the on / off time correspondence table for different vehicle lights from the brightness time correspondence table, determine the frequency of on / off based on the on / off time correspondence table, judge the vehicle light display abnormal when the on / off frequency is high, determine the abnormal probability of flickering based on the number of on / off frequencies, and generate a flickering abnormality warning based on the abnormal probability, thereby indirectly judging the stability of hub power generation and further improving the detection dimension of hub usage status.

[0149] Methods for determining flicker also include:

[0150] Step 204: Based on the flickering abnormality warning, acquire an interface image of the hub and determine the wire characteristics from the interface image.

[0151] When a warning of abnormal headlight flashing is issued, a picture of the hub interface is captured. The interface picture is a picture that clearly shows the connection interface between the hub and the vehicle. The interface picture can be captured by a camera, and the method of capturing the interface picture is selected by the staff according to the actual situation.

[0152] Cable features refer to the image features of the cables on both sides of the interface. Cable features can be identified from the interface image through image processing technology. The methods for identifying cable features are common knowledge to those in the field.

[0153] Step 205: Determine the interface length from the interface image based on the cable characteristics.

[0154] Interface length refers to the length of the male and female connectors of the power supply lines connecting the hub and the vehicle. The interface length can be identified from the interface image using image processing technology. The method for identifying interface length is common knowledge to those in the field.

[0155] Step 206: Determine the loosening distance based on the interface length.

[0156] The loosening distance refers to the length at which the male connector detaches from the female connector at the interface. The loosening distance is calculated as the difference between the interface length and the mating length. The mating length refers to the length at which the male connector does not detach from the female connector. The mating length is selected by the staff based on the actual situation.

[0157] Step 207: If the loosening distance is greater than a preset distance threshold, determine the loosening probability based on the loosening distance.

[0158] The distance threshold refers to the maximum distance at which an interface is at risk of detachment. This threshold is selected by staff based on actual conditions. A detachment distance greater than the distance threshold indicates a risk of detachment. The detachment probability is a numerical value used to represent this risk; a longer detachment distance results in a higher probability. The detachment probability can be found in a table that records different detachment distances, correlation coefficients, and their corresponding detachment probabilities.

[0159] Step 208: In response to the loosening probability generation, display an interface loosening warning.

[0160] Interface detachment warnings are information used to notify staff of the risk of interface detachment. The method for generating interface detachment warnings is common knowledge in the field.

[0161] When the headlights flicker abnormally, the hub interface image is captured, and the loosening distance of the connector is determined from the interface image. If the loosening distance is large, the loosening probability is determined based on the loosening distance, and an interface loosening warning is generated based on the loosening probability. The abnormal headlight flickering is associated with the hub interface loosening to further determine the cause of the flickering abnormality.

[0162] Methods for determining flicker also include:

[0163] Step 209: If the detachment distance is greater than a preset distance threshold, identify the actual height of the vehicle from the driving image.

[0164] Actual height refers to the actual height of a vehicle at each position during driving. The actual height can be identified from driving images using image processing technology. The method for identifying actual height is common knowledge to those in the field.

[0165] Step 210: Compare the preset reference height with the actual height to determine the degree of bumpiness.

[0166] The reference height refers to the height of a vehicle on a stable surface. The method for determining the reference height is selected by the staff based on the actual situation.

[0167] The degree of bumpiness refers to the degree of deviation between the actual height and the reference height. The standard deviation between the actual height and the reference height can be calculated as the degree of bumpiness. The method for calculating the degree of bumpiness is selected by the staff according to the actual situation.

[0168] Step 211: Calculate the correlation coefficient by combining the degree of turbulence and the flicker frequency.

[0169] The correlation coefficient refers to the degree of linear correlation between the degree of bumpiness and the frequency of flicker. The linear correlation coefficient between the degree of bumpiness and the frequency of flicker can be calculated as the correlation coefficient. The method for calculating the correlation coefficient is selected by the staff according to the actual situation.

[0170] Step 212: If the correlation coefficient is greater than the preset correlation threshold, update the loosening probability based on the loosening distance and the correlation coefficient.

[0171] The relevant threshold refers to the minimum normal impact of the degree of vibration on the flicker frequency. The relevant threshold is selected by the staff based on the actual situation. A correlation coefficient greater than the relevant threshold indicates that the degree of vibration has an excessive impact on the flicker frequency. The larger the correlation coefficient, the higher the probability of detachment. The detachment probability corresponding to different correlation coefficients and detachment distances can be found in the detachment probability correspondence table.

[0172] When the detachment distance is large, the degree of vehicle bumpiness is determined by comparing the actual height of the vehicle with the reference height. Then, the correlation coefficient is calculated by comparing the degree of bumpiness with the flicker frequency. If the correlation coefficient is large, it is determined that the degree of bumpiness has a greater impact on the flicker, which further verifies the causal relationship between the flicker abnormality and the interface detachment, and improves the accuracy of the cause of the flicker abnormality.

[0173] Reference Figure 3 Methods for determining aging include:

[0174] Step 300: If the loosening distance is not greater than a preset distance threshold, determine the increase brightness value based on the headlight brightness, and determine the acceleration speed based on the increase brightness value.

[0175] A loosening distance not exceeding the distance threshold indicates that the hub interface is not loose. The increase in brightness value refers to the required increase in brightness value that can be clearly detected by the change in headlight brightness. The increase in brightness value corresponding to different headlight brightness can be found in the increase in brightness data table. The increase in brightness data table is a data table of different headlight brightness and their corresponding increase in brightness values ​​obtained from experiments.

[0176] Acceleration speed refers to the wheel speed required to reach the brightness increase value. The higher the brightness increase value, the greater the acceleration speed. The acceleration speed corresponding to different brightness increase values ​​can be found in the acceleration speed correspondence table, which is a data table that records different brightness increase values ​​and their corresponding acceleration speeds.

[0177] Step 301: Calculate the expected rotational speed by combining the wheel rotational speed and acceleration speed.

[0178] The expected rotational speed refers to the wheel speed at which the brightness increase value is reached. The sum of the wheel speed and the acceleration speed at this point is calculated as the expected rotational speed. The calculation method for the expected rotational speed is selected by the staff based on the actual situation.

[0179] Step 302: When the wheel speed is consistent with the expected speed, update the headlight brightness based on the expected speed.

[0180] When the wheel speed matches the expected speed, it means that the wheel speed has reached the expected speed, and the updated actual headlight brightness is determined based on the expected speed.

[0181] Step 303: Compare the brightness of the headlights to determine the increase in brightness.

[0182] The growth rate refers to the increase in headlight brightness. It can be calculated as the difference between the updated actual headlight brightness and the headlight brightness. The calculation method for the growth rate is selected by the staff based on the actual situation.

[0183] Step 304: If the growth rate is lower than the growth brightness value, determine the aging probability based on the growth rate.

[0184] A growth rate lower than the growth brightness value means that when the wheel speed reaches the expected speed, the headlight brightness does not reach the expected brightness value. The aging probability is a value used to show the degree of risk of hub aging. First, the quotient of the growth rate and the growth brightness value is calculated as the growth coefficient. The smaller the growth coefficient, the higher the aging probability. Then, the aging probability corresponding to the growth coefficient is looked up from the aging probability correspondence table. The aging probability record table is a data table that records different growth coefficients and their corresponding aging probabilities.

[0185] Step 305: In response to the aging probability generation, an aging warning is displayed.

[0186] An aging warning is a message used to notify workers of the aging risk of the hub. The method for generating aging warnings is common knowledge to those in the field.

[0187] When there is no risk of the interface becoming loose, there is a certain increase in brightness from the current brightness value to the point where the headlight becomes bright enough to be clearly detected. Reaching this increase in brightness value requires a certain acceleration. Based on the wheel speed at the current brightness value, the wheel speed after acceleration is estimated. When the estimated wheel speed is reached, the headlight brightness is identified. If the increase in headlight brightness between the current brightness value and the previous brightness value is less than the increase in brightness value before reaching the previous value, the hub is judged to be aging. This eliminates the influence of interface looseness on hub status detection and improves the accuracy of hub aging status judgment.

[0188] Methods for determining aging also include:

[0189] Step 306: Identify the water accumulation area from the driving image, extract the water-filled road section from the driving image based on the water accumulation area, and retrieve the vehicle position from the driving status.

[0190] The water accumulation area refers to the area covered by water accumulation. The water accumulation area can be identified from driving images using image processing technology. The method for identifying the water accumulation area is common knowledge to those in the field.

[0191] Flooded road sections refer to road sections where water has accumulated. Flooded road sections can be extracted from driving images by measuring the area of ​​the accumulated water. The extraction method for flooded road sections is selected by the staff based on the actual situation.

[0192] Vehicle location refers to the vehicle's position on the road. The vehicle location can be retrieved from the driving status. The method for retrieving the vehicle location is selected by the staff based on the actual situation.

[0193] Step 307: Determine the duration of wading by comparing the waterlogged sections and vehicle locations.

[0194] The duration of wading refers to the time a vehicle stays in a flooded section of road. It can be calculated by summing the time a vehicle spends in a flooded section of road. The method for calculating the duration of wading is selected by the staff based on the actual situation.

[0195] Step 308: Determine the degree of aging by combining the immersion time and the rate of increase.

[0196] The degree of aging refers to the extent to which the performance of the hub deteriorates. The longer the wading time, the smaller the increase in performance, and the higher the degree of aging of the hub. You can look up the degree of aging corresponding to different wading times and increase coefficients in the aging degree correspondence table. The aging degree correspondence table is a data table that records different wading times and increase coefficients and their corresponding degrees of aging.

[0197] Step 309: Generate and display an aging status report in response to the aging level.

[0198] The aging condition display report is information that shows workers the degree of aging of the hub. The method for generating the aging condition display report is common knowledge to those in the field.

[0199] The system extracts road sections with water accumulation from driving images, calculates the total time the vehicle spends in the water-filled sections and defines it as wading time. The longer the wading time, the more severe the aging. By analyzing the impact of wading time on hub aging, the system quantifies the degree of aging and makes hub aging detection more consistent with the actual working environment of sanitation vehicles.

[0200] Based on the same inventive concept, embodiments of the present invention provide a status detection system for a self-generating flower drum, comprising:

[0201] The data acquisition module is used to collect driving status data.

[0202] A memory for storing the program for any of the above-mentioned methods for detecting the state of a self-generating flower drum;

[0203] The processor is the unit of memory that allows programs to be loaded and executed by the processor.

[0204] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional modules is used as an example. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device, and unit described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0205] The above description is merely a preferred embodiment of the present invention. The scope of protection of the present invention is not limited to the above embodiments. All technical solutions falling within the scope of the present invention's concept are within the scope of protection of the present invention. It should be noted that for those skilled in the art, any improvements and modifications made without departing from the principles of the present invention should also be considered within the scope of protection of the present invention.

Claims

1. A method for detecting the condition of a self-generating hub, characterized in that, include: Step 100: Collect the vehicle's driving status and determine the vehicle battery level based on the driving status; Step 101: When the vehicle battery charge is less than a preset charge threshold, determine the wheel speed based on the driving state; Step 102: Determine the power generation of the hub based on the wheel speed; Step 103: When the power generation of the hub is greater than the preset power generation threshold, determine the charging amount based on the power generation of the hub; Step 104: If the charging power is not greater than the preset power supply threshold, generate and send a hub direct supply command, and respond to the hub power generation by generating and displaying a usage status detection report; It also includes a display state determination method, the display state determination method comprising: Step 105: If the charging power is not greater than the preset power supply threshold, acquire driving images; Step 106: Extract the left and right view images from the driving image, and identify the two maximum brightness values ​​and brightness value locations based on the left and right view images; Step 107: Calculate the brightness difference based on the two maximum brightness values, and determine the brightness distance according to the position of the brightness values; Step 108: Calculate the quotient of the brightness difference and the brightness distance as the attenuation coefficient; Step 109: Determine the headlight brightness based on the attenuation coefficient, and generate a brightness time correspondence table based on the headlight brightness; Step 110: Generate and display a display status report of the vehicle lights in response to the brightness time correspondence table; The method for determining the display state further includes: Step 111: When the attenuation coefficient is greater than the preset attenuation threshold, select the larger image with the larger brightness value from the left and right view images based on the two maximum brightness values; Step 112: Determine the relative position of the larger brightness value based on the larger image; Step 113: Determine the mirror position based on the relative position, and extract the smaller brightness value from the driving image based on the mirror position; Step 114: Update the headlight brightness in response to the lower brightness value.

2. The method for detecting the state of a self-generating flower drum according to claim 1, characterized in that, The method for determining the display state further includes: Step 115: When the attenuation coefficient is greater than the preset attenuation threshold, determine the larger brightness value based on the larger image; Step 116: Determine the brightness distribution map based on the larger brightness value; Step 117: Determine smaller images based on the larger images, and identify smaller distribution maps from the smaller images; Step 118: Calculate the difference between the smaller distribution map and the brightness distribution map, and define it as the difference distribution map; Step 119: In response to the difference distribution map, identify the difference brightness and update the smaller brightness value.

3. The method for detecting the state of a self-generating flower drum according to claim 2, characterized in that, It also includes a method for determining flicker anomalies, the method comprising: Step 200: Extract the on / off time correspondence tables for each of the two headlights from the brightness time correspondence table; Step 201: Determine the flicker frequency of the vehicle lights based on the corresponding table of on / off times; Step 202: When the flicker frequency is greater than a preset frequency threshold, determine the anomaly probability based on the flicker frequency; Step 203: In response to the anomaly probability generation, display a flashing anomaly warning.

4. The method for detecting the state of a self-generating flower drum according to claim 3, characterized in that, The method for determining flicker anomalies also includes: Step 204: Based on the flickering abnormality warning, acquire an interface image of the hub and determine the wire characteristics from the interface image; Step 205: Determine the interface length from the interface image based on the cable characteristics; Step 206: Determine the loosening distance based on the interface length; Step 207: If the loosening distance is greater than a preset distance threshold, determine the loosening probability based on the loosening distance; Step 208: In response to the loosening probability generation, display an interface loosening warning.

5. The method for detecting the state of a self-generating flower drum according to claim 4, characterized in that, The method for determining flicker anomalies also includes: Step 209: If the detachment distance is greater than a preset distance threshold, identify the actual height of the vehicle from the driving image; Step 210: Compare the preset reference height with the actual height to determine the degree of bumpiness; Step 211: Calculate the correlation coefficient by combining the degree of bumpiness and the flicker frequency; Step 212: If the correlation coefficient is greater than the preset correlation threshold, update the loosening probability based on the loosening distance and the correlation coefficient.

6. The method for detecting the state of a self-generating flower drum according to claim 5, characterized in that, It also includes an aging determination method, the aging determination method comprising: Step 300: If the loosening distance is not greater than a preset distance threshold, determine the increase brightness value based on the headlight brightness, and determine the acceleration speed based on the increase brightness value; Step 301: Calculate the expected rotational speed by combining the wheel rotational speed and acceleration speed; Step 302: When the wheel speed matches the expected speed, update the headlight brightness based on the expected speed; Step 303: Compare the brightness of the headlights to determine the increase in brightness; Step 304: If the growth rate is lower than the growth brightness value, determine the aging probability based on the growth rate; Step 305: In response to the aging probability generation, an aging warning is displayed.

7. The method for detecting the state of a self-generating flower drum according to claim 6, characterized in that, The aging determination method further includes: Step 306: Identify the water accumulation area from the driving image, extract the water-filled road section from the driving image based on the water accumulation area, and retrieve the vehicle position from the driving status; Step 307: Determine the duration of wading by comparing the waterlogged sections and vehicle locations; Step 308: Determine the degree of aging by combining the immersion time and the rate of increase; Step 309: Generate and display an aging status report in response to the aging level.

8. A status detection system for self-generating hubs, characterized in that, include: The data acquisition module is used to collect driving status data. A memory for storing a program for a method of detecting the state of a self-generating flower drum as described in any one of claims 1 to 7; The processor is the unit of memory that allows programs to be loaded and executed by the processor.

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