Method and system for measuring illumination brightness of whole vehicle body of mobile machine

Abstract

The invention discloses a mobile machinery whole vehicle body illumination brightness measurement method and system, and the method comprises the steps: obtaining the illumination data of a light source of a mobile machinery irradiating the surface of an irradiated object, and obtaining the illumination of the surface of the object according to the illumination data; obtaining the scene brightness of the object surface according to the illumination and the reflection data of the irradiated object surface; converting the scene brightness into a digital pixel value through CMOS image equipment; and processing the digital pixel value through a digital image technology to obtain a light illumination calculation function and a total illumination distribution diagram of the mobile machinery. Through scientific parameter selection, a reasonable technical path and a digital processing means, the accuracy, authenticity, comprehensiveness and analyzability of mobile mechanical illumination brightness measurement are improved, and powerful technical support is provided for research, development, debugging, detection and optimization of a mobile mechanical illumination system.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of brightness measurement, and particularly discloses a mobile mechanical whole vehicle body lighting brightness measurement method and system. BACKGROUND

[0002] Agricultural machinery accident refers to an accident of agricultural machinery in the field and yard during agricultural activities. The accident rate of agricultural machinery at night is more than 40%, and insufficient lighting is the main cause.

[0003] According to the recommended requirements of GB / T 10485-2025 Road Vehicles-External Luminous and Light Signalling Devices-Durability in Environment, GB / T 28780-2024 Mechanical Safety-Integral Lighting Systems for Machines, JB / T11973-2014 Work Lamps for Tractors, etc., technical research and development are carried out. In the production access, lighting detection is also included in the agricultural machinery safety compulsory certification (such as EU harmonized standard ENISO 4254-1:2015, EU machinery directive 2006 / 42 / EC, etc.). In actual demand, agricultural machinery customers generally reflect that the body of agricultural machinery product has insufficient work light. For example, the illuminance in some areas of agricultural seeding machine is low and cannot meet the light observation requirements during seeding, and the lighting range of the work light is narrow, which affects the operation efficiency of the driver and the operation of the equipment.

[0004] The typical lighting defect problems of existing agricultural machinery are as follows:

[0005] 1. Design and installation defects

[0006] 1) Missing lamps, leading to safety hazards at night; 2) Unreasonable installation position.

[0007] 2. Optical performance does not meet standards

[0008] 1) Insufficient illumination: the light intensity of old machine type work light is low, and the light distribution is uneven, with sharp changes between bright and dark.

[0009] 2) Glare and flicker: poor quality lamps have serious glare, low frequency fluorescent lamp flicker and mechanical motion frequency resonance, which easily leads to visual misjudgment.

[0010] 3. Lack of whole vehicle lighting solution

[0011] The body needs to be equipped with multiple work lights, but each light is designed and installed separately, which leads to the inability to design and supplement light systematically and integrally, and there are multiple dark or uneven brightness areas, which seriously affects the work efficiency of agricultural machinery.

[0012] Therefore, the above-mentioned lighting defects of existing agricultural machinery are the technical problems to be solved at present. SUMMARY

[0013] The application provides a mobile mechanical full vehicle body illumination brightness measurement method and system, aiming at solving at least one defect in the prior art.

[0014] An aspect of the application relates to a mobile mechanical full vehicle body illumination brightness measurement method, comprising the following steps:

[0015] Obtaining illumination data of a light source of a mobile machine irradiating to a surface of an irradiated object, and obtaining the illumination of the surface of the object according to the illumination data, wherein the illumination data comprises a measured illumination value, a measured brightness value, a total lumen value of the light source, an irradiated area, a distance from the light source to the surface of the irradiated object, and a light incidence angle;

[0016] Obtaining the scene brightness of the surface of the object according to the illumination and reflection data of the surface of the irradiated object, wherein the reflection data comprises the reflectivity of the surface of the object;

[0017] Converting the scene brightness into a digital pixel value through a CMOS image device;

[0018] Processing the digital pixel value through a digital image technology to obtain a light illumination calculation function and a full illumination distribution diagram of the mobile machine.

[0019] Further, in the step of obtaining the illumination of the surface of the object according to the illumination data of the light source of the mobile machine irradiating to the surface of the irradiated object, the illumination of the surface of the object is calculated by the following formula:

[0020]

[0021] Wherein, E represents the illumination of the surface of the object, φ represents the total lumen value of the light source, A represents the irradiated area, d represents the distance from the light source to the surface of the irradiated object, and θ represents the light incidence angle.

[0022] Further, in the step of obtaining the scene brightness of the surface of the object according to the illumination and reflection data of the surface of the irradiated object, the scene brightness of the surface of the object is calculated by the following formula:

[0023]

[0024] Wherein, L represents the scene brightness of the surface of the object, E represents the illumination of the surface of the object, ρ represents the inverse rate, and π represents the normalization factor.

[0025] Further, the conversion of the scene brightness into a digital pixel value through the CMOS image device comprises:

[0026] Collecting the scene brightness vertically above the mobile machine through a CMOS image device carried by a UAV;

[0027] According to the scene brightness and the preset CMOS image device sensor response, the scene brightness is converted into a digital pixel value.

[0028] Further, in the step of converting the scene brightness into a digital pixel value according to the scene brightness and the preset CMOS image device sensor response, the scene brightness and the digital pixel value have a one-to-one correspondence in the CMOS image device sensor response, and the corresponding relationship between the scene brightness value and the digital pixel value is:

[0029] I=k.L γ

[0030] Wherein, I represents the digital pixel value, k represents the sensor gain, L represents the scene brightness of the object surface, and γ represents the gamma coefficient.

[0031] Another aspect of the present application relates to a mobile mechanical full vehicle body lighting brightness measurement system, comprising:

[0032] An illumination acquisition module is configured to acquire lighting data of a light source of a mobile machine irradiating to an irradiated object surface, and derive the illumination of the object surface according to the lighting data, wherein the lighting data includes a measured illumination value, a measured brightness value, a total lumen value of the light source, an irradiated area, a distance from the light source to the irradiated object surface, and a light incidence angle;

[0033] A scene brightness acquisition module is configured to derive the scene brightness of the object surface according to the illumination and reflection data of the irradiated object surface, wherein the reflection data includes the reflectivity of the object surface;

[0034] A scene brightness conversion module is configured to convert the scene brightness into a digital pixel value by a CMOS image device;

[0035] An illumination distribution acquisition module is configured to derive a light illumination calculation function and a full illumination distribution diagram of the mobile machine by processing the digital pixel value through a digital image technology.

[0036] Further, in the illumination acquisition module, the illumination of the object surface is calculated by the following formula (generally, an illuminometer is used to acquire the illumination of the object surface):

[0037]

[0038] Wherein, E represents the illumination of the object surface, Φ represents the total lumen value of the light source, A represents the irradiated area, d represents the distance from the light source to the irradiated object surface, and θ represents the light incidence angle.

[0039] Further, in the scene brightness acquisition module, the scene brightness of the object surface is calculated by the following formula:

[0040]

[0041] Wherein, L represents the scene brightness of the object surface, E represents the illumination of the object surface, p represents the inverse rate, and p represents the normalization factor.

[0042] Further, the scene brightness conversion module comprises:

[0043] A scene brightness acquisition unit is configured to acquire the scene brightness vertically above the mobile machine by a CMOS image device carried by a UAV.

[0044] A scene brightness conversion unit is configured to convert the scene brightness into a digital pixel value according to the scene brightness and a preset CMOS image device sensor response.

[0045] Further, in the scene brightness conversion unit, the CMOS image device sensor response has a one-to-one correspondence between the scene brightness and the digital pixel value, and the corresponding relationship between the scene brightness value and the digital pixel value is:

[0046] I=k.L γ

[0047] Wherein, I represents the digital pixel value, k represents the sensor gain, L represents the scene brightness of the object surface, and g represents the gamma coefficient.

[0048] The present application has the following advantages:

[0049] The present application provides a mobile machine full-body lighting brightness measurement method and system, which obtains the illumination of an object surface according to the illumination data of a light source of a mobile machine irradiated to the object surface, obtains the scene brightness of the object surface according to the illumination and the reflection data of the object surface, converts the scene brightness into a digital pixel value by a CMOS image device, and obtains the light illumination calculation function and the full-illumination distribution map of the mobile machine by processing the digital pixel value through a digital image technology. The mobile machine full-body lighting brightness measurement method and system provided by the present application improve the accuracy, authenticity, comprehensiveness and analyzability of the mobile machine lighting brightness measurement through scientific parameter selection, reasonable technical path and digital processing means, and provide strong technical support for the research and development, debugging, detection and optimization of the mobile machine lighting system. BRIEF DESCRIPTION OF DRAWINGS

[0050] Figure 1 FIG. 1 is a flowchart of an embodiment of the mobile machine full-body lighting brightness measurement method of the present application;

[0051] Figure 2 FIG. 2 is a functional block diagram of an embodiment of the mobile machine full-body lighting brightness measurement system of the present application;

[0052] Figure 3This is a schematic diagram of the illuminance calculation function for a corn harvester working light and low beam headlight according to an embodiment of the present invention;

[0053] Figure 4 This is a schematic diagram of the illuminance calculation function for the first embodiment of the working light of the wheat harvester of the present invention;

[0054] Figure 5 This is a schematic diagram of the illuminance calculation function for the second embodiment of the working light of the wheat harvester of the present invention;

[0055] Figure 6 This is a full illuminance distribution diagram of an embodiment of the working light and low beam headlight of a corn harvester according to the present invention.

[0056] Explanation of icon numbers:

[0057] 10. Illuminance Acquisition Module; 20. Scene Brightness Acquisition Module; 30. Scene Brightness Conversion Module; 40. Illuminance Distribution Acquisition Module. Detailed Implementation

[0058] To better understand the above technical solutions, the following will provide a detailed explanation of the technical solutions in conjunction with the accompanying drawings and specific implementation methods.

[0059] like Figure 1 As shown, the first embodiment of the present invention proposes a method for measuring the brightness of the full-body lighting of mobile machinery, including the following steps:

[0060] Step S100: Obtain the illumination data of the light source of the mobile machinery illuminating the surface of the irradiated object, and obtain the illuminance of the object surface based on the illumination data. The illumination data includes the measured illuminance value, measured brightness value, total lumen value of the light source, irradiated area, distance from the light source to the surface of the irradiated object, and light incident angle.

[0061] Total lumens of a light source refers to the total luminous flux emitted by a mobile mechanical light source (such as vehicle lights, work lights, etc.) per unit time, and is a core parameter for measuring the total amount of light emitted by a light source.

[0062] The illuminated area refers to the area on the surface of the illuminated object that is actually illuminated by the light emitted from the mobile mechanical light source.

[0063] The distance from the light source to the surface of the illuminated object refers to the straight-line distance from the light-emitting center (or reference point) of the moving mechanical light source to the surface of the illuminated object.

[0064] The angle of incidence of light refers to the angle between the light emitted from the light source and the normal to the surface of the illuminated object (an imaginary line perpendicular to the surface of the object).

[0065] Through the cooperative calculation of the total lumen value of the light source, the irradiated area, the distance from the light source to the surface of the irradiated object, and the light incidence angle in the lighting data, the actual received illuminance of the object surface is accurately derived, laying a foundation for subsequent scene brightness analysis.

[0066] In step S200, the scene brightness of the object surface is obtained according to the illuminance and the reflection data of the irradiated object surface, wherein the reflection data includes the reflectivity of the object surface.

[0067] The scene brightness refers to the brightness perceived by the human eye or imaging device after the light is reflected by the object surface, which is directly related to the illuminance and the reflectivity of the object surface.

[0068] The reflectivity of the object surface refers to the ratio of the reflected light flux to the incident light flux on the irradiated object surface, which is a physical quantity for measuring the light reflection ability of the object surface. The reflectivity directly reflects the reflection efficiency of the object surface to light - the higher the reflectivity (such as mirror or white object), the greater the proportion of reflected light flux to incident light flux; the lower the reflectivity (such as black object), the more light is absorbed and the less light is reflected.

[0069] By defining the reflectivity and its relationship with the illuminance, the scene brightness of the object surface is accurately derived, laying a foundation for subsequent conversion into digital pixel values by CMOS devices.

[0070] In step S300, the scene brightness is converted into digital pixel values by a CMOS image device.

[0071] Converting the scene brightness into digital pixel values by a CMOS image device refers to a process of converting the scene brightness (physical optical signal) formed by the reflection of the object surface into pixel values (digital signal digitization results) in a digital image by using the photoelectric conversion characteristics of a CMOS (complementary metal oxide semiconductor) image sensor. This process is a key link between physical optical quantities and digital image data.

[0072] The CMOS image device includes a photoelectric conversion module and a signal amplification and quantization module. The photoelectric conversion module includes a photodiode, which is used to absorb photons and convert light energy into photoelectrons to form an analog electrical signal (charge or voltage) proportional to the light intensity. The signal amplification and quantization module includes an amplifier and an analog-to-digital converter. The amplifier is used to amplify the analog electrical signal. The analog-to-digital converter is used to convert the amplified analog electrical signal into discrete digital values (i.e., digital pixel values), ultimately forming a pixel matrix of a digital image.

[0073] In step S400, the digital pixel values are processed by digital image technology to obtain a light illuminance calculation function of the mobile machine and a full-illuminance distribution map.

[0074] The digital pixel value is processed by digital image technology to obtain a light illumination calculation function of the mobile machine and a full-illumination distribution diagram, which is a process of converting abstract digital image data into quantifiable and visualized light illumination characteristic results. The core is to map the calibrated digital pixel value to the actual physical space illumination value through a series of image processing algorithms, and present the spatial distribution law of the light in the form of mathematical function and image, without the need for a large number of repeated measurements to present the illumination distribution of any area at a fixed point and quantity.

[0075] The digital image technology processing device includes an image preprocessing unit, a pixel value-illumination mapping conversion unit, a spatial coordinate calibration unit and a distribution characteristic extraction unit. The image preprocessing unit is used to denoise (eliminate sensor noise and environmental light interference), distortion correction (correct lens optical distortion), exposure calibration (eliminate the influence of different exposure parameters on pixel value), etc. to ensure the stability and accuracy of the pixel value. The pixel value-illumination mapping conversion unit is used to convert the relative value digital pixel value into absolute value illumination value (unit: lux, lx) through a pre-established calibration model (such as a sensor response curve), to realize the conversion from “digital signal” to “physical photometric quantity”. The spatial coordinate calibration unit is used to map the pixel coordinates (row and column numbers) of the image to the actual physical space coordinates (such as three-dimensional space coordinates with the mobile machine as the origin or two-dimensional coordinates of the irradiation plane), to ensure that the illumination value corresponds to the actual irradiation position one by one. The distribution characteristic extraction unit is used to complete the spatial sparse data through interpolation, fitting and other algorithms to generate a continuous illumination space distribution model.

[0076] The light illumination calculation function of the mobile machine refers to a mathematical function describing the change of illumination value of the light of the mobile machine in the irradiation space (or a specific irradiation plane) with the spatial position. Usually, the spatial coordinates are taken as the independent variable and the illumination value is taken as the dependent variable. If the two-dimensional coordinates (x, y) in the irradiation plane are used to represent the position (x and y correspond to the actual physical distance, such as meters), the distribution function can be represented as E(x, y), wherein E is the illumination value (lx) at the position. For three-dimensional space, it can be extended to E(x, y, z) to reflect the illumination distribution in the three-dimensional space. The light illumination calculation function of the mobile machine as a mathematical model provides a basis for the quantitative analysis of the light performance (such as the irradiation range, the brightness decay rate and the uniformity index), and is used to compare the advantages and disadvantages of different light design schemes.

[0077] The full-illuminance distribution diagram of the mobile machine refers to a result of presenting a light illuminance calculation function in an intuitive image form through a visualization technique, which is a "visual expression" of the illuminance spatial distribution. The full-illuminance distribution diagram of the mobile machine can be a two-dimensional pseudo-color diagram (or a gray-scale diagram) or a three-dimensional solid diagram. Compared with an abstract mathematical function, the full-illuminance distribution diagram can intuitively reflect the illumination range (such as whether the work area is covered) of the mobile machine light, the brightness blind area (such as the area with illuminance lower than a safety threshold), the spot shape (such as whether it is regular), the uniformity (such as whether there is a significant bright-dark mutation), and the like, thereby providing an intuitive basis for light layout optimization and lighting performance evaluation (such as night work safety).

[0078] In the embodiment, through the digital image technology, the transformation of "digital signal → physical quantity → law modeling → visual presentation" is realized, so that the lighting characteristics of the mobile machine light change from "invisible physical phenomena" to "quantifiable analysis and intuitive evaluation engineering data".

[0079] Further, the mobile machine full-vehicle body illumination brightness measurement method provided in the embodiment, in step S100, the illuminance of the object surface is calculated by the following formula:

[0080]

[0081] In formula (1), E represents the illuminance of the object surface, Φ represents the total lumen value of the light source, the unit is lm; A represents the irradiated area, the unit is m 2 ; d represents the distance from the light source to the irradiated object surface, the unit is m; θ represents the light incidence angle, the unit is degree, and cosθ = 1 when the incidence is perpendicular.

[0082] Preferably, the mobile machine full-vehicle body illumination brightness measurement method provided in the embodiment, in step S200, the scene brightness of the object surface is calculated by the following formula:

[0083]

[0084] In formula (2), L represents the scene brightness of the object surface, the unit is nit, which is equivalent to cd / m 2 ; E represents the illuminance of the object surface, the unit is lux (lx); represents the reflectivity of the object surface, and π represents a normalization factor.

[0085] Further, the mobile machine full-vehicle body illumination brightness measurement method provided in the embodiment, step S300 includes:

[0086] In step S310, the scene brightness is vertically collected above the mobile machine by the CMOS image device carried by the unmanned aerial vehicle.

[0087] The scene brightness is collected vertically above the mobile machine by the unmanned aerial vehicle carrying the CMOS image device, which is a measurement method for obtaining the brightness distribution of the surrounding environment or the surface (such as the light irradiation area, the working surface, etc.) of the mobile machine by using the aerial remote sensing and image sensing technology.

[0088] The collected object is the scene brightness around the mobile machine (such as engineering machinery, agricultural machinery, special operation vehicles, etc.), including the irradiation area of the machine's own light (such as the coverage range of the headlamp and working lamp), the reflected brightness of the machine surface, and the illuminated brightness of the working environment (such as the ground and materials).

[0089] The collection angle is that the unmanned aerial vehicle hovers or flies directly above the mobile machine (or at an approximately vertical angle), ensuring that the optical axis of the CMOS image device is perpendicular to the horizontal plane (such as the ground or the top surface of the machine) of the collected scene, so as to reduce the brightness measurement deviation caused by the inclined angle (such as the perspective distortion and the influence of the incident angle difference on the brightness).

[0090] The advantage of vertical collection is that the vertical angle can maximize the consistency of the light incident direction of each point in the scene and the receiving direction of the sensor (reduce the influence of cosine attenuation), so that the mapping relationship between the DN (Digital Number) value of the pixel in the image and the actual scene brightness is more stable, which is convenient for subsequent calibration and quantitative analysis.

[0091] In step S320, the scene brightness is converted into a digital pixel value according to the scene brightness and the preset sensor response of the CMOS image device.

[0092] The process of converting the scene brightness into a digital pixel value is the core process of the CMOS image device converting the physical optical signal into a digital signal through the optical system, photoelectric conversion, signal processing, and analog-to-digital conversion. The conversion process is a process of mapping the physical optical signal into a digital signal through multiple links, and the core is to establish a quantitative relationship between the scene brightness and the digital pixel value through the sensor response characteristics and system parameters.

[0093] Preferably, in the mobile machine full-body illumination brightness measurement method provided by the embodiment, in step S320, the sensor response of the CMOS image device maps a one-to-one correspondence relationship between the scene brightness and the digital pixel value, and the corresponding relationship between the scene brightness value and the digital pixel value is:

[0094] I=k.L γ (3)

[0095] In formula (3), I represents the digital pixel value, k represents the sensor gain, L represents the scene brightness of the object surface, and γ represents the gamma coefficient.

[0096] In the RGB mode, the pixel brightness formula is:

[0097] I brightneas = 0.299R + 0.587G + 0.114B (4)

[0098] In formula (4), I brightness is a digital pixel value in RGB mode, R is a digital value of a red component in the pixel, G is a digital value of a green component in the pixel, and B is a digital value of a blue component in the pixel.

[0099] In combination of formula (3) and formula (4), a relationship between a digital pixel value and an actual illumination is obtained:

[0100]

[0101] In formula (5), I represents a digital pixel value, k represents a sensor gain, E represents an illumination of an object surface, and a unit is lux (lx); p represents a reflectivity of the object surface, p represents a normalized factor, e represents a noise term, and g represents a gamma coefficient.

[0102] Preferably, the mobile machine full vehicle body lighting brightness measurement method provided in the embodiment comprises the following steps.

[0103] In step S410, the field measurement data is imported into CurveFitter for function fitting, and a light illumination calculation function of the mobile machine is obtained.

[0104] The light illumination calculation function of the mobile machine is obtained by importing the light illumination data (distance, height, environmental conditions, and associated data of corresponding illumination values) of the mobile machine (such as engineering machinery, agricultural machinery, special vehicles, etc.) measured in the actual working scene into the CurveFitter software, and after data preprocessing, model screening and parameter optimization, an empirical fitting function capable of quantitatively describing the mathematical relationship between the light illumination and the influencing factors (such as distance, installation height, environmental attenuation, etc.) is obtained. The light illumination calculation function of the mobile machine is used to predict the illumination value of the mobile machine light under specific conditions, and provides a quantitative basis for light layout design, work safety evaluation, etc.

[0105] In step S420, after the original digital image is processed by image processing, the full illumination distribution map and various vehicle body light analysis maps are obtained in combination with the light illumination calculation function.

[0106] The full-illumination distribution diagram and the various vehicle body light analysis diagram refer to an image set that is based on an original digital image, after image processing (such as correction, segmentation, feature extraction), and combining a mobile mechanical light illumination calculation function, quantitatively analyzes and visually presents the illumination coverage range, intensity distribution, and key area compliance of vehicle body light in a work scene. The full-illumination distribution diagram focuses on the spatial distribution of global illumination, and the various vehicle body light analysis diagram analyzes the performance and influence of specific light (such as working light, headlight, warning light), which provides intuitive basis for light system optimization and work safety evaluation.

[0107] See Figure 2 The embodiment also provides a mobile mechanical full-vehicle body illumination brightness measurement system, which comprises an illumination acquisition module 10, a scene brightness acquisition module 20, a scene brightness conversion module 30, and an illumination distribution acquisition module 40. The illumination acquisition module 10 is used to acquire illumination data of light source irradiation to a surface of an irradiated object of a mobile machine, and to obtain the illumination of the surface of the object according to the illumination data. The illumination data comprises a measured illumination value, a measured brightness value, a total lumen value of the light source, an irradiated area, a distance from the light source to the surface of the irradiated object, and a light incidence angle. The scene brightness acquisition module 20 is used to obtain the scene brightness of the surface of the object according to the illumination and reflection data of the surface of the irradiated object. The reflection data comprises a reflectivity of the surface of the object. The scene brightness conversion module 30 is used to convert the scene brightness into a digital pixel value through a CMOS image device. The illumination distribution acquisition module 40 is used to obtain a light illumination calculation function and a full-illumination distribution diagram of the mobile machine by processing the digital pixel value through a digital image technology.

[0108] The illumination acquisition module 10 accurately deduces the illumination actually received by the surface of the object by cooperative calculation of the total lumen value of the light source, the irradiated area, the distance from the light source to the surface of the irradiated object, and the light incidence angle in the illumination data, thereby laying a foundation for subsequent scene brightness analysis.

[0109] The scene brightness acquisition module 20 accurately deduces the scene brightness of the surface of the object by defining the reflectivity and its association with the illumination, thereby laying a foundation for subsequent conversion into a digital pixel value through a CMOS device.

[0110] The scene brightness conversion module 30 converts the scene brightness into digital pixel values through the CMOS image device. The scene brightness conversion module 30 utilizes the photoelectric conversion characteristics of the CMOS (complementary metal oxide semiconductor) image sensor to convert the scene brightness (physical light signal) formed by the reflection of the object surface into the pixel value (electrical signal digitization result) in the digital image, which is the core link connecting the physical optical quantity and the digital image data. The CMOS image device includes a photoelectric conversion module and a signal amplification and quantization module, wherein the photoelectric conversion module includes a photodiode, which is used to absorb photons and convert light energy into photoelectrons to form an analog electrical signal (charge or voltage) proportional to the light intensity. The signal amplification and quantization module includes an amplifier and an analog-to-digital converter, wherein the amplifier is used to amplify the analog electrical signal. The analog-to-digital converter is used to convert the amplified analog electrical signal into discrete digital values (i.e., digital pixel values), and finally form the pixel matrix of the digital image.

[0111] The illumination distribution acquisition module 40 processes the digital pixel values through digital image technology to obtain the light illumination calculation function and the full illumination distribution diagram of the mobile machine. The illumination distribution acquisition module 40 converts the abstract digital image data into quantifiable and visualizable light illumination characteristic results. The core is to map the calibrated digital pixel values to the actual physical space illumination values through a series of image processing algorithms, and present the spatial distribution law of the light in the form of mathematical function and image. The digital image technology processing device includes an image preprocessing unit, a pixel value-illumination mapping conversion unit, a spatial coordinate calibration unit and a distribution feature extraction unit, wherein the image preprocessing unit is used to denoise (eliminate sensor noise and environmental light interference), distortion correction (correct lens optical distortion), exposure calibration (eliminate the influence of different exposure parameters on pixel values), etc. to ensure the stability and accuracy of the pixel value. The pixel value-illumination mapping conversion unit is used to convert the relative value digital pixel value into the absolute value illumination value (unit: lux, lx) through the pre-established calibration model (such as the sensor response curve), to realize the conversion from “digital signal” to “physical photometric quantity”. The spatial coordinate calibration unit is used to map the pixel coordinates (row and column numbers) of the image to the actual physical space coordinates (such as the three-dimensional space coordinates with the mobile machine as the origin or the two-dimensional coordinates of the irradiation plane), to ensure that the illumination value corresponds to the actual irradiation position one by one. The distribution feature extraction unit is used to complete the spatial sparse data through interpolation, fitting and other algorithms to generate a continuous illumination space distribution model.

[0112] Further, the mobile machine full vehicle body illumination brightness measurement system provided by the embodiment calculates the illumination of the object surface through the following formula in the illumination acquisition module 10:

[0113]

[0114] In formula (6), E represents the illuminance of the object surface, φ represents the total lumen value of the light source, the unit is lm; A represents the irradiated area, the unit is m 2 ; d represents the distance from the light source to the surface of the irradiated object, the unit is m; θ represents the light incidence angle, the unit is degree, and cosθ = 1 when the incidence is perpendicular.

[0115] Preferably, the mobile machinery full vehicle body lighting brightness measurement system provided by the embodiment, in the scene brightness acquisition module 20, the scene brightness of the object surface is calculated by the following formula:

[0116]

[0117] In formula (7), L represents the scene brightness of the object surface, the unit is nit, which is equivalent to cd / m 2 ; E represents the illuminance of the object surface, the unit is lux (lx); represents the inverse rate, and π represents the normalization factor.

[0118] Further, the mobile machinery full vehicle body lighting brightness measurement system provided by the embodiment, the scene brightness conversion module 30 includes a scene brightness acquisition unit and a scene brightness conversion unit, wherein the scene brightness acquisition unit is used for vertically collecting the scene brightness above the mobile machinery by the CMOS image device carried by the unmanned aerial vehicle; the scene brightness conversion unit is used for converting the scene brightness into a digital pixel value according to the scene brightness and the preset CMOS image device sensor response.

[0119] The scene brightness acquisition unit vertically collects the scene brightness above the mobile machinery by the CMOS image device carried by the unmanned aerial vehicle. The scene brightness acquisition unit uses air remote sensing and image sensing technology to obtain the brightness distribution of the surrounding environment or the surface of the mobile machinery (such as the light irradiation area, the working surface, etc.).

[0120] The collection object is the surrounding scene brightness centered on the mobile machinery (such as engineering machinery, agricultural machinery, special operation vehicles, etc.), including the irradiation area of the machinery itself light (such as the coverage range of the headlamp and the working lamp), the reflected brightness of the machinery surface, the illuminated brightness of the working environment (such as the ground and the material), etc.

[0121] The collection angle is that the unmanned aerial vehicle hovers or flies directly above (or at an approximately vertical angle) the mobile machinery, ensuring that the optical axis of the CMOS image device is perpendicular to the horizontal plane (such as the ground and the top surface of the machinery) of the collected scene, so as to reduce the brightness measurement deviation (such as perspective distortion and the influence of incidence angle difference on brightness) caused by the inclination of the viewing angle.

[0122] The advantage of vertical collection: the vertical view angle can maximize the consistency of the light incident direction of each point in the scene and the receiving direction of the sensor (reduce the influence of cosine attenuation), so that the mapping relationship between the DN (Digital Number) value of the pixel in the image and the actual scene brightness is more stable, which is convenient for subsequent calibration and quantitative analysis.

[0123] The scene brightness conversion unit converts the scene brightness into a digital pixel value. The CMOS image device converts the physical light signal into a digital signal through optical systems, photoelectric conversion, signal processing, and analog-to-digital conversion. This conversion process is a process of mapping the physical light signal into a digital signal through multiple links, and the core is to establish a quantitative relationship between the scene brightness and the digital pixel value through the sensor response characteristics and system parameters.

[0124] Further, the mobile mechanical full-body illumination brightness measurement system provided by the embodiment, in the scene brightness conversion unit, the CMOS image device sensor response has a one-to-one correspondence between the scene brightness and the digital pixel value, and the corresponding relationship between the scene brightness value and the digital pixel value is:

[0125] I=k.L γ (8)

[0126] In formula (8), I represents the digital pixel value, k represents the sensor gain, L represents the scene brightness of the object surface, and γ represents the gamma coefficient.

[0127] In the RGB mode, the pixel brightness formula is:

[0128] I brightness =0.299R+0.587G+0.114B (9)

[0129] In formula (9), I brightness represents the digital pixel value in the RGB mode, R represents the digital value of the red component in the pixel, G represents the digital value of the green component in the pixel, and B represents the digital value of the blue component in the pixel.

[0130] Integrating formula (3) and formula (4), the relationship between the digital pixel value and the actual illumination is obtained:

[0131]

[0132] In formula (10), I represents the digital pixel value, k represents the sensor gain, E represents the illumination of the object surface, and the unit is lux (lx); ρ represents the reflectivity of the object surface, π represents the normalization factor, ∈ represents the noise term, and γ represents the gamma coefficient.

[0133] Furthermore, the mobile machinery full-vehicle lighting brightness measurement system provided in this embodiment includes an illuminance distribution acquisition module 40 comprising a light illuminance calculation function acquisition unit and a full illuminance distribution map acquisition unit. The light illuminance calculation function acquisition unit is used to import the on-site measured data into CurveFitter for function fitting to obtain the light illuminance calculation function of the mobile machinery. The illuminance distribution map acquisition unit is used to process the original digital image and combine it with the light illuminance calculation function to obtain a full illuminance distribution map and various vehicle body light analysis maps.

[0134] The illuminance calculation function acquisition unit imports measured illuminance data (correlation data between distance, height, environmental conditions, etc. and corresponding illuminance values) of mobile machinery (such as construction machinery, agricultural machinery, and special vehicles) in actual operating scenarios into CurveFitter software. After data preprocessing, model screening, and parameter optimization, an empirical fitting function is obtained that quantitatively describes the mathematical relationship between illuminance and influencing factors (such as distance, installation height, environmental attenuation, etc.). The illuminance calculation function for mobile machinery is used to predict the illuminance value of mobile machinery lights under specific conditions, providing a quantitative basis for lighting layout design and operational safety assessment.

[0135] The total illuminance distribution map acquisition unit uses raw digital images as a base. After image processing (such as correction, segmentation, and feature extraction), and combined with the mobile machinery lighting illuminance calculation function, it presents a set of images that quantitatively analyze and visualize the illuminance coverage, intensity distribution, and key area compliance of vehicle body lights in the work scenario. The total illuminance distribution map focuses on the spatial distribution of global illuminance, while various vehicle body light analysis maps provide specialized analysis of the performance and impact of specific lights (such as work lights, headlights, and warning lights), providing intuitive evidence for lighting system optimization and work safety assessment.

[0136] like Figures 1 to 6 As shown, the following detailed description of the mobile machinery full-vehicle lighting brightness measurement method and system provided by the present invention will be based on specific embodiments:

[0137] The headlight illuminance calculation function can be either a piecewise function or a single function. The headlight illuminance calculation function takes various forms, and the specific function used is based on the data fitted from actual vehicle measurements. The following are some examples of headlight illuminance calculation function relationships.

[0138] Please see Figure 3 , Figure 3 This is a schematic diagram illustrating the illuminance calculation function of the working light and low beam headlight of a corn harvester according to an embodiment of the present invention. In this embodiment:

[0139] I. Calculation function for illuminance of lights on mobile machinery

[0140] ① When the brightness is below 50 pixels

[0141] y = 13.324x 0.6155

[0142] R 2 = 0.9657.

[0143] wherein, x is the pixel brightness value I, y is the illumination value E at the pixel position fitted out, R 2 The meaning of R square value: the R square value is an index of the fitting degree of the trend line, the numerical value can reflect the fitting degree between the estimated value of the trend line and the corresponding actual data, the higher the fitting degree, the higher the reliability of the trend line.

[0144] The R square value is a value in the range of 0-1, when the R square value of the trend line is equal to 1 or close to 1, the reliability is the highest, otherwise the reliability is lower. The R square value is also called the determination coefficient.

[0145] In statistics, the calculation method of R square value is as follows:

[0146] R square value = regression sum of squares (ssreg) / total sum of squares (sstotal)

[0147] Regression sum of squares = total sum of squares - residual sum of squares (ssresid).

[0148] ② 50-150 pixel brightness

[0149] y = 2.3976x + 23.007

[0150] R 2 = 0.9869.

[0151] ③ Greater than 150 pixel brightness

[0152] y = 0.0268x 2 -5.0108x + 531

[0153] R 2 = 0.9933.

[0154] See Figure 4 , Figure 4 is the illumination calculation function diagram of the lamp of an embodiment of the TG120 wheat harvester working lamp, in this embodiment:

[0155] y = 6E-05x 3 -0.0146x 2 + 2.7547x + 2.3154

[0156] R 2 = 0.9949.

[0157] where 6E-05 represents 6 times 10 raised to the power of -5, i.e. 0.00006, and E is the scientific notation symbol.

[0158] See Figure 5 , Figure 5 is a schematic diagram of a light intensity calculation function of an embodiment of the TF220 wheat harvester working light of the present application. In this embodiment:

[0159] y = 2E-05x 3 -0.0079x 2 + 2.9083x + 4.7058

[0160] R 2 = 0.9983.

[0161] II. Full-illumination distribution diagram and analysis diagram of each type of vehicle body light

[0162] The full-illumination distribution diagram and analysis diagram of each type of vehicle body light can be in the form of a picture or in the form of software, as shown in Figure 6 .

[0163] The mobile machine full-vehicle body illumination brightness measurement method and system provided in this embodiment have the following beneficial effects compared with the prior art:

[0164] 1. Improved measurement accuracy and reliability: By directly obtaining key physical parameters such as total lumen value, distance, and incident angle of the light source to calculate the illumination, and combining reflection data such as object surface reflectivity to construct measurement logic from the optical principle level, the illumination calculation function obtained by fitting a large amount of measured data is used to predict the illumination data of each point, which reduces various measurement errors caused by improper use of the illuminometer measurement method in traditional measurement and errors caused by environmental interference or indirect conversion between devices, making the measurement results more consistent with the actual lighting physical characteristics.

[0165] 2. Real scene restoration of lighting effect: The introduction of reflection data such as object surface reflectivity to calculate the "scene brightness" instead of only measuring the parameters of the light source can more realistically reflect the actual lighting effect of the mobile machine in different working environments (such as different road surfaces and different material object surfaces), making the measurement results more practically applicable.

[0166] 3. Promote the digitization and refinement of lighting evaluation: With the help of CMOS image devices and digital image technology, the scene brightness is converted into digital pixel values and processed, and finally the light intensity calculation function and full-illumination distribution diagram are obtained. This not only realizes the digital storage and analysis of lighting data, but also intuitively presents the spatial distribution characteristics of lighting (such as bright and dark areas, uniformity, etc.), providing quantitative basis for the design optimization and fault diagnosis of the lighting system.

[0167] 4. Enhance the comprehensiveness and systematicness of the measurement: measure for "full body lighting", finally output "full illumination distribution map", which can comprehensively cover the lighting range and superposition effect of each light of the mobile machinery body, avoid the limitation of local measurement, and help to evaluate whether the lighting performance of the mobile machinery meets the standards of work safety, field of view demand, etc. from the whole.

[0168] 5. Greatly reduce the cost of measurement and improve the efficiency of measurement: replace the traditional illuminometer repeated measurement process, realize multi-point synchronous acquisition and dynamic analysis of illumination distribution, compared with the traditional grid measurement method, it is simple to operate without grid paving, saves time and effort, workload is small, does not need to measure all the points of the measured area, the measurement range is large and is not limited by the size of the measured vehicle, has high applicability, the required parameters can be arbitrarily adjusted, the measurement result has high precision, digital measurement can provide data basis for further intelligent development, etc.

[0169] 6. Can simulate the lighting effect of different light angles (horizontal angle, vertical angle), simulate the light range effect generated by multiple lights. Application scenarios include but are not limited to:

[0170] ① Can simulate the recommended light range and standard of the national standard, which can be used as a basis for body lamp design.

[0171] ② Can simulate the actual light effect of various lamps, and can visually predict the lighting improvement degree after installing the lamps on the vehicle body.

[0172] ③ The better the light effect quality is, the more gentle the illumination calculation function curve obtained by actual measurement is, the higher the fitting degree is, and the data uniformity will be greatly improved, which can prove that the brightness uniformity and continuity of the lamp are excellent.

[0173] Although the preferred embodiments of the present application have been described, those skilled in the art can make further changes and modifications to these embodiments once they know the basic inventive concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the present application. Obviously, those skilled in the art can make various modifications and changes to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and changes of the present application fall within the scope of the claims of the present application and their equivalents, the present application also intends to include these modifications and changes.

Claims

1. A method of measuring the luminance of a mobile machine full body illumination, characterized by, The method comprises the following steps: obtaining illumination data of a light source of a mobile machine irradiating onto a surface of an irradiated object, and obtaining illumination of the surface of the object according to the illumination data, wherein the illumination data comprises a measured illumination value, a measured brightness value, a total lumen value of the light source, an irradiated area, a distance from the light source to the surface of the irradiated object, and an incident angle of light rays; obtaining scene brightness of the surface of the object according to the illumination and reflection data of the surface of the irradiated object, wherein the reflection data comprises reflectivity of the surface of the object; converting the scene brightness into a digital pixel value by using a CMOS image device; processing the digital pixel value by using a digital image technology to obtain a light illumination calculation function and a full-illumination distribution diagram of the mobile machine.

2. The mobile machine full body luminaire brightness measurement method of claim 1, wherein, In the step of obtaining the illumination data of the light source of the mobile machine irradiating onto the surface of the irradiated object, and obtaining the illumination of the surface of the object according to the illumination data, the illumination of the surface of the object is calculated by the following formula: wherein E represents the illumination of the surface of the object, Φ represents the total lumen value of the light source, A represents the irradiated area, d represents the distance from the light source to the surface of the irradiated object, and θ represents the incident angle of the light rays.

3. The mobile machine full body luminaire brightness measurement method of claim 1, wherein, In the step of obtaining the scene brightness of the surface of the object according to the illumination and the reflection data of the surface of the irradiated object, the scene brightness of the surface of the object is calculated by the following formula: wherein L represents the scene brightness of the surface of the object, E represents the illumination of the surface of the object, ρ represents a reciprocal rate, and π represents a normalization factor.

4. The mobile machine full body luminaire brightness measurement method of claim 1, wherein, The step of converting the scene brightness into the digital pixel value by using the CMOS image device comprises: vertically collecting the scene brightness above the mobile machine by using a CMOS image device carried by a UAV; converting the scene brightness into the digital pixel value according to the scene brightness and a preset sensor response of the CMOS image device.

5. The mobile machine full body luminaire brightness measurement method of claim 4, wherein, In the step of converting the scene brightness into the digital pixel value according to the scene brightness and the preset sensor response of the CMOS image device, the sensor response of the CMOS image device has a one-to-one corresponding relationship between the scene brightness and the digital pixel value, and the corresponding relationship between the scene brightness value and the digital pixel value is as follows: I = k.L γ wherein I represents the digital pixel value, k represents a sensor gain, L represents the scene brightness of the surface of the object, and γ represents a gamma coefficient.

6. A mobile machine full vehicle body illumination brightness measurement system characterized by, The method comprises the following steps: an illumination obtaining module (10) for obtaining illumination data of a light source of a mobile machine irradiating onto a surface of an irradiated object, and obtaining illumination of the surface of the object according to the illumination data, wherein the illumination data comprises a measured illumination value, a measured brightness value, a total lumen value of the light source, an irradiated area, a distance from the light source to the surface of the irradiated object, and an incident angle of light rays; a scene brightness obtaining module (20) for obtaining scene brightness of the surface of the object according to the illumination and reflection data of the surface of the irradiated object, wherein the reflection data comprises reflectivity of the surface of the object; a scene brightness converting module (30) for converting the scene brightness into a digital pixel value by using a CMOS image device; an illumination distribution obtaining module (40) for processing the digital pixel value by using a digital image technology to obtain a light illumination calculation function and a full-illumination distribution diagram of the mobile machine.

7. The mobile machine full body luminaire brightness measurement system of claim 6, wherein, In the illuminance acquisition module (10), the illuminance of the object surface is calculated by the following formula: Wherein, E represents the illuminance of the object surface, φ represents the total lumen value of the light source, A represents the irradiated area, d represents the distance from the light source to the irradiated object surface, and θ represents the light incidence angle.

8. The mobile machine full body luminaire brightness measurement system of claim 6, wherein, In the scene brightness acquisition module (20), the scene brightness of the object surface is calculated by the following formula: Wherein, L represents the scene brightness of the object surface, E represents the illuminance of the object surface, ρ represents the inverse rate, and π represents the normalization factor.

9. The mobile machine full body luminaire brightness measurement system of claim 6, wherein, The scene brightness conversion module (30) comprises: A scene brightness acquisition unit, configured to vertically acquire the scene brightness above the moving machine by a CMOS image device carried by a UAV; A scene brightness conversion unit, configured to convert the scene brightness into a digital pixel value according to the scene brightness and a preset CMOS image device sensor response.

10. The mobile machine full body luminaire brightness measurement system of claim 9, wherein, In the scene brightness conversion unit, the CMOS image device sensor response maps a one-to-one correspondence between the scene brightness and the digital pixel value, and the corresponding relationship between the scene brightness value and the digital pixel value is as follows: I = k.L γ Wherein, I represents the digital pixel value, k represents the sensor gain, L represents the scene brightness of the object surface, and γ represents the gamma coefficient.

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