A safety evaluation method and system based on LED garden lights

Abstract

The present invention discloses a safety evaluation method and system based on LED garden lights, and relates to the technical field of LED light safety evaluation. The evaluation method comprises a cloud management platform receiving a safety evaluation request for an LED garden light, and obtaining characteristic data of the LED garden light, analyzing and processing the characteristic data, comprehensively evaluating the performance safety index of the LED garden light through an LED service processor, and performing performance operation alarm prompts on the LED garden light through a safety evaluation execution model. The present invention can perform performance analysis and alarm prompts according to multiple evaluation dimensions of the LED garden light, realizes timely and effective multi-directional data evaluation for the LED garden light, and can discover possible hidden defects of the LED garden light, thereby greatly improving the timeliness of maintenance and management of the LED garden light, and fully ensuring the overall safe use performance and reliability of the LED garden light.

Description

Technical Field

[0001] The present invention relates to the technical field of LED lamp safety assessment, and in particular to a safety assessment method and system based on LED garden lamps. Background Art

[0002] With the advancement of modern sustainable development concepts, reducing lighting energy consumption and alleviating the impact of lighting energy use on the environment have become the current focus of attention. LED garden lights are a type of garden lighting equipment that uses LED technology as a light source. They have a longer service life and are more durable than traditional lamps. With the promotion of LED garden light applications, a series of safety issues have arisen. Since LED garden lights are usually installed in open-air environments and are affected by external natural factors for a long time, performance degradation and potential safety defects are inevitable. Therefore, LED garden lights need to be subject to comprehensive safety monitoring and performance evaluation.

[0003] The prior art, such as the street lamp fault monitoring system disclosed in the invention patent with announcement number: CN103327701B, collects the electrical parameters of each street lamp through a node controller, generates fault type information through the electrical parameters, and forwards the fault information including the fault type information, the generation time of the fault type information and the identification information of the node controller to the street lamp server through a centralized controller. The street lamp server obtains the location information corresponding to the fault information, and sends the fault information and the location information corresponding to the fault information to the monitoring terminal. Since the information sent by the street lamp server to the monitoring terminal includes the fault information and the location information corresponding to the fault information, the management personnel can obtain the fault information of the street lamp in real time through the monitoring terminal, and can know the location of the faulty street lamp without the need for the management personnel to conduct inspections on the road, which solves the problem that the management and maintenance workload of the existing public lighting system is large and easy to cause omissions.

[0004] Based on the above scheme, the current safety monitoring and evaluation of LED garden lights has the limitation that there is no timely and effective multi-dimensional data evaluation for LED garden lights, which makes it impossible to timely discover the hidden defects of LED garden lights, thereby greatly compromising the timeliness of LED garden light maintenance and management. Maintenance personnel may need to spend more time to check and repair the defects of LED garden lights, which indirectly increases the maintenance and management costs of LED garden lights and fails to improve the overall performance and reliability of LED garden lights. Summary of the invention

[0005] In view of the deficiencies in the prior art, the present invention provides a method and system for evaluating the safety level of LED garden lights, which can effectively solve the problems involved in the above-mentioned background technology.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: The first aspect of the present invention provides a method for evaluating the safety level of LED garden lights, including: a cloud management platform receives a safety assessment request for LED garden lights and obtains characteristic data of the LED garden lights.

[0007] The characteristic data is analyzed and processed, the performance safety index of the LED garden light is comprehensively evaluated through the LED service processor, and the performance operation alarm prompt of the LED garden light is issued by the safety level evaluation execution model.

[0008] As a preferred design scheme, the performance operation alarm prompt of the LED garden light is performed by the safety level assessment execution model. The specific process includes: according to the performance safety index of the LED garden light, the safety level assessment execution model is imported for analysis and processing to obtain the performance safety assessment execution result of the LED garden light. If the performance safety assessment execution result of the LED garden light is an execution alarm, the alarm prompt information of the LED garden light is generated for automatic alarm prompt, wherein the safety level assessment execution model is as follows: .

[0009] in, The performance safety index of LED garden lights. It is the execution alarm trigger value corresponding to the predefined performance safety index of the LED garden light.

[0010] As a preferred design solution, the performance safety index of the LED garden lamp is specifically evaluated and calculated as follows: .

[0011] In the formula, The performance safety index of LED garden lights. , , They are the first manufacturing performance evaluation index of LED garden lights, the second application performance evaluation index of LED garden lights, and the third external environment impact index of LED garden lights. , , are the evaluation weight factors of the first manufacturing performance evaluation index, the second application performance evaluation index and the third external environment impact index of the set LED garden lamp, respectively. It is the performance safety compensation ratio coefficient of the set LED garden light.

[0012] As a preferred design scheme, the first manufacturing performance evaluation index of the LED garden lamp is specifically calculated and evaluated in the following process: based on the characteristic data of the LED garden lamp, manufacturing test data of the LED garden lamp is extracted, including a volt-ampere characteristic curve, a test temperature rise curve, and a brightness adjustment test curve.

[0013] Extract the volt-ampere characteristic curve to arrange discrete points, count the IV coordinate values ​​corresponding to each discrete point, and perform combined difference processing to extract the IV combined difference corresponding to each discrete point, marked as , m is the number of each discrete point, , u is the number of discrete points.

[0014] The temperature valley point and temperature peak point are located from the test temperature rise curve, and according to the predefined temperature rise warning value, the time consumed by the LED garden light to reach the temperature rise warning value is extracted, which is recorded as .

[0015] According to the brightness adjustment test curve, it is evenly divided and the adjustment brightness difference of each period is extracted and marked as , and at the same time verify it with the predefined brightness adjustment reference test curve, extract the length of the brightness adjustment test curve overlap, and record it as , q is the number of each time period, , z is the number of time periods.

[0016] Calculate the first manufacturing performance evaluation index of LED garden lights, and the execution model is: ,in: In the formula, , , They are the evaluation correction factors of the set volt-ampere characteristic curve, test temperature rise curve and brightness adjustment test curve, respectively. , Define deviation values ​​for predefined IV combinations and differences from reference IV combinations, respectively. , The temperature values ​​for locating the temperature valley points and temperature peak points in the test temperature rise curve, It is the deviation limit temperature value between the predefined temperature valley point and the temperature peak point. , is the temperature rise warning value and the preset temperature rise warning rate. is the time interval of period q, , They are the performance evaluation interference factor for the set brightness adjustment deviation rate and the compensation coefficient for the unit overlap length of the brightness adjustment test curve.

[0017] As a preferred design scheme, the second application performance evaluation index of the LED garden lamp has a specific evaluation calculation process as follows: according to the characteristic data of the LED garden lamp, the application data of the LED garden lamp is extracted therefrom, including the illumination brightness curve and electrical response information in the specified collection period, and the electrical response information is the start-up delay and the start-stop delay of each historical use, which are marked as , , i is the number of each historical use, , g is the total number of historical uses.

[0018] According to the illumination brightness curve of LED garden lights in the specified collection period, random screening points are arranged, and the illumination brightness of each screening point and the cumulative duration of each illumination brightness range are counted.

[0019] Calculate the second application performance evaluation index of LED garden lights, and the execution expression is: ,in: .

[0020] In the above formula, It is the second application performance evaluation index of LED garden lights. Influencing factors for the performance evaluation of LED garden lights, is the illumination brightness of screening point j, is the cumulative duration of the illumination brightness range r, is the duration of the specified collection period, is the illumination brightness corresponding to the maximum value of the cumulative duration, , is the reference adaptation duration ratio of the predefined illumination brightness range r and the adaptation illumination brightness of the LED garden lamp, j is the number of each screening point, , n is the total number of screening points, r is the number of each illumination brightness range, , w is the total number of illumination brightness ranges, is the evaluation interference factor corresponding to the unit deviation value of the set illumination brightness, and e is a natural constant.

[0021] As a preferred design scheme, the performance evaluation influencing factor of the LED garden lamp is executed as follows: obtaining the start-up management electrical node position of the LED garden lamp and the layout position point of the LED garden lamp, extracting the reference electrical flow link length of the LED garden lamp, and marking it as .

[0022] The cumulative activation time and natural placement time of LED garden lights are counted and recorded as , .

[0023] Calculate the performance evaluation influencing factor of LED garden lights, and the execution expression is: ,in: .

[0024] In the formula, To define the threshold value for the performance evaluation of LED garden lights, , The application license startup delay is set for the cumulative activation unit time and the natural placement unit time. , The application permission start and stop delays are respectively the set cumulative activation unit duration and the natural placement unit duration. , They are the additional compensation proportional coefficients for the set start delay and start-stop delay, , They are respectively the reference limit deviation start delay and the reference limit deviation start-stop delay per unit length of the set benchmark electrical circulation link.

[0025] As a preferred design scheme, the third external environment impact index of the LED garden lamp is specifically evaluated and calculated as follows: extracting each combination of structural materials and their materials from the characteristic data of the LED garden lamp, and comparing the reference external environment impact coefficients of each combination of structural materials corresponding to each material according to the predefined reference external environment impact coefficients, and obtaining the reference external environment impact coefficients of each combination of structural materials of the LED garden lamp, which are recorded as , d is the number of each combined structural material, , is the number of combined construction materials.

[0026] The third external environment impact index of the LED garden light is obtained according to the environment numerical processing execution model, wherein the environment numerical processing execution model is as follows: .

[0027] in, It is the third external environment impact index of LED garden lights. , They are the first meteorological influencing characteristic value and the second meteorological influencing characteristic value of LED garden lights, , They are the additional compensation correction coefficients for the set meteorological first impact characteristic value and the meteorological second impact characteristic value respectively.

[0028] As a preferred design scheme, the meteorological first impact characteristic value and the meteorological second impact characteristic value of the LED garden light are specifically processed as follows: extracting the cumulative application period of the LED garden light, and extracting the regional meteorological element information of the LED garden light in the cumulative application period, including the total amount and total duration of each type of precipitation, respectively recorded as , , h is the number of each type of precipitation, , is the number of precipitation types.

[0029] Analyze the meteorological first impact characteristic value of LED garden lights, and the execution formula is: .

[0030] In the formula, , , The total amount of precipitation, the influencing characteristic factor of unit duration and the reference limit precipitation rate for the set precipitation type h are: It is the set precipitation impact correction coefficient.

[0031] Analyze the meteorological second impact characteristic value of LED garden lights, and the execution formula is: ,in: .

[0032] In the above formula, is the correction coefficient of the meteorological factor influence, , , , , They are the average daily irradiance, sunshine duration, temperature range, relative humidity, and maximum wind force level of the application period day y extracted from the regional meteorological element information. , , They are the set reference daily average irradiance, reference illumination duration, and reference temperature range. , , is the average irradiance, average illumination duration and average temperature difference of the area in the cumulative application cycle of LED garden lights, y is the number of the day of each application cycle, , The number of days for the application cycle.

[0033] A second aspect of the present invention provides a safety assessment system based on LED garden lights, comprising: a cloud management platform for receiving a safety assessment request of an LED garden light and acquiring characteristic data of the LED garden light.

[0034] The characteristic data processing module is used to analyze and process the characteristic data and comprehensively evaluate the performance safety index of the LED garden light through the LED service processor.

[0035] The performance safety warning prompt module is used to provide performance operation warning prompts for LED garden lights through a safety level assessment execution model.

[0036] Compared with the prior art, the embodiments of the present invention have at least the following beneficial effects:

[0037] (1) The present invention provides a method and system for evaluating the safety level of LED garden lights. By extracting and processing multi-dimensional data and providing performance operation alarm prompts, the present invention realizes timely and effective multi-dimensional data evaluation of LED garden lights. It can timely discover the hidden defects that may exist in LED garden lights, thereby greatly improving the timeliness of maintenance and management of LED garden lights. Maintenance personnel can locate and repair defects of LED garden lights more reliably, which not only reduces the maintenance and management costs of LED garden lights, but also fully guarantees the overall performance and reliability of LED garden lights.

[0038] (2) The present invention improves the accuracy and comprehensiveness of the performance safety evaluation of LED garden lights by comprehensively evaluating the performance safety index of LED garden lights based on multi-dimensional data processing, and can timely discover the potential risks of LED garden lights. By providing timely warnings, it helps to prevent the occurrence of safety risks in the use of LED garden lights, further ensure the safety and stability of the garden lighting system, and better meet the user experience.

[0039] (3) The present invention obtains the third external environment impact index of the LED garden light by processing, fully taking into account the intrusive impact of the external open-air environment on the LED garden light, providing a more solid and reliable data basis for a comprehensive analysis of the safe use performance of the LED garden light, and helping to take preventive maintenance measures more timely, greatly reducing the performance safety hazards of the LED garden light caused by external environmental problems. Of course, any product implementing the present invention does not necessarily need to achieve all of the above advantages at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 It is a schematic diagram of the method steps of the present invention.

[0041] Figure 2 It is a schematic diagram of the connection of the system function modules of the present invention. Implementation

[0042] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0043] In the description of the present invention, it should be understood that the terms "opening", "upper", "lower", "thickness", "top", "middle", "length", "inside", "all around" and the like indicating orientation or positional relationship are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the components or elements referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as limiting the present invention.

[0044] See also Figure 1 As shown, the first aspect of the embodiment of the present invention provides a method for evaluating the safety level of LED garden lights, including: a cloud management platform receives a safety evaluation request for the LED garden lights, and obtains characteristic data of the LED garden lights.

[0045] The characteristic data is analyzed and processed, the performance safety index of the LED garden light is comprehensively evaluated through the LED service processor, and the performance operation alarm prompt of the LED garden light is issued by the safety level evaluation execution model.

[0046] Specifically, the performance operation alarm prompt of the LED garden light by the safety level assessment execution model includes: according to the performance safety index of the LED garden light, the safety level assessment execution model is imported for analysis and processing to obtain the performance safety assessment execution result of the LED garden light; if the performance safety assessment execution result of the LED garden light is an execution alarm, the alarm prompt information of the LED garden light is generated for automatic alarm prompt, wherein the safety level assessment execution model is as follows: .

[0047] In a specific embodiment of the present invention, by comprehensively evaluating the performance safety index of LED garden lights and based on multi-dimensional data processing, the accuracy and comprehensiveness of the performance safety evaluation of LED garden lights are improved, and potential risks of LED garden lights can be discovered in a timely manner. By providing timely warnings, it helps to prevent the occurrence of safety risks in the use of LED garden lights, further ensure the safety and stability of the garden lighting system, and better meet the user experience.

[0048] In an embodiment, the alarm prompt information of the LED garden light is automatically generated for alarm prompting, and the alarm prompt information is synchronously transmitted to the mobile receiving terminal of the user of the LED garden light and the mobile receiving terminal of the maintenance personnel. This can prevent the LED garden light from being further used in the case of hidden defects and causing a series of safety risks. It can also remind the maintenance personnel to make timely control, thereby highly ensuring the application stability of the LED garden light.

[0049] in, The performance safety index of LED garden lights. It is the execution alarm trigger value corresponding to the predefined performance safety index of the LED garden light.

[0050] Specifically, the performance safety index of the LED garden lamp is evaluated and calculated as follows: .

[0051] In the formula, The performance safety index of LED garden lights. , , They are the first manufacturing performance evaluation index of LED garden lights, the second application performance evaluation index of LED garden lights, and the third external environment impact index of LED garden lights. , , are the evaluation weight factors of the first manufacturing performance evaluation index, the second application performance evaluation index and the third external environment impact index of the set LED garden lamp, respectively. It is the performance safety compensation ratio coefficient of the set LED garden light.

[0052] Furthermore, the first manufacturing performance evaluation index of the LED garden lamp is specifically calculated and evaluated in the following process: based on the characteristic data of the LED garden lamp, manufacturing test data of the LED garden lamp is extracted, including a volt-ampere characteristic curve, a test temperature rise curve, and a brightness adjustment test curve.

[0053] In the embodiment, the above-mentioned volt-ampere characteristic curve has current as the vertical axis and voltage as the horizontal axis, the test temperature rise curve has time as the horizontal axis and the test temperature as the vertical axis, and the brightness adjustment test curve has time as the horizontal axis and brightness as the vertical axis. Usually, LED garden lights will pass multiple performance tests when they are used before leaving the factory, and they are allowed to be actually used only if they meet the standards. However, it is found in this embodiment that there are still differences in the performance of LED garden lights when they meet the application standards. By considering this dimension, the performance of LED garden lights can be fully evaluated, so that they can be convincing and supportive in subsequent alarm prompts.

[0054] Extract the volt-ampere characteristic curve to arrange discrete points, count the IV coordinate values ​​corresponding to each discrete point, and perform combined difference processing to extract the IV combined difference corresponding to each discrete point, marked as , m is the number of each discrete point, , u is the number of discrete points.

[0055] It should be understood that the IV combination difference corresponding to the above-mentioned discrete points refers to the coordinate difference of each discrete point, that is, the current and voltage difference corresponding to each discrete point. Under ideal conditions, the volt-ampere characteristic curve should be linear, and the current and voltage difference corresponding to each discrete point should be equivalent. In the embodiments, due to various factors, the volt-ampere characteristic curve will also fluctuate differentially, resulting in inconsistencies in the current and voltage differences corresponding to each discrete point.

[0056] The temperature valley point and temperature peak point are located from the test temperature rise curve, and according to the predefined temperature rise warning value, the time consumed by the LED garden light to reach the temperature rise warning value is extracted, which is recorded as According to the brightness adjustment test curve, it is evenly divided and the adjustment brightness difference of each time period is extracted and marked as , and at the same time verify it with the predefined brightness adjustment reference test curve, extract the length of the brightness adjustment test curve overlap, and record it as , q is the number of each time period, , z is the number of time periods.

[0057] Calculate the first manufacturing performance evaluation index of LED garden lights, and the execution model is: ,in: .

[0058] In the formula, , , They are the evaluation correction factors of the set volt-ampere characteristic curve, test temperature rise curve and brightness adjustment test curve, respectively. , Define deviation values ​​for predefined IV combinations and differences from reference IV combinations, respectively. , The temperature values ​​for locating the temperature valley points and temperature peak points in the test temperature rise curve, It is the deviation limit temperature value between the predefined temperature valley point and the temperature peak point. , is the temperature rise warning value and the preset temperature rise warning rate. is the time interval of period q, , They are the performance evaluation interference factor for the set brightness adjustment deviation rate and the compensation coefficient for the unit overlap length of the brightness adjustment test curve.

[0059] Furthermore, the second application performance evaluation index of the LED garden lamp has a specific evaluation calculation process as follows: according to the characteristic data of the LED garden lamp, the application data of the LED garden lamp is extracted therefrom, including the illumination brightness curve and electrical response information in the specified collection period, and the electrical response information is the start-up delay and the start-stop delay of each historical use, which are marked as , , i is the number of each historical use, , g is the total number of historical uses.

[0060] In the embodiment, the illumination brightness curve takes the time of the specified collection period as the horizontal axis and the illumination brightness of the LED garden light as the vertical axis. The illumination brightness can be sensed and extracted by a light sensor. The specified collection period uses the date to which the current evaluation time point belongs as the time node for dividing the time, and reversely extracts the adjacent illumination usage time period in the past history as the specified collection period.

[0061] According to the illumination brightness curve of LED garden lights in the specified collection period, random screening points are arranged, and the illumination brightness of each screening point and the cumulative duration of each illumination brightness range are counted.

[0062] Calculate the second application performance evaluation index of LED garden lights, and the execution expression is: ,in: .

[0063] In the above formula, It is the second application performance evaluation index of LED garden lights. Influencing factors for the performance evaluation of LED garden lights, is the illumination brightness of screening point j, is the cumulative duration of the illumination brightness range r, is the duration of the specified collection period, is the illumination brightness corresponding to the maximum value of the cumulative duration, , is the reference adaptation duration ratio of the predefined illumination brightness range r and the adaptation illumination brightness of the LED garden lamp, j is the number of each screening point, , n is the total number of screening points, r is the number of each illumination brightness range, , w is the total number of illumination brightness ranges, is the evaluation interference factor corresponding to the unit deviation value of the set illumination brightness, and e is a natural constant.

[0064] Furthermore, the performance evaluation influencing factors of the LED garden lamp are processed as follows: the start-up management electrical node position of the LED garden lamp and the layout position point of the LED garden lamp are obtained, and the reference electrical flow link length of the LED garden lamp is extracted and marked as .

[0065] In the embodiment, the benchmark electrical flow link length of the above-mentioned LED garden light refers to the length of the electrical transmission line between the start-up management electrical node position of the LED garden light and the layout location of the LED garden light. The above-mentioned start-up management electrical node position is the location point where the LED garden light is adjacent to the access to electrical energy.

[0066] The cumulative activation time and natural placement time of LED garden lights are counted and recorded as , .

[0067] In the embodiment, the difference between the cumulative activation time and the natural placement time is that the cumulative activation time refers to the cumulative actual startup and usage time from the installation of the application to the current evaluation time node, while the natural placement time refers to the cumulative time in the natural placement state remaining except the cumulative actual startup and usage time.

[0068] Calculate the performance evaluation influencing factor of LED garden lights, and the execution expression is: ,in: .

[0069] In the formula, To define the threshold value for the performance evaluation of LED garden lights, , The application license startup delay is set for the cumulative activation unit time and the natural placement unit time. , The application permission start and stop delays are respectively the set cumulative activation unit duration and the natural placement unit duration. , They are the additional compensation proportional coefficients for the set start delay and start-stop delay, , They are respectively the reference limit deviation start delay and the reference limit deviation start-stop delay per unit length of the set benchmark electrical circulation link.

[0070] In the embodiment, the startup delay and start-stop delay used are important bases for measuring the response sensitivity of the LED garden light. Through analysis, it is helpful to timely discover the response performance of the LED garden light during the startup process and the start-stop process, and can further feedback the possible risks and defects in the transmission process of electric energy.

[0071] Specifically, the third external environment impact index of the LED garden lamp is specifically evaluated and calculated as follows: extracting each combination of structural materials and their materials from the characteristic data of the LED garden lamp, and comparing the reference external environment impact coefficients of each combination of structural materials corresponding to each material according to the predefined reference external environment impact coefficients, and obtaining the reference external environment impact coefficients of each combination of structural materials of the LED garden lamp, which are recorded as , d is the number of each combined structural material, , is the number of combined construction materials.

[0072] In this embodiment, examples of each combined structural material and its material are as follows: each combined structural material includes a lamp housing, a lampshade, a lamp holder, a supporting structure, a base, etc., wherein the lamp housing is the outer protective cover of the garden light, usually made of weather-resistant and waterproof materials to withstand external weather conditions such as rain, snow, sunlight and wind, etc. The materials used include aluminum alloy, stainless steel, plastic or fiberglass, etc. The lampshade covers the light source of the lamp to play a scattering and protective role. The lampshade is usually made of transparent or translucent materials such as glass, acrylic or plastic, etc. The lamp holder is the part connecting the lamp and the supporting structure, usually made of durable metal materials such as aluminum alloy or steel. The supporting structure can support the weight of the entire garden light and connect the lamp to the base fixed to the ground. This part is usually made of solid metal, such as cast aluminum or steel. The base is used to fix the LED garden light on the ground and is usually made of solid metal or concrete.

[0073] The third external environment impact index of the LED garden light is obtained according to the environment numerical processing execution model, wherein the environment numerical processing execution model is as follows: .

[0074] in, It is the third external environment impact index of LED garden lights. , They are the first meteorological influencing characteristic value and the second meteorological influencing characteristic value of LED garden lights, , They are the additional compensation correction coefficients for the set meteorological first impact characteristic value and the meteorological second impact characteristic value respectively.

[0075] In a specific embodiment of the present invention, a third external environment impact index of the LED garden lamp is obtained by processing, which fully takes into account the intrusive effect of the external open-air environment on the LED garden lamp, provides a more solid and reliable data basis for a comprehensive analysis of the safe use performance of the LED garden lamp, and helps to take preventive maintenance measures more timely, thereby significantly reducing the performance safety risks of the LED garden lamp caused by external environmental problems.

[0076] Furthermore, the meteorological first impact characteristic value and the meteorological second impact characteristic value of the LED garden light are specifically processed as follows: extracting the cumulative application period of the LED garden light, and extracting the regional meteorological element information of the LED garden light in the cumulative application period, including the total amount and total duration of each type of precipitation, respectively recorded as , , h is the number of each type of precipitation, , is the number of precipitation types.

[0077] It should be understood that the cumulative application cycle of LED garden lights refers to the period from the time of installation completion to the current evaluation time point, and the regional meteorological element information of LED garden lights during the cumulative application cycle can be extracted from the regional meteorological center platform.

[0078] As a further example, the above-mentioned types of precipitation include but are not limited to: snowfall, rain, hail, etc.

[0079] Analyze the meteorological first impact characteristic value of LED garden lights, and the execution formula is: .

[0080] In the formula, , , The total amount of precipitation, the influencing characteristic factor of unit duration and the reference limit precipitation rate for the set precipitation type h are: It is the set precipitation impact correction coefficient.

[0081] In the embodiment, due to the influence of the characteristics of each type of precipitation, the impact on the LED garden lights is also different. Analysis of precipitation at different types and levels can timely and effectively reflect the interference of the external meteorological environment on the LED garden lights, and further provide a reasonable basis for the alarm prompts of the LED garden lights.

[0082] Analyze the meteorological second impact characteristic value of LED garden lights, and the execution formula is: ,in: .

[0083] In the above formula, is the correction coefficient of the meteorological factor influence, , , , , They are the average daily irradiance, sunshine duration, temperature range, relative humidity, and maximum wind force level of the application period day y extracted from the regional meteorological element information. , , They are the set reference daily average irradiance, reference illumination duration, and reference temperature range. , , is the average irradiance, average illumination duration and average temperature difference of the area in the cumulative application cycle of LED garden lights, y is the number of the day of each application cycle, , The number of days for the application cycle.

[0084] As a supplementary explanation, the calculation formulas for the average irradiance, average illumination duration and average temperature range of the above LED garden lights in the cumulative application cycle are: , , .

[0085] It should be understood that the above-mentioned average daily irradiance, duration of illumination, extreme temperature difference, relative humidity, and maximum wind speed level are all important dimensions that reflect the external meteorological influences on LED garden lights during their cumulative application cycle. Excessively large values ​​of the above-mentioned parameters will bring a series of negative effects to LED garden lights, such as aging of components, loose structure, weakened waterproof performance, and reduced lighting effects. The analysis of these meteorological element information provides a more reliable and supportive data basis for the alarm prompts of LED garden lights.

[0086] See also Figure 2 As shown, the second aspect of the embodiment of the present invention provides a safety assessment system based on LED garden lights, including: a cloud management platform, a feature data processing module, and a performance safety alarm prompt module.

[0087] The cloud management platform is used to receive a security assessment request for an LED garden light and obtain characteristic data of the LED garden light.

[0088] The characteristic data processing module is used to analyze and process the characteristic data and comprehensively evaluate the performance safety index of the LED garden light through the LED service processor.

[0089] The performance safety warning prompt module is used to provide performance operation warning prompts for LED garden lights through a safety level assessment execution model.

[0090] In a specific embodiment of the present invention, by providing a method and system for evaluating the safety level of LED garden lights, multi-dimensional data extraction and processing, and performance operation alarm prompts are implemented to achieve timely and effective multi-dimensional data evaluation of LED garden lights, and possible hidden defects of LED garden lights can be discovered in time, thereby greatly improving the timeliness of maintenance and management of LED garden lights. Maintenance personnel can locate and repair defects of LED garden lights more reliably, which not only reduces the maintenance and management costs of LED garden lights, but also fully guarantees the overall performance and reliability of LED garden lights.

[0091] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0092] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to the specific implementation methods described. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that technicians in the relevant technical field can understand and use the present invention well. As long as they do not deviate from the structure of the present invention or exceed the scope defined by the present invention, they should all belong to the protection scope of the present invention.

Claims

1. A safety assessment method based on LED garden lights, characterized by: include: The cloud management platform receives a security assessment request for the LED garden light and obtains characteristic data of the LED garden light; Analyze and process the characteristic data, comprehensively evaluate the performance safety index of the LED garden light through the LED service processor, and issue a performance operation alarm prompt to the LED garden light through the safety level evaluation execution model; The performance safety index of the LED garden lamp is specifically evaluated and calculated as follows: Wherein, ψ is the performance safety index of the LED garden light, α1, α2, and α3 are respectively the first manufacturing performance evaluation index of the LED garden light, the second application performance evaluation index of the LED garden light, and the third external environment impact index of the LED garden light, A1, A2, and A3 are respectively the evaluation weight factors of the first manufacturing performance evaluation index, the second application performance evaluation index, and the third external environment impact index of the set LED garden light, and δ0 is the performance safety compensation ratio coefficient of the set LED garden light; The first manufacturing performance evaluation index of the LED garden lamp is specifically calculated and evaluated as follows: According to the characteristic data of LED garden lights, the manufacturing test data of LED garden lights are extracted, including the volt-ampere characteristic curve, the test temperature rise curve and the brightness adjustment test curve; Extract the volt-ampere characteristic curve to arrange discrete points, count the IV coordinate values ​​corresponding to each discrete point, perform combined difference processing, extract the IV combined difference corresponding to each discrete point, and mark it as ΔIV m , m is the number of each discrete point, m = 1, 2, ..., u, u is the number of discrete points; Locate the temperature valley point and temperature peak point from the test temperature rise curve, and extract the time it takes for the LED garden light to reach the temperature rise warning value according to the predefined temperature rise warning value, recorded as T0; According to the brightness adjustment test curve, the brightness difference of each period is extracted and marked as D q , and at the same time verify it with the predefined brightness adjustment reference test curve, extract the length of the brightness adjustment test curve overlap, record it as L, q is the number of each time period, q = 1, 2, ..., z, z is the number of time periods; Calculate the first manufacturing performance evaluation index of LED garden lights, and the execution model is: in: Where γ1, γ2, and γ3 are the evaluation correction factors of the set volt-ampere characteristic curve, test temperature rise curve, and brightness adjustment test curve, respectively; IV″ and IV0 are the predefined IV combination limit deviation value and the reference IV combination difference value, respectively; C min , C max is the temperature value of the temperature valley point and the temperature peak point in the test temperature rise curve, ΔC is the predefined deviation limit temperature value between the temperature valley point and the temperature peak point, C0 and S0 are the temperature rise warning value and the preset temperature rise warning rate, t q is the time interval of period q, χ1 and χ2 are the performance evaluation interference factor of the set brightness adjustment deviation rate and the compensation coefficient of the unit overlap length of the brightness adjustment test curve respectively; The second application performance evaluation index of the LED garden lamp, the specific evaluation calculation process is: According to the characteristic data of LED garden lights, the application data of LED garden lights is extracted, including the irradiation brightness curve and electrical response information in the specified collection period. The electrical response information is the start delay and start-stop delay of each historical use, which are marked as Y 1→i , Y 2→i , i is the number of each historical use, i = 1, 2, ..., g, g is the total number of historical uses; According to the brightness curve of LED garden lights in the specified collection period, random screening points are arranged, and the brightness of each screening point and the cumulative duration of each brightness range are counted; Calculate the second application performance evaluation index of LED garden lights, and the execution expression is: ， in: In the above formula, α2 is the second application performance evaluation index of LED garden lights, β is the performance evaluation influencing factor of LED garden lights, Q j is the illumination brightness of screening point j, J r is the cumulative duration of the illumination brightness range r, J0 is the duration of the specified acquisition period, max(Q) is the illumination brightness corresponding to the maximum value of the cumulative duration, ΔJ r , Q0 is the reference adaptation duration ratio of the predefined illumination brightness range r and the adaptation illumination brightness of the LED garden lamp, j is the number of each screening point, j = 1, 2, ..., n, n is the total number of screening points, r is the number of each illumination brightness range, r = 1, 2, ..., w, w is the total number of illumination brightness ranges, λ″ is the evaluation interference factor of the set illumination brightness corresponding to the unit deviation value, and e is a natural constant; The third external environment impact index of the LED garden lamp is specifically evaluated and calculated as follows: Extract each combination of structural materials and their materials from the characteristic data of the LED garden lamp, and compare the reference external environmental impact coefficients of each material corresponding to each predefined combination of structural materials to obtain the reference external environmental impact coefficients of each combination of structural materials of the LED garden lamp, which are recorded as μd, where d is the number of each combination of structural materials, d=1, 2, ..., d″, and d″ is the number of combination of structural materials; The third external environment impact index of the LED garden light is obtained according to the environment numerical processing execution model, wherein the environment numerical processing execution model is as follows: Among them, α3 is the third external environment impact index of the LED garden light, σ1 and σ2 are the meteorological first impact characteristic value and the meteorological second impact characteristic value of the LED garden light respectively, and τ1 and τ2 are the additional compensation correction coefficients of the set meteorological first impact characteristic value and the meteorological second impact characteristic value respectively.

2. The method for evaluating the safety level of LED garden lights according to claim 1 is characterized in that: The safety level assessment execution model performs performance operation alarm prompts on the LED garden light, and the specific process includes: According to the performance safety index of the LED garden light, the safety level assessment execution model is imported for analysis and processing to obtain the performance safety assessment execution result of the LED garden light. If the performance safety assessment execution result of the LED garden light is an execution alarm, the alarm prompt information of the LED garden light is generated for automatic alarm prompt. The safety level assessment execution model is as follows: Wherein, ψ is the performance safety index of the LED garden light, and ψ0 is the execution alarm trigger value corresponding to the predefined performance safety index of the LED garden light.

3. The method for evaluating the safety level of LED garden lights according to claim 1 is characterized in that: The performance evaluation influencing factors of the LED garden lamp are processed as follows: Obtain the start-up management electrical node position of the LED garden light and the layout position of the LED garden light, extract the reference electrical flow link length of the LED garden light, marked as H0; The cumulative activation time and natural placement time of the LED garden lights are counted and recorded as E1 and E2 respectively; Calculate the performance evaluation influencing factor of LED garden lights, and the execution expression is: in: Wherein, Δβ is the threshold value for the impact of performance evaluation of the set LED garden lamp, b1 and b2 are the application-permitted start delays for the set cumulative activation unit time and the natural placement unit time, f1 and f2 are the application-permitted start-stop delays for the set cumulative activation unit time and the natural placement unit time, κ1 and κ2 are the additional compensation proportional coefficients for the set start delay and start-stop delay, υ1 and υ2 are the reference limit deviation start delay and reference limit deviation start-stop delay for the set unit length of the benchmark electrical circulation link, respectively.

4. The method for evaluating the safety level of LED garden lights according to claim 1 is characterized in that: The specific processing process of the meteorological first impact characteristic value and the meteorological second impact characteristic value of the LED garden lamp is as follows: Extract the cumulative application period of LED garden lights, and extract the regional meteorological element information of LED garden lights in the cumulative application period, including the total amount and total duration of each type of precipitation, recorded as Gh and Th respectively, where h is the number of each type of precipitation, h=1, 2, ..., h″, and h″ is the number of precipitation types; Analyze the meteorological first impact characteristic value of LED garden lights, and the execution formula is: In the formula, ΔGh, φh, Vh→ are the defined precipitation amount of the set precipitation type h, the influencing characteristic factor of the unit duration, and the reference limit precipitation rate. is the set precipitation impact correction coefficient; Analyze the meteorological second impact characteristic value of LED garden lights, and the execution formula is: σ2=(σ2→1+σ2→2)*ξ0, where: In the above formula, ξ0 is the set meteorological factor influence correction coefficient, Fy, ty, Wy, Uy, and Xy are respectively the average daily irradiance, sunshine duration, temperature range, relative humidity, and maximum wind force level of the application period day y extracted from the regional meteorological factor information, ΔF0, Δt0, and ΔW0 are respectively the set reference daily average irradiance, reference sunshine duration, and reference temperature range. is the average irradiance, average illumination duration and average temperature range of the area in the cumulative application cycle of the LED garden light, y is the number of each application cycle day, y=1, 2, ..., y″, y″ is the number of application cycle days.

5. A system for applying the safety assessment method based on LED garden lights as claimed in any one of claims 1 to 4, characterized in that: include: A cloud management platform, used for receiving a security assessment request of an LED garden lamp and obtaining characteristic data of the LED garden lamp; A characteristic data processing module, used for analyzing and processing the characteristic data, and comprehensively evaluating the performance safety index of the LED garden light through the LED service processor; The performance safety warning prompt module is used to provide performance operation warning prompts for LED garden lights through a safety level assessment execution model.

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