LED intelligent street lamp illumination control system suitable for different road conditions

Abstract

The invention discloses an LED intelligent street lamp illumination control system suitable for different road conditions, and relates to the field of LED intelligent street lamp illumination control, and the system comprises a server which is in communication connection with a data collection unit, a line analysis unit, an environment dynamic unit, a comprehensive evaluation unit, an information matching unit, a matching verification unit and a display terminal. Line information, environment information and dynamic information of different roads are analyzed to obtain line influence values, environment bad influence values and dynamic influence values, the line influence values, the environment bad influence values and the dynamic influence values are judged and analyzed to obtain an illuminance demand road set and a color temperature demand road set, and the illuminance demand road set and the color temperature demand road set are matched with corresponding illuminance and color temperature. According to the method, illumination and color temperature matching corresponding to different sets is obtained, matching quality information is analyzed, matching verification feedback signals are obtained, states of street lamps under various conditions can be comprehensively considered, the occurrence rate of accidents can be reduced, and resource consumption is greatly reduced.

Description

Technical Field

[0001] The present invention relates to the field of LED smart street lamp lighting control for different road conditions, and specifically to an LED smart street lamp lighting control system suitable for different road conditions. Background Art

[0002] With the continuous development of society and the continuous progress of economy, the urban process is also getting faster and faster, and more and more roads need to be managed, among which the LED street lighting control problem is particularly important. Traditional street lighting control is too dependent on manual control and cannot prepare and adjust lighting parameters in time. LED smart street lighting control systems for different road conditions have emerged.

[0003] The existing LED smart street lighting control systems for different road conditions cannot take into account various situations in the road lines, the impact of the external environment of the road and pedestrians and vehicles, and cannot consider automatic adjustment of different illumination and color temperatures, resulting in a significant increase in traffic accident rates, increased energy costs for street lamp management, and occasional street lamp safety accidents.

[0004] The existing LED smart street lighting control system for different road conditions cannot take into account the quality information of street lighting during operation, and thus cannot know the quality results of street lighting control, resulting in the inability to provide timely feedback to relevant staff.

[0005] In order to solve the above defects, a technical solution is now provided. Summary of the invention

[0006] In order to solve the technical problems raised by the above background technology, the present invention is proposed. The embodiments of the present invention provide an LED smart street lamp lighting control system suitable for different road conditions.

[0007] The purpose of the present invention can be achieved through the following technical solutions: an LED smart street lamp lighting control system suitable for different road conditions, including a server, the server is communicatively connected with a data acquisition unit, a line analysis unit, an environmental dynamics unit, a comprehensive evaluation unit, an information matching unit, a matching verification unit and a display terminal.

[0008] The line analysis unit performs a qualitative analysis of the line information in the road condition information of the smart street lamp lighting work to obtain a line impact value, and sends it to the comprehensive evaluation unit;

[0009] The environmental dynamic unit performs a qualitative analysis of the environmental impact on the environmental information in the road condition information of the smart street lighting work to obtain an environmental impact value; performs a qualitative analysis of the dynamic impact on the dynamic information in the road condition information of the smart street lighting work to obtain a dynamic impact value, and sends it to the comprehensive evaluation unit;

[0010] The comprehensive evaluation unit receives the bending influence factor coefficient, the environmental impact value, the pedestrian asynchronous coefficient, the vehicle flow speed value and the dynamic impact value, and makes a judgment and analysis on them to obtain a set of illumination demand roads and a set of color temperature demand roads, and sends them to the information matching unit;

[0011] The information matching unit matches the illuminance requirement road set and the color temperature requirement road set with corresponding illuminance and color temperature respectively.

[0012] Furthermore, the specific operation steps of the line impact value are as follows:

[0013] Obtain the lamp placement influence factor coefficient, road material reflection influence factor coefficient, water accumulation influence factor coefficient, geological influence factor coefficient, bending influence factor coefficient and bridge and tunnel shape influence factor coefficient of the line information in the road condition information of the smart street lighting work, and obtain the line influence value xy according to the formula analysis.

[0014] Furthermore, the specific operation steps of the bending influence factor coefficient and the bridge and tunnel shape influence factor coefficient are as follows:

[0015] Obtain the curve curvature radius, longitudinal slope value, curve density, curve deflection angle and curve sight distance of the line information in the road condition information of the smart street lighting work, and calculate by formula analysis to obtain the curve change influence factor coefficient wb;

[0016] The tunnel entrance and exit hole height, tunnel cross-sectional area, tunnel dust content and tunnel linear curvature of the line information in the road condition information of the smart street lighting are obtained, and the tunnel shape value szy is calculated by formula analysis; the span-width ratio and bridge deck material reflectivity of the bridge in the line information in the road condition information of the smart street lighting are obtained, and the weighted calculation is performed and multiplied by the corresponding proportional factor to obtain the bridge status value; the tunnel shape value and the bridge status value are processed according to the graphical construction and marked as the bridge-tunnel shape influencing factor coefficient.

[0017] Furthermore, the specific operation steps of the environmental impact value are as follows:

[0018] Obtain the environmental information weather deterioration value, boundary value and tree density value in the road condition information of the smart street lighting work, and obtain the environmental deterioration impact value jlz through formula analysis.

[0019] Furthermore, the specific operation steps of the environmental information weather bad value are as follows:

[0020] The road condition information of smart street lighting is obtained, including the snow purity, snow crystal density, atmospheric particulate matter concentration, rain visibility and fog droplet number density in bad weather, and the weather deterioration value te of the environmental information is obtained by analysis.

[0021] Furthermore, the specific operation steps of the dynamic impact value are as follows:

[0022] Obtain dynamic information from the road condition information of smart street lighting, monitor pedestrian information within the road area, decompose the area into several sub-areas, obtain the unit pedestrian density of the sub-area, use time as the horizontal coordinate and pedestrian density as the total coordinate, establish a two-dimensional pedestrian density change curve, and analyze and obtain the pedestrian abnormality value xrz of the sub-area;

[0023] The pedestrian abnormality value is compared with the set pedestrian abnormality value reference interval for analysis. When the pedestrian abnormality value is greater than the maximum value of the pedestrian abnormality value reference interval, the sub-region is a first-level pedestrian abnormality region. When the pedestrian abnormality value is within the pedestrian abnormality value reference interval, the sub-region is a second-level pedestrian abnormality region. When the pedestrian abnormality value is less than the minimum value of the pedestrian abnormality value reference interval, the sub-region is a third-level pedestrian abnormality region. The number of first-level pedestrian abnormality regions, second-level pedestrian abnormality regions, and third-level pedestrian abnormality regions is counted and calculated as yg, eg, and sg. According to the set formula The pedestrian asynchronous coefficient xbx is obtained, where d1, d2 and d3 are the correction factor coefficients of the number of first-level pedestrian abnormal areas, the number of second-level pedestrian abnormal areas and the number of third-level pedestrian abnormal areas, respectively.

[0024] Obtain the vehicle height value, vehicle trajectory value, and vehicle flow rate value of the dynamic information section in the road condition information of the smart street lighting, and calibrate them as ct, cg, and cl respectively, and calculate them with the pedestrian asynchronous coefficient xbx through formula processing to obtain the dynamic impact value dyz;

[0025] Furthermore, the specific operation steps of the illumination requirement road set and the color temperature requirement road set are as follows:

[0026] The bending influence factor coefficient wb, the environmental influence value jlz and the dynamic influence value dyz are processed according to the graph construction to obtain the road illumination demand value;

[0027] Set the gradient reference intervals X1, X2 and X3 of the road illumination demand value, and substitute the road illumination demand value into the preset gradient reference intervals X1, X2 and X3 for comparative analysis, wherein X1, X2 and X3 increase in a gradient manner;

[0028] When the road illumination demand value is within the preset gradient reference interval X1, the corresponding road is classified into the third-level illumination demand road set A3; when the road illumination demand value is within the preset gradient reference interval X2, the corresponding road is classified into the second-level illumination demand road set A2; when the road illumination demand value is within the preset gradient reference interval X3, the corresponding road is classified into the first-level illumination demand road set A1;

[0029] Obtain the traffic flow jl in the road condition information of the smart street lighting work, analyze the bending influence factor coefficient wb, the environmental influence value jlz, the pedestrian asynchronous coefficient xbx and the traffic flow jl to obtain the road condition color temperature demand value lsq;

[0030] The road color temperature requirement value is compared and analyzed with the preset complete reference threshold TH1. When the road color temperature requirement value is greater than the preset complete reference threshold TH1, the corresponding road is classified into the first-level color temperature requirement road set B1. When the road color temperature requirement value is equal to the preset complete reference threshold TH1, the corresponding road is classified into the second-level color temperature requirement road set B2. When the road color temperature requirement value is less than the preset complete reference threshold TH1, the corresponding road is classified into the third-level color temperature requirement road set B3.

[0031] Furthermore, the specific operation steps for matching the corresponding illumination and color temperature are as follows:

[0032] If the road is in the first-level illumination demand road set A1, the corresponding road illumination is adjusted to y1 times the design standard value; if the road is in the second-level illumination demand road set A2, the corresponding road illumination is adjusted to y2 times the design standard value; if the road is in the third-level illumination demand road set A3, the corresponding road illumination is adjusted to y3 times the design standard value; where y1>y2>y3;

[0033] If the road is in the first-level color temperature requirement road set B1, the corresponding road lighting color temperature is adjusted to y4 times the design standard value; if the road is in the second-level color temperature requirement road set B2, the corresponding road lighting color temperature is adjusted to y5 times the design standard value; if the road is in the third-level color temperature requirement road set B3, the corresponding road lighting color temperature is adjusted to y6 times the design standard value; among them, y4>y5>y6.

[0034] Furthermore, the server communication connection also includes:

[0035] The data collection unit is used to collect the line information, environmental information and dynamic feature information in the road condition information of the smart street lamp lighting, and send it to the line analysis unit and the environmental dynamic unit;

[0036] The matching verification unit retrieves the matching quality information of the smart street lighting work to perform matching verification training analysis and processing.

[0037] Furthermore, the specific operation steps of the matching verification training analysis process are as follows:

[0038] Real-time acquisition of energy-saving value, luminous flux maintenance rate, traffic accident rate, and light decay stability value of matching quality information in smart street lighting work, and analysis to obtain the matching quality coefficient χ of lighting work;

[0039] Compare and analyze the matching quality coefficient of the lighting work with the set comparison threshold TT2. When the matching quality coefficient is less than the set comparison threshold TT2, a matching verification negative feedback signal is generated. Conversely, when the matching quality coefficient is greater than or equal to the set comparison threshold TT2, a matching verification positive feedback signal is generated.

[0040] When a matching verification positive feedback signal is generated, it is sent to the display terminal for display in the form of a text description of "the smart street lighting has been well matched and adjusted";

[0041] When a matching verification negative feedback signal is generated, it is sent to the display terminal for display in the form of a text description of "the smart street lighting has not been well matched and adjusted".

[0042] Compared with the prior art, the present invention has the following beneficial effects:

[0043] 1. The present invention analyzes the line information, environmental information and dynamic information of different roads to obtain the line impact value, environmental impact value and dynamic impact value respectively, and performs judgment and analysis on them to obtain the illumination demand road set and the color temperature demand road set, and matches them with the corresponding illumination and color temperature to obtain the corresponding illumination and color temperature matching corresponding to different sets. It can consider various situations in the road line, the influence of the external environment of the road and pedestrians and vehicles, and can consider automatic adjustment of different illumination and color temperatures, which greatly reduces the traffic accident rate, reduces the energy cost of street lamp management, and reduces the occurrence of street lamp safety accidents.

[0044] 2. The present invention obtains the matching quality coefficient of the lighting work by analyzing the matching quality information, and compares and analyzes it with the set comparison threshold to obtain a matching verification feedback signal, and sends it to the display terminal for display and explanation. It can consider the quality information of street lamp lighting, know the quality results of street lamp lighting control, and provide timely feedback to relevant staff. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. The following drawings are not intentionally scaled to the actual size, and the focus is on illustrating the main purpose of the present invention.

[0046] Figure 1 It is a system block diagram of the present invention. DETAILED DESCRIPTION

[0047] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work also fall within the scope of protection of the present invention.

[0048] like Figure 1 As shown, an LED smart street lamp lighting control system suitable for different road conditions includes a server, and the server is communicatively connected to a data acquisition unit, a line analysis unit, an environmental dynamics unit, a comprehensive evaluation unit, an information matching unit, a matching verification unit and a display terminal.

[0049] The data acquisition unit is used to collect line information, environmental information and dynamic feature information from the road condition information of the smart street lighting work, and send it to the line analysis unit and the environmental dynamic unit;

[0050] When the route analysis unit receives the route information in the road condition information of the smart street lighting, and performs a qualitative analysis of the route impact based on it, the specific operation process is as follows:

[0051] Obtain the line information bending influence factor coefficient, bridge and tunnel shape influence factor coefficient, water accumulation influence factor coefficient, geological influence factor coefficient, lamp placement influence factor coefficient and road material reflection influence factor coefficient in the road condition information of smart street lighting, and calibrate them as wb, qs, js, dy, dz and lc respectively, and perform normalization analysis on them. According to the formula

[0052] The line influence value xy is obtained, wherein ω1, ω2, ω3, ω4, ω5 and ω6 are correction factor coefficients of the bending influence factor coefficient, the bridge and tunnel shape influence factor coefficient, the water accumulation influence factor coefficient, the geological influence factor coefficient, the lighting influence factor coefficient and the road material reflection influence factor coefficient, and ω1, ω2, ω3, ω4, ω5 and ω6 are all natural numbers greater than 0;

[0053] It should be noted that the waterlogging impact factor coefficient refers to the weighted calculation of the waterlogging area, water turbidity value and waterlogging depth per unit area, and multiplying it by the corresponding impact factor; the geological impact factor coefficient refers to the weighted calculation of the surrounding rock crack depth, road settlement and slope sliding coefficient, and multiplying it by the corresponding impact factor; the lighting placement impact factor coefficient refers to the number of street lights arranged per unit road surface area; the road material reflection impact factor coefficient refers to the reflectivity of the road surface material;

[0054] It should also be pointed out that the solution process of the bending influence factor coefficient wb and the bridge and tunnel shape anomaly influence factor coefficient is as follows:

[0055] Obtain the curve curvature radius, longitudinal slope value, curve density, curve deflection angle and curve sight distance of the line information in the road condition information of the smart street lighting work, and calibrate them as wq, zp, wm, wp and ws respectively, and perform normalization analysis on them. According to the formula

[0056] The bending influence factor coefficient wb is obtained, where a1, a2, a3, a4 and a5 are the correction factor coefficients of the curve curvature radius, longitudinal slope value, curve density, curve deflection angle and curve sight distance respectively, and e is a natural constant with a value of 2.718;

[0057] The tunnel entrance and exit hole height, tunnel cross-sectional area, tunnel dust content and tunnel linear curvature of the line information in the road condition information of the smart street lighting are obtained, and they are calibrated as rg, dm, tp and xw respectively, and normalized and analyzed according to the formula The tunnel shape value szy is obtained, where b1, b2, b3 and b4 are the correction factor coefficients of the tunnel entrance and exit hole height, tunnel cross-sectional area, tunnel dust content and tunnel linear curvature respectively; the span-width ratio and bridge deck material reflectivity of the bridge in the line information of the road condition information of the smart street lighting are obtained, and the weighted calculation is performed and multiplied by the corresponding proportional factor to obtain the bridge state value; the tunnel shape value is converted into length according to a certain ratio, and an equilateral triangle is constructed with the length of the tunnel shape value as the side length of the equilateral triangle; the bridge state value is converted into length according to a certain ratio, and a square is constructed inside the equilateral triangle with the length of the bridge state value as the side length of the square. The center of the square coincides with the center of the equilateral triangle, and the non-overlapping area formed is identified and marked as the bridge-tunnel shape influencing factor coefficient;

[0058] When the environmental dynamic unit receives environmental information in the road condition information of the smart street lighting work, and performs qualitative analysis and processing of environmental impact based on it; receives dynamic information in the road condition information of the smart street lighting work, and performs qualitative analysis and processing of dynamic impact based on it, the specific operation process is as follows:

[0059] Obtain the environmental information weather value, boundary value and tree density value in the road condition information of smart street lighting, and calibrate them as te, jx and js respectively, and perform normalization analysis on them. According to the formula The environmental impact value jlz is obtained, where UO1, UO2 and UO3 are the preset weight factors of the environmental information weather value, the environmental line value and the tree density value, and σ is the preset correction factor;

[0060] It should be noted that the boundary value refers to the sum of the road environment light values, mainly moonlight, starlight and billboard reflection light; the tree density value is obtained by taking the road as the center and a certain distance as the radius to obtain the sum of the building area, the average building height, the number of trees and the tree crown distribution value within the range, and weighted calculation, and multiplying it by the corresponding preset weight factor;

[0061] It should also be pointed out that the solution process of the environmental information weather deterioration value te is as follows:

[0062] Obtain environmental information such as snow purity, snow crystal density, atmospheric particulate matter concentration, rain visibility and fog droplet density in bad weather during road condition information of smart street lighting, and calibrate them as xc, xm, dk, yn and wd respectively, normalize them and substitute them into the formula

[0063] The environmental information weather deterioration value te is obtained, where λ1, λ2, λ3, λ4 and λ5 are respectively the preset weight factors of snow purity, snow crystal density, atmospheric particulate matter concentration, rain visibility and fog droplet number density, and κ is the preset correction factor;

[0064] Obtain dynamic information from the road condition information of smart street lighting, monitor pedestrian information within the road area, decompose the area into several sub-areas, obtain the unit pedestrian density of the sub-area, use time as the horizontal coordinate and pedestrian density as the total coordinate, establish a two-dimensional pedestrian density change curve chart, and mark it as xm i , i is the number of the monitoring time point, i = 1, 2, 3...I, I is a positive integer, according to the formula Get the average pedestrian density Draw a tangent to the curve at each monitoring point and obtain the acute angle θ formed by the tangent and the horizontal line i , take the cosine value cosθ of the monitoring point i , according to the set formula Get the pedestrian fluctuation value xb, where c1 and c2 are the correction factor coefficients of the unit pedestrian density and the cosine value of the monitoring point, respectively, and X1 is the cosine value of the set reference monitoring point; get the maximum pedestrian density x in the pedestrian density change curve max , the minimum pedestrian density x min , according to the set formula The pedestrian abnormality value xrz of the sub-region is obtained, c3 is the correction factor coefficient of the pedestrian fluctuation value, c4 and c5 are the correction factor coefficients of the maximum and minimum pedestrian density values ​​in the formula, c6 and c7 are the correction factor coefficients of the maximum and minimum pedestrian density values ​​in the formula;

[0065] The pedestrian abnormality value is compared with the set pedestrian abnormality value reference interval for analysis. When the pedestrian abnormality value is greater than the maximum value of the pedestrian abnormality value reference interval, the sub-region is a first-level pedestrian abnormality region. When the pedestrian abnormality value is within the pedestrian abnormality value reference interval, the sub-region is a second-level pedestrian abnormality region. When the pedestrian abnormality value is less than the minimum value of the pedestrian abnormality value reference interval, the sub-region is a third-level pedestrian abnormality region. The number of first-level pedestrian abnormality regions, second-level pedestrian abnormality regions, and third-level pedestrian abnormality regions is counted and calculated as yg, eg, and sg. According to the set formula The pedestrian asynchronous coefficient xbx is obtained, where d1, d2 and d3 are correction factor coefficients of the number of first-level pedestrian abnormal areas, the number of second-level pedestrian abnormal areas and the number of third-level pedestrian abnormal areas respectively;

[0066] Obtain the dynamic information of the road condition information of the smart street lighting, including the vehicle height value, vehicle trajectory value, and vehicle flow rate value, and calibrate them as ct, cg, and cl respectively, and normalize them with the pedestrian asynchronous coefficient xbx and substitute them into the formula The dynamic influence value dyz is obtained; wherein LP1, LP2, LP3 and LP4 are preset weight factors of vehicle height value, vehicle trajectory value, vehicle flow speed value and pedestrian asynchronous coefficient, and ρ is a preset correction factor;

[0067] It should be noted that the vehicle height value refers to the value obtained by weighting the sum of the volume of vehicles on the road and the average height multiplied by the corresponding proportional factor; the vehicle trajectory value refers to the sum of the number of vehicle U-turns, turns and lane change trajectories on the road; the vehicle flow rate value refers to the value obtained by weighting the road traffic flow and the average vehicle speed multiplied by the corresponding proportional factor;

[0068] The comprehensive evaluation unit is used to receive the bending influence factor coefficient wb, the environmental influence value jlz, the pedestrian asynchronous coefficient xbx, the vehicle flow speed value cl and the dynamic influence value dyz, and make judgments and analyses on them to obtain the illumination demand road set and the color temperature demand road set. The specific analysis is as follows:

[0069] The bending influence factor coefficient wb and the environmental impact value jlz are converted into lengths according to a certain ratio, and an ellipse is constructed with the bending influence factor coefficient wb and the environmental impact value jlz as the short axis and long axis of the ellipse respectively; the dynamic influence value dyz is converted into lengths according to a certain ratio, and an equilateral triangle is constructed with the length of the dynamic influence value dyz as the side length of the equilateral triangle. The center of the equilateral triangle coincides with the endpoint of the long axis on the right side of the ellipse, and the non-overlapping area formed by the equilateral triangle and the ellipse is identified and marked as the road illumination demand value;

[0070] Set the gradient reference intervals X1, X2 and X3 of the road illumination demand value, and substitute the road illumination demand value into the preset gradient reference intervals X1, X2 and X3 for comparative analysis, wherein X1, X2 and X3 increase in a gradient manner;

[0071] When the road illumination demand value is within the preset gradient reference interval X1, the corresponding road is classified into the third-level illumination demand road set A3; when the road illumination demand value is within the preset gradient reference interval X2, the corresponding road is classified into the second-level illumination demand road set A2; when the road illumination demand value is within the preset gradient reference interval X3, the corresponding road is classified into the first-level illumination demand road set A1;

[0072] Obtain the traffic flow jl in the road condition information of smart street lighting, normalize the bending influence factor coefficient wb, environmental influence value jlz, pedestrian asynchronous coefficient xbx and traffic flow jl, and calculate the value according to the set formula The road color temperature demand value lsq is obtained, where μ is a preset correction factor, and β1, β2, β3 and β4 are all preset weight factors; it should be noted that when the flow of people and vehicles is large, when the color temperature is adjusted low, it is conducive to improving people's comfort and reducing the irritability of congestion;

[0073] Compare and analyze the road color temperature requirement value with the preset complete reference threshold TH1. When the road color temperature requirement value is greater than the preset complete reference threshold TH1, the corresponding road is classified into the first-level color temperature requirement road set B1. When the road color temperature requirement value is equal to the preset complete reference threshold TH1, the corresponding road is classified into the second-level color temperature requirement road set B2. When the road color temperature requirement value is less than the preset complete reference threshold TH1, the corresponding road is classified into the third-level color temperature requirement road set B3.

[0074] The information matching unit receives the road set with illumination requirements and the road set with color temperature requirements, and matches them with the corresponding illumination and color temperature. The specific analysis is as follows:

[0075] If the road is in the first-level illumination demand road set A1, the corresponding road illumination is adjusted to y1 times the design standard value; if the road is in the second-level illumination demand road set A2, the corresponding road illumination is adjusted to y2 times the design standard value; if the road is in the third-level illumination demand road set A3, the corresponding road illumination is adjusted to y3 times the design standard value; the illumination of expressways and trunk roads is stipulated to be 20-30 lux, that of secondary trunk roads is 15-20 lux, and that of branch roads is 8-10 lux, where y1>y2>y3, the value range of y1 is 0.95-1.05, the value range of y2 is 0.9-0.94, and the value range of y3 is 0.85-0.89;

[0076] If the road is in the first-level color temperature demand road set B1, the corresponding road lighting color temperature is adjusted to y4 times the design standard value; if the road is in the second-level color temperature demand road set B2, the corresponding road lighting color temperature is adjusted to y5 times the design standard value; if the road is in the third-level color temperature demand road set B3, the corresponding road lighting color temperature is adjusted to y6 times the design standard value; the road lighting color temperature range is 4000-5000K, K is the Kelvin temperature unit, y4>y5>y6, y4 range is 0.95-1.10, y5 range is 0.91-0.94, y6 range is 0.85-0.90;

[0077] When the matching verification unit retrieves the matching quality information of the smart street lighting work for matching verification training analysis and processing, the specific operation process is as follows:

[0078] The energy saving value, luminous flux maintenance rate, traffic accident rate, and light decay stability value of the matching quality information in the smart street lighting work are obtained in real time, and they are calibrated as δ, γ, ε, and α respectively, and they are analyzed in a formula. The matching quality coefficient χ of the lighting work is obtained, p1, p2, p3 and p4 are the correction factor coefficients of the energy saving value, the luminous flux maintenance rate, the traffic accident rate and the light decay stability value respectively, and ζ is the preset correction factor;

[0079] It should be noted that the energy saving value refers to the difference between the energy consumption after matching and before matching, the luminous flux maintenance rate refers to the ratio of the luminous flux of the street lamp after a certain period of use to the initial luminous flux; the light decay stability value refers to the maintenance rate of the brightness of the street lamp after a certain period of use;

[0080] Compare and analyze the matching quality coefficient of the lighting work with the set comparison threshold TT2. When the matching quality coefficient is less than the set comparison threshold TT2, a matching verification negative feedback signal is generated. Conversely, when the matching quality coefficient is greater than or equal to the set comparison threshold TT2, a matching verification positive feedback signal is generated.

[0081] When a matching verification positive feedback signal is generated, it is sent to the display terminal for display in the form of a text description of "the smart street lighting has been well matched and adjusted";

[0082] When a matching verification negative feedback signal is generated, it is sent to the display terminal for display in the form of a text description of "the smart street lighting has not been well matched and adjusted".

[0083] The formulas given in this application are all custom constructed by technicians and pre-stored in the server, and the weight factors and correction factors preset in the formulas are all custom set by technicians.

[0084] The above is an explanation of the present invention and should not be considered as a limitation thereof. Although several exemplary embodiments of the present invention have been described, it will be readily appreciated by those skilled in the art that many modifications may be made to the exemplary embodiments without departing from the novel teachings and advantages of the present invention. Therefore, all such modifications are intended to be included within the scope of the present invention as defined in the claims. It should be understood that the above is an explanation of the present invention and should not be considered as being limited to the specific embodiments disclosed, and modifications to the disclosed embodiments and other embodiments are intended to be included within the scope of the appended claims. The present invention is defined by the claims and their equivalents.

Claims

1. An LED smart street lighting control system suitable for different road conditions, including a server, characterized in that: The server communication connections are: The line analysis unit performs a qualitative analysis of the line information in the road condition information of the smart street lighting work to obtain the line impact value and sends it to the comprehensive evaluation unit; The environmental dynamic unit performs qualitative analysis and processing of environmental information in the road condition information of the smart street lighting work to obtain the environmental impact value; performs qualitative analysis and processing of dynamic information in the road condition information of the smart street lighting work to obtain the dynamic impact value, and sends it to the comprehensive evaluation unit; The comprehensive evaluation unit receives the bending influence factor coefficient, the environmental impact value, the pedestrian asynchronous coefficient, the vehicle flow speed value and the dynamic impact value, and makes judgments and analyses them to obtain the illumination demand road set and the color temperature demand road set, and sends them to the information matching unit; The information matching unit matches the illumination requirement road set and the color temperature requirement road set with the corresponding illumination and color temperature respectively.

2. The LED smart street lamp lighting control system applicable to different road conditions according to claim 1 is characterized in that: The specific operation steps of the line impact value are as follows: Obtain the lighting placement influence factor coefficient, road material reflection influence factor coefficient, water accumulation influence factor coefficient, geological influence factor coefficient, bending influence factor coefficient and bridge and tunnel shape influence factor coefficient of the line information in the road condition information of the smart street lighting work, and obtain the line impact value based on the formula analysis.

3. The LED smart street lamp lighting control system applicable to different road conditions according to claim 2 is characterized in that: The specific operation steps of the bending influence factor coefficient and the bridge and tunnel shape influence factor coefficient are as follows: Obtain the curve curvature radius, longitudinal slope value, curve density, curve deflection angle and curve sight distance of the line information in the road condition information of the smart street lighting work, and analyze them to obtain the curve change influence factor coefficient; The tunnel entrance and exit hole height, tunnel cross-sectional area, tunnel dust content and tunnel linear curvature of the line information in the road condition information of the smart street lighting work are obtained, and the tunnel state value szy is obtained by analysis and calculation; the span-width ratio and bridge deck material reflectivity of the bridge of the line information in the road condition information of the smart street lighting work are obtained, and the weighted calculation and multiplication by the corresponding proportional factor are obtained to obtain the bridge state value; The tunnel condition value and bridge status value are processed according to the graphical construction and marked as the coefficient of the bridge-tunnel condition influencing factor.

4. The LED smart street lamp lighting control system applicable to different road conditions according to claim 1 is characterized in that: The specific operation steps of the environmental impact value are as follows: Obtain the environmental information weather deterioration value, boundary value and building density value in the road condition information of smart street lighting work, and analyze to obtain the environmental deterioration impact value.

5. The LED smart street lamp lighting control system applicable to different road conditions according to claim 4 is characterized in that: The specific operation steps of the environmental information weather deterioration value are as follows: The road condition information of smart street lighting is obtained, including snow purity, snow crystal density, atmospheric particulate matter concentration, rain visibility and fog droplet density in bad weather, and the environmental information weather deterioration value is obtained by analysis.

6. The LED smart street lamp lighting control system applicable to different road conditions according to claim 1 is characterized in that: The specific operation steps of the dynamic impact value are as follows: Obtain dynamic information from the road condition information of smart street lighting, monitor pedestrian information within the road area, decompose the area into several sub-areas, obtain the unit pedestrian density of the sub-area, use time as the horizontal coordinate and pedestrian density as the total coordinate, establish a two-dimensional pedestrian density change curve, and analyze and obtain the pedestrian abnormality value xrz of the sub-area; The pedestrian abnormality value is compared with the set pedestrian abnormality value reference interval for analysis. When the pedestrian abnormality value is greater than the maximum value of the pedestrian abnormality value reference interval, the sub-region is a first-level pedestrian abnormality region. When the pedestrian abnormality value is within the pedestrian abnormality value reference interval, the sub-region is a second-level pedestrian abnormality region. When the pedestrian abnormality value is less than the minimum value of the pedestrian abnormality value reference interval, the sub-region is a third-level pedestrian abnormality region. The number of first-level pedestrian abnormality regions, second-level pedestrian abnormality regions, and third-level pedestrian abnormality regions is counted and calculated as yg, eg, and sg. According to the set formula The pedestrian asynchronous coefficient xbx is obtained, where d1, d2 and d3 are correction factor coefficients of the number of first-level pedestrian abnormal areas, the number of second-level pedestrian abnormal areas and the number of third-level pedestrian abnormal areas respectively; The vehicle height value, vehicle trajectory value, and vehicle flow rate value of the dynamic information section in the road condition information of the smart street lighting are obtained, and the pedestrian asynchronous coefficient xbx is processed and calculated by formula to obtain the dynamic impact value dyz.

7. The LED smart street lamp lighting control system applicable to different road conditions according to claim 1 is characterized in that: The specific operation steps of the illumination requirement road set and the color temperature requirement road set are as follows: The bending influence factor coefficient wb, the environmental influence value jlz and the dynamic influence value dyz are processed according to the graph construction to obtain the road illumination demand value; Set the gradient reference intervals X1, X2 and X3 of the road illumination demand value, and substitute the road illumination demand value into the preset gradient reference intervals X1, X2 and X3 for comparative analysis, wherein X1, X2 and X3 increase in a gradient manner; When the road illumination demand value is within the preset gradient reference interval X1, the corresponding road is classified into the third-level illumination demand road set A3; when the road illumination demand value is within the preset gradient reference interval X2, the corresponding road is classified into the second-level illumination demand road set A2; when the road illumination demand value is within the preset gradient reference interval X3, the corresponding road is classified into the first-level illumination demand road set A1; Obtain the traffic flow jl in the road condition information of the smart street lighting work, analyze the bending influence factor coefficient wb, the environmental influence value jlz, the pedestrian asynchronous coefficient xbx and the traffic flow jl to obtain the road condition color temperature demand value lsq; The road color temperature requirement value is compared and analyzed with the preset complete reference threshold TH1. When the road color temperature requirement value is greater than the preset complete reference threshold TH1, the corresponding road is classified into the first-level color temperature requirement road set B1. When the road color temperature requirement value is equal to the preset complete reference threshold TH1, the corresponding road is classified into the second-level color temperature requirement road set B2. When the road color temperature requirement value is less than the preset complete reference threshold TH1, the corresponding road is classified into the third-level color temperature requirement road set B3.

8. The LED smart street lamp lighting control system applicable to different road conditions according to claim 1 is characterized in that: The specific operation steps for matching the corresponding illumination and color temperature are as follows: If the road is in the first-level illumination demand road set A1, the corresponding road illumination is adjusted to y1 times the design standard value; if the road is in the second-level illumination demand road set A2, the corresponding road illumination is adjusted to y2 times the design standard value; if the road is in the third-level illumination demand road set A3, the corresponding road illumination is adjusted to y3 times the design standard value; where y1>y2>y3; If the road is in the first-level color temperature requirement road set B1, the corresponding road lighting color temperature is adjusted to y4 times the design standard value; if the road is in the second-level color temperature requirement road set B2, the corresponding road lighting color temperature is adjusted to y5 times the design standard value; if the road is in the third-level color temperature requirement road set B3, the corresponding road lighting color temperature is adjusted to y6 times the design standard value; among them, y4>y5>y6.

9. The LED smart street lamp lighting control system applicable to different road conditions according to claim 1 is characterized in that: The server also communicates with: The data collection unit is used to collect the line information, environmental information and dynamic feature information in the road condition information of the smart street lamp lighting, and send it to the line analysis unit and the environmental dynamic unit; The matching verification unit is used to retrieve the matching quality information of the smart street lighting work for matching verification training analysis and processing.

10. The LED smart street lamp lighting control system applicable to different road conditions according to claim 9, characterized in that: The specific operation steps of the matching verification training analysis process are as follows: Real-time acquisition of energy-saving value, luminous flux maintenance rate, traffic accident rate, and light decay stability value of matching quality information in smart street lighting work, and analysis to obtain the matching quality coefficient χ of lighting work; Compare and analyze the matching quality coefficient of the lighting work with the set comparison threshold TT2. When the matching quality coefficient is less than the set comparison threshold TT2, a matching verification negative feedback signal is generated. Conversely, when the matching quality coefficient is greater than or equal to the set comparison threshold TT2, a matching verification positive feedback signal is generated. When a matching verification positive feedback signal is generated, it is sent to the display terminal for display in the form of a text description of "the smart street lighting has been well matched and adjusted"; When a matching verification negative feedback signal is generated, it is sent to the display terminal for display in the form of a text description of "the smart street lighting has not been well matched and adjusted".

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