JP6539144B2 - Method and system for predicting deterioration of lighting - Google Patents

Description

  The present invention relates to a method and system for predicting deterioration of a lamp, and in particular, a method for photographing a lamp on a tunnel lining surface by a photographing means mounted on a vehicle traveling in a tunnel to predict the degree of deterioration of each lamp. And the system.

  In tunnels such as expressways, the driver's visual environment is bad. For this reason, depending on the traffic volume, construction of lighting equipment and interior work, inspection of various facilities and cleaning of tunnel accessories are performed.

Deterioration of the lighting equipment in the tunnel is a major factor that reduces the visual environment in the tunnel.

For this reason, attempts are made to evaluate the degree of deterioration of the lighting equipment in the tunnel. Conventionally, an illuminance measurement vehicle is periodically run to measure the illuminance in the vicinity of the road surface to evaluate the degree of deterioration of the lighting equipment.

Patent Document 1 below describes an invention that determines the replacement time of a lighting fixture based on data of the replacement cost of the lighting fixture and the cost of power consumption.

Further, in Patent Document 2 below, an illuminance measurement unit is provided to a cleaning robot that cleans a plurality of lighting fixtures arranged along a tunnel, and the illuminance measurement is performed when the cleaning robot is located in the vicinity of the lighting fixture to be measured. The invention is described in which the light output of the luminaire to be measured is measured in part.

JP 2007-59133 A JP 2005-339920 A

However, in the prior art, it was not possible to evaluate the deterioration of each lamp.

Therefore, the present invention evaluates the degree of deterioration of individual lightings, that is, the decrease in illumination output and the turbidity of the glass surface, for example, by running a tunnel lining surface taking vehicle and analyzing the image taken. The problem to be solved is to be able to accurately predict the cleaning time of each lamp and the replacement time of each lamp.

The first invention is
A correspondence setting step of setting in advance correspondence relations between the turbidity of the illumination light, the illumination output of the illumination light, and the illumination ratio as a ratio of the illumination intensity of the illumination to the reference value;
A photographing step of photographing a lamp to be subjected to deterioration prediction;
A luminance distribution curve is acquired from the photographed image, and a coefficient of variation as a slope when shifting to the maximum value of luminance is obtained on the luminance distribution curve, and turbidity of the deterioration prediction target lamp is estimated based on the coefficient of variation. Turbidity estimation step to calculate the value,
An illumination output estimation step of computing an estimated value of the illumination output of the illumination lamp for deterioration prediction based on the luminance maximum value on the luminance distribution curve and the turbidity estimated value;
Illuminance ratio estimation step of applying the turbidity estimated value and the illumination output estimated value to the set correspondence relationship to obtain an estimated value of the illuminance ratio of the deterioration prediction target lamp; It is characterized in that it is a method.

The second invention is the first invention,
In the turbidity estimation step, a luminance distribution curve is obtained for each turbidity, and based on the luminance distribution curve for each turbidity, a turbidity estimation operation equation is calculated in advance to estimate and calculate the turbidity using a variation coefficient as a variable The turbidity estimated value is calculated by applying the variation coefficient obtained from the photographed image of the deterioration prediction target lamp to the turbidity estimation calculation equation.

The third invention relates to the first invention or the second invention,
In the illumination output estimation step, a luminance distribution curve is obtained for each turbidity, and an illumination output is estimated and calculated using the luminance maximum value as a variable based on the luminance distribution curve and the turbidity estimated value for each turbidity. An estimated calculation equation is calculated in advance, and the maximum illumination value and the turbidity estimated value determined from the photographed image of the deterioration prediction target lamp are applied to the illumination output estimation calculation equation to calculate the estimated illumination output value. It is characterized by

The fourth invention is any one of the first invention to the third invention,
The deterioration prediction target lamp installed on the tunnel lining surface is photographed by a photographing unit mounted on a vehicle traveling in the tunnel.

The fifth invention is
It is a deterioration prediction system of a lamp, which photographs a deterioration prediction target lamp installed on a tunnel lining surface by a photographing means mounted on a vehicle traveling in the tunnel and predicts the deterioration of the deterioration forecast lamp. ,
The correspondence relationship between the turbidity of the lamp, the illumination output of the lamp, and the illumination ratio as a ratio to the reference value of the illumination of the lamp is set in advance,
The illumination light of the deterioration prediction target is photographed by the photographing means,
A luminance distribution curve is acquired from the photographed image, and a coefficient of variation as a slope when shifting to the maximum value of luminance is obtained on the luminance distribution curve, and turbidity of the deterioration prediction target lamp is estimated based on the coefficient of variation. Calculate the value,
The estimated value of the illumination output of the illumination lamp subject to deterioration prediction is calculated based on the luminance maximum value on the luminance distribution curve and the turbidity estimated value,
Applying the turbidity estimated value and the illumination output estimated value to the set correspondence relationship to obtain an estimated value of the illuminance ratio of the deterioration prediction target lamp;
Necessity of cleaning of the deterioration prediction target lamp and the deterioration degree of the light source of the deterioration prediction target lamp based on the turbidity estimation value of the deterioration prediction target lamp, the illumination output estimation value, and the illuminance ratio estimation value To predict.

The sixth invention is the fifth invention,
A brightness distribution curve is obtained for each turbidity, and based on the brightness distribution curve for each turbidity, a turbidity estimation operation equation for estimating and calculating the turbidity using the variation coefficient as a variable is obtained in advance, and the turbidity estimation is performed. The turbidity estimated value is calculated by applying the variation coefficient obtained from the photographed image of the deterioration prediction target lamp to the arithmetic expression.

The seventh invention is the fifth invention or the sixth invention,
A luminance distribution curve is obtained for each turbidity, and an illumination output estimation calculation equation is calculated in advance for estimating and calculating an illumination output with the maximum luminance value as a variable based on the luminance distribution curve and the turbidity estimated value for each turbidity. The lighting output estimated value is calculated by applying the maximum luminance value and the turbidity estimated value obtained from the photographed image of the deterioration prediction target lamp to the lighting output estimation arithmetic expression.

The eighth invention is any of the fifth invention to the seventh invention,
The lighting device for deterioration prediction includes a plurality of lighting devices for prediction of deterioration, and is characterized in that the deterioration of the lighting device for prediction of deterioration is predicted by predicting the deterioration of each lighting device for prediction of deterioration. .

  According to the present invention, it is possible to evaluate the degree of deterioration of individual lightings, that is, the decrease in illumination output and the turbidity of the glass surface, for example, by traveling a tunnel lining surface imaging vehicle and analyzing the captured image. As a result, it is possible to accurately predict the cleaning time of each lamp and the replacement time of each lamp.

FIG. 1 is a view showing a configuration of a deterioration prediction system for a lamp according to the present invention. FIG. 2 is a flowchart showing the processing procedure of the method of predicting deterioration of a lamp according to the present invention. Fig.3 (a) is a figure which shows a lighting fixture, FIG.3 (b) is a figure which shows the experimental fixture used for the pre-processing for preparation of a lighting degradation evaluation processing program. FIG. 4 is a view showing the correspondence between the turbidity of the lamp, the illumination output of the lamp, and the illumination ratio of the lamp. Fig.5 (a) is a figure which shows an example of the picked-up image of a lighting fixture, and the illumination output is 100% in FIG.5 (b), (c), (d), (e), respectively, and turbidity is It is a figure which shows the image of the analysis area at the time of each level of 0, 1, 3, 5 in FIG. FIG. 6 is a graph showing a luminance distribution curve in the image of the analysis area, in which the horizontal direction pixel position of the analysis area is taken on the horizontal axis, and the luminance value (gray scale) is shown on the vertical axis. FIG. 7 is a graph showing the relationship between the variation coefficient obtained from the analysis result of the brightness distribution curve shown in FIG. 6 and the turbidity (level of turbidity), with the variation coefficient taken along the horizontal axis and the turbidity as the logarithm It is the figure taken on the vertical axis. FIG. 8 shows the maximum luminance value (peak value) and the illumination output obtained from the analysis result of the luminance distribution curve for each level of the illumination output and the turbidity (luminance output: 0 to 100%, turbidity: 0 to 5 levels) It is the graph which showed the relationship with (%), and is the figure which took the luminance maximum value (peak value) on the horizontal axis, and took the illumination output (%) on the vertical axis. Fig.9 (a) is a graph which shows the correspondence of a turbidity estimation calculation value and inclination, and FIG.9 (b) is a graph which shows the correspondence of a turbidity estimation calculation and an intercept. FIG. 10 is a view showing a luminance distribution curve obtained from the measurement result of the embodiment. FIG. 11 is a diagram showing a diagnostic example of the lighting apparatus.

  Hereinafter, with reference to the drawings, embodiments of a method and system for predicting deterioration of a lamp according to the present invention will be described.

FIG. 1 shows the configuration of a deterioration prediction system for a lamp according to the present invention.

The vehicle 1 is a work vehicle based on a work truck used, for example, for road maintenance work. The vehicle 1 is equipped with a photographing unit 10 and an image data storage unit 20.

The personal computer 2 outside the vehicle 1 is installed with a program for the lamp deterioration prediction process.

That is, while the vehicle 1 travels in the tunnel, the lighting device 50 installed on the tunnel lining surface 90 is photographed by the photographing means 10 mounted on the vehicle 1. The lighting apparatus 50 is comprised from each illuminating lamp 51, 51 ... as shown to Fig.3 (a). Each illuminating lamp 51 is configured of, for example, an LED element.

The image data storage unit 20 of the vehicle 1 stores the image data captured by the imaging unit 10. The image data stored in the image data storage unit 20 is read out for the deterioration prediction process of the lamp 51, and taken into an external personal computer 2 via a storage medium or a data communication network 95 such as the Internet.

FIG. 2 is a flowchart showing the processing procedure of the method of predicting deterioration of a lamp according to the present invention. The processing contents of the lamp deterioration prediction method are pre-processing (steps 101, 102, and 103) previously performed for creating the above-described lamp deterioration prediction processing program, and a personal on which the lamp deterioration prediction processing program is installed. It consists of an image analysis process, a deterioration factor calculation process, and a lighting equipment deterioration prediction process (steps 104, 105, 106, 107) executed by the computer 2.

FIG. 3 (b) shows a laboratory tool used for pre-processing for creating a lamp deterioration prediction processing program.

That is, as shown in FIG. 3A, the same luminaire 50 installed on the tunnel lining surface 90 is prepared and installed on the stand 61. An illumination meter 70 and a single-lens reflex camera 80 are disposed in front of the lighting device 50.

Hereinafter, the process of the deterioration prediction method of the lamp shown in FIG. 2 will be described.

(Preprocessing)
In the pre-processing, first, processing of setting in advance a correspondence relationship M between the turbidity of the lamp 51, the illumination output of the lamp 51, and the illuminance ratio as a ratio to the reference value of the illuminance of the lamp 51 is performed.

  For this purpose, first, each single lamp 51 of the lighting fixture 50 is photographed by the single-lens reflex camera 80 shown in FIG. 3B, and the illuminance of the lighting fixture 50 is measured by the illuminance meter 70. .

  The factor of the illuminance reduction of the luminaire 50 in the tunnel is the reduction of the light output which is the deterioration of the individual lamps 51 (LED elements) and the turbidity which is mainly the dirt degree of the glass surface of the luminaire 50.

Therefore, in FIG. 3 (b), in order to reproduce the degree of dirt on the glass surface which is the front of the lighting fixture 50, the number of vinyls coated on the front of the lighting fixture 50 is changed to change the turbidity in six steps. I did. Moreover, in order to reproduce the illumination output which is deterioration of each illuminating lamp 51 (LED element), the power applied to the illuminating lamp 51, that is, the illumination output was switched in 9 steps and changed. The illuminance was measured by an illuminance meter 70 for each level of turbidity and illumination output.

  Thus, the illuminance is measured by the illuminance meter 70 for each of the six levels of turbidity and the level of illumination output, and is measured for each level of turbidity and illumination output, and the measured illuminance (lux) value is a predicted value (True value)

  FIG. 4 shows the correspondence M between the turbidity of the lamp 51, the illumination output of the lamp 51, and the illuminance ratio of the lamp 51. As shown in FIG. In FIG. 4, the degree of deterioration of the lighting device 50 is additionally indicated by a photograph.

That is, the turbidity is expressed at each level of 0, 1, 2, 3, 4, and 5, and the degree of contamination increases sequentially as the numerical value of the level increases, and the illumination output is 100, 90, 80, 70 60, 50, 40, 30, and 20, and it is assumed that the illumination output decreases sequentially as the percentage (%) of the illumination output decreases.

The illuminance ratio is a ratio of the measured illuminance to a reference value. The measured illuminance when the illumination output of the lamp 51 is maximum (100%) and the turbidity is minimum (0 level) is the reference value (illuminance ratio 1.00), and the reference value of the measured illuminance for each level (1 The ratio to .00) is shown as the illuminance ratio. For example, the illuminance ratio when the turbidity is 3 levels and the illumination output is 60% is 0.59 (step 101).

In the pre-processing, next, based on the luminance distribution curve for each turbidity, a turbidity estimation equation for calculating the turbidity using the variation coefficient as a variable is calculated.

That is, with the single-lens reflex camera 80 shown in FIG. 3B, the respective illumination lamps 51, 51... Of the illumination fixture 50 were photographed for each level of turbidity and illumination output.

Thus, for each of the six levels of turbidity and the nine levels of illumination output, the single-lens reflex camera 80 acquired a captured image for analysis.

FIG. 5A shows an example of a photographed image of the lighting device 50. An area 52 around a specific lamp 51 among the lamps 51 constituting the lighting apparatus 50 is an analysis area.

5 (b), (c), (d) and (e), the image of the analysis area 52 when the illumination output is 100% and the turbidity is each level of 0, 1, 3, 5 Indicates The center of the analysis area 52 corresponds to the center position of the specific lamp 51. When the image of the analysis area 52 is represented by gray scale of the gradation of luminance, in the figure, the luminance sequentially increases as it changes from black to white. In the photographing, an ND filter was used so that the peak of the luminance value of the illuminating lamp 51 could be captured.

FIG. 6 is a graph showing the luminance distribution curve in the image of the analysis area 52, and the pixel position in the transverse direction T (see FIGS. 5 (b), (c), (d) and (e)) of the analysis area 52 On the horizontal axis, the luminance value (gray scale) is on the vertical axis. The luminance distribution curve when the illumination output is 100% and the turbidity is 0 level is L0, the illumination output is 100%, and the luminance distribution curve when the turbidity is 1 level is L1 and the illumination output Is 100%, and the luminance distribution curve when the turbidity is 3 levels is L3, and the illumination output is 100%, the luminance distribution curve when the turbidity is 5 levels is L5.

As can be seen from FIG. 6, as the turbidity increases (stains) to levels 0, 1, 3 and 5, a uniform tendency is observed in the brightness distribution shape, with the peak portion of the brightness value decreasing. Therefore, five values of an average value, a standard deviation, a maximum value, a minimum value, and a contrast, which have differences in the distribution shape of the luminance distribution curve, are calculated as analysis values. As a result, the variation coefficient calculated from the average value and the standard deviation of the analysis values was adopted as a factor affecting the turbidity prediction. This is to grasp the difference due to the turbidity level as a slope when shifting to the maximum luminance value. The variation coefficient is expressed as a slope when shifting to the brightness maximum value on the brightness distribution curve.

FIG. 7 shows the relationship L11 between the variation coefficient obtained from the analysis result of the luminance distribution curve shown in FIG. 6 and the turbidity (level of turbidity). FIG. 7 is a graph in which the coefficient of variation is taken on the horizontal axis and the turbidity is taken on the vertical axis as a logarithm.

From the relationship L11 between the coefficient of variation and the turbidity (level of turbidity) shown in FIG. 7, as shown in the following equation (1), the turbidity estimation computing equation for estimating and calculating turbidity y with variable coefficient as variable x can get.
y =-3. 303 x ln (x) + 0.0491 (1)
y: turbidity level (estimated calculation value)
x: coefficient of variation (step 102)

In the pre-processing, next, a lighting output estimation computing equation is calculated, which estimates and calculates the lighting output with the maximum luminance value as a variable, based on the luminance distribution curve and the turbidity estimation value for each turbidity.

FIG. 8 shows a luminance distribution curve (illumination output 100% in FIG. 6) for each level of luminance and turbidity (luminance output: 0 to 100%, turbidity: 0 to 5 levels). 3 shows relationships L20, L21, L22, L23, L24, and L25 between the maximum value of luminance (peak value) and the illumination output (%) obtained from the analysis result of. FIG. 8 is a graph in which the luminance maximum value (peak value) is taken on the horizontal axis and the illumination output (%) is taken on the vertical axis.

The correspondence (linear) at the 0 level of turbidity is L20, the correspondence at the 1 level of turbidity (linear) is the L21, and the correspondence at 2 levels of turbidity (linear) is L22 The correspondence (linear) at 3 levels of turbidity is L23, the correspondence (linear) at 4 levels of turbidity is L24, and the correspondence (linear) at 5 levels of L25 It shows by each.

From the correspondence L20, L21, L22, L23, L24, L25 of the maximum luminance value (peak value) for each turbidity level and the illumination output (%) shown in FIG. An illumination output estimation equation that estimates the illumination output v with the maximum value as a variable u is obtained.

However, the slope a of the linear function in the following equation (2) and the intercept b can be obtained from the turbidity estimation operation value y obtained from the turbidity estimation computing equation of the above equation (1).

The correspondence L31 between the turbidity estimated calculation value y and the slope a is shown in FIG. 9 (a). Further, the correspondence L32 between the turbidity estimated calculation value y and the intercept b is shown in FIG. 9 (b).

Therefore, the gradient a can be obtained by applying the turbidity estimation calculation value y to the correspondence relationship L31. Further, the intercept b is obtained by applying the turbidity estimation calculation value y to the correspondence relationship L32.
v = a × u + b (2)
v: Lighting output (estimated calculation value)
u: Maximum luminance (peak value)
a: Slope (turbidity estimation calculation value y is applied to the correspondence L31)
b: Intercept (turbidity estimation operation value y is applied to the correspondence L32)
(Step 103)

(Image analysis processing and deterioration factor calculation processing and deterioration prediction processing executed by the personal computer 2)
The relationship M between the turbidity of the lamp 51 shown in FIG. 4 and the illumination output of the lamp 51 and the illuminance ratio of the lamp 51, obtained as described above, is shown in the above equation (1) As shown in FIG. 9 (b), the correlation L31 for obtaining the slope a from the turbidity estimation computing equation, the illumination output estimation computing equation shown in the above equation (2), the turbidity estimation computing value y shown in FIG. Based on the correspondence relationship L 32 for obtaining the intercept b from the estimated turbidity calculation value y, a lamp degradation prediction processing program in which these are incorporated is created and installed in the personal computer 2.

Then, the vehicle 1 is actually traveled, and as shown in FIG. 1, the lighting device 50 (illumination lamp 51) of the deterioration prediction target is photographed.

That is, while the vehicle 1 travels in the tunnel, the lighting device 50 installed on the tunnel lining surface 90 is photographed by the photographing means 10 mounted on the vehicle 1. The image data storage unit 20 of the vehicle 1 stores the image data captured by the imaging unit 10. The image data stored in the image data storage unit 20 is read out and taken into an external personal computer 2 for the deterioration prediction process of the illumination lamp 51. In the personal computer 2, a lamp degradation prediction processing program is executed.

(Turbidity estimation operation processing)
In the same manner as described with reference to FIGS. 5 and 6, a process of obtaining a luminance distribution curve is performed from the image data for a specific illumination lamp 51 of the lighting devices 50 of the deterioration prediction target.

Here, for example, it is assumed that a luminance distribution curve L41 corresponding to L3 (turbidity level 3) is obtained as shown in FIG.

Therefore, the process of obtaining the value of the variation coefficient x from the luminance distribution curve L41 is then executed. For example, it is assumed that a value 0.4 corresponding to turbidity level 3 is obtained (see arrow A in FIG. 7).

Then, the calculated coefficient of variation x (for example, 0.4) is applied to the turbidity estimation computing equation (y = −3.303 × ln (x) +0.0491) of the above equation (1) to obtain turbidity. A degree estimation calculation value y (for example, about 3 levels of turbidity estimation calculation value) is obtained (step 104).

(Lighting output calculation processing)
Next, processing for obtaining the maximum luminance value u as the peak value from the luminance distribution curve L41 is executed.

Here, for example, it is assumed that a value 40 corresponding to the illumination output 60% is obtained as the luminance maximum value u (see arrow B in FIG. 10 and arrow C in FIG. 8).

Then, the obtained luminance maximum value u (for example, 40) is applied to the illumination output arithmetic expression (v = a × u + b) of the above equation (2) to obtain an illumination output estimation operation value v (for example, illumination output estimation arithmetic A value of about 60% is required. However, the slope a in the above equation (2) can be obtained by applying the turbidity estimation calculation value y (about three levels) obtained in step 104 to the correspondence L31 shown in FIG. See arrow D in FIG. 9 (a)). In addition, it can be obtained by applying the intercept b in the above equation (2) and the turbidity estimated calculation value y (about 3 levels) obtained in step 104 to the correspondence L32 shown in FIG. 9 (b) arrow E)).

As described above, the turbidity estimation calculation value y (for example, about 3 levels) and the illumination output estimation calculation value v (for example, about 60%) are calculated (step 105).

(Lighting ratio calculation processing)
Next, the turbidity estimated value y (for example, about 3 levels) obtained in step 104 and the illumination output estimated value v (for example, about 60%) obtained in step 105 are applied to the correspondence M shown in FIG. A process of obtaining an estimated value of the illuminance ratio of the deterioration prediction target lamp 51 is executed.

For example, the illuminance ratio when the turbidity estimated calculation value y is about 3 and the illumination output estimation calculation value is about 60% is about 0.59 according to the correspondence relationship M shown in FIG. 4 (step 106).

(Lighting fixture deterioration prediction processing)
As described above, based on the turbidity estimation value y, the illumination output estimation value v, and the illuminance ratio estimation value of the deterioration prediction target lamp 51 thus determined, the diagnosis that predicts the deterioration of each deterioration prediction target lamp 51 Processing is performed. Furthermore, by predicting the deterioration of each deterioration prediction target illumination lamp 51, a diagnostic process for predicting the deterioration of the deterioration prediction target lighting fixture 50 is performed. This diagnostic process diagnoses the soundness of the entire lighting fixture 50 from the turbidity estimation value y, the lighting output estimation value v, and the illumination ratio estimation value for each lamp 51 constituting the lighting fixture 50, and the need for cleaning It is to predict the degree of progress of the gender and the degree of deterioration.

FIG. 11 shows a diagnostic example of the lighting device 50. In this case, a predetermined threshold value is provided for the turbidity estimated value y, the illumination output estimated value v, and the illuminance ratio estimated value for each lamp 51, and “good” (solid line by comparison with this threshold) The results of the diagnosis of “enclosed box”, “OK” (opened box), and a defect (opened box).

For example, a certain illuminating lamp 51a is judged as "bad" because "the turbidity estimated value y is 3.21, the illumination output estimated value v is 62%, and the degree ratio estimated value is about 0.59". The illuminating lamp 51b is judged as "good" because "the turbidity estimated value y is 1.85, the illumination output estimated value v is 78%, and the degree ratio estimated value is about 0.79".

About lightings 51a and 51a 'judged as "defective", appropriate measures, such as exchange, can be taken.

In addition, the overall deterioration of the lighting device 50 can be predicted from the results of obtaining the turbidity estimation values y, the lighting output estimation value v, and the illumination ratio estimation value of the plurality of lighting devices 51 that constitute the lighting device 50.

For example, among the plurality of lighting devices 51 that constitute the lighting device 50, the number of the lighting devices 51 that have become "defective", the average value of the turbidity estimation values y of all the lighting devices 51, the average of the lighting output estimation value v By determining the average value of the value and the illuminance ratio estimated value, and comparing these with a predetermined threshold value, it is possible to predict the deterioration of the entire luminaire 50.

In the example of FIG. 11, the number of lighting devices 51 that have become “defective” is “2”, the average value of the estimated turbidity values y of all the lighting devices 51 is 2.2, and the average value of the estimated lighting output values v Is 78%, and the average value of the illuminance ratio estimated values is 0.77. From the comparison with these and the threshold value, for example, although there is a lamp 51 that becomes "bad", the lighting fixture 50 as a whole is The degree of deterioration of the lighting device 50 as a whole can be evaluated and predicted.

According to this embodiment, three factors such as the turbidity estimation value y, the illumination output estimation value v, and the illuminance ratio estimation value can be obtained. Therefore, the individual lighting lamps 51 or the lighting fixture 50 can be appropriately maintained and maintained. Decision and take appropriate action.

For example, in the case where the estimated illumination output value v is high (there is no abnormality in the LED element) and the estimated turbidity value y is high (the soiling of the glass surface is severe), the illumination lamp 51 or the illumination fixture including the illumination lamp 51 It can be coped with by cleaning 50. Moreover, when the lighting output estimated value v is low (there is an abnormality in the LED element), it can be dealt with by replacing the lighting 51 or the lighting fixture 50 including the lighting 51 without cleaning. (Step 107).

As described above, according to the present embodiment, the turbidity estimated value y, the illumination output estimated value v, and the illuminance ratio estimated value are obtained for each lamp 51, so especially the maintenance of the lighting fixtures in the tunnel The road facilities can be maintained and managed optimally, for example, because they can carry out the optimum work and efficiently clean the concrete lining surface and the interior panel.

In addition, although the Example demonstrated the illuminating light in a tunnel, and the lighting fixture and demonstrated, this invention is not limited to this, It can apply to the deterioration prediction of arbitrary lightings and lighting fixtures.

DESCRIPTION OF SYMBOLS 1 vehicle 2 personal computer 10 imaging | photography means 20 image data storage part 50 lighting fixture 51 lighting lamp 90 tunnel lining surface

Claims (8)

A correspondence setting step of setting in advance correspondence relations between the turbidity of the illumination light, the illumination output of the illumination light, and the illumination ratio as a ratio of the illumination intensity of the illumination to the reference value;
A photographing step of photographing a lamp to be subjected to deterioration prediction;
A luminance distribution curve is acquired from the photographed image, and a coefficient of variation as a slope when shifting to the maximum value of luminance is obtained on the luminance distribution curve, and turbidity of the deterioration prediction target lamp is estimated based on the coefficient of variation. Turbidity estimation step to calculate the value,
An illumination output estimation step of computing an estimated value of the illumination output of the illumination lamp for deterioration prediction based on the luminance maximum value on the luminance distribution curve and the turbidity estimated value;
Illuminance ratio estimation step of applying the turbidity estimated value and the illumination output estimated value to the set correspondence relationship to obtain an estimated value of the illuminance ratio of the deterioration prediction target lamp; Method. In the turbidity estimation step, a luminance distribution curve is obtained for each turbidity, and based on the luminance distribution curve for each turbidity, a turbidity estimation operation equation is calculated in advance to estimate and calculate the turbidity using a variation coefficient as a variable The illumination lamp according to claim 1, wherein a turbidity estimated value is calculated by applying a variation coefficient obtained from a photographed image of the deterioration prediction target lamp to the turbidity estimation calculation equation. How to predict the deterioration of In the illumination output estimation step, a luminance distribution curve is obtained for each turbidity, and illumination is estimated and calculated using the luminance maximum value as a variable based on the luminance distribution curve for each turbidity and the turbidity estimated value. An output estimation equation is obtained in advance, and the maximum illumination value and the turbidity estimated value determined from the photographed image of the deterioration prediction target lamp are applied to the illumination output estimation equation to obtain an illumination output estimated value. The deterioration prediction method of a lamp according to claim 1 or 2, wherein the calculation is performed. 4. The deterioration of the lamp according to any one of claims 1 to 3, wherein the deterioration prediction target lamp installed on the tunnel lining surface is photographed by a photographing unit mounted on a vehicle traveling in the tunnel. Forecasting method. It is a deterioration prediction system of a lamp, which photographs a deterioration prediction target lamp installed on a tunnel lining surface by a photographing means mounted on a vehicle traveling in the tunnel and predicts the deterioration of the deterioration forecast lamp. ,
The correspondence relationship between the turbidity of the lamp, the illumination output of the lamp, and the illumination ratio as a ratio to the reference value of the illumination of the lamp is set in advance,
The illumination light of the deterioration prediction target is photographed by the photographing means,
A luminance distribution curve is acquired from the photographed image, and a coefficient of variation as a slope when shifting to the maximum value of luminance is obtained on the luminance distribution curve, and turbidity of the deterioration prediction target lamp is estimated based on the coefficient of variation. Calculate the value,
The estimated value of the illumination output of the illumination lamp subject to deterioration prediction is calculated based on the luminance maximum value on the luminance distribution curve and the turbidity estimated value,
Applying the turbidity estimated value and the illumination output estimated value to the set correspondence relationship to obtain an estimated value of the illuminance ratio of the deterioration prediction target lamp;
A deterioration prediction system of a lamp according to claim 1, wherein the deterioration prediction of the target lamp for deterioration prediction is predicted based on the turbidity estimated value of the target lamp for deterioration prediction, the estimated value of the illumination output, and the estimated value of the illumination ratio. A brightness distribution curve is obtained for each turbidity, and based on the brightness distribution curve for each turbidity, a turbidity estimation operation equation for estimating and calculating the turbidity using the variation coefficient as a variable is obtained in advance, and the turbidity estimation is performed. The deterioration prediction system of a lamp according to claim 5, wherein a turbidity estimated value is calculated by applying a variation coefficient obtained from a photographed image of the deterioration prediction target lamp to an arithmetic expression. A luminance distribution curve is obtained for each turbidity, and an illumination output estimation equation is calculated in advance for estimating and calculating an illumination output with the maximum luminance value as a variable based on the luminance distribution curve and the turbidity estimated value for each turbidity. The lighting output estimated value is calculated by applying the maximum luminance value and the turbidity estimated value obtained from the photographed image of the deterioration prediction target lamp to the lighting output estimation arithmetic expression. The deterioration prediction system of the illuminating light according to claim 5 or 6.   The lighting device for deterioration prediction includes a plurality of lighting devices for prediction of deterioration, and is characterized in that the deterioration of the lighting device for prediction of deterioration is predicted by predicting the deterioration of each lighting device for prediction of deterioration. The deterioration prediction system according to any one of claims 5 to 7.