Patent Description:
In related arts, in an oil storage tank or an oil filled apparatus such as a transformer, there has been a concern that oil leakage may occur due to deterioration, an accident, or the like. Since leakage oil may lead to environmental pollution or a disaster, there has been a demand for a technique for detecting leakage oil in an initial stage simply and with high accuracy.

As a technique in a related art for solving the problem, there is a technique described in PTL <NUM>. PTL <NUM> describes a technique of detecting leakage oil by detecting fluorescence reflected by the leakage oil when ultraviolet light including an absorption wavelength of the leakage oil is irradiated to an object to be measured (an inspect target object such as a transformer), and more specifically, calculating the brightness and saturation of each pixel of a captured image by performing image processing on the pixels during ultraviolet light irradiation, creating a brightness-saturation graph and a brightness-saturation characteristic curve, and recognizing pixels deviated from the brightness-saturation characteristic curve by a predetermined value or more as a fluorescent spot, that is, a leakage oil spot. Furthermore, in PTL_2, a method and a system for detecting an oil spillage on an apparatus is described in which occurring oil leakages are determined by additional frequency distribution analysis. More specifically, said method and apparatus stipulate to initially expose a given apparatus with near infrared (nIR) light and detect the reflected light by means of an image sensor. Subsequently, so generated grey images are analyzed for leakage detection by performing pixel-wise examination of the corresponding frequency distribution of the reflected light pixel and comparing said frequency distributions with predefined structural threshold values. In addition, in PTL <NUM>, also an oil leakage detection method for atomic and chemical plants is delineated which utilizes enhanced edge detection mechanism to identify appearing oil/liquid patterns in dynamic grey-scale images. Herein, time-dependent grey-scale images are taken from a given plant-element, such as a pipe, and are identified for oil leakage patterns by both, searching for maximal intensity variations between pixels (edge detection) and comparing a taken grey-scale image with images of older timelines. Moreover, in PTL <NUM>, an oil leak detection device is mentioned which comprises an illuminating means for alternatingly irradiating a given sample with ultraviolet and visible light. On that basis, improved image detection is provided by generating differential image analysis of both irradiation types.

Although the technique described in PTL <NUM> is effective for detecting leakage oil in a period of time in which an illuminance is low, such as at night, when background noise due to daytime sunlight is large, a detection accuracy of the leakage oil decreases.

The present invention has been made in view of the above facts, and an object of the present invention is to provide a leakage oil detection device and a leakage oil detection method capable of accurately detecting leakage oil when a background noise due to daytime sunlight is large.

To solve the above-mentioned problem, the invention according to the independent claims is suggested. Dependent claims refer to favorable embodiments of the invention. From the above, the present invention relates to "a leakage oil detection device configured to detect leakage oil in an oil filled apparatus, the leakage oil detection device including: a light source configured to irradiate the oil filled apparatus with light; an imaging device configured to capture an image of the oil filled apparatus; a control device configured to control operations of the light source and the imaging device; a storage device configured to store a captured image; an image processing device configured to process the stored image; and a display device configured to display a processing result, in which the light source and the imaging device are arranged in a manner of being capable of capturing specular reflection light from a surface of the oil filled apparatus as a target object, and the image processing device recognizes a brightest portion and a dark portion adjacent to the brightest portion on the captured image as leakage oil adhesion portions when a three-layer structure of luminance having bright portions having different luminances and a dark portion is observed in the image.

Further, the present invention relates to "a leakage oil detection device configured to detect leakage oil in an oil filled apparatus, the leakage oil detection device including: a light source configured to irradiate the oil filled apparatus with light; an imaging device configured to capture an image of the oil filled apparatus; a control device configured to control operations of the light source and the imaging device; a storage device configured to store a captured image; an image processing device configured to process the stored image; and a display device configured to display a processing result, in which the light source and the imaging device are arranged in a manner of being capable of capturing specular reflection light from a surface of the oil filled apparatus as a target object, and the image processing device recognizes a bright portion in luminance as a leakage oil adhesion portion when the bright portion is observed inside a dark portion of the captured image at an end portion of the image.

Further, the present invention relates to "a leakage oil detection method for detecting leakage oil of an oil filled apparatus by using an image obtained by irradiating the oil filled apparatus with light and capturing an image of the oil filled apparatus, the leakage oil detection method including: recognizing a brightest portion and a dark portion adjacent to the brightest portion on the captured image as leakage oil adhesion portions when a three-layer structure of luminance having bright portions having different luminances and a dark portion is observed in the image.

Further, the present invention relates to "a leakage oil detection method for detecting leakage oil of an oil filled apparatus by using an image obtained by irradiating the oil filled apparatus with light and capturing an image of the oil filled apparatus, the leakage oil detection method including: recognizing a bright portion in luminance as a leakage oil adhesion portion when the bright portion is observed inside a dark portion of the captured image at an end portion of the image.

According to the present invention, leakage oil can be accurately detected when a background noise due to daytime sunlight is large.

Hereinafter, embodiments of a leakage oil detection device and a leakage oil detection method of the present invention will be described with reference to the drawings. In the embodiments, the same components are denoted by the same reference numerals.

A leakage oil detection device <NUM> and a leakage oil detection method according to the first embodiment of the present invention for inspecting oil adhering to a surface of an oil filled apparatus will be described with reference to <FIG>. In the present embodiment, an oil filled transformer in a substation will be described as an example.

<FIG> is a diagram showing a schematic configuration example of an inspection target object <NUM> and a leakage oil detection device <NUM> according to a first embodiment. The inspection target object <NUM> is an oil filled apparatus such as a transformer, a capacitor, a hydraulic operation device of a gas insulated switchgear (GIS), a rectifier, an inverter, or a converter.

In the present embodiment, an oil filled transformer disposed in the substation will be described as the inspection target object <NUM>.

As shown in <FIG>, the leakage oil detection device <NUM> includes a light source <NUM>, an imaging device <NUM>, a control device <NUM> that controls the operations of the devices <NUM> and <NUM>, a storage device <NUM> that stores captured images, an image processing device <NUM> that processes the stored images, and a display device <NUM> that displays processing results. The leakage oil detection device <NUM> captures an image of a leakage oil <NUM> adhering to a surface of the inspection target object <NUM>, and finally displays an inspection result of the leakage oil on the display device <NUM>.

Here, any lamp including visible light may be used as the light source <NUM>. As the imaging device <NUM>, a general-purpose product such as a digital camera or a monitoring camera that captures visible light can be used.

In the present invention, the light source <NUM>, which is a visible light source, is used, and the specular reflected light of the oil is captured by the imaging device <NUM>, and thereby minute leakage oil is detected.

<FIG> is a diagram for explaining a concept of a leakage oil detection method according to the present invention. Only a specular reflection portion of the target object surface is shown. An upper part of <FIG> shows the surface of the target object <NUM> to which the leakage oil <NUM> is attached, and a lower part of <FIG> shows luminances of parts in the captured image of the surface of the target object <NUM>.

Although as shown in the upper part of <FIG>, when the leakage oil <NUM> adheres to the surface of the target object <NUM>, the outermost surface 8a of the oil is parallel to the surface of the target object <NUM>, a boundary portion 8b between the oil and the target object surface is formed. Here, it is assumed that the light source <NUM> and the imaging device <NUM> are arranged in a manner of being capable to capture specular reflected light from the surface of the target object <NUM>. In an example of <FIG>, the light source <NUM> and the imaging device <NUM> are installed at positions in a direction orthogonal to the surface of the target object <NUM>, and the reflected light from the surface of the target object <NUM> is imaged by the imaging device <NUM>. Accordingly, when the oil <NUM> adheres to the portion of the specular reflected light, the specular reflected light from the oil <NUM> is also captured in the same manner.

However, at a boundary portion 8b between the oil <NUM> and the target object <NUM>, reflected light is directed in another direction different from a direction toward the imaging device <NUM>, and therefore the specular reflected light is not observed by the imaging device <NUM>. Therefore, on the captured image, an oil surface specular reflected light portion <NUM> corresponding to the outermost surface 8a of the oil <NUM> and a target object surface specular reflected light portion <NUM> corresponding to the surface to which the oil is not attached are bright, but an oil surface specular reflected light portion <NUM> corresponding to the boundary portion 8b between the oil and the target object is dark.

When comparing the oil surface specular reflected light portion <NUM> and the target object surface specular reflected light portion <NUM>, the oil surface specular reflected light portion <NUM> is observed as an image brighter than the target object surface specular reflected light portion <NUM> because a reflectance of the oil <NUM> with respect to visible light is higher than a reflectance of the surface of the target object <NUM>.

That is, as shown in the lower part of <FIG>, in the image, K1 > K3 > K2, where the luminance of the oil surface specularly reflected light portion <NUM> is K1, the luminance of the boundary portion <NUM> between the oil and the target object is K2, and the luminance of the target object surface specular reflected light generating portion <NUM> is K3.

As a result, a three-layer structure as shown in the lower part of <FIG> is observed in the observed image. The oil surface specular reflected portion <NUM> is the brightest, the adjacent boundary portion <NUM> between the oil and the target object is dark, and the subsequently adjacent specular reflected portion <NUM> of the target object surface is bright. In addition, the luminance of the oil surface specular reflection portion <NUM> is observed to be lower than the luminance of the specular reflected portion of the target object surface.

In this way, when an adjacent three-layer structure is observed as a portion having the luminances of K1 > K3 > K2, both the oil surface specular reflected portion <NUM> and the adjacent boundary portion <NUM> between the oil <NUM> and the target object <NUM> are recognized as leakage oil sites.

Further, the leakage oil site can be extracted alone by using the feature of the pattern configured by the three-layer structure and by using a machine learning method.

<FIG> is a diagram showing a concept of extracting a leakage oil site using the machine learning method. As shown in <FIG>, as a machine learning method, first, shapes of various target objects <NUM>, an irradiation shape of a light source, and a state of leakage oil are considered, a large amount of images are captured to obtain images 1a to 1n as learning data, and a leakage oil pattern is self-learned in the image processing device <NUM>. Next, a determination image 1x is input, and the leakage oil <NUM> is extracted alone from the determination image 1x based on the learning result.

When the portion of the extracted leakage oil <NUM> is provided on an original image or the same image obtained when the light source is not irradiated by a method such as marker attachment and displayed on the display device <NUM>, even an unskilled inspector can easily identify a leakage oil location.

It is not necessary to perform all procedures of the present embodiment, and a part of the procedures can be performed alone according to a situation of the location where the procedures are performed.

According to the leakage oil detection device of the present embodiment, when background noise due to daytime sunlight is large, leakage oil can be detected with high accuracy.

A leakage oil detection device <NUM> and the leakage oil detection method according to the second embodiment of the present invention for inspecting oil adhering to the surface of the oil filled apparatus will be described with reference to <FIG>. Repetitive descriptions of points common to the first embodiment will be omitted.

In the leakage oil detection device <NUM> according to the second embodiment shown in <FIG>, light from a light source <NUM> includes both ultraviolet light and visible light. A filter <NUM> is mounted in front of the light source <NUM>. The filter <NUM> transmits ultraviolet light having a center wavelength of <NUM> and a half value width of about <NUM>, and visible light having a center wavelength of <NUM> and a half value width of about <NUM>. Of course, two filters may be used. Similarly, a filter <NUM> is mounted in front of the imaging device <NUM>. The filter <NUM> transmits the visible light having the center wavelength of <NUM> and the half value width of about <NUM>.

<FIG> shows a porch diagram of a spectrum obtained when a mineral oil for a transformer is irradiated with an ultraviolet light source having a peak value of <NUM>. A strongest peak was observed in the vicinity of <NUM>.

<FIG> is a diagram for explaining reflected light from the target object surface according to the second embodiment. As shown in <FIG>, when the oil <NUM> is irradiated with ultraviolet light having a peak value of <NUM>, fluorescence from the oil is also observed in addition to the reflected light. At the time, intensity K1' of light from oil surface specular reflected portion <NUM> = intensity of specular reflected light K1 + fluorescence, intensity K2' of light from adjacent boundary portion <NUM> between oil and object = intensity of diffuse reflection light + fluorescence, and intensity K3' of light from subsequently adjacent specular reflected portion <NUM> of target object surface = intensity of specular reflection light. In this way, fluorescence is not observed in a portion to which oil is not attached. In this way, the intensity of the light at the oil surface specular reflection generating portion <NUM> can be further improved, and therefore a detection sensitivity can be improved.

In general, since the intensity of the fluorescence is weaker than that of the specular reflection light, the brightness of the boundary portion <NUM> between the oil <NUM> and the target object <NUM> is the lowest as compared with the luminance of the oil surface specular reflected portion <NUM> and the specular reflected portion <NUM> on the target object surface.

On the other hand, when the filter <NUM> having a center wavelength of <NUM> and a half-value width of about <NUM> is used, an intensity of ambient light can be reduced by about <NUM>%. For example, as shown in <FIG>, when the filter <NUM> is not used, an intensity P1 of the light source needs to be larger than the intensity of ambient light BG1; on the other hand, when the filter <NUM> is used, an intensity P2 of the light source is only required to be larger than the intensity of ambient light intensity BG2. Therefore, the required intensity of the light source can also be greatly reduced.

of course, when a wavelength of an irradiation light source and a color of a fluorescence are different depending on a type of the oil, the present method can be applied by selecting a filter having an appropriate wavelength range.

According to the leakage oil detection device of the present embodiment, the required intensity of the light source can be reduced, and a cost of the detection device can be reduced.

The leakage oil detection method according to the third embodiment of the present invention for inspecting oil adhering to the surface of an oil filled apparatus will be described with reference to <FIG>. Repetitive descriptions of common points as in the first embodiment are omitted.

In the third embodiment, as shown in <FIG>, a case is assumed in which the leakage oil <NUM> adheres to the specular reflected portion <NUM> on the target object surface and the leakage oil 8A adheres to a vicinity <NUM> of the specular reflected portion on the target object surface. At this time, in addition to the oil surface specular reflected portion <NUM>, specular reflected light is observed by the imaging device <NUM> from a boundary portion 11A between the leakage oil 8A and the target object. The above is based on an assumption that leakage oil is present in each of a central portion and a peripheral portion of the captured image.

In such a case, a five-layer structure as shown in a lower part of <FIG> is observed. As a result, the vicinity <NUM> of the specular reflected portion on the target object surface is dark, the boundary portion 11A between the leakage oil 8A and the target object and the oil surface specular reflection generating portion <NUM> are the brightest, the adjacent boundary portion <NUM> between the oil and the target object is dark, and the subsequently adjacent specular reflected portion <NUM> of the target object surface is bright. In addition, the luminance of the boundary portion 11A between the leakage oil 8A and the target object and the oil surface specular reflection generating portion <NUM> is higher than the luminance of the specular reflected portion <NUM> on the target object surface.

In this case, the portion 11A observed brightly in the vicinity of the specular reflected portion on the target object surface, and the oil surface specular reflection generating portion <NUM> and the adjacent dark portion <NUM> in the specular reflected portion of the target object surface are recognized as leakage oil adhesion portions.

In this case, in addition to the three-layer structure in a central portion of the image in <FIG>, a bright portion and a dark portion are observed in an end portion of the image, and in this case, the bright portion can be regarded as an oil leakage portion. That is, when a bright portion and a dark portion are observed at the end portion of the image, and particularly when THE bright portion is observed in the dark portion, the bright portion can be regarded as the oil leakage portion.

In some cases, the luminance of the boundary portion <NUM> between the oil and the target object and the luminance of the vicinity <NUM> of the target object surface specular reflected light generating portion are substantially equal to each other.

Further, the leakage oil site can be extracted alone in the same manner as in the first embodiment by using the feature of the pattern configured by the five-layer structure described above and by using a machine learning method.

As described above, according to the leakage oil detection device of the present embodiment, when the background noise due to the daytime sunlight is large, the leakage oil can be detected with high accuracy.

Next, the leakage oil detection method according to the fourth embodiment of the present invention for inspecting oil adhering to the surface of an oil filled apparatus will be described with reference to <FIG>. Repetitive descriptions of common points as in the first embodiment and the third embodiment are omitted.

In <FIG>, a case is assumed in which the leakage oil <NUM> does not adhere to the specular reflected portion <NUM> on the target object surface and the leakage oil 8A adheres to the vicinity <NUM> of the specular reflected portion on the target object surface. This is based on an assumption that there is leakage oil only in the peripheral portion of the specular reflection portion of the target object surface in the captured image. At this time, only specular reflected light is observed by the imaging device <NUM> from the boundary portion 11A between the leakage oil 8A and the target object.

In this way, a three-layer structure as shown in the lower part of <FIG> is observed. At the time, the vicinity <NUM> of the target object surface specular reflected light generating portion is dark, the adjacent boundary portion 11A between the leakage oil 8A and the target object is the brightest, and the adjacent specular reflection generating portion <NUM> of the target object surface is bright, but has a luminance lower than that of the boundary portion 11A.

Also in this case, similar as in the third embodiment, when a bright portion and a dark portion are observed at the end portion of the image, and the bright portion is observed in the dark portion, the bright portion can be set as the oil leakage portion.

Further, the leakage oil site can be extracted alone in the same manner as in the first embodiment by using the feature of the pattern configured by the three-layer structure and by using the machine learning method.

Claim 1:
A leakage oil detection device (<NUM>) configured to detect leakage oil (<NUM>) in an oil filled apparatus by luminance recognition of a captured image of the oil filled apparatus, the leakage oil detection device (<NUM>) comprising:
a light source (<NUM>) configured to irradiate the oil filled apparatus with light;
an imaging device (<NUM>) configured to capture the image of the oil filled apparatus;
a control device (<NUM>) configured to control operations of the light source (<NUM>) and the imaging device (<NUM>);
a storage device (<NUM>) configured to store a captured image;
an image processing device (<NUM>) configured to process the stored image; and
a display device (<NUM>) configured to display a processing result, wherein
the light source (<NUM>) and the imaging device (<NUM>) are arranged in a manner of being capable of capturing specular reflection light from a surface of the oil filled apparatus as a target object (<NUM>),
characterized in that
the image processing device (<NUM>) recognizes a brightest portion (8a) and a dark portion (8b) adjacent to the brightest portion (8a) on the captured image as leakage oil adhesion portions when a three-layer structure of luminance having bright portions (K1; K3) having different luminances and a dark portion (K2) is observed in the image.