WO2020103464A1

WO2020103464A1 - Method and system for identifying error light of equipment in mechanical room

Info

Publication number: WO2020103464A1
Application number: PCT/CN2019/094510
Authority: WO
Inventors: 何东杰; 杨洁
Original assignee: 中国银联股份有限公司
Priority date: 2018-11-22
Filing date: 2019-07-03
Publication date: 2020-05-28
Also published as: CN111209782B; CN111209782A

Abstract

The present invention relates to a method and system for identifying an error light of equipment in a mechanical room. The method comprises: a step of changing object distance such that a camera starts to change on the basis of an initial object distance, so that the camera captures images on the basis of the changed object distance; a determination step of identifying, with respect to a captured image, the light spot size of a signal light and the proportion of black in a histogram of the image, so as to determine whether the light spot falls in a first pre-configured prescribed range and whether the proportion of the black in the histogram of the image falls in a second pre-configured prescribed range, and if it is determined that the light spot does not fall in the first pre-configured prescribed range and that the proportion of the black in the histogram of the image does not fall in the second pre-configured prescribed range, repeating the step of changing object distance until the light spot falls in the first pre-configured prescribed range and the proportion falls in the second pre-configured prescribed range; and an identification step of analyzing the image and identifying an error light. The invention optimizes the effect of image capturing, such that an error light and a normal light are more prominent in an image.

Description

Method and system for identifying abnormal lights in equipment room

Technical field

The present invention relates to image analysis technology, and in particular to a method and system for identifying abnormal lights in equipment rooms.

Background technique

As the scale of the equipment room continues to increase, there is a large amount of work in the way of manual equipment inspection to find equipment abnormalities. The industry began to use wheeled robots to automatically walk in the computer room and take pictures of the device through the camera to identify abnormal lights.

Existing inspection robots generally take pictures of the environment through the auto-focusing method of the camera, and then perform depth analysis and abnormal light recognition on the image. The typical steps are as follows:

Focus and photograph the equipment in the equipment room through the camera;

For feature analysis of the photos taken, machine learning algorithms or deep learning algorithms are generally used to improve the effect of feature analysis.

Due to the ambient light in the equipment room, the light transmission of the equipment panel, and the cabinet, the picture is dark, the noise is large, and the signal lights are not obvious. In this case, the core of the existing technical solutions is to design better machine learning or deep learning algorithms to improve the extraction effect of signal lights and abnormal light features, thereby achieving a higher recognition rate.

However, in such prior art, weaker light will cause more noise to affect the extraction and recognition of the characteristics of signal lamps and abnormal lights, and strong light will make the light of signal lamps and abnormal lights less prominent, affecting the lamp's Recognition. Obviously, the strength of the light has a greater impact on the recognition of the light. The machine learning or deep learning algorithms have higher requirements and are more difficult.

The information disclosed in the background section of the present invention is merely intended to increase the understanding of the general background of the present invention and should not be taken as an acknowledgement or in any way suggesting that the information constitutes prior art that is well known to those of ordinary skill in the art.

Summary of the invention

In view of the above problems, the present invention aims to provide a method and a system for identifying abnormal lights of a computer room device that can optimize the photographing effect and reduce the influence of impurities on the photographing.

An identification method of an abnormal light in a computer room equipment according to an aspect of the present invention is characterized by including:

In the object distance obtaining step, focus on the cabinet door in the equipment room through the camera to obtain the corresponding object distance u;

The step of changing the object distance causes the camera to start changing based on the initial object distance and causes the camera to shoot with the changed object distance;

In the judging step, for the size of the light spot of the captured picture recognition signal lamp and the black proportion in the picture histogram, determine whether the light spot meets the preset first preset range and whether the black proportion in the picture histogram meets the second preset Specified range, if it is judged that the light spot does not meet the first preset specified range and the proportion of black in the slice histogram does not meet the second preset specified range, the step of changing the object distance is repeated until Comply with the first preset prescribed range and the second preset prescribed range; and

Recognition step, analyze the picture and identify abnormal lights.

Optionally, in the step of changing the object distance, the camera takes u as the initial object distance and reduces the object distance by δ, so that the camera shoots the cabinet door at the reduced object distance, where δ is much smaller than u.

Optionally, in the step of changing the object distance, the camera is made to have an initial object distance of 0 and the object distance is increased by δ, and the camera is caused to shoot at the increased object distance, where δ is much smaller than u.

Optionally, in the judging step, the first preset specified range refers to the size of the small hole of the cabinet door.

Optionally, in the identification step, the picture is subjected to brightness detection to identify the signal lamp, and chromaticity analysis is performed to identify the signal lamp color, thereby determining the abnormal lamp.

Optionally, the δ is equal to 0.01u, and the second preset specified range is more than 90%.

According to one aspect of the present invention, a system for identifying abnormal lights in an equipment room includes:

Camera, used to photograph cabinet door;

The object distance obtaining module focuses the cabinet door in the equipment room through the camera to obtain the corresponding object distance u;

The object distance changing module causes the camera to start changing based on the initial object distance and causes the camera to shoot at the changed object distance;

The judgment module determines whether the spot size of the image recognition signal lamp obtained by shooting and the black proportion in the picture histogram meet the preset first preset range and whether the black proportion in the picture histogram meets the second preset Specified range, if it is determined that the light spot does not meet the first preset specified range and the black ratio in the slice histogram does not meet the second preset specified range, repeating the step of changing the object distance Act until the first preset specified range and the second preset specified range are met; and the identification module analyzes the picture taken by the camera and identifies the abnormal light.

Optionally, in the object distance changing module, the camera takes u as the initial object distance and reduces the object distance by δ, so that the camera shoots the cabinet door at the reduced object distance, where δ is much smaller than u.

Optionally, in the object distance changing module, the camera is made to have an initial object distance of 0 and the object distance is increased by δ, and the camera is caused to shoot at the increased object distance, where δ is much smaller than u.

Optionally, the first preset specified range refers to the size of the small hole of the cabinet door.

Optionally, the identification module performs brightness detection on the picture to identify the signal light and performs chromaticity analysis to identify the color of the signal light, thereby determining an abnormal light.

The computer-readable storage medium of the present invention has a computer program stored thereon, which is characterized in that when the program is executed by a processor, the above method for identifying abnormal lights of a computer room device is realized.

The computer device of the present invention includes a memory, a processor, and a computer program stored on the memory and capable of running on the processor, and is characterized in that, when the processor executes the program, the above-mentioned method for identifying abnormal lights of equipment rooms .

As described above, according to the present invention, the photographing effect can be optimized, so that the abnormal light and the normal light are more prominent in the picture, and the influence of noise or impurities on the photograph recognition is greatly reduced, so that it can be more simple, efficient, and accurate It is recognized that there is no need for complex machine learning as in the prior art.

Other features and advantages possessed by the method and apparatus of the present invention will become more specifically cleared or clarified by the drawings incorporated herein and the specific embodiments used to explain some principles of the present invention together with the drawings .

BRIEF DESCRIPTION

FIG. 1 is a flowchart showing a method for identifying an abnormal light in an equipment room according to an embodiment of the present invention.

FIG. 2 is a schematic diagram showing the structure of a system for identifying abnormal lights in an equipment room according to an embodiment of the present invention.

detailed description

The following introduces some of the multiple embodiments of the present invention and aims to provide a basic understanding of the present invention. It is not intended to confirm the key or decisive elements of the present invention or to limit the scope of protection.

In the identification of abnormal lights in the equipment room, generally, when the cabinet is opened, the machine room inspection robot directly takes pictures of the device. Due to the various colors on the device panel, there are a large number of areas that are relatively close to the color of the lamp , Making identification difficult. When the cabinet is closed, the machine room inspection robot takes a picture of the closed device. Because the focus is on the cabinet door, the cabinet door reflects light and the brightness is high, so it is impossible to effectively distinguish the lights of different colors. Therefore, the inventor found through the above research that when taking pictures of the device, it is necessary to adjust the focus of light diffraction and the aperture of the cabinet door to diffract the light to reduce the influence of the cabinet door reflection and the like.

When the cabinet is opened or closed, take pictures of the equipment in the equipment room. Due to the weak light, the pictures have more noise, and the lighting is not obvious. Suppose the object distance when the camera shoots is u. The robot is stationary, and the object distance is reduced to continue taking pictures. As the object distance is reduced, the device is out of the focus point, and the lights will be blurred, making it easier to identify. The other parts of the device will become more blurred due to blur, and the whole will become gray and dark. Then, keep reducing the object distance, so that the black part in the photo histogram occupies most of the size. When closing the cabinet door, the size of the blurred light is basically the same as the size of the small hole on the cabinet door. The blurred light in the final picture will not affect the formation of light spots. At the same time, most of the other pictures are basically black or gray. You can use this picture to identify signal lights and abnormal lights. The brightness and chromaticity analysis can easily and efficiently complete the identification of signal lights and abnormal lights. In this way, it is possible to prevent noise from affecting the extraction and recognition of signal lights and abnormal light features, and no complicated learning is required.

Next, a method for recognizing the abnormal light of the equipment room in the embodiment of the present invention will be described.

As shown in FIG. 1, a method for identifying abnormal lights in a computer room according to an embodiment of the present invention includes the following steps:

Step S1: When the cabinet is closed or opened, the machine room inspection robot focuses on the cabinet door through the camera to obtain the corresponding object distance u;

Step S2: Taking the object distance u as the initial object distance, reduce the object distance by δ (where δ is much smaller than u, for example, as an example, it can be assumed to be 0.01u), that is, reduce the object distance to u-δ, and Shooting, in addition, as a modification, the object distance u may be used as the initial object distance, and the object distance may be reduced (u-δ), so that the camera shoots the cabinet door with the reduced object distance , Where δ is much smaller than u;

Step S3: Analyze the captured picture, analyze the spot size of the identification signal lamp and the percentage of black in the picture histogram;

Step S4: If the light spot is too small to be effectively recognized and the black in the picture histogram is relatively small, then step S5 will be entered. In step S5, the object distance is reduced by δ and shooting is performed, and then return to step S3, another In terms of aspect, when the size of the light spot is basically the same as the size of the small hole of the cabinet door and the black account is relatively high (for example, the black accounted for more than 90%), it indicates that the picture at the object distance can be used to identify the signal light and abnormal light;

Step S6: Perform brightness detection on the picture to identify the signal light, and perform chroma analysis to identify the color of the signal light to determine the abnormal light.

Next, a modification of the above embodiment will be described.

The method for recognizing abnormal lights in equipment rooms of this modification includes the following steps:

(1) When the cabinet is closed or opened, the machine room inspection robot focuses on the cabinet door through the camera to obtain the corresponding object distance u;

(2) Taking 0 as the initial object distance of the camera, increase the object distance from 0, for example, increase δ (where δ is much smaller than u, for example, it can be assumed to be 0.01u), and take a picture;

(3) Analyze the picture, analyze the spot size of the identification signal lamp and the proportion of black in the picture histogram. At this time, the spot is larger and obviously larger than the small hole of the cabinet door, and the black accounts for a larger proportion. Continue to increase the object distance and make the object The distance is less than u;

(4) When the size of the light spot is basically the same as the size of the small hole of the cabinet door and the proportion of black is relatively high (for example, more than 85%, or more than 90%, etc.), use the picture at the object distance to identify the signal light and abnormal light;

(5) Perform brightness detection on the picture to identify the signal light, and perform chroma analysis to identify the color of the signal light to determine the abnormal light.

The method of identifying the abnormal light of the equipment room of the present invention has been described above, and then the identification system of the abnormal light of the equipment room of the present invention will be described.

As shown in FIG. 2, a system for identifying abnormal lights in a computer room according to an embodiment of the present invention includes:

Camera 100, used to photograph cabinet doors;

The object distance obtaining module 200 is used to obtain the object distance u for the camera to focus on the cabinet door in the equipment room;

The object distance reduction module 300 causes the camera to start changing based on the initial object distance and causes the camera to shoot at the changed object distance;

The judging module 400 determines whether the light spot size of the captured picture identification signal lamp and the black proportion in the picture histogram are within the first preset range and whether the black proportion in the picture histogram meets the second preset Set a prescribed range, and if it is determined that the light spot does not meet the first preset prescribed range and the proportion of black in the slice histogram does not meet the second preset prescribed range, repeat the object distance changing module The action of 300 until it meets the first preset specified range and the second preset specified range; and

The identification module 500 performs brightness detection on the picture to identify the signal light and performs chromaticity analysis to identify the color of the signal light, thereby determining the abnormal light.

The object distance changing module 300 makes the camera take u as the initial object distance and reduces the object distance by δ, so that the camera shoots the cabinet door with the reduced object distance, where δ is much smaller than u, where, for example, δ = 0.01u.

It may also be that the object distance changing module 300 makes the camera take u as the initial object distance and reduces the object distance to δ, so that the camera shoots the cabinet door with the reduced object distance, where δ is much smaller than u, for example, δ = 0.01u. In this case, when the judgment module 500 judges that the light spot does not meet the preset first preset specified range and the black occupancy in the picture histogram does not meet the second preset specified range, the object distance changing module 300 changes the object distance Continue to decrease and allow the camera to shoot the cabinet door at the reduced object distance.

Or another case may be that the object distance changing module 300 makes the camera take the initial object distance of 0 and increases the object distance by δ, and causes the camera to shoot at the increased object distance, where δ is much smaller than u.

Here, the first preset specified range may be set to be substantially the same as the size of the small hole of the cabinet door, for example. The second preset predetermined range may be set to a value of, for example, 85% or more, 90% or more, and so on.

The present invention also provides a computer-readable storage medium on which a computer program is stored, which is characterized in that, when the program is executed by a processor, the above method for identifying abnormal lights of a computer room equipment is realized.

The present invention also provides a computer device, including a memory, a processor, and a computer program stored on the memory and capable of running on the processor, characterized in that, when the processor executes the program, the foregoing abnormal light of the equipment room equipment is realized Identification method.

The machine room inspection robot directly takes pictures of the device. Since there are various colors on the device panel, there are a large number of areas that are relatively close to the color of the lamp, which makes the recognition difficult. When the cabinet is closed, the machine room inspection robot takes a picture of the closed device. Because the focus is on the cabinet door, the cabinet door reflects light and the brightness is high, so it is impossible to effectively distinguish the lights of different colors. Therefore, the inventor found through the above research that when taking pictures of the device, it is necessary to adjust the focus of the light and the diffraction of the light on the cabinet door to reduce the influence of the cabinet door reflection and the like.

The method for identifying abnormal lights in a computer room and the system for identifying abnormal lights in a computer room of the present invention, when taking pictures of the equipment in the cabinet when the cabinet is opened or closed, will cause the equipment to be out of the focus point due to the reduced object distance. It will be blurred and more easily recognized. Other parts of the device will become more blurred due to the blur, and the whole will become gray and dark. Next, keep reducing the object distance so that the black part of the photo histogram occupies the most part. When the cabinet door is closed, the size of the blurred light is basically the same as the size of the small hole on the cabinet door. There is no influence between the light spots formed by the light, and most of the other pictures are basically black or gray. Therefore, through simple brightness and chromaticity analysis of the picture, the identification of signal lights and abnormal lights can be completed simply and efficiently.

The above examples mainly illustrate the method for identifying abnormal lights of machine room equipment and the identification system of abnormal lights for equipment room of the present invention. Although only some of the specific embodiments of the present invention have been described, those of ordinary skill in the art should understand that the present invention can be implemented in many other forms without departing from the spirit and scope of the invention. Therefore, the examples and embodiments shown are to be regarded as illustrative rather than restrictive, and the present invention may cover various modifications without departing from the spirit and scope of the present invention as defined by the appended claims. And replace.

Claims

A method for recognizing abnormal lights in equipment rooms includes:

In the object distance obtaining step, focus on the cabinet door in the equipment room through the camera to obtain the corresponding object distance u;

The step of changing the object distance causes the camera to start changing based on the initial object distance and causes the camera to shoot with the changed object distance;

In the judging step, for the size of the light spot of the captured picture recognition signal lamp and the black proportion in the picture histogram, determine whether the light spot meets the preset first preset range and whether the black proportion in the picture histogram meets the second preset Specified range, if it is judged that the light spot does not meet the first preset specified range and the proportion of black in the slice histogram does not meet the second preset specified range, the step of changing the object distance is repeated until Comply with the first preset prescribed range and the second preset prescribed range; and

Recognition step, analyze the picture and identify abnormal lights.
The method for identifying abnormal lights of a computer room equipment according to claim 1, wherein:

In the step of changing the object distance, the camera takes u as the initial object distance and reduces the object distance by δ, so that the camera shoots the cabinet door at the reduced object distance, where δ is much smaller than u.
The method for identifying abnormal lights of a computer room equipment according to claim 1, wherein:

In the step of changing the object distance, the camera is made to have an initial object distance of 0 and the object distance is increased by δ, and the camera is made to shoot at the increased object distance, where δ is much smaller than u.
The method for recognizing an abnormal light of a machine room equipment according to any one of claims 1 to 3, characterized in that

In the judging step, the first predetermined range refers to the size of the small hole of the cabinet door.
The method for recognizing an abnormal light of a machine room equipment according to any one of claims 1 to 3, wherein:

In the identifying step, the picture is subjected to brightness detection to identify the signal lamp, and chromaticity analysis is performed to identify the signal lamp color, thereby determining the abnormal lamp.
The method for recognizing an abnormal light of a machine room equipment according to any one of claims 1 to 3, characterized in that

The δ is equal to 0.01u, and the second preset specified range is more than 90%.
A system for identifying abnormal lights in equipment rooms includes:

Camera, used to photograph cabinet door;

The object distance obtaining module focuses the cabinet door in the equipment room through the camera to obtain the corresponding object distance u;

The object distance changing module causes the camera to start changing based on the initial object distance and causes the camera to shoot at the changed object distance;

The judgment module determines whether the spot size of the image recognition signal lamp obtained by shooting and the black proportion in the picture histogram meet the preset first preset range and whether the black proportion in the picture histogram meets the second preset Specified range, if it is determined that the light spot does not meet the first preset specified range and the black ratio in the slice histogram does not meet the second preset specified range, repeating the step of changing the object distance Act until the first preset specified range and the second preset specified range are met; and

The recognition module analyzes the pictures taken by the camera and recognizes abnormal lights.
The system for identifying abnormal lights of equipment rooms according to claim 7, wherein:

In the object distance changing module, the camera takes u as the initial object distance and reduces the object distance by δ, so that the camera shoots the cabinet door at the reduced object distance, where δ is much smaller than u.
The system for identifying abnormal lights of equipment rooms according to claim 7, wherein:

In the object distance changing module, the camera is made to have an initial object distance of 0 and the object distance is increased by δ, and the camera is made to shoot at the increased object distance, where δ is much smaller than u.
The system for identifying abnormal lights in an equipment room according to any one of claims 7 to 9, wherein:

The first preset specified range refers to the size of the small hole of the cabinet door.
The system for identifying abnormal lights in equipment rooms according to any one of claims 7 to 9, wherein:

The identification module performs brightness detection on the picture to identify the signal light and performs chroma analysis to identify the color of the signal light, thereby determining an abnormal light.
The system for identifying abnormal lights in equipment rooms according to any one of claims 7 to 9, wherein:

The δ is equal to 0.01u, and the second preset specified range is more than 90%.
A computer-readable storage medium on which a computer program is stored, characterized in that, when the program is executed by a processor, the method for identifying an abnormal light of a machine room device according to any one of claims 1 to 6 is realized.
A computer device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, when the processor executes the program, any one of claims 1 to 6 is realized The method for identifying abnormal lights in equipment room.