CN114005088A - Safety rope wearing state monitoring method and system - Google Patents
Safety rope wearing state monitoring method and system Download PDFInfo
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- CN114005088A CN114005088A CN202111292574.7A CN202111292574A CN114005088A CN 114005088 A CN114005088 A CN 114005088A CN 202111292574 A CN202111292574 A CN 202111292574A CN 114005088 A CN114005088 A CN 114005088A
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Abstract
The invention provides a method for monitoring the wearing state of a safety rope, which comprises the following steps: when a vehicle appears in the monitoring area, monitoring the state of the roof through visual analysis, and when the roof is identified to have a person, storing an image and recording the coordinates of the portrait area; and B: b, searching the position of the safety rope in the image stored in the step A through visual analysis, and recording the coordinate of the safety rope; and C: and taking an intersection from the coordinates of the portrait area and the safety rope, if the intersection is not empty, the worker is considered to wear the safety rope, and if the intersection is empty, the worker does not wear the safety rope. The invention also provides a corresponding monitoring system. The invention has the advantages that: the position of the safety rope is searched in the picture of the monitored portrait, whether the safety rope is worn or not is judged through coordinate intersection, the calculation amount is small, the processing speed is high, the judgment logic is simple and effective, the result can be given in real time, the control center can be fed back in time, and the monitoring of the state that the safety rope is worn by an operator is effectively realized.
Description
Technical Field
The invention relates to the technical field of visual analysis, in particular to a method and a system for monitoring a wearing state of a safety rope.
Background
The safety rope is a protective device which can not be opened during high-altitude operation, and in industrial production engineering, the casualty accident rate caused by falling of people without wearing the safety rope is quite high, and most accidents are fatal accidents. Therefore, the safety rope for high-altitude operation is the life line of workers. However, in the transportation and delivery process of the cement industry, a driver needs to work after getting on the car roof and wearing the safety rope, and as the transportation driver is generally not a factory worker and has no better management means, the driver often does not operate according to the requirements, so that great hidden danger is buried in the safety production. At present, the wearing condition of the safety rope is detected in a manual inspection mode, and unmanned intelligent detection is not realized by a good method. At present, devices such as a pressure sensor and an infrared sensor are added on a body part based on a gyroscope acceleration sensor or CN208893510U by adopting CN102512773B in the industry, so that the wearing state of the safety rope is remotely monitored. This kind of mode needs to increase new device, and the mode of wearing to the monitoring object requires more complicatedly, and it is very inconvenient to use, probably further leads to the operation personnel to be unwilling to wear the safety rope, promotes and has certain limitation.
Disclosure of Invention
The invention aims to provide a method for monitoring the wearing state of a safety rope based on visual analysis. The invention solves the technical problems through the following technical scheme: a method for monitoring the wearing state of a safety rope comprises
Step A: when a vehicle appears in the monitoring area, monitoring the state of the roof through visual analysis, and when the roof is identified to have a person, storing an image and recording the coordinates of the portrait area;
and B: b, searching the position of the safety rope in the image stored in the step A through visual analysis, and recording the coordinate of the safety rope;
and C: and taking an intersection from the coordinates of the portrait area and the safety rope, if the intersection is not empty, the worker is considered to wear the safety rope, and if the intersection is empty, the worker does not wear the safety rope.
The position of the safety rope is searched in the picture of the monitored portrait, whether the safety rope is worn or not is judged through coordinate intersection, the calculation amount is small, the processing speed is high, the judgment logic is simple and effective, the result can be given in real time, the control center can be fed back in time, and the monitoring of the state that the safety rope is worn by an operator is effectively realized.
Preferably, the method for judging the presence of the vehicle in the monitoring area in the step a includes: a photoelectric switch is arranged in a vehicle working area, and the photoelectric switch is triggered when a vehicle enters the working area.
Preferably, the method further comprises the step of identifying and storing the license plate information after the photoelectric switch is triggered.
Preferably, a camera is arranged in the monitoring area, a car roof personnel detection algorithm is called to process pictures obtained by the camera, when people are detected at the car roof, the coordinates of the person image area are recorded, and the images are transmitted to the safety rope detection algorithm.
Preferably, the car roof personnel detection algorithm is obtained by acquiring image data and learning through a yolo network algorithm, wherein the image data comprises multi-scene image data of no car, no car and no person in a monitoring area, the scene with the car comprises the situations that the car is a car roof and a car side is a person, the scenes with the car are marked as the same category, other scenes are marked as the other category, meanwhile, the image data are randomly zoomed, rotated and compared, and the marked and operated images are input into the yolo network algorithm to learn to obtain the car roof personnel detection algorithm.
Preferably, the safety rope detection algorithm is obtained by acquiring image data and learning through a yolo network algorithm, the image data comprises images in three states of no safety rope, natural suspension of the safety rope and connection of the safety rope and a human body, the connection of the safety rope and the human body is marked as a normal state, other images are marked as an abnormal state, and the marked images are input into the yolo network algorithm to learn to obtain the safety rope detection algorithm.
Preferably, a plurality of cameras with different visual angles are arranged in the monitoring area, the cameras with each visual angle respectively collect pictures of vehicle roof personnel and the safety rope in different states for training, and the pictures are respectively acquired for recognition.
Preferably, the car roof personnel detection algorithm obtains pictures from the camera in a polling mode, detection is performed once every second until a car roof person signal is detected, coordinates of a person image area are stored, the pictures are sent to the safety rope detection algorithm, the area coordinates of the safety rope are detected, an intersection is taken for the person image area and the safety rope area, when the intersection is not empty, the safety rope is considered to be normally worn, when the intersection is empty, detection is continued, if the car roof person is detected, the signal of wearing the safety rope is not detected within a preset time period, an alarm signal is sent to the control center, and a video is stored.
The invention also provides a safety rope wearing state monitoring system, which comprises
The camera is used for acquiring a picture of a monitoring area;
the license plate recognition module is used for detecting whether vehicles exist in the monitoring area or not and acquiring license plate information of the vehicles;
the system comprises a vehicle roof personnel detection module, a vehicle roof personnel detection module and a vehicle roof personnel detection module, wherein the vehicle roof personnel detection module monitors the state of the vehicle roof through visual analysis when a vehicle appears in a monitored area, stores an image and records the coordinates of a portrait area when the vehicle roof is identified as a person;
the safety rope detection module searches the position of the safety rope in the image stored in the step A through visual analysis and records the coordinates of the safety rope;
and the judgment module is used for taking an intersection from the coordinates of the image area and the safety rope, considering that the worker wears the safety rope if the intersection is not empty, and not wearing the safety rope if the intersection is empty.
Preferably, the method for judging the presence of the vehicle in the monitoring area comprises the following steps: a photoelectric switch is arranged in a vehicle working area, and the photoelectric switch is triggered when a vehicle enters the working area; after the photoelectric switch is triggered, the method also comprises the steps of identifying and storing the license plate information;
the car roof personnel detection module and the safety rope detection module respectively collect personnel and safety rope pictures in different states, carry out manual marking, and complete training through learning by a yolo network algorithm after marking is completed;
the car roof personnel detection module obtains pictures from the camera in a polling mode, the pictures are detected once every second until a car roof person signal is detected, the coordinates of the person image area are stored, the pictures are sent to the safety rope detection module, the area coordinates of the safety rope are detected, an intersection is taken for the person image area and the safety rope area, the safety rope is normally worn when the intersection is not empty, the intersection is continuously detected when the intersection is empty, if the car roof person is detected, the signal of wearing the safety rope is not detected within a preset time length, an alarm signal is sent to the control center, and a video is stored.
The safety rope wearing state monitoring method and the safety rope wearing state monitoring system have the advantages that: the position of the safety rope is searched in the picture of the monitored portrait, whether the safety rope is worn or not is judged through coordinate intersection, the calculation amount is small, the processing speed is high, the judgment logic is simple and effective, the result can be given in real time, the control center can be fed back in time, and the monitoring of the state that the safety rope is worn by an operator is effectively realized. The image recognition method has the advantages that the recognition model is obtained by manually marking the images of different scenes, recognition accuracy is high, recognition precision is higher and higher along with the increase of use feedback, the yolo algorithm can detect the object state and the region in the image, intersection operation is conveniently taken, analysis is carried out through a plurality of visual angles, and the accuracy of the result is ensured.
Drawings
Fig. 1 is a flowchart of a safety rope wearing state monitoring method according to an embodiment of the present invention.
Detailed Description
To make the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention are described below in detail and completely with reference to the accompanying drawings, and it is apparent that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in FIG. 1, the embodiment provides a method for monitoring wearing state of a safety rope, which comprises the steps of
Step A: when a vehicle appears in the monitoring area, monitoring the state of the roof through visual analysis, and when the roof is identified to have a person, storing an image and recording the coordinates of the portrait area;
and B: b, searching the position of the safety rope in the image stored in the step A through visual analysis, and recording the coordinate of the safety rope;
and C: and taking an intersection from the coordinates of the portrait area and the safety rope, if the intersection is not empty, the worker is considered to wear the safety rope, and if the intersection is empty, the worker does not wear the safety rope.
According to the embodiment, the position of the safety rope is searched in the picture of the monitored portrait, whether the safety rope is worn or not is judged through coordinate intersection, the calculation amount is small, the processing speed is high, the judgment logic is simple and effective, the result can be given in real time, the control center is fed back in time, and the monitoring of the state that the safety rope is worn by an operator is effectively achieved.
Specifically, the method for judging the presence of the vehicle in the monitoring area comprises the following steps: a photoelectric switch is arranged in a vehicle working area, and the photoelectric switch is triggered when a vehicle enters the working area.
The monitoring area is also internally provided with a camera, and after the photoelectric switch is triggered, the license plate information can be identified and stored through the camera so as to check the state of the vehicle at a later stage.
When the personnel on the roof are detected, the pictures obtained by the camera are detected through a personnel detection algorithm on the roof, when the personnel on the roof are detected, the coordinates of the portrait area are recorded, and the pictures are transmitted to a safety rope detection algorithm.
The vehicle roof personnel detection algorithm is obtained by acquiring image data and learning through a yolo network algorithm, wherein the image data comprises multi-scene image data of no vehicle, no vehicle and no vehicle, the scene with the vehicle comprises the conditions of the presence of the vehicle roof and the presence of people beside the vehicle in a monitoring area, the scene with the vehicle and the presence of people on the vehicle roof are marked into the same category, other scenes are marked into the other category, meanwhile, the image data are randomly zoomed, rotated (less than 30 degrees) and adjusted through a contrast map, and the marked and operated images are input into the yolo network algorithm to learn to obtain the vehicle roof personnel detection algorithm.
And learning the data and the labels through a yolo network algorithm, and outputting a network model. When in detection, a picture is input, and the result of the vehicle roof detection person and the image position area can be predicted and output by using the model.
The safety rope detection algorithm is obtained by acquiring image data and learning through a yolo network algorithm, wherein the image data comprises images in three states of no safety rope, natural suspension of the safety rope and connection of the safety rope and a human body, the safety rope and the human body are connected and marked to be in a normal state, other images are marked to be in an abnormal state, and the marked images are input into the yolo network algorithm to learn to obtain the safety rope detection algorithm.
In order to ensure accurate detection results, in the preferred embodiment, a plurality of cameras with different viewing angles are arranged in a monitoring area, the influence of overlapping of the viewing angles on the detection results is detected through multiple viewing angles, when the safety rope is worn in part of the viewing angle detection, verification is carried out through other viewing angles, and only when the monitoring results of the cameras at all the viewing angles indicate that the safety rope is worn by a worker, the worker is considered to lack the safety rope, so that normal operation can be carried out.
Preferably, the safety rope still needs to be connected with the fixed rod, and if necessary, the positions of the safety rope and the fixed rod can be detected simultaneously, and when the coordinate of the safety rope and the coordinate of the fixed rod have an intersection, the safety rope is considered to be connected with the fixed rod, so that accidents caused by the fact that the safety rope is not fixed are prevented.
The car roof personnel detection algorithm obtains pictures from the camera in a polling mode, detection is carried out once every second until a car roof person signal is detected, the coordinates of the person image area are stored, the pictures are sent to the safety rope detection algorithm, the area coordinates of the safety rope are detected, an intersection is taken for the person image area and the safety rope area, the safety rope is considered to be normally worn when the intersection is not empty, the detection continues when the intersection is empty, and if the car roof person is detected, a warning signal is sent to the control center and a video is stored when a signal that the safety rope is not worn is not detected in a preset time (30S is taken in the embodiment).
This embodiment supports to add the polyphaser simultaneously and carries out multi-angle safety rope and detect, avoids or reduces because of sheltering from the hourglass problem of examining that leads to. And detecting whether the person on the roof exists or not by adopting a camera polling detection mode, acquiring a picture from the camera, sending the picture into a roof person detection algorithm, detecting once every second until the situation that the person exists on the roof is detected, and storing the position area information A. And then the picture is sent into a safety rope detection algorithm to detect safety rope position information B. And calculating the area intersection ratio IoU of the operator and the safety rope, judging that the operator wears the safety rope to operate if the IoU is larger than 0, and otherwise, indicating that the operator does not wear the safety rope to operate. If the safety rope is not detected, the camera polling phase is returned to continue to detect again.
The system detection decision adopts multiple cameras to realize multi-angle safety rope wearing detection, analysis and identification, and within a period of time, if the multiple cameras do not detect the condition of a safety rope, the system alarms a central system to remind a user that a behavior without the safety rope possibly occurs, simultaneously stores suspicious violation videos and records license plate information.
This embodiment still provides a safety rope wearing state monitoring system, include
The camera is used for acquiring a picture of a monitoring area;
the license plate recognition module is used for detecting whether vehicles exist in the monitoring area or not and acquiring license plate information of the vehicles;
the system comprises a vehicle roof personnel detection module, a vehicle roof personnel detection module and a vehicle roof personnel detection module, wherein the vehicle roof personnel detection module monitors the state of the vehicle roof through visual analysis when a vehicle appears in a monitored area, stores an image and records the coordinates of a portrait area when the vehicle roof is identified as a person;
the safety rope detection module searches the position of the safety rope in the image stored in the step A through visual analysis and records the coordinates of the safety rope;
and the judgment module is used for taking an intersection from the coordinates of the image area and the safety rope, considering that the worker wears the safety rope if the intersection is not empty, and not wearing the safety rope if the intersection is empty.
The method for judging the presence of the vehicle in the monitoring area comprises the following steps: a photoelectric switch is arranged in a vehicle working area, and the photoelectric switch is triggered when a vehicle enters the working area; after the photoelectric switch is triggered, the method also comprises the steps of identifying and storing the license plate information;
the car roof personnel detection module and the safety rope detection module respectively collect personnel and safety rope pictures in different states, carry out manual marking, and complete training through learning by a yolo network algorithm after marking is completed;
the car roof personnel detection module obtains pictures from the camera in a polling mode, the pictures are detected once every second until a car roof person signal is detected, the coordinates of the person image area are stored, the pictures are sent to the safety rope detection module, the area coordinates of the safety rope are detected, an intersection is taken for the person image area and the safety rope area, the safety rope is normally worn when the intersection is not empty, the intersection is continuously detected when the intersection is empty, if the car roof person is detected, the signal of wearing the safety rope is not detected within a preset time length, an alarm signal is sent to the control center, and a video is stored.
The above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. A safety rope wearing state monitoring method is characterized in that: comprises that
Step A: when a vehicle appears in the monitoring area, monitoring the state of the roof through visual analysis, and when the roof is identified to have a person, storing an image and recording the coordinates of the portrait area;
and B: b, searching the position of the safety rope in the image stored in the step A through visual analysis, and recording the coordinate of the safety rope;
and C: and taking an intersection from the coordinates of the portrait area and the safety rope, if the intersection is not empty, the worker is considered to wear the safety rope, and if the intersection is empty, the worker does not wear the safety rope.
2. The safety rope wearing state monitoring method according to claim 1, characterized in that: the method for judging the presence of the vehicle in the monitoring area in the step A comprises the following steps: a photoelectric switch is arranged in a vehicle working area, and the photoelectric switch is triggered when a vehicle enters the working area.
3. The safety rope wearing state monitoring method according to claim 2, characterized in that: after the photoelectric switch is triggered, the method also comprises the step of identifying and storing the license plate information.
4. The safety rope wearing state monitoring method according to claim 1, characterized in that: and a camera is arranged in the monitoring area, a car roof personnel detection algorithm is called to process pictures obtained by the camera, when people are detected at the car roof, the coordinates of the person image area are recorded, and the images are transmitted to a safety rope detection algorithm.
5. The safety rope wearing state monitoring method according to claim 4, characterized in that: the car roof personnel detection algorithm is obtained by acquiring image data and learning through a yolo network algorithm, wherein the image data comprises multi-scene image data of no car, no car and no person in a monitoring area, the scene with the car comprises the conditions that the car roof is occupied and the car is beside the occupied, the scene with the car is marked as the same category, other scenes are marked as the other category, meanwhile, the operations of zooming, rotating and adjusting a comparison graph are randomly carried out on the image data, and the marked and operated images are input into the yolo network algorithm to learn to obtain the car roof personnel detection algorithm.
6. The safety rope wearing state monitoring method according to claim 4, characterized in that: the safety rope detection algorithm is obtained by acquiring image data and learning through a yolo network algorithm, wherein the image data comprises images in three states of no safety rope, natural suspension of the safety rope and connection of the safety rope and a human body, the safety rope and the human body are connected and marked to be in a normal state, other images are marked to be in an abnormal state, and the marked images are input into the yolo network algorithm to learn to obtain the safety rope detection algorithm.
7. The safety rope wearing state monitoring method according to claim 4, characterized in that: the monitoring area is internally provided with a plurality of cameras with different visual angles, the cameras with each visual angle respectively collect pictures of car roof personnel and the safety rope in different states for training, and the pictures are respectively obtained for recognition.
8. The safety rope wearing state monitoring method according to claim 7, characterized in that: the car roof personnel detection algorithm obtains pictures from the camera in a polling mode, detection is carried out once every second until a car roof person signal is detected, the coordinates of the person image area are stored, the pictures are sent to the safety rope detection algorithm, the area coordinates of the safety rope are detected, an intersection is taken for the person image area and the safety rope area, the safety rope is considered to be normally worn when the intersection is not empty, the detection continues when the intersection is empty, if the car roof person is detected, the signal of wearing the safety rope is not detected within a preset time length, an alarm signal is sent to the control center, and a video is stored.
9. The utility model provides a safety rope wearing state monitoring system which characterized in that: comprises that
The camera is used for acquiring a picture of a monitoring area;
the license plate recognition module is used for detecting whether vehicles exist in the monitoring area or not and acquiring license plate information of the vehicles;
the system comprises a vehicle roof personnel detection module, a vehicle roof personnel detection module and a vehicle roof personnel detection module, wherein the vehicle roof personnel detection module monitors the state of the vehicle roof through visual analysis when a vehicle appears in a monitored area, stores an image and records the coordinates of a portrait area when the vehicle roof is identified as a person;
the safety rope detection module searches the position of the safety rope in the image stored in the step A through visual analysis and records the coordinates of the safety rope;
and the judgment module is used for taking an intersection from the coordinates of the image area and the safety rope, considering that the worker wears the safety rope if the intersection is not empty, and not wearing the safety rope if the intersection is empty.
10. The safety line wearing state monitoring system according to claim 9, wherein: the method for judging the presence of the vehicle in the monitoring area comprises the following steps: a photoelectric switch is arranged in a vehicle working area, and the photoelectric switch is triggered when a vehicle enters the working area; after the photoelectric switch is triggered, the method also comprises the steps of identifying and storing the license plate information;
the car roof personnel detection module and the safety rope detection module respectively collect personnel and safety rope pictures in different states, carry out manual marking, and complete training through learning by a yolo network algorithm after marking is completed;
the car roof personnel detection module obtains pictures from the camera in a polling mode, the pictures are detected once every second until a car roof person signal is detected, the coordinates of the person image area are stored, the pictures are sent to the safety rope detection module, the area coordinates of the safety rope are detected, an intersection is taken for the person image area and the safety rope area, the safety rope is normally worn when the intersection is not empty, the intersection is continuously detected when the intersection is empty, if the car roof person is detected, the signal of wearing the safety rope is not detected within a preset time length, an alarm signal is sent to the control center, and a video is stored.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114884842A (en) * | 2022-04-13 | 2022-08-09 | 哈工大机器人（合肥）国际创新研究院 | Visual security detection system and method for dynamically configuring tasks |
| CN115393360A (en) * | 2022-10-28 | 2022-11-25 | 常州海图信息科技股份有限公司 | Tail rope monitoring control method and tail rope monitoring control device |
-
2021
- 2021-11-03 CN CN202111292574.7A patent/CN114005088A/en active Pending
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114884842A (en) * | 2022-04-13 | 2022-08-09 | 哈工大机器人（合肥）国际创新研究院 | Visual security detection system and method for dynamically configuring tasks |
| CN114884842B (en) * | 2022-04-13 | 2023-09-05 | 哈工大机器人（合肥）国际创新研究院 | Visual security detection system and method for dynamic configuration task |
| CN115393360A (en) * | 2022-10-28 | 2022-11-25 | 常州海图信息科技股份有限公司 | Tail rope monitoring control method and tail rope monitoring control device |
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