CN116129603A - Workshop safety monitoring system based on image recognition - Google Patents
Workshop safety monitoring system based on image recognition Download PDFInfo
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- CN116129603A CN116129603A CN202310136753.4A CN202310136753A CN116129603A CN 116129603 A CN116129603 A CN 116129603A CN 202310136753 A CN202310136753 A CN 202310136753A CN 116129603 A CN116129603 A CN 116129603A
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/02—Alarms for ensuring the safety of persons
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/40—Scenes; Scene-specific elements in video content
- G06V20/41—Higher-level, semantic clustering, classification or understanding of video scenes, e.g. detection, labelling or Markovian modelling of sport events or news items
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/18—Status alarms
- G08B21/182—Level alarms, e.g. alarms responsive to variables exceeding a threshold
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/18—Status alarms
- G08B21/24—Reminder alarms, e.g. anti-loss alarms
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V2201/00—Indexing scheme relating to image or video recognition or understanding
- G06V2201/07—Target detection
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Abstract
The invention discloses a workshop safety monitoring system based on image recognition, which relates to the field of workshop safety monitoring and comprises the following components: the video acquisition module is used for acquiring videos in the production workshop; the wireless transmission module is used for transmitting the video acquired by the video acquisition module to the analysis module; the analysis module is used for analyzing the video by utilizing a computer vision target detection algorithm, identifying whether an operator exists in a dangerous area of the production workshop or not, and identifying whether the operator wears a safety helmet or not; the early warning module is used for carrying out early warning according to the identification result of the analysis module. According to the invention, the video monitoring subunit can be carried to the corresponding dangerous area for inspection by using the walking track, the track trolley and the lifting mechanism of the video acquisition module, and the workshop safety monitoring is carried out based on the video data acquired by the high-definition zoom camera and in combination with the computer vision target detection algorithm, so that the monitoring efficiency is improved.
Description
Technical Field
The invention relates to the field of workshop safety monitoring, in particular to a workshop safety monitoring system based on image recognition.
Background
In recent years, with the development of artificial intelligence technology, image recognition technology in computer vision has gained a large number of floor applications, such as word recognition in various product instruction pictures, recognition of various abnormal objects in medical photographing CT sheets, recognition of various satellite cloud patterns in weather forecast, face recognition, human body key point recognition, and the like. Image recognition technology has been widely applied to people's daily life and management decisions.
Currently, when safety monitoring is performed on an automatic workshop, patrol personnel mainly need to watch a monitoring picture for a long time or go to the workshop for patrol, and the monitoring is performed on two aspects of personnel and equipment. For personnel monitoring, whether the personnel wear safety helmets when entering a dangerous area regulated in an automatic workshop is mainly monitored, the dangerous area is usually marked by scribing, but the personnel do not wear the safety helmets and enter the dangerous area; the monitoring of the equipment mainly prevents the burn-out of the equipment caused by the aging short circuit of the equipment in long-term operation.
In a production workshop, ensuring the safety production of operators is always one of the conditions that national policies emphasize that construction enterprises must ensure implementation, however, in reality, because the management difficulty of construction enterprises is high, and the safety consciousness of the operators is light, the requirements that the operators must always wear safety helmets when entering a specified dangerous area in the safety production cannot be completely implemented, if high-altitude falling objects and the like happen, the life safety of the operators cannot be guaranteed.
Because the safety consciousness of the operators is not high, or the operators forget to wear the safety helmet due to certain external factors, the safety accident happens frequently, so that the operators who do not wear the safety helmet are reminded to wear the safety helmet, and the safety accident can be reduced to a certain extent. In workshop monitoring, the patrol personnel need watch the monitoring picture for a long time or go to the workshop to patrol, time consuming and laborious, and in large-scale workshop, need a large amount of personnel to monitor all monitoring pictures or patrol the workshop simultaneously, not only cause the manpower extravagant, the monitoring personnel can not guarantee to monitor all pictures yet, monitoring efficiency is low.
Disclosure of Invention
The invention aims to provide a workshop safety monitoring system based on image recognition so as to improve the efficiency of workshop safety monitoring.
In order to achieve the above object, the present invention provides the following solutions:
a shop safety monitoring system based on image recognition, comprising:
the video acquisition module is used for acquiring videos in the production workshop; the video acquisition module comprises a fixed video acquisition unit and a movable video acquisition unit; the fixed video acquisition unit comprises a plurality of high-definition zoom cameras; the fixed video acquisition unit is fixed at a preset position of the production workshop; the movable video acquisition unit comprises a walking track, a track trolley, a driving subunit, a lifting mechanism and a video monitoring subunit; the track trolley is arranged on the walking track; the driving subunit is respectively connected with the track trolley and the lifting mechanism and is used for controlling the movement of the track trolley and the lifting of the lifting mechanism; the video monitoring subunit is arranged on the lifting mechanism and is used for collecting videos in a production workshop;
the wireless transmission module is connected with the video acquisition module and used for transmitting the video acquired by the video acquisition module to the analysis module;
the analysis module is connected with the wireless transmission module and is used for analyzing the video by utilizing a computer vision target detection algorithm, identifying whether an operator exists in a dangerous area of a production workshop or not and identifying whether the operator wears a safety helmet or not; the dangerous area is an area below a suspended object in the production workshop;
and the early warning module is connected with the analysis module and is used for carrying out early warning according to the identification result of the analysis module.
Optionally, the video monitoring subunit comprises a truncated rectangular pyramid and four high-definition zoom cameras; the truncated rectangular pyramid is arranged on the lifting mechanism; the high-definition zoom camera is arranged on the side face of the truncated rectangular pyramid.
Optionally, the analysis module includes:
the video framing unit is used for framing the video and extracting key frames in a set time range;
the video frame preprocessing unit is connected with the video framing unit and is used for eliminating fuzzy and jittery video frames in the key frames to obtain clear video frames;
the detection unit is connected with the video frame preprocessing unit and is used for analyzing the clear video frame by utilizing a computer vision target detection algorithm, identifying whether an operator exists in a dangerous area of a production workshop or not and identifying whether the operator wears a safety helmet or not;
the first-stage early warning control unit is connected with the detection unit and is used for sending a first-stage early warning signal to the early warning module according to the identification result of the detection unit.
Optionally, the method further comprises:
the sensor module is used for collecting environment data; the sensor module comprises a temperature and humidity sensor, an illuminance sensor, a dust concentration sensor, a combustible gas sensor and a toxic gas sensor; the environmental data comprise temperature and humidity, illuminance, dust concentration, combustible gas concentration and toxic gas concentration in a production workshop;
the wireless transmission module is connected with the sensor module and used for transmitting the environmental data acquired by the sensor module to the analysis module.
Optionally, the analysis module further comprises:
the threshold judging unit is used for judging whether the temperature and humidity, the illuminance, the dust concentration, the combustible gas concentration or the toxic gas concentration exceed corresponding set thresholds or not;
and the secondary early warning control unit is connected with the threshold judging unit and is used for sending a secondary early warning signal to the early warning module according to the judging result of the threshold judging unit.
Optionally, the early warning module includes:
the primary early warning unit is used for carrying out primary early warning according to the identification result;
and the secondary early warning unit is used for carrying out secondary early warning according to the secondary early warning signal.
Optionally, the primary early warning unit is a light alarm.
Optionally, the secondary early warning unit is a buzzer alarm.
Optionally, a two-dimensional code is printed on the helmet of the operator; and the two-dimensional code stores the information of the operator.
Optionally, the analysis module further comprises:
the two-dimensional code identification unit is used for identifying the operator information stored in the two-dimensional code and judging whether the operator is a fixed operator in the production workshop according to the operator information.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
according to the workshop safety monitoring system based on image recognition, the walking track, the track trolley and the lifting mechanism are utilized to carry the video monitoring units to corresponding dangerous areas for inspection, the fixed video acquisition units can be used for acquiring videos in the workshop, so that no dead zone exists in the workshop, based on video data acquired by the high-definition zoom camera, the real-time performance and accuracy are considered in combination with a computer vision target detection algorithm, whether personnel in the dangerous areas in the workshop wear safety helmets or not is monitored in real time, the safety management level in the workshop is effectively improved for enterprises, the monitoring efficiency is improved through intelligent and automatic monitoring and calculation, the cost of manpower and material resources and inspection time can be saved, and the monitoring and detection flow is optimized.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions of the prior art, the drawings that are needed in the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a diagram of a workshop safety monitoring system based on image recognition.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The invention aims to provide a workshop safety monitoring system based on image recognition so as to improve the efficiency of workshop safety monitoring.
In order that the above-recited objects, features and advantages of the present invention will become more readily apparent, a more particular description of the invention will be rendered by reference to the appended drawings and appended detailed description.
As shown in fig. 1, the workshop safety monitoring system based on image recognition provided by the invention comprises:
the video acquisition module 101 is used for acquiring videos in a production workshop; the video acquisition module comprises a fixed video acquisition unit and a movable video acquisition unit; the fixed video acquisition unit comprises a plurality of high-definition zoom cameras; the fixed video acquisition unit is fixed at a preset position of the production workshop; the movable video acquisition unit comprises a walking track, a track trolley, a driving subunit, a lifting mechanism and a video monitoring subunit; the track trolley is arranged on the walking track; the driving subunit is respectively connected with the track trolley and the lifting mechanism and is used for controlling the movement of the track trolley and the lifting of the lifting mechanism; the video monitoring subunit is arranged on the lifting mechanism and is used for collecting videos in a production workshop. In practical application, the driving subunit is arranged in the control box, and the control box also comprises a power supply which supplies power to the driving subunit. The video monitoring subunit comprises a truncated rectangular pyramid and four high-definition zoom cameras.
Vertical suspension rods are arranged on the upper side edge of the walking track at intervals, and a top mounting plate is arranged at the top end of each vertical suspension rod; the track trolley is mounted on the walking track and walks along the walking track; the top of the control box is fixedly arranged on the track trolley; the lifting mechanism is arranged on the lower side surface of the control box, the truncated rectangular pyramid is inversely arranged on the suspension end of the lifting mechanism, and the lifting mechanism drives the truncated rectangular pyramid to move in a lifting manner. The four high-definition zoom cameras are respectively arranged on four side conical surfaces of the truncated rectangular pyramid and mainly monitor whether a person is under the suspended object or whether the suspended object collides with other objects. In addition, the fixed video acquisition unit is fixed in the preset position department of workshop, can 360 the video in the collection workshop at no dead angle.
A sensor module 102 for collecting environmental data; the sensor module comprises a temperature and humidity sensor, an illuminance sensor, a dust concentration sensor, a combustible gas sensor and a toxic gas sensor; the environmental data comprise temperature and humidity, illuminance, dust concentration, combustible gas concentration and toxic gas concentration in the production workshop. The combustible gas comprises ammonia, hydrogen sulfide and the like, and the toxic gas comprises nitrogen dioxide, sulfur dioxide, carbon monoxide and the like. In practical application, the sensor module 102 is disposed on the track trolley, and can monitor the environmental data at any position along with the movement of the track trolley, and can accurately position the position of the abnormal environmental data by combining the video acquired by the high-definition zoom camera.
And the wireless transmission module 103 is respectively connected with the video acquisition module 101 and the sensor module 102 and is used for transmitting the video acquired by the video acquisition module and the environmental data acquired by the sensor module to the analysis module.
And the analysis module 104 is connected with the wireless transmission module 103 and is used for analyzing the video by utilizing a computer vision target detection algorithm, identifying whether an operator exists in a dangerous area of the production workshop and identifying whether the operator wears a safety helmet. The dangerous area is an area below a suspended object in the production workshop. And the device is also used for judging whether the temperature and humidity, the illuminance, the dust concentration, the combustible gas concentration or the toxic gas concentration exceed corresponding set thresholds. In practical application, the received video in the workshop is imported into a detection model, and is analyzed and evaluated through a computer vision target detection algorithm to identify whether potential safety hazards exist in the current workshop.
In practical application, the safety helmet of the operator is printed with a two-dimensional code; and the two-dimensional code stores the information of the operator. The workshop fixing personnel can be identified through the two-dimension code; or by scanning two-dimension codes and identifying the workshop visitors.
The analysis module further includes:
the two-dimensional code identification unit is used for identifying the operator information stored in the two-dimensional code and judging whether the operator is a fixed operator in the production workshop according to the operator information.
As an alternative embodiment, the analysis module 104 includes:
and the video framing unit is used for framing the video and extracting key frames in a set time range.
And the video frame preprocessing unit is connected with the video framing unit and is used for eliminating fuzzy and jittery video frames in the key frames to obtain clear video frames.
The detection unit is connected with the video frame preprocessing unit and is used for analyzing the clear video frame by utilizing a computer vision target detection algorithm, identifying whether an operator exists in a dangerous area of a production workshop or not and identifying whether the operator wears a safety helmet or not.
The first-stage early warning control unit is connected with the detection unit and is used for sending a first-stage early warning signal to the early warning module according to the identification result of the detection unit.
And the threshold judging unit is used for judging whether the temperature and humidity, the illuminance, the dust concentration, the combustible gas concentration or the toxic gas concentration exceed corresponding set thresholds or not.
And the secondary early warning control unit is connected with the threshold judging unit and is used for sending a secondary early warning signal to the early warning module according to the judging result of the threshold judging unit.
In practical applications, the processing steps of the analysis module 104 of the present invention for the collected video are as follows:
s101: and the high-definition camera collects video data in a workshop.
S102: and compressing and storing the acquired video data, framing the video within a certain time range, and extracting key frames.
S103: preprocessing the extracted key frame, and returning to S102 to re-extract the key frame if the frame is jittery and fuzzy; if the frame is not jittered and blurred, the next processing is performed.
S104: detecting the preprocessed key video frames, and firstly, detecting a human body in the video frame range through a computer vision target; and tracking the human body according to the target tracking, intercepting an image in a certain range of the human body when the human body is found to enter a specified dangerous area, detecting whether to wear the safety helmet, and identifying.
S105: whether or not to alarm is judged based on the detection data (recognition result) of S104, and alarm information is sent to the user.
The system safety precaution is carried out through the image recognition technology, the system platform informs the corresponding responsible person to carry out safety precaution monitoring in a telephone, weChat applet, short message and other modes, so that the potential safety hazard is effectively reduced, the safety management and the working efficiency are improved, and the safety of operators is ensured.
And the early warning module 105 is connected with the analysis module 104 and is used for carrying out early warning according to the identification result of the analysis module 104. In practical application, the early warning module can inform the corresponding user to perform safety prevention monitoring in a telephone, weChat applet, short message and other modes.
As an alternative embodiment, the early warning module 105 includes:
and the primary early warning unit is used for carrying out primary early warning according to the identification result. In practical application, the primary early warning unit performs primary early warning according to the primary early warning signal. The primary early warning unit is a light alarm.
And the secondary early warning unit is used for carrying out secondary early warning according to the secondary early warning signal. The secondary early warning unit is a buzzer alarm.
When the workshop safety monitoring system based on image recognition performs primary early warning, operators can be reminded to wear safety helmets, and safety accidents are avoided as much as possible. When carrying out the second grade early warning, can remind the operation personnel in the workshop, the humiture is too high in the workshop, illuminance is too high, dust concentration is too high, toxic gas concentration is too high or combustible gas concentration is too high, has the potential safety hazard, and the operation personnel can in time handle, has improved monitoring efficiency, has ensured the safety of operation personnel in the workshop.
According to the workshop safety monitoring system based on image recognition, the walking track, the track trolley and the lifting mechanism are utilized to carry the video monitoring units to corresponding dangerous areas for inspection, based on video data collected by the high-definition camera, real-time performance and accuracy are considered, whether personnel in the dangerous areas in the workshop wear safety helmets or not is monitored in real time, the safety management level in the workshop is effectively improved for enterprises, the monitoring efficiency is improved through intelligent and automatic monitoring and calculation, meanwhile, the cost of manpower and material resources and inspection time can be saved, and the monitoring and detection flow is optimized.
In addition, the invention can comprehensively collect the workshop environment information through the arrangement of the sensor module, avoid major safety accidents such as fire, explosion and the like, and further improve the monitoring efficiency through the cooperation of the video equipment and the sensor; the first-level early warning unit and the second-level early warning unit effectively prevent the occurrence of false alarm and false alarm in the safety production process; the invention is convenient for staff to check the abnormal reasons of workshop production in time, effectively prevents the interruption of workshop production and ensures the safe and smooth workshop production.
In the present specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different point from other embodiments, and identical and similar parts between the embodiments are all enough to refer to each other.
The principles and embodiments of the present invention have been described herein with reference to specific examples, the description of which is intended only to assist in understanding the methods of the present invention and the core ideas thereof; also, it is within the scope of the present invention to be modified by those of ordinary skill in the art in light of the present teachings. In view of the foregoing, this description should not be construed as limiting the invention.
Claims (10)
1. A workshop safety monitoring system based on image recognition, comprising:
the video acquisition module is used for acquiring videos in the production workshop; the video acquisition module comprises a fixed video acquisition unit and a movable video acquisition unit; the fixed video acquisition unit comprises a plurality of high-definition zoom cameras; the fixed video acquisition unit is fixed at a preset position of the production workshop; the movable video acquisition unit comprises a walking track, a track trolley, a driving subunit, a lifting mechanism and a video monitoring subunit; the track trolley is arranged on the walking track; the driving subunit is respectively connected with the track trolley and the lifting mechanism and is used for driving the track trolley to move and the lifting mechanism to lift; the video monitoring subunit is arranged on the lifting mechanism and is used for collecting videos in a production workshop;
the wireless transmission module is connected with the video acquisition module and used for transmitting the video acquired by the video acquisition module to the analysis module;
the analysis module is connected with the wireless transmission module and is used for analyzing the video by utilizing a computer vision target detection algorithm, identifying whether an operator exists in a dangerous area of a production workshop or not and identifying whether the operator wears a safety helmet or not; the dangerous area is an area below a suspended object in the production workshop;
and the early warning module is connected with the analysis module and is used for carrying out early warning according to the identification result of the analysis module.
2. The image recognition-based shop safety monitoring system according to claim 1, wherein the video monitoring subunit comprises a truncated rectangular pyramid and four high-definition zoom cameras; the truncated rectangular pyramid is arranged on the lifting mechanism; the high-definition zoom camera is arranged on the side face of the truncated rectangular pyramid.
3. The image recognition-based plant safety monitoring system of claim 2, wherein the analysis module comprises:
the video framing unit is used for framing the video and extracting key frames in a set time range;
the video frame preprocessing unit is connected with the video framing unit and is used for eliminating fuzzy and jittery video frames in the key frames to obtain clear video frames;
the detection unit is connected with the video frame preprocessing unit and is used for analyzing the clear video frame by utilizing a computer vision target detection algorithm, identifying whether an operator exists in a dangerous area of a production workshop or not and identifying whether the operator wears a safety helmet or not;
the first-stage early warning control unit is connected with the detection unit and is used for sending a first-stage early warning signal to the early warning module according to the identification result of the detection unit.
4. The image recognition-based shop safety monitoring system according to claim 1, further comprising:
the sensor module is used for collecting environment data; the sensor module comprises a temperature and humidity sensor, an illuminance sensor, a dust concentration sensor, a combustible gas sensor and a toxic gas sensor; the environmental data comprise temperature and humidity, illuminance, dust concentration, combustible gas concentration and toxic gas concentration in a production workshop;
the wireless transmission module is connected with the sensor module and used for transmitting the environmental data acquired by the sensor module to the analysis module.
5. The image recognition-based plant safety monitoring system of claim 4, wherein the analysis module further comprises:
the threshold judging unit is used for judging whether the temperature and humidity, the illuminance, the dust concentration, the combustible gas concentration or the toxic gas concentration exceed corresponding set thresholds or not;
and the secondary early warning control unit is connected with the threshold judging unit and is used for sending a secondary early warning signal to the early warning module according to the judging result of the threshold judging unit.
6. The image recognition-based plant safety monitoring system of claim 5, wherein the pre-warning module comprises:
the primary early warning unit is used for carrying out primary early warning according to the identification result;
and the secondary early warning unit is used for carrying out secondary early warning according to the secondary early warning signal.
7. The system of claim 6, wherein the primary pre-warning unit is a light alarm.
8. The image recognition-based workshop safety monitoring system according to claim 6, wherein the secondary early warning unit is a buzzer alarm.
9. The workshop safety monitoring system based on image recognition according to claim 1, wherein the safety helmet of the operator is printed with a two-dimensional code; and the two-dimensional code stores the information of the operator.
10. The image recognition-based plant safety monitoring system of claim 9, wherein the analysis module further comprises:
the two-dimensional code identification unit is used for identifying the operator information stored in the two-dimensional code and judging whether the operator is a fixed operator in the production workshop according to the operator information.
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| CN202310136753.4A CN116129603A (en) | 2023-02-09 | 2023-02-09 | Workshop safety monitoring system based on image recognition |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116934091A (en) * | 2023-07-25 | 2023-10-24 | 广东至衡工程管理有限公司 | Construction site monitoring method and device, computer equipment and storage medium |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116934091A (en) * | 2023-07-25 | 2023-10-24 | 广东至衡工程管理有限公司 | Construction site monitoring method and device, computer equipment and storage medium |
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