CN114241737B - Method and device for monitoring climbing iron tower based on deep learning - Google Patents
Method and device for monitoring climbing iron tower based on deep learning Download PDFInfo
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- CN114241737B CN114241737B CN202111444415.4A CN202111444415A CN114241737B CN 114241737 B CN114241737 B CN 114241737B CN 202111444415 A CN202111444415 A CN 202111444415A CN 114241737 B CN114241737 B CN 114241737B
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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
- G08B21/22—Status alarms responsive to presence or absence of persons
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B13/00—Burglar, theft or intruder alarms
- G08B13/18—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength
- G08B13/189—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems
- G08B13/194—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems using image scanning and comparing systems
- G08B13/196—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems using image scanning and comparing systems using television cameras
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B13/00—Burglar, theft or intruder alarms
- G08B13/18—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength
- G08B13/189—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems
- G08B13/194—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems using image scanning and comparing systems
- G08B13/196—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems using image scanning and comparing systems using television cameras
- G08B13/19602—Image analysis to detect motion of the intruder, e.g. by frame subtraction
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
- H04N23/60—Control of cameras or camera modules
- H04N23/698—Control of cameras or camera modules for achieving an enlarged field of view, e.g. panoramic image capture
Abstract
The application provides a method and a device for monitoring climbing an iron tower based on deep learning, and relates to the technical field of data processing. The method utilizes the intelligent edge box to energize the traditional camera, intelligentizes the traditional camera, and completely covers and shoots the whole overall view of the iron tower; detecting whether personnel exist in the shooting area, and if the personnel exist, further detecting whether the personnel climb the iron tower; and if detecting that the person is climbing the iron tower, sending prompt information. It can be seen that this embodiment easy operation need not carry out any operation on the iron tower, only need add the intelligent edge box that has the algorithm on traditional camera, and the accuracy is high, uses manpower sparingly resource.
Description
Technical Field
The application relates to the technical field of data processing, in particular to a method and a device for monitoring climbing of an iron tower based on deep learning.
Background
The iron tower is widely applied in the field of communication signal transmission, but the communication iron tower and equipment are inevitably damaged after being exposed to the use working condition of the natural environment for a long time, so that maintenance work needs to be carried out in time, and maintenance personnel have certain danger during high-altitude operation and need to ensure the safety of the operation.
Currently, the monitoring is done manually by a camera or detected by a sensor. However, manual monitoring is prone to careless mistakes, abnormal behavior is not reported an alarm in time, and installation of other sensor devices is complicated and high in cost. Therefore, there is a need to solve this technical problem.
Disclosure of Invention
In view of the above problems, the present application is proposed to provide a method and apparatus for monitoring climbing iron tower based on deep learning, which overcomes or at least partially solves the above problems, and has the advantages of simple operation, no need of performing any operation on the iron tower, only need of adding an intelligent edge box with algorithm on the traditional camera, high accuracy and labor saving. The technical scheme is as follows:
in a first aspect, a method for monitoring climbing an iron tower based on deep learning is provided, which includes:
enabling the traditional camera by using the intelligent edge box, intelligentizing the traditional camera and completely covering and shooting the whole overall view of the iron tower;
detecting whether personnel exist in the shooting area, and if the personnel exist, further detecting whether the personnel climb the iron tower;
and if the fact that the person is climbing the iron tower is detected, sending out prompt information.
In one possible implementation, if it is detected that there is a person climbing the tower, the method further includes:
calculating the current climbing height of a climbing person by using an image acquired by a current camera;
the thickness of the air cushion needing to be inflated at the bottom of the iron tower is calculated according to the climbing height, so that climbing personnel can be guaranteed to be reliably and safely held by the air cushion if falling accidentally.
In a possible implementation manner, the vertex of the lower left corner of an image collected by a camera is taken as an origin, the left frame of the image is upward to be a Y axis, the lower frame of the image is rightward to be an X axis to establish a planar rectangular coordinate system, the unit length of the X axis of the coordinate system is a distance value between two adjacent transverse pixel points of the image, and the unit length of the Y axis of the coordinate system is a distance value between two adjacent longitudinal pixel points of the image;
judging whether people climb the iron tower or not according to the detection result of the detection personnel in the shooting area of the camera in unit time by using the following formula:
wherein P isi(t) a judgment value for judging whether the ith personal person is climbing the iron tower at the current moment; t represents the current time; t represents a unit time; (x)i(t-T)，yi(T-T)) represents that the ith personal coordinate point existing within the photographing region is detected at time T-T; (x)i(t)，yi(t)) represents the ith person sitting in the shooting area at the current timeMarking points, wherein if the person cannot be detected, the coordinate point is (0, 0); (X)min0) representing a coordinate point at the leftmost end of the bottom of the iron tower; (X)max0) represents a coordinate point at the rightmost end of the bottom of the iron tower; n represents taking intersection symbols;
if Pi(t) 1 represents that the ith personnel is climbing the iron tower at the current moment, and at the moment, an alarm system is started to inform the staff of dealing with the climbing situation in the coming and a safety air cushion at the bottom end of the iron tower is started;
if PiAnd (t) ═ 0 represents that the ith personnel is not climbing the iron tower at the current moment.
In one possible implementation, the current climbing height of the climbing person is calculated from the coordinates of the climbing person in the image captured by the current camera using the following formula:
wherein h (t) represents the highest climbing height among the climbing persons detected at the present moment; h represents the height of the iron tower; y ismaxThe ordinate value of a coordinate point of the tower tip of the iron tower in the image acquired by the camera is represented; n represents the total number of people in the shooting area detected at the time T-T;
the maximum value in brackets is obtained by taking the value of i from 1 to n.
In a possible implementation mode, when the fact that a person is climbing the iron tower is detected, an internal system of the iron tower can automatically pop out the inflatable air cushion at the bottom and automatically inflate the inflatable air cushion, and then the thickness of the air cushion needing to be inflated at the bottom of the iron tower is calculated according to the climbing height by using the following steps so as to ensure that all climbing persons can be reliably and safely held by using the air cushion if falling accidentally:
d represents the minimum air cushion thickness of the bottom of the iron tower, wherein the air cushion needs to be inflated; m represents the maximum mass of an adult known at present; g represents the acceleration of gravity; v represents the minimum value of the volume of the person; ρ represents the gas density charged in the gas cushion.
In a second aspect, a device for monitoring climbing iron tower based on deep learning is provided, which includes:
the shooting module is used for enabling the traditional camera by utilizing the intelligent edge box, intelligentizing the traditional camera and shooting the whole overall appearance of the iron tower in a covering manner;
the detection module is used for detecting whether personnel exist in the shooting area or not, and further detecting whether the personnel climb the iron tower or not if the personnel exist;
and the prompting module is used for sending out prompting information if the fact that the person climbs the iron tower is detected.
In one possible implementation, the apparatus further includes:
the calculation module is used for calculating the current climbing height of the climbing personnel by using the image acquired by the current camera if the condition that the climbing personnel climb the iron tower is detected; the thickness of the air cushion which needs to be inflated at the bottom of the iron tower is calculated according to the climbing height, so that climbing personnel can be reliably and safely held by the air cushion if falling accidentally.
In a possible implementation manner, the vertex of the lower left corner of an image collected by a camera is taken as an origin, the left frame of the image is upward to be a Y axis, the lower frame of the image is rightward to be an X axis to establish a planar rectangular coordinate system, the unit length of the X axis of the coordinate system is a distance value between two adjacent transverse pixel points of the image, and the unit length of the Y axis of the coordinate system is a distance value between two adjacent longitudinal pixel points of the image;
the detection module is further configured to:
judging whether people climb the iron tower or not according to the detection result of the detection personnel in the shooting area of the camera in unit time by using the following formula:
wherein P isi(t) a judgment value for judging whether the ith personal person is climbing the iron tower at the current moment; t represents the current time; t represents a unit time; (x)i(t-T)，yi(T-T)) represents that the ith personal coordinate point existing within the photographing region is detected at time T-T; (x)i(t)，yi(t)) represents the ith individual person coordinate point in the shooting area at the current moment, and if the person is not detected, the coordinate point is (0, 0); (X)min0) represents a coordinate point at the leftmost end of the bottom of the iron tower; (X)max0) represents a coordinate point at the rightmost end of the bottom of the iron tower; n represents taking intersection symbol;
if Pi(t) 1 represents that the ith person climbs the iron tower at the current moment, and at the moment, an alarm system is started to inform workers of dealing with the climbing condition in the future, and a safety air cushion at the bottom end of the iron tower is started;
if PiAnd (t) is 0, which indicates that the ith personnel is not climbing the iron tower at the current moment.
In one possible implementation, the calculation module is further configured to:
calculating the current climbing height of the climbing personnel according to the coordinates of the climbing personnel in the image acquired by the current camera by using the following formula:
wherein h (t) represents the highest climbing height among the climbing persons detected at the present moment; h represents the height of the iron tower; y ismaxThe vertical coordinate value of a coordinate point of the tower tip of the iron tower in the image collected by the camera is represented; n represents the total number of persons detected to be present in the shooting area at the time T-T;
the maximum value in brackets is obtained by taking the value of i from 1 to n.
In one possible implementation, the computing module is further configured to:
when detecting that personnel are climbing the iron tower, an internal system of the iron tower can automatically pop out the inflatable air cushion at the bottom and carry out automatic inflation, and then the thickness of the air cushion needing to be inflated at the bottom of the iron tower is calculated according to the climbing height by using the following formula, so that all climbing personnel can be reliably and safely received by using the air cushion if falling accidentally:
d represents the minimum air cushion thickness of the air cushion required to be inflated at the bottom of the iron tower; m represents the maximum mass of an adult known at present; g represents the gravitational acceleration; v represents the minimum value of the volume of the person; ρ represents the gas density charged in the gas cushion.
By means of the technical scheme, the method and the device for monitoring the climbing iron tower based on the deep learning provided by the embodiment of the application enable the traditional camera by using the intelligent edge box, and the traditional camera is intelligentized to completely cover and shoot the whole overall view of the iron tower; detecting whether personnel exist in the shooting area, and if the personnel exist, further detecting whether the personnel climb the iron tower; and if the fact that the person is climbing the iron tower is detected, sending out prompt information. It can be seen that this embodiment easy operation need not carry out any operation on the iron tower, only needs to add the intelligent edge box that has the algorithm on traditional camera, and the accuracy is high, uses manpower sparingly.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings used in the description of the embodiments of the present application will be briefly described below.
Fig. 1 shows a flow chart of a method for monitoring climbing a tower based on deep learning according to an embodiment of the present application;
fig. 2 shows a block diagram of a device for monitoring climbing a tower based on deep learning according to an embodiment of the present application; and
fig. 3 shows a block diagram of a deep learning based climbing tower monitoring device according to another embodiment of the present application.
Detailed Description
Exemplary embodiments of the present application will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present application are shown in the drawings, it should be understood that the present application may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
It should be noted that the terms "first," "second," and the like in the description and claims of this application and in the accompanying drawings are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that such uses are interchangeable under appropriate circumstances such that the embodiments of the application described herein are capable of operation in other sequences than those illustrated or described herein. Furthermore, the term "include" and its variants are to be read as open-ended terms meaning "including, but not limited to".
The embodiment of the application provides a climbing iron tower monitoring method based on deep learning, and as shown in fig. 1, the climbing iron tower monitoring method based on deep learning may include the following steps S101 to S103:
step S101, enabling a traditional camera by using an intelligent edge box, intelligentizing the traditional camera, and taking a whole overall view of the iron tower in a covering manner;
step S102, detecting whether personnel exist in the shooting area, and further detecting whether the personnel climb the iron tower if the personnel exist;
and step S103, sending out prompt information if the fact that the person is climbing the iron tower is detected.
According to the embodiment of the application, the camera can be arranged in the direction opposite to the iron tower, the whole overall appearance of the iron tower can be completely covered and shot by the camera, the traditional camera is energized by the intelligent edge box, the traditional camera is intelligentized, and the whole overall appearance of the iron tower is completely covered and shot; detecting whether personnel exist in the shooting area, and if the personnel exist, further detecting whether the personnel climb the iron tower; and if the fact that the person is climbing the iron tower is detected, sending out prompt information. It can be seen that this embodiment easy operation need not carry out any operation on the iron tower, only need add the intelligent edge box that has the algorithm on traditional camera, and the accuracy is high, uses manpower sparingly.
The embodiment of the application provides a possible implementation mode, if the situation that people climb the iron tower is detected, the current climbing height of the climbing people can be calculated by using the image acquired by the current camera; and then the thickness of the air cushion needing to be inflated at the bottom of the iron tower is calculated according to the climbing height, so that climbing personnel can be reliably and safely held by the air cushion if falling accidentally.
The embodiment of the application provides a possible implementation mode, the vertex of the lower left corner of an image collected by a camera is used as an origin, the left frame of the image is upward to be a Y axis, the lower frame of the image is rightward to be an X axis to establish a planar rectangular coordinate system, the unit length of the X axis of the coordinate system is a distance value between two adjacent transverse pixel points of the image, and the unit length of the Y axis of the coordinate system is a distance value between two adjacent longitudinal pixel points of the image;
judging whether people climb the iron tower or not according to the detection result of the detection personnel in the shooting area of the camera in unit time by using the following formula:
wherein P isi(t) a judgment value for judging whether the ith personal person is climbing the iron tower at the current moment; t represents the current time; t represents a unit time; (x)i(t-T)，yi(T-T)) indicates that the ith individual coordinate point existing within the photographing region is detected at time T-T; (x)i(t)，yi(t)) represents the ith personal coordinate point in the shooting area at the current moment, and if the personal coordinate point is not detected, the coordinate point is (0, 0); (X)min0) representing a coordinate point at the leftmost end of the bottom of the iron tower; (X)max0) representing a coordinate point at the rightmost end of the bottom of the iron tower; n represents taking intersection symbols;
if Pi(t) 1 represents that the ith personnel is climbing the iron tower at the current moment, and at the moment, an alarm system is started to inform the staff of dealing with the climbing situation in the coming and a safety air cushion at the bottom end of the iron tower is started;
if PiAnd (t) ═ 0 represents that the ith personnel is not climbing the iron tower at the current moment.
According to the detection result of the camera in the shooting area, whether personnel climb the iron tower is judged, so that the condition that the personnel climb the iron tower is ensured, the personnel passing through the iron tower and the personnel not climbing are eliminated, and the reliability of identification is ensured.
The embodiment of the application provides a possible implementation manner, and the current climbing height of a climbing person can be calculated according to the coordinates of the climbing person in an image acquired by a current camera by using the following formula:
wherein h (t) represents the highest climbing height among the climbing persons detected at the present moment; h represents the height of the iron tower; y ismaxThe ordinate value of a coordinate point of the tower tip of the iron tower in the image acquired by the camera is represented; n represents the total number of persons detected to be present in the shooting area at the time T-T;
the maximum value in brackets is obtained by taking the value of i from 1 to n.
The present embodiment calculates the current climbing height of the climbing personnel according to the coordinates of the climbing personnel in the image acquired by the current camera, and aims to find the highest climbing height among the climbing personnel, thereby ensuring that each climbing personnel can be safely caught by subsequent air cushion control.
The embodiment of the application provides a possible implementation manner, when detecting that a person is climbing an iron tower, an internal system of the iron tower can automatically pop out an inflatable air cushion at the bottom and automatically inflate the inflatable air cushion, and then the thickness of the air cushion needing to be inflated at the bottom of the iron tower is calculated according to the climbing height by using the following formula, so that all climbing persons can be reliably and safely held by using the air cushion if falling accidentally:
d represents the minimum air cushion thickness of the air cushion required to be inflated at the bottom of the iron tower; m represents the maximum mass of an adult known at present; g represents the gravitational acceleration; v represents the minimum value of the volume of the person; ρ represents the gas density charged in the gas cushion. The maximum mass of the m and the minimum volume of the V are used for ensuring that the air cushion is effective to all people and ensuring the reliability and safety of the air cushion.
In this embodiment, the normal volume of a person is between 0.04 and 0.08 cubic meters, and the value of V is 0.04 cubic meters; to ensure that the gas can take over the falling person requires that the gas density be greater than
In order to ensure the reliability and safety of the air cushion, the obtained D value is increased by 0.5 time of safety amount to inflate to obtain the thickness of the air cushion of 1.5D, and all climbing personnel can be reliably and safely held by the air cushion if falling accidentally.
It should be noted that, in practical applications, all the possible embodiments described above may be combined in any combination manner to form possible embodiments of the present application, and details are not described herein again.
Based on the same inventive concept, the embodiment of the application further provides a climbing iron tower monitoring device based on deep learning.
Fig. 2 shows a block diagram of a deep learning based climbing tower monitoring device according to an embodiment of the present application. As shown in fig. 2, the device for monitoring climbing a tower based on deep learning may include a photographing module 210, a detecting module 220, and a prompting module 230.
The shooting module 210 is used for enabling a traditional camera by using an intelligent edge box, intelligentizing the traditional camera and shooting the whole overall view of the iron tower in a covering manner;
the detection module 220 is configured to detect whether a person exists in the shooting area, and if the person exists, further detect whether the person climbs the iron tower;
and the prompt module 230 is configured to send a prompt message if it is detected that a person is climbing the iron tower.
In an embodiment of the present application, a possible implementation manner is provided, as shown in fig. 3, the apparatus shown in fig. 2 above may further include a calculating module 310, configured to calculate a current climbing height of a climbing person by using an image acquired by a current camera if it is detected that a person is climbing the iron tower; the thickness of the air cushion which needs to be inflated at the bottom of the iron tower is calculated according to the climbing height, so that climbing personnel can be reliably and safely held by the air cushion if falling accidentally.
The embodiment of the application provides a possible implementation mode, the vertex of the lower left corner of an image collected by a camera is used as an origin, the left frame of the image is upward to be a Y axis, the lower frame of the image is rightward to be an X axis to establish a planar rectangular coordinate system, the unit length of the X axis of the coordinate system is a distance value between two adjacent transverse pixel points of the image, and the unit length of the Y axis of the coordinate system is a distance value between two adjacent longitudinal pixel points of the image;
the detection module 220 is further configured to:
judging whether people climb the iron tower or not according to the detection result of the detection personnel in the shooting area of the camera in unit time by using the following formula:
wherein P isi(t) a judgment value for judging whether the ith personal person is climbing the iron tower at the current moment; t represents the current time; t represents a unit time; (x)i(t-T)，yi(T-T)) represents that the ith individual person who is present in the photographing area is detected at time T-TMarking points; (x)i(t)，yi(t)) represents the ith personal coordinate point in the shooting area at the current moment, and if the personal coordinate point is not detected, the coordinate point is (0, 0); (X)min0) representing a coordinate point at the leftmost end of the bottom of the iron tower; (X)max0) representing a coordinate point at the rightmost end of the bottom of the iron tower; n represents taking intersection symbol;
if Pi(t) 1 represents that the ith person climbs the iron tower at the current moment, and at the moment, an alarm system is started to inform workers of dealing with the climbing condition in the future, and a safety air cushion at the bottom end of the iron tower is started;
if PiAnd (t) is 0, which indicates that the ith personnel is not climbing the iron tower at the current moment.
In an embodiment of the present application, a possible implementation manner is provided, and the calculating module 310 is further configured to:
calculating the current climbing height of the climbing personnel according to the coordinates of the climbing personnel in the image acquired by the current camera by using the following formula:
wherein h (t) represents the highest climbing height among the climbing persons detected at the present moment; h represents the height of the iron tower; y ismaxThe vertical coordinate value of a coordinate point of the tower tip of the iron tower in the image collected by the camera is represented; n represents the total number of persons detected to be present in the shooting area at the time T-T;
the maximum value in brackets is obtained by taking the value of i from 1 to n.
In an embodiment of the present application, which provides a possible implementation manner, the calculating module 310 is further configured to:
when detecting that personnel are climbing the iron tower, an internal system of the iron tower can automatically pop out the inflatable air cushion at the bottom and carry out automatic inflation, and then the thickness of the air cushion needing to be inflated at the bottom of the iron tower is calculated according to the climbing height by using the following formula, so that all climbing personnel can be reliably and safely received by using the air cushion if falling accidentally:
d represents the minimum air cushion thickness of the air cushion required to be inflated at the bottom of the iron tower; m represents the maximum mass of an adult known at present; g represents the gravitational acceleration; v represents the minimum value of the volume of the person; ρ represents the gas density charged in the gas cushion.
It can be clearly understood by those skilled in the art that the specific working processes of the system, the apparatus, and the module described above may refer to the corresponding processes in the foregoing method embodiments, and for the sake of brevity, the detailed description is omitted here.
Those of ordinary skill in the art will understand that: the technical solution of the present application may be essentially implemented or all or part of the technical solution may be implemented in a form of a software product, where the computer software product is stored in a storage medium and includes program instructions, so that an electronic device (for example, a personal computer, a server, or a network device) executes all or part of the steps of the method described in the embodiments of the present application when the program instructions are executed. And the aforementioned storage medium includes: a U disk, a removable hard disk, a Read Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, an optical disk, or the like.
Alternatively, all or part of the steps of the foregoing method embodiments may be implemented by hardware (such as an electronic device, for example, a personal computer, a server, or a network device) related to program instructions, where the program instructions may be stored in a computer-readable storage medium, and when the program instructions are executed by a processor of the electronic device, the electronic device executes all or part of the steps of the method according to the embodiments of the present application.
The above embodiments are only used to illustrate the technical solutions of the present application, and not to limit the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments can be modified or some or all of the technical features can be equivalently replaced within the spirit and principle of the present application; such modifications or substitutions do not depart from the scope of the present application.
Claims (6)
1. A climbing iron tower monitoring method based on deep learning is characterized by comprising the following steps:
enabling a traditional camera by using an intelligent edge box, intelligentizing the traditional camera, and completely covering and shooting the whole overall appearance of the iron tower;
detecting whether personnel exist in the shooting area, and if the personnel exist, further detecting whether the personnel climb the iron tower;
if the fact that the person is climbing the iron tower is detected, prompt information is sent out;
wherein, if it is detected that there is a person climbing the iron tower, the iron tower climbing monitoring method further comprises:
calculating the current climbing height of a climbing person by using an image acquired by a current camera;
calculating the thickness of the air cushion needing to be inflated at the bottom of the iron tower according to the climbing height so as to ensure that climbing personnel can be reliably and safely received by the air cushion if falling accidentally;
the method comprises the following steps of taking the top point of the lower left corner of an image collected by a camera as an origin, setting the left frame of the image upwards as a Y axis, setting the lower frame of the image rightwards as an X axis to establish a rectangular plane coordinate system, setting the unit length of the X axis of the coordinate system as the distance value between two adjacent transverse pixel points of the image, and setting the unit length of the Y axis of the coordinate system as the distance value between two adjacent longitudinal pixel points of the image;
judging whether people climb the iron tower or not according to the detection result of the detection personnel in the shooting area of the camera in unit time by using the following formula:
wherein P isi(t) a decision value for deciding whether the ith individual person is climbing the iron tower at the current moment; t represents the current time; t represents a unit time; (x)i(t-T)，yi(T-T)) indicates that the ith individual coordinate point existing within the photographing region is detected at time T-T; (x)i(t)，yi(t)) represents the ith individual person coordinate point in the shooting area at the current moment, and if the person is not detected, the coordinate point is (0, 0); (X)min0) representing a coordinate point at the leftmost end of the bottom of the iron tower; (X)max0) representing a coordinate point at the rightmost end of the bottom of the iron tower; n represents taking intersection symbols;
if Pi(t) 1 represents that the ith personnel is climbing the iron tower at the current moment, and at the moment, an alarm system is started to inform the staff of dealing with the climbing situation in the coming and a safety air cushion at the bottom end of the iron tower is started;
if PiAnd (t) ═ 0 represents that the ith personnel is not climbing the iron tower at the current moment.
2. The method for monitoring climbing iron tower based on deep learning according to claim 1, wherein the current climbing height of the climbing person is calculated according to the coordinates of the climbing person in the image acquired by the current camera by using the following formula:
wherein h (t) represents the highest climbing height among the climbing persons detected at the present moment; h represents the height of the iron tower; y ismaxThe ordinate value of a coordinate point of the tower tip of the iron tower in the image acquired by the camera is represented; n represents the total number of persons detected to be present in the shooting area at the time T-T;
the maximum value in brackets is obtained by taking the value of i from 1 to n.
3. The method for monitoring climbing iron tower based on deep learning as claimed in claim 2, wherein when it is detected that there is a person climbing iron tower, the internal system of the iron tower will automatically pop up the bottom air cushion and automatically inflate the air cushion, and then calculate the thickness of the air cushion to be inflated at the bottom of the iron tower according to the climbing height by using the following formula, so as to ensure that all climbing persons can be reliably and safely held by the air cushion if they accidentally fall down:
d represents the minimum air cushion thickness of the bottom of the iron tower, wherein the air cushion needs to be inflated; m represents the maximum mass of an adult known at present; g represents the gravitational acceleration; v represents the minimum value of the volume of the person; ρ represents the gas density charged in the gas cushion.
4. The utility model provides a climb iron tower monitoring devices based on deep learning which characterized in that includes:
the shooting module is used for enabling a traditional camera by using the intelligent edge box, intelligentizing the traditional camera and shooting the whole overall appearance of the iron tower in a covering manner;
the detection module is used for detecting whether personnel exist in the shooting area or not, and further detecting whether the personnel climb the iron tower or not if the personnel exist;
the prompting module is used for sending out prompting information if the fact that the person is climbing the iron tower is detected;
wherein, climb iron tower monitoring devices and still include:
the calculation module is used for calculating the current climbing height of the climbing personnel by using the image acquired by the current camera if the condition that the climbing personnel climb the iron tower is detected; calculating the thickness of an air cushion needing to be inflated at the bottom of the iron tower according to the climbing height so as to ensure that climbing personnel can be reliably and safely held by the air cushion if falling accidentally;
the method comprises the following steps of taking the top point of the lower left corner of an image collected by a camera as an origin, taking the left frame of the image upwards as a Y axis, taking the lower frame of the image rightwards as an X axis, establishing a plane rectangular coordinate system, taking the unit length of the X axis of the coordinate system as the distance value between two adjacent transverse pixel points of the image, and taking the unit length of the Y axis of the coordinate system as the distance value between two adjacent longitudinal pixel points of the image;
the detection module is further configured to:
judging whether people climb the iron tower or not according to the detection result of the detection personnel in the shooting area of the camera in unit time by using the following formula:
wherein P isi(t) a decision value for deciding whether the ith individual person is climbing the iron tower at the current moment; t represents the current time; t represents a unit time; (x)i(t-T)，yi(T-T)) indicates that the ith individual coordinate point existing within the photographing region is detected at time T-T; (x)i(t)，yi(t)) represents the ith individual person coordinate point in the shooting area at the current moment, and if the person is not detected, the coordinate point is (0, 0); (X)min0) representing a coordinate point at the leftmost end of the bottom of the iron tower; (X)max0) representing a coordinate point at the rightmost end of the bottom of the iron tower; n represents taking intersection symbol;
if Pi(t) 1 represents that the ith person climbs the iron tower at the current moment, and at the moment, an alarm system is started to inform workers of dealing with the climbing condition in the future, and a safety air cushion at the bottom end of the iron tower is started;
if PiAnd (t) ═ 0 represents that the ith personnel is not climbing the iron tower at the current moment.
5. The deep learning based climbing iron tower monitoring device according to claim 4, wherein the computing module is further configured to:
calculating the current climbing height of the climbing personnel according to the coordinates of the climbing personnel in the image acquired by the current camera by using the following formula:
wherein h (t) represents the highest climbing height among the climbing persons detected at the present moment; h represents the height of the iron tower; y ismaxThe vertical coordinate value of a coordinate point of the tower tip of the iron tower in the image collected by the camera is represented; n represents the total number of people in the shooting area detected at the time T-T;
the maximum value in brackets is obtained by taking the value of i from 1 to n.
6. The deep learning based climbing iron tower monitoring device according to claim 5, wherein the computing module is further configured to:
when detecting that personnel are climbing the iron tower, the internal system of the iron tower can automatically pop out the inflatable air cushion at the bottom and automatically inflate the inflatable air cushion, and then the thickness of the air cushion needing to be inflated at the bottom of the iron tower is calculated according to the climbing height by using the following formula so as to ensure that all climbing personnel can be reliably and safely accommodated by using the air cushion if falling accidentally:
d represents the minimum air cushion thickness of the air cushion required to be inflated at the bottom of the iron tower; m represents the maximum mass of an adult known at present; g represents the acceleration of gravity; v represents the minimum value of the volume of the person; ρ represents the gas density charged in the gas cushion.
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