CN118004900B - Portal crane security protection system based on visual monitoring - Google Patents
Portal crane security protection system based on visual monitoring Download PDFInfo
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- 238000012544 monitoring process Methods 0.000 title claims abstract description 70
- 230000000007 visual effect Effects 0.000 title claims abstract description 14
- 238000000034 method Methods 0.000 claims abstract description 17
- 238000012806 monitoring device Methods 0.000 claims abstract description 9
- 239000003086 colorant Substances 0.000 claims abstract description 7
- 238000003708 edge detection Methods 0.000 claims abstract description 7
- 238000001514 detection method Methods 0.000 claims description 25
- 210000000744 eyelid Anatomy 0.000 claims description 16
- 238000011897 real-time detection Methods 0.000 claims description 2
- 230000002159 abnormal effect Effects 0.000 abstract description 2
- 230000006996 mental state Effects 0.000 abstract 1
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- 238000005516 engineering process Methods 0.000 description 3
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- 230000009286 beneficial effect Effects 0.000 description 1
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Abstract
The invention relates to the technical field of automatic early warning of a door machine, in particular to a door machine security system based on visual monitoring, which comprises a travel monitoring component, wherein a set is established in a two-dimensional coordinate system of a shot image through an edge detection algorithm to judge whether a door machine travel route is blocked or not; the monitoring device is used for judging whether the driver is in a fatigue state or not by monitoring the opening area of eyes of the driver; the method comprises the steps of detecting the edge of a cargo hold and fusing color images through an edge detection algorithm, extracting color RGB values of dry bulk cargo in the outline range of the edge of the cargo hold, establishing RGB values of the RGB values under different brightness, and detecting whether abnormal colors appear in the outline range of the cargo hold or not when each grab bucket grabs. The invention can monitor the advancing safety of the gantry crane, the operation mental state of a driver and the grabbing safety of the grab bucket in real time, thereby improving the safety and the efficiency of the gantry crane operation.
Description
Technical Field
The invention relates to the technical field of automatic early warning of door machines, in particular to a door machine security system based on visual monitoring.
Background
A gantry crane (hereinafter referred to as a portal crane) is an important machine for loading and unloading dry bulk cargo at a dock, and the existing gantry crane has defects in security and protection, and mainly comprises:
1. Safety protection between the door machines is generally considered in the automatic operation of the door machines, and blocking of other objects on the door machines in the advancing process of the door machines is ignored;
2. The door machine is usually operated for a long time, the grabbing and detaching process of the grab bucket is extremely short, and if the driver is tired, the driver is not concentrated, and danger can be generated;
3. the grab bucket is required to be stretched into the bulk cargo cabin to be grabbed, a part of cabin inner area is necessarily in a visual field blind area, the grab bucket is not visible to a driver, and if other machines or people are not in a safe position in the blind area, the grab bucket can be damaged.
Disclosure of Invention
The invention provides the following technical scheme for solving the technical problems: a door machine security protection system based on visual monitoring comprises a door machine and a traveling monitoring component. The advancing monitoring assembly is connected to the middle of the bottom surface of the cross beam of the door machine and comprises an advancing monitoring camera, and a laser detector is connected to the lower portion of the advancing monitoring camera in a rotating mode. The image information shot by the travelling monitoring camera comprises images of the joints of travelling wheels and the tracks on two sides of the cart at the bottom of the gantry crane.
The door opening of the cab of the door machine is provided with an access control device with a face recognition function, the cab of the door machine is provided with an operation monitoring device, and the operation monitoring device comprises an infrared camera used for capturing eye images of a driver.
One side fixedly connected with operation shooting camera of grab bucket of door machine, the shooting direction of operation shooting camera is parallel with the flexible direction of grab bucket.
And the processing core is used for receiving and analyzing data sent by the advancing monitoring assembly, the face recognition access control device, the operation monitoring device and the operation shooting camera.
Preferably, after the processing core receives the image shot by the travelling monitoring camera, a two-dimensional coordinate system is established according to the size of the image, the rail edges on two sides of the cart at the bottom of the gantry crane are detected through an edge detection algorithm, coordinate data of the rail edges are established into a coordinate set in the two-dimensional coordinate system of the image, and an alarm is sent out when no rail edge information exists in the coordinates in the corresponding coordinate set in the image shot in real time.
Preferably, after detecting the coordinate data set in the image in real time, the processing core further detects edge information of a middle area in the image, which takes coordinates of rails on two sides as a boundary, and when the edge information of the middle area is detected, the processing core starts the laser detector to detect in the direction with the edge information, and sends a signal to the processing core according to a detection result.
Preferably, the laser detector and the travelling monitoring camera are arranged in the same plane perpendicular to the ground, the initial direction of the laser detector is parallel to the direction of the travelling monitoring camera, the laser detector rotates according to the indication of the travelling monitoring camera, and the processing core judges the position of the corresponding obstacle according to the detection result of the laser detector.
Preferably, the judgment formula of the obstacle is a=sin|a|x c, wherein a is the distance between the obstacle and the central line represented by the direction of the travelling monitoring camera, a is the included angle between the laser detector and the central line represented by the direction of the travelling monitoring camera, c is the actual distance detected by the laser detector, and an alarm is sent out when a is smaller than a set threshold value, otherwise, the alarm is ignored.
Preferably, the method for judging the obstacle is to use the position of the travelling monitoring camera as a reference, the furthest distance and the track shot by the camera as boundaries, use laser to detect and detect the angle and the distance value of each point corresponding to the boundaries, establish a detection set, and send out an alarm when the angle in the data detected in real time accords with the angle in the set and the distance value is smaller than the value in the detection set, otherwise ignore.
Preferably, after the infrared camera shoots the facial image of the driver, the processing core detects the eye position through an AdaBoost algorithm, a two-dimensional coordinate system of the eye image is established by the detected eye image, coordinate data of the edge information of the eyes in the two-dimensional coordinate system of the eye image is detected through an edge algorithm, the maximum distance between the upper eyelid and the lower eyelid and the width of the eyes are further obtained, the eye opening area is obtained by multiplying the maximum distance between the upper eyelid and the lower eyelid by the width of the eyes, the standard eye opening area is established, and when the real-time monitored eye opening area is smaller than the standard eye opening area, the driver fatigue is judged when the standard eye opening area reaches the set proportion and the set duration.
Preferably, each time a new face is identified by the door access device, a signal is sent to the processing core, which reestablishes a new standard eye opening area.
Preferably, the operation shooting camera is used for shooting a color picture in the bulk bin, obtaining a cargo hold outline through an edge algorithm, fitting the cargo hold outline with the color image, extracting RGB values of main colors of dry bulk cargo in the cargo hold outline, establishing an RGB value set based on the RGB values under different brightness, stopping the grab bucket action and giving an alarm when the values which are not in line with the RGB value set appear in the inner range of the cargo hold outline.
Compared with the prior art, the invention has the following beneficial effects:
1. The fixed monitoring camera is arranged at the middle part of the crossbeam at the bottom of the door machine, so that the monitoring range covers the tracks at two sides, and the fixed camera can prevent a monitoring blind area caused by rotation of the camera. Detecting obstacles in the range of the camera by using a laser detector, and transmitting information of the obstacles to a processing core when the laser detector rotates and scans to the information age and the height of the obstacles possibly affects the running of a door machine, wherein the processing core transmits corresponding information to a display of a cab and a monitoring display of a remote control center;
2. An infrared camera is arranged in a cab to shoot eye images of a driver, the eye opening area of the driver is calculated, and an alarm is sent out to remind monitoring personnel of the driver and a remote control center when the eye opening area of the driver is lower than a threshold value. The entrance guard device with the face recognition function rebuilds the standard of the opening area of the eyes after recognizing the new face, so that different standards of the opening area of the eyes are built according to different people;
3. The camera with the same telescopic direction as the grab bucket is arranged on the grab bucket, the blind area of a driver is made up, whether other colors which are not corresponding to the dry bulk cargo colors exist in the bulk cargo ship cabin grabbed by the grab bucket or not is calculated according to the direction algorithm, abnormal color information is sent to the processing core, and the processing core sends the information to a display of the cab and a monitoring display of a remote control center.
Additional advantages, objects, and features of the invention will be set forth in part in the description which follows and in part will become apparent to those having ordinary skill in the art upon examination of the following or may be learned from practice of the invention.
Drawings
FIG. 1 is a schematic diagram of the functional structure of the present invention;
FIG. 2 is a schematic diagram of a door machine travel monitoring flow according to the present invention;
fig. 3 is a schematic diagram of a grab bucket grabbing safety monitoring flow.
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.
Referring to fig. 1-3, the invention provides a door machine security system based on visual monitoring, which comprises a door machine, wherein a processing core is arranged in the door machine. The device comprises a beam, a beam bottom surface of the beam, a traveling monitoring assembly, a laser detector, a control system and a control system. The image information shot by the advancing monitoring camera at least comprises images of the connecting positions of the advancing wheels and the track on two sides of the cart at the bottom of the portal crane, the advancing monitoring camera which is fixedly arranged can prevent visual blind areas caused by rotation, and the orientation of the advancing monitoring camera is positioned at the center line position of the images. Judging whether an obstacle exists in a set range through image information shot by the advancing monitoring camera, judging whether the obstacle can block the advancing of the gantry crane through the laser detector, wherein when the track is blocked, the obstacle can be directly judged to block the advancing of the gantry crane without detecting by using the laser detector.
The specific judgment mode is that firstly, under the condition that a field is empty and safe, an image is shot by using a travelling monitoring camera, after the processing core receives the image shot by the travelling monitoring camera, a two-dimensional coordinate system is built according to the size of the image, rail edges on two sides of a cart at the bottom of a gantry crane are detected through an edge detection algorithm such as a Canny algorithm and the like, and a set is built according to coordinate data of the rail edges in the two-dimensional coordinate system of the image. Since the travelling monitoring camera is fixed, the position of the track in the image is fixed in the image information shot at any time, and the coordinate data of the track edge information after edge detection in the two-dimensional coordinate system is also fixed, when the track edge information does not exist in the coordinates in the corresponding coordinate data set in the image shot in real time, the track is blocked, and an alarm is sent.
After detecting the coordinate data set in the real-time detection image, the processing core further detects edge information of a middle area, which takes coordinates of rails at two sides as a boundary, in the image, when the edge information is detected in the middle area, the processing core indicates that an obstacle exists between the rails at two sides, whether the height of the obstacle reaches the extent that the running of a gantry crane is influenced or not is required to be judged, at the moment, a laser detector is started to detect the direction with the edge information, the laser detector can detect the height representing the obstacle, the height of the laser detector is equal to the height of the laser detector, the running can be influenced, if the detection is not carried out, the height of the obstacle is judged to be insufficient to influence the running of the gantry crane, and the detection result is sent to the processing core.
The laser detector and the advancing monitoring camera are arranged in the same plane perpendicular to the ground, the orientation of the laser detector is parallel to the orientation of the advancing monitoring camera, so that the laser detector and the advancing monitoring camera are positioned at the same point in a two-dimensional coordinate system of an image, and under the default condition, the 0-degree detection angle of the laser detector coincides with a center line in the image shot by the advancing monitoring camera, so that the laser detector can conveniently judge the rotating direction according to the position of an obstacle in the image, obtain the rotating angle according to the rotating direction, and the left or right rotated angle is equal. The laser detector rotates according to the indication of the advancing monitoring camera, and the processing core judges the position of the corresponding obstacle according to the detection result of the laser detector. The invention comprises two methods for judging the obstacle according to the laser detection result.
The first method for judging the position of the obstacle according to the laser detection result is that the position of the obstacle is judged according to a position judging formula of the obstacle, wherein the judging formula of the obstacle is a=sin|a|xc, a is the distance between the obstacle and a central line represented by the direction of the travelling monitoring camera, and the distance is equal to the relative position of the obstacle in a width plane of the door machine. A is the included angle between the laser detector and the midline represented by the direction of the advancing monitoring camera, c is the actual distance detected by the laser detector, and an alarm is sent out when a is smaller than a set threshold value, otherwise, the alarm is ignored. Setting a threshold value, referring to the distance between the laser detector and two side edges of a cart at the bottom of the door machine, and when a is smaller than the threshold value, indicating that an obstacle is in the width range of the door machine, possibly blocking the door machine from travelling; a is larger than the threshold value, which means that the obstacle is out of the width range of the door machine and does not influence the running of the door machine. The travelling monitoring camera needs to shoot the junction of the travelling wheel and the track of the cart at the bottom of the portal crane, so the travelling monitoring camera is inclined towards the ground, and the detection direction of the laser detector is parallel to the ground, so an obstacle outside the shooting range of the travelling monitoring camera can be detected by adopting an obstacle position judgment formula, and the accurate linear distance x of the obstacle from the portal crane is obtained through the obstacle distance formula x=sin (90 degrees-A|) x c, so that an early warning function can be provided for a driver or a worker in a remote monitoring center.
The second judging method is that the position of the travelling monitoring camera is taken as a reference, the furthest distance shot by the camera and the track are taken as boundaries, the angle and the distance value of each point corresponding to the boundaries are detected by using a laser detector, a detection set is established, the detection set comprises the furthest detection distance corresponding to the rotation of the laser detector to the corresponding angle, and when the angle in the data detected in real time accords with the angle in the detection set and the distance value is smaller than the value in the detection set, the situation that the obstacle exists in the direction of the corresponding angle is indicated, and an alarm is sent out; when the distance value corresponding to the corresponding angle in the real-time detected data is larger than the value in the detection set, the obstacle is not in the image range shot by the travel monitoring camera, and the information of the corresponding obstacle is ignored. The detection range of the method is limited to the shooting range of the travel monitoring camera, and the method is more focused on assisting the travel monitoring camera in detection. The two obstacle position judging methods can be used independently or in combination, and the second obstacle judging method is used for judging whether the position of the obstacle is in the warning range needing special attention or not under the condition of combination, and the first obstacle position judging method is used for obtaining the accurate position of the obstacle.
The door opening of the cab of the door machine is provided with an access control device with a face recognition function, the cab of the door machine is provided with an operation monitoring device, and the operation monitoring device at least comprises an infrared camera used for capturing eye images of a driver. Specifically, after the infrared camera shoots the facial image of the driver, the processing core detects the eye position through an AdaBoost algorithm, a two-dimensional coordinate system is established by the detected eye image, coordinate data of the edge of the eye in the two-dimensional coordinate system of the eye image are detected through an edge algorithm, the maximum distance between the upper eyelid and the lower eyelid and the width of the eye are obtained, and at the moment, the obtained maximum distance between the upper eyelid and the lower eyelid and the width of the eye are data obtained in the two-dimensional coordinate system of the eye image and are not required to be real data. For example, the detected eye edge information includes four end value coordinate data (x 1, y 1), (x 2, y 2), (x 3, y 3), (x 4, y 4), and in the corresponding two-dimensional coordinate system with x representing the abscissa y representing the ordinate, when x1 is the minimum x value and x2 is the maximum x value, the width of the eye is the value obtained by subtracting x1 from x 2; when y3 is the maximum y value and y4 is the minimum y value, the maximum distance between the upper eyelid and the lower eyelid is the value obtained by subtracting y4 from y 3. And multiplying the maximum distance between the upper eyelid and the lower eyelid by the width of the eyes to obtain the eye opening area and establishing a standard eye opening area, and judging that the driver is tired when the real-time monitored eye opening area is lower than the standard eye opening area and exceeds a set proportion for a set time. The method for detecting the open area of the eyes is similar to the detection method for realizing the PERCLOS method in the prior art, but is different from the method for detecting the frequency of opening and closing eyes by using the PERCLOS method, wherein the fatigue state is judged after the time required for closing the eyes exceeds a certain proportion, and the fatigue state is judged after the time required for closing the eyes exceeds a certain proportion by monitoring that the open area of the eyes is lower than the standard open area of the eyes for a certain time and reaches a threshold value in real time. And when the real-time detected change time of the opening area of the eyes is lower than the set time, neglecting the judgment to exclude the blinking time.
Further, when the access control device recognizes a new face each time, a signal is sent to the processing core, and the processing core reestablishes a new standard eye opening area, so that after different drivers enter the cab, the standard eye opening area belonging to the current driver can be reestablished according to different eye sizes.
The grab bucket side fixedly connected with operation of door machine shoots the camera, and the shooting direction of operation shooting the camera is parallel with the flexible direction of grab bucket.
The operation shooting camera is used for shooting a color image in a bulk cargo hold, when the grab bucket shoots a dry bulk cargo for the first time, the grab bucket waits for the operation camera to shoot the image at a specific position, a cargo hold contour map is obtained through an edge detection algorithm, the cargo hold contour map is fitted with the color image, RGB values of colors of the dry bulk cargo inside the cargo hold contour are extracted by using the prior art such as KMeans clustering algorithm, color quantization algorithm and the like, and an RGB value set based on the RGB values and under different brightness is established. When the grab bucket moves to a specific position on the upper portion of the cargo hold, the operation camera shoots a real-time picture, extracts a color picture of the dry bulk cargo in the contour range of the cargo hold, extracts RGB values of the dry bulk cargo, compares the RGB values with values in the RGB value set, stops the action of the grab bucket and gives an alarm when the values which are not in accordance with the values contained in the RGB value set appear in the inner range of the contour of the cargo hold, and does not react. Only one kind of dry bulk cargo will be loaded in the same cargo compartment, the colour change of which only changes under different illumination levels, and when completely different colours occur, usually the in-compartment excavating machinery, personnel or the cargo compartment bilges are exposed to the shooting range.
The remote processing core is connected with the display of the cab, is also connected with the signal sending device, and sends information to the display of the remote monitoring center through the signal sending device, and when the driver does not pay attention to the alarm in time, the operator of the remote monitoring center reminds the alarm in time.
Based on the above embodiments, the processors, modules, corresponding control programs, algorithm programs and other supporting technologies mentioned in the present application may be implemented in combination with existing electrical technologies, information technologies, software technologies and general protocols, which are not included in the protection scope of the present application.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential characteristics thereof. Accordingly, the embodiments are to be considered in all respects as illustrative and not restrictive.
Claims (6)
1. The utility model provides a door machine security protection system based on visual monitoring, includes the door machine, its characterized in that still includes: the traveling monitoring assembly is connected to the middle of the bottom surface of the cross beam of the door machine and comprises a traveling monitoring camera, a laser detector is rotationally connected below the traveling monitoring camera, and image information shot by the traveling monitoring camera comprises images of the joints of traveling wheels and rails on two sides of a cart at the bottom of the door machine;
the door opening of the cab of the door machine is provided with an access control device with a face recognition function, the cab of the door machine is provided with an operation monitoring device, and the operation monitoring device comprises an infrared camera used for capturing eye images of a driver;
one side of a grab bucket of the door machine is fixedly connected with an operation shooting camera, and the shooting direction of the operation shooting camera is parallel to the telescopic direction of the grab bucket;
the processing core is used for receiving and analyzing data sent by the advancing monitoring assembly, the face recognition access control device, the operation monitoring device and the operation shooting camera;
After receiving an image shot by the travelling monitoring camera, the processing core establishes a two-dimensional coordinate system according to the size of the image, detects rail edges on two sides of a cart at the bottom of the gantry crane through an edge detection algorithm, establishes a coordinate set in the two-dimensional coordinate system of the image according to the coordinate data of the rail edges, and gives an alarm when no rail edge information exists in the coordinates in the corresponding coordinate set in the image shot in real time;
The laser detector and the travelling monitoring camera are arranged in the same plane vertical to the ground, the initial direction of the laser detector is parallel to the direction of the travelling monitoring camera, the laser detector rotates according to the indication of the travelling monitoring camera, and the processing core judges the position of the corresponding obstacle according to the detection result of the laser detector;
the operation shooting camera is used for shooting a color picture in the bulk bin, obtaining a cargo hold outline through an edge algorithm, fitting the cargo hold outline drawing with the color image, extracting RGB values of main colors of dry bulk cargo inside the cargo hold outline, establishing an RGB value set based on the RGB values under different brightness, stopping grab bucket action and giving an alarm when the values which are not in line with the values contained in the RGB value set appear in the inner range of the cargo hold outline.
2. The door machine security system based on visual monitoring according to claim 1, wherein the processing core detects the coordinates set in the real-time detection image, further detects edge information of a middle area in the image, which is bounded by coordinates of rails on two sides, and when the edge information of the middle area is detected, starts the laser detector to detect in a direction with the edge information, and sends a signal to the processing core according to a detection result.
3. The door machine security system based on visual monitoring according to claim 1, wherein the position judgment formula of the obstacle is a=sin|a|xc, wherein a is the distance between the obstacle and a central line represented by the direction of the travelling monitoring camera, a is the included angle between the laser detector and the central line represented by the direction of the travelling monitoring camera, c is the actual distance detected by the laser detector, and an alarm is given when a is smaller than a set threshold value, otherwise, the alarm is ignored.
4. The door machine security system based on visual monitoring according to claim 1, wherein the position judging method of the obstacle is to use the position of the travelling monitoring camera as a reference, the furthest distance shot by the camera and the track as a boundary, use laser to detect and detect the angle and the distance value of each point corresponding to the boundary, establish a detection set, and send out an alarm when the angle in the data detected in real time accords with the angle in the detection set and the distance value is smaller than the value in the detection set, otherwise ignore.
5. The door machine security system based on visual monitoring according to claim 1, wherein after the infrared camera shoots the face image of the driver, the processing core detects the eye position through an AdaBoost algorithm, and establishes a two-dimensional coordinate system of the eye image with the detected eye image, detects coordinate data of the edge information of the eye in the two-dimensional coordinate system of the eye image through an edge algorithm, further obtains the maximum distance between the upper eyelid and the lower eyelid and the width of the eye, multiplies the maximum distance between the upper eyelid and the lower eyelid and the width of the eye to obtain the eye opening area and establishes a standard eye opening area, and when the real-time monitored eye opening area is smaller than the standard eye opening area to reach a set proportion and a set duration.
6. The door operator security system based on visual monitoring of claim 5, wherein the door operator device sends a signal to the processing core each time a new face is identified, the processing core reestablishing a new standard eye opening area.
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