CN116253248A - Crane operation monitoring method, crane anti-collision human redundancy system and storage medium - Google Patents
Crane operation monitoring method, crane anti-collision human redundancy system and storage medium Download PDFInfo
- Publication number
- CN116253248A CN116253248A CN202310111346.8A CN202310111346A CN116253248A CN 116253248 A CN116253248 A CN 116253248A CN 202310111346 A CN202310111346 A CN 202310111346A CN 116253248 A CN116253248 A CN 116253248A
- Authority
- CN
- China
- Prior art keywords
- crane
- dynamic object
- information
- preset
- positioning
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66C—CRANES; LOAD-ENGAGING ELEMENTS OR DEVICES FOR CRANES, CAPSTANS, WINCHES, OR TACKLES
- B66C13/00—Other constructional features or details
- B66C13/16—Applications of indicating, registering, or weighing devices
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66C—CRANES; LOAD-ENGAGING ELEMENTS OR DEVICES FOR CRANES, CAPSTANS, WINCHES, OR TACKLES
- B66C15/00—Safety gear
- B66C15/06—Arrangements or use of warning devices
- B66C15/065—Arrangements or use of warning devices electrical
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66C—CRANES; LOAD-ENGAGING ELEMENTS OR DEVICES FOR CRANES, CAPSTANS, WINCHES, OR TACKLES
- B66C23/00—Cranes comprising essentially a beam, boom, or triangular structure acting as a cantilever and mounted for translatory of swinging movements in vertical or horizontal planes or a combination of such movements, e.g. jib-cranes, derricks, tower cranes
- B66C23/005—Cranes comprising essentially a beam, boom, or triangular structure acting as a cantilever and mounted for translatory of swinging movements in vertical or horizontal planes or a combination of such movements, e.g. jib-cranes, derricks, tower cranes with balanced jib, e.g. pantograph arrangement, the jib being moved manually
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66C—CRANES; LOAD-ENGAGING ELEMENTS OR DEVICES FOR CRANES, CAPSTANS, WINCHES, OR TACKLES
- B66C23/00—Cranes comprising essentially a beam, boom, or triangular structure acting as a cantilever and mounted for translatory of swinging movements in vertical or horizontal planes or a combination of such movements, e.g. jib-cranes, derricks, tower cranes
- B66C23/88—Safety gear
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
Landscapes
- Engineering & Computer Science (AREA)
- Mechanical Engineering (AREA)
- Control And Safety Of Cranes (AREA)
Abstract
The invention discloses a crane operation monitoring method, a crane anti-collision human redundancy system and a storage medium.
Description
Technical Field
The invention relates to the technical field of cranes, in particular to a crane operation monitoring method, a crane anti-collision human redundancy system and a storage medium.
Background
The crane is used as important material transferring equipment for a building construction site, is widely applied to the building construction site due to the advantages of wide working coverage range and high working efficiency, and along with the wide application of the crane, the accident fault cases generated in the working process are increased, meanwhile, because the construction site usually has more workers, crane operators usually need more energy to pay attention to the condition of the construction site in real time in the operation process, and special ground personnel are also needed to assist in the construction peak period; for a tower crane, which is one of the most widely used crane types in building construction, in order to improve the working reliability of the tower crane, a plurality of tower cranes are provided with redundant braking units to ensure the reliability of the braking function of the tower crane, meanwhile, due to the increasing development of the technology of the Internet of things, the monitoring equipment of the construction site has not only a single function of taking and monitoring as a site image, but also a digital twin model and visual output can be constructed on the site through the cooperation of a background server and loading related software through an image data file, so that the intuitiveness of a background monitoring personnel is improved, and on the basis, how to optimize the monitoring intervention mechanism of the crane in the running process, improve the intervention reliability of a main braking unit and a redundant braking unit of the crane, and reliably monitor and early warn the position relation between a dynamic object of the construction site and the crane are very practical problems.
Disclosure of Invention
In view of the above, the invention aims to provide a crane operation monitoring method, a crane anti-collision human redundant system and a storage medium, which are reliable in implementation, flexible in application, high in response efficiency and capable of effectively assisting in ensuring the safety of a crane operation site.
In order to achieve the technical purpose, the invention adopts the following technical scheme:
a crane operation monitoring method having a main brake unit and a redundant brake unit, and a brake switching unit for switching operation interventions of the main brake unit and the redundant brake unit, the operation monitoring method comprising:
responding to a work starting signal of the crane, and acquiring running information and pose information of the crane in real time;
responding to a work starting signal of the crane, and carrying out real-time positioning on a dynamic object in an open air area of a preset range of a construction site where the crane is positioned, so as to generate a dynamic object positioning result;
according to the real-time running information and pose information of the crane and the real-time generated dynamic object positioning result, the relative position data of the crane and the dynamic object are obtained, and an active braking unit or a redundant braking unit of the crane is started according to the relative position data and a preset condition to intervene in the running of the starter and/or to perform movement early warning or movement intervention on the dynamic object.
As a possible implementation manner, the solution further includes:
according to the dynamic object positioning result generated in the preset time, predicting the action track of the dynamic object in the future preset time to generate a dynamic object action track prediction result;
according to the running information and pose information of the crane in the preset time, predicting the action track of the crane in the future preset time, and generating a crane running track prediction result;
acquiring a crane running track prediction result and a dynamic object running track prediction result, dynamically judging the relative positions of the crane and the dynamic object within a preset time, and generating a predicted position judgment result;
and according to the predicted position judgment result, starting an active braking unit or a redundant braking unit of the crane to intervene in the operation of the starter and/or to perform movement early warning or movement intervention on the dynamic object.
As a preferred implementation option, preferably, the crane in this solution is a tower crane, and the operation information of the crane includes: the travelling speed information of a loading trolley on a crane arm, the rotation speed information of a crane rotary tower body, the lifting speed information of a crane lifting hook and the load information.
As a preferred implementation option, preferably, the pose information of the crane according to the present solution includes: the crane comprises boom position information, balance arm position information, position information of a load trolley on the boom, position information of a lifting hook and position information of a suspended object on the lifting hook, wherein a plurality of positioning units which are mutually spaced and used for marking positions are arranged on the boom, the balance arm, the load trolley, the lifting hook and the suspended object of the crane, and the positioning units on the boom, the balance arm, the load trolley, the lifting hook and the suspended object are distributed at intervals along the length direction of the positioning units.
As a preferred implementation choice, preferably, the construction site where the crane is located in the scheme is provided with a plurality of image capturing units, and the images captured by the plurality of image capturing units cover an open area within a preset range of the construction site;
responding to a work starting signal of the crane, carrying out real-time positioning on a dynamic object in an open air area of a preset range of a construction site where the crane is located, and generating a dynamic object positioning result comprises the following steps:
the image shooting unit responds to a work starting signal of the crane, performs image shooting on an open air area in a preset range of a construction site where the crane is located, and generates an image data file;
Acquiring image data files generated at different times, selecting an initial reference image data file according to preset conditions, then deriving an image frame from the initial reference image data file, positioning, identifying and marking elements in the image frame through a trained neural network, and generating baseline reference data;
the method comprises the steps of calling image data files generated after initial reference of the image data files according to preset time intervals, respectively deriving image frames, positioning, identifying and marking elements in the image frames through a trained neural network, and determining dynamic objects in the image frames by combining reference data;
constructing a three-dimensional digital twin model corresponding to a construction site where a crane is located, defining the ground where the construction site is located as an x-axis plane, defining the y-axis plane in the model, defining the z-axis plane as a vertical direction, selecting a preset position as a reference origin (0, 0), constructing elements in an image data file into the three-dimensional digital twin model in a corresponding digital simulation mode according to the reference data and the determined dynamic object, obtaining dynamic object coordinate data correspondingly, and setting the dynamic object coordinate data as a dynamic object positioning result, wherein the dynamic object and the non-dynamic object in the three-dimensional digital twin model have different rendering strategies and marks.
As a preferred implementation option, preferably, elements in the image frame corresponding to the base reference data in this embodiment are marked with a unique ID and a recognition result, where the recognition result includes: when generating basic reference data, performing secondary definition on elements in an image according to a recognition result to obtain a dynamic object and a non-dynamic object;
the method comprises the steps of calling image data files generated after initial reference of the image data files according to preset time intervals, respectively deriving image frames, positioning, identifying and marking elements in the image frames through a trained neural network, and determining dynamic objects in the image frames by combining reference data, wherein the steps of:
the method comprises the steps of calling image data files generated after an initial reference image data file according to preset time intervals, and then respectively guiding out image frames;
positioning, identifying and marking elements in the image frame through the trained neural network, comparing the elements with elements in the reference data, judging the moving condition of the same elements in the image frame, and redefining a non-dynamic object with changed position in the image frame as a dynamic object;
And collecting information of elements defined as dynamic objects in all the image data, and finishing the determination of the dynamic objects.
As a preferred implementation choice, preferably, according to the real-time operation information and pose information of the crane and the real-time generated dynamic object positioning result, the method obtains the relative position data of the crane and the dynamic object, and starts the active braking unit or the redundant braking unit of the crane according to the relative position data and a preset condition to intervene in the operation of the starter and/or perform movement early warning or movement intervention on the dynamic object, which includes:
acquiring real-time running information and pose information of the crane, and defining coordinates corresponding to the pose information as:
Q i =(X i ,Y i ,Z i )
wherein Q is i The method comprises the steps that (i) the position coordinates of a positioning unit on a crane boom, a balance arm, a load trolley, a lifting hook and a suspended object in a three-dimensional digital twin model of a crane are preset numbers corresponding to the positioning unit on the crane boom, the balance arm, the load trolley, the lifting hook and the suspended object;
the method comprises the steps of obtaining a dynamic object positioning result generated in real time, and defining the coordinates of a dynamic object as:
D j =(X j ,Y j ,Z j )
wherein D is j The method comprises the steps that the position coordinates of different dynamic objects in a three-dimensional digital twin model are defined, j is the ID of the different dynamic objects, and in addition, a datum point defined by the dynamic object coordinates is a preset geometric position of a contour positioned in an image frame;
Calculating the relative position data of each part positioning unit of the crane and the dynamic object, wherein the formula is as follows:
S ijx =|X i -X j |
S ijy =|Y i -Y j |
S ijz =|Z i -Z j |
wherein S is ijx 、S ijy 、S ijy 、S ij The relative spacing between the positioning unit and the dynamic object in the x, y and z directions on each part of the crane and the relative spacing in the three-dimensional space are respectively;
comparing the relative position data of each part of the dynamic object and the crane with a preset distance threshold value, and starting an active braking unit or a redundant braking unit of the crane to intervene in the running of the starter according to preset conditions when the relative position data is smaller than or equal to a preset first threshold value, and meanwhile, performing movement early warning or movement intervention on the dynamic object;
when the moving pre-warning or moving intervention is performed on the dynamic object, the moving pre-warning or moving intervention is performed on the dynamic object when the moving pre-warning or moving intervention is performed on the dynamic object and the moving pre-warning or moving intervention is performed on the dynamic object;
when the relative position data is larger than a preset second threshold value and smaller than or equal to a preset third threshold value, acquiring the relative position data of the dynamic object and each part of the crane at the last preset time point, comparing, and when the relative position data is reduced, carrying out movement early warning on the dynamic object;
the first threshold, the second threshold and the third threshold are sequentially increased, the moving early warning mode is to send out photoelectric alarms, and the moving intervention mode is to set roadblock.
As a preferred implementation choice, preferably, in the operation monitoring method of the present disclosure, according to a dynamic object positioning result generated in a preset time, a motion track of a dynamic object in a future preset time is estimated, and generating a motion track prediction result of the dynamic object includes:
the method comprises the steps of obtaining a dynamic object positioning result generated in a preset time, extracting coordinates of the dynamic object, converting coordinate two-dimensional processing of the dynamic object into two-dimensional coordinate information by taking the ground of a construction site as a two-dimensional coordinate plane, wherein the formula is as follows:
D j ’=(X j ,Y j )
wherein D is j ' digital twin model in three dimensions for dynamic objectThe projection position coordinates are projected to a two-dimensional coordinate plane with the ground of a construction site, and j is the ID of different dynamic objects;
labeling two-dimensional coordinate information which is generated in preset time and corresponds to the two-dimensional processing of the dynamic object positioning result in a two-dimensional coordinate system, sequentially connecting the two-dimensional coordinate information to form a two-dimensional coordinate curve, constructing trend lines to generate a plurality of mathematical models matched with the two-dimensional coordinate information, and selecting a prediction model with a correlation coefficient meeting preset requirements;
calculating the moving speed V of the dynamic object according to the two-dimensional coordinate information of the dynamic object at different time points, and calculating the movable distance R of the dynamic object by combining the future time point T to be predicted, wherein R=VT;
Obtaining a prediction model, taking the tail end of a curve of the prediction model as a circle center, and establishing a circle with the radius of R as a possible position range of a dynamic object at a time point T to obtain a dynamic object action track prediction result;
in the operation monitoring method, according to operation information and pose information of a crane in preset time, a motion track of the crane in future preset time is estimated, and the generation of a crane operation track prediction result comprises the following steps:
acquiring pose information of the crane within preset time, and generating track information of the crane within corresponding preset time;
acquiring running information of a current crane, calling running speed information of a load trolley on a crane arm and rotating speed information of a crane rotating tower body, taking the running speed information and the rotating speed information as fixed parameters, calculating positions of the crane arm, a balance arm, the load trolley, a lifting hook and a suspended object at a future time point T by combining current pose information of the crane, comparing the pose information of the crane with the pose information of the current crane at the future time point T, and setting a movement track range between the pose information as a crane running track prediction result.
As a preferred implementation choice, preferably, the dynamic object in the scheme is a moving object on the ground of a construction site;
In the operation monitoring method, obtaining a crane operation track prediction result and a dynamic object action track prediction result, dynamically judging the relative positions of a crane and a dynamic object in preset time, and generating a prediction position judgment result comprises the following steps:
acquiring a crane running track prediction result and a dynamic object running track prediction result;
projecting the position of the suspended object in the predicted result of the crane running track to a two-dimensional coordinate plane of the ground where the construction site is located, and then dynamically calculating the relative spacing S between the suspended object and the dynamic object within preset time;
comparing the relative distance S with a preset threshold value according to the relative distance S to generate a predicted position judgment result;
in the operation monitoring method, according to the judgment result of the predicted position, starting an active braking unit or a redundant braking unit of the crane to intervene in the operation of the starter and/or to perform mobile early warning or mobile intervention on a dynamic object comprises the following steps:
acquiring a predicted position judgment result, and outputting a first instruction when the predicted position judgment result points to a preset area above the dynamic object when the relative spacing S is smaller than a preset threshold value, or outputting a second instruction when the suspended object passes through the preset area above the dynamic object;
According to the first instruction, an active braking unit or a redundant braking unit of the crane is started to intervene in the operation of the starter and/or to perform movement early warning or movement intervention on the dynamic object.
Based on the scheme, the invention also provides a crane anti-collision person redundant system, the crane is provided with a main braking unit and a power driving unit, the crane anti-collision person redundant system is loaded with the crane operation monitoring method, the dynamic object comprises a person, and the crane anti-collision person redundant system comprises:
the positioning units are a plurality of lifting arms, balance arms, load-carrying trolleys, lifting hooks and suspended articles which are arranged on the crane;
the starting induction unit is used for inducing a work starting signal of the crane;
the operation monitoring unit is used for acquiring operation information and pose information of the crane in real time;
the image monitoring unit is used for capturing images of an open-air area in a preset range of a construction site where the crane is located, and generating a monitoring image;
the neural network unit is used for positioning the dynamic object in the monitoring image in real time according to the monitoring image and generating a dynamic object positioning result;
the data processing unit is used for acquiring the relative position data of the crane and the dynamic object according to the real-time running information and the pose information of the crane and the dynamic object positioning result generated in real time, and outputting an intervention instruction according to the relative position data and a preset condition;
The redundant braking unit is used for braking the crane;
the brake switching unit is used for switching the braking of the main braking unit and the redundant braking unit to work and intervene the crane;
the command receiving unit is used for acquiring the intervention command and starting an active braking unit or a redundant braking unit of the crane to intervene in the operation of the starter according to the intervention command.
Based on the above scheme, the invention also provides a computer readable storage medium, wherein at least one instruction, at least one section of program, code set or instruction set is stored in the storage medium, and the at least one instruction, the at least one section of program, the code set or the instruction set is loaded and executed by a processor to realize the crane operation monitoring method.
By adopting the technical scheme, compared with the prior art, the invention has the beneficial effects that: the scheme of the invention skillfully detects pose information, running information and dynamic objects of a construction site of the crane in real time, realizes running early warning of the crane by continuously judging the positions of the dynamic objects and each action part of the crane, simultaneously, improves the reliability and flexibility of the braking of the crane by introducing a main braking unit or a redundant braking unit of the crane into the braking operation of the crane based on actual monitoring conditions, and avoids the problem of braking failure caused by sudden failure.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the 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 schematic flow chart of a simplified implementation of the method of the present invention;
FIG. 2 is a schematic representation of the crane of the method of the invention when in operation;
FIG. 3 is a second schematic flow chart of a simplified implementation of the method of the present invention;
FIG. 4 is a schematic diagram of the method of the present invention for predicting the action track of a dynamic object;
fig. 5 is a schematic diagram of a brief implementation of the system of the present invention.
Detailed Description
The invention is described in further detail below with reference to the drawings and examples. It is specifically noted that the following examples are only for illustrating the present invention, but do not limit the scope of the present invention. Likewise, the following examples are only some, but not all, of the examples of the present invention, and all other examples, which a person of ordinary skill in the art would obtain without making any inventive effort, are within the scope of the present invention.
As shown in fig. 1 and 2, the present embodiment is a crane operation monitoring method, which has a main brake unit and a redundant brake unit, and a brake switching unit for switching between operation interventions of the main brake unit and the redundant brake unit, the operation monitoring method including:
s01, responding to a work starting signal of the crane, and acquiring running information and pose information of the crane in real time;
s02, responding to a work starting signal of the crane, and carrying out real-time positioning on a dynamic object in an open area of a preset range of a construction site where the crane is located to generate a dynamic object positioning result;
s03, acquiring relative position data of the crane and the dynamic object according to real-time operation information and pose information of the crane and a dynamic object positioning result generated in real time, and starting an active braking unit or a redundant braking unit of the crane according to the relative position data and a preset condition to intervene in the operation of the starter and/or perform movement early warning or movement intervention on the dynamic object.
In this scheme, the hoist is tower crane, the operation information of hoist includes: the travelling speed information of a loading trolley on a crane arm, the rotation speed information of a crane rotary tower body, the lifting speed information of a crane lifting hook and the load information.
In this scheme, the position appearance information of hoist includes: the crane comprises boom position information, balance arm position information, position information of a load trolley on the boom, position information of a lifting hook and position information of a suspended object on the lifting hook, wherein a plurality of positioning units which are mutually spaced and used for marking positions are arranged on the boom, the balance arm, the load trolley, the lifting hook and the suspended object of the crane, and the positioning units on the boom, the balance arm, the load trolley, the lifting hook and the suspended object are distributed at intervals along the length direction of the positioning units.
In order to be able to conveniently obtain real-time images of a construction site, the construction site where the crane is located is provided with a plurality of image capturing units, and the images captured by the plurality of image capturing units cover an open area of a preset range of the construction site.
In this scheme S02, responding to a work start signal of a crane, performing real-time positioning of a dynamic object in an open area within a preset range of a construction site where the crane is located, where generating a dynamic object positioning result includes:
s021, an image shooting unit responds to a work starting signal of the crane, and performs image shooting on an open air area in a preset range of a construction site where the crane is positioned to generate an image data file;
S022, acquiring image data files generated at different times, selecting an initial reference image data file according to preset conditions, then deriving an image frame from the initial reference image data file, positioning, identifying and marking elements in the image frame through a trained neural network, and generating baseline reference data;
s023, calling the image data file generated after the initial reference image data file according to a preset time interval, respectively deriving image frames, positioning, identifying and marking elements in the image frames through a trained neural network, and determining dynamic objects in the image frames by combining with reference data;
s024, constructing a three-dimensional digital twin model corresponding to a construction site where the crane is located, defining the ground where the construction site is located as a plane where an x-axis and a y-axis are located in the model, defining the z-axis as a vertical direction, selecting a preset position as a reference origin (0, 0), constructing elements in an image data file into the three-dimensional digital twin model in a corresponding digital simulation mode according to reference data and the determined dynamic object, correspondingly obtaining dynamic object coordinate data, and setting the dynamic object coordinate data as a dynamic object positioning result, wherein the dynamic object and the non-dynamic object in the three-dimensional digital twin model have different rendering strategies and identifications.
In this scheme, the trained neural network includes a positioning neural network and a detection neural network, wherein the positioning neural network performs contour positioning on elements in an image frame by loading an existing contour recognition algorithm, then extracts elements in the positioned contour, guides the elements into the detection neural network to detect specific information of the elements, and then generates a recognition result, preferably, the recognition result includes: one of a person, a carrier, an animal, equipment, a building material, a building construction, a terrain construction.
For the training of the detection neural network, the detection neural network can be used for identifying and training by preloading objects, structures and biological elements which possibly appear in a construction site, the training method is an existing scheme, details of the existing scheme are not repeated here, and the neural network for identifying the contours of the elements in the images is also existing.
As a preferred implementation choice, preferably, the elements in the image frames corresponding to the base reference data in this scheme are marked with unique IDs and recognition results, and after the base reference data is generated, the elements in the image are defined as dynamic objects and non-dynamic objects in advance according to the recognition results.
For the method for determining the dynamic object, the method S023 calls the image data file generated after the initial reference image data file according to the preset time interval, then respectively derives the image frames, locates, identifies and marks the elements in the image frames through the trained neural network, and combines the reference data to determine the dynamic object in the image frames, which includes:
s0231, calling the image data file generated after the initial reference image data file according to a preset time interval, and then respectively guiding out image frames;
s0232, positioning, identifying and marking elements in the image frame through a trained neural network, comparing the elements with elements in the reference data, judging the moving condition of the same elements in the image frame, and redefining a non-dynamic object with changed position in the image frame as a dynamic object;
s0233, collecting information of all elements defined as dynamic objects in the image data, and finishing the determination of the dynamic objects.
According to the scheme, whether each element is a dynamic object is judged according to the corresponding element positions in the image frames of the image data file under the same monitoring view angle at different time points, and in addition, the identification result of the detection neural network is combined to assist in definition, namely, the dynamic object is defined as a person or a carrier, and the dynamic object is not defined in advance, and the dynamic object is secondarily defined through the movement of the positions in different image frames, so that the problem of poor monitoring feedback effect caused by incomplete definition of the dynamic object in the crane monitoring process is avoided.
In this scheme S03, according to real-time operation information and pose information of a crane and a dynamic object positioning result generated in real time, acquiring relative position data of the crane and the dynamic object, and starting an active braking unit or a redundant braking unit of the crane according to a preset condition according to the relative position data to intervene in the operation of the starter and/or perform movement early warning or movement intervention on the dynamic object includes:
s031, acquiring real-time operation information and pose information of a crane, and defining coordinates corresponding to the pose information as:
Q i =(X i ,Y i ,Z i )
wherein Q is i The method comprises the steps that (i) the position coordinates of a positioning unit on a crane boom, a balance arm, a load trolley, a lifting hook and a suspended object in a three-dimensional digital twin model of a crane are preset numbers corresponding to the positioning unit on the crane boom, the balance arm, the load trolley, the lifting hook and the suspended object;
s032, acquiring a real-time generated dynamic object positioning result, and defining the coordinates of the dynamic object as:
D j =(X j ,Y j ,Z j )
wherein D is j The method comprises the steps that the position coordinates of different dynamic objects in a three-dimensional digital twin model are defined, j is the ID of the different dynamic objects, and in addition, a datum point defined by the dynamic object coordinates is a preset geometric position of a contour positioned in an image frame;
S033, calculating relative position data of each part positioning unit of the crane and the dynamic object, wherein the formula is as follows:
S ijx =|X i -X j |
S ijy =|Y i -Y j |
S ijz =|Z i -Z j |
wherein S is ijx 、S ijy 、S ijy 、S ij The relative distance between the positioning units and the dynamic object in the x, y and z directions and the relative distance between the positioning units and the dynamic object in the three-dimensional space are respectively calculated by defining the position coordinates of different positioning units and the position coordinates of the dynamic object, and then the position relation between each movable part of the crane and the dynamic object is indirectly known, wherein the number of the positioning units on each movable part (a crane arm, a balance arm, a load trolley, a lifting hook and a suspended object) of the crane is not less than 3, in this form, the position judgment reliability can be improved, in addition, the position judgment reliability can also be improved by establishing a reference line (defining the outline of the crane), then the position relation between the coordinate position of the dynamic object and the position closest to the reference line is judged, but the mode needs to occupy higher calculation force resources, and the positioning units are more convenient by improving the density of the positioning units, and meanwhile, the positioning units are mostly reusable devices, so that the cost is relatively lower;
s034, comparing the dynamic object with a preset distance threshold according to the relative position data of each part of the crane,
(1) When the operation of the starter is interfered by an active braking unit or a redundant braking unit of the crane according to a preset condition and meanwhile, a moving early warning or moving interference is carried out on a dynamic object, in the scheme, the intermittent participation operation of the redundant braking unit can be realized by setting the operation participation frequency of the active braking unit and the redundant braking unit, for example, the 21 st redundant braking unit is involved in braking through switching after the active braking unit is involved in 20 times, and then is switched back, in this way, the problem that the redundant braking unit suddenly needs to participate in the operation and fails after long-term 'falling asleep' can be avoided, namely, the daily sampling inspection effect can be achieved by intermittently starting the redundant braking unit to operate, and at the moment, the state of the redundant braking system can be more comprehensively recorded by recording the braking parameters of the intermittent operation and the intervention operation of the redundant braking system;
(2) When the moving pre-warning or moving intervention is performed on the dynamic object, the moving pre-warning or moving intervention is performed on the dynamic object when the moving pre-warning or moving intervention is performed on the dynamic object and the moving pre-warning or moving intervention is performed on the dynamic object;
(3) When the relative position data is larger than a preset second threshold value and smaller than or equal to a preset third threshold value, acquiring the relative position data of the dynamic object and each part of the crane at the last preset time point, comparing, and when the relative position data is reduced, carrying out movement early warning on the dynamic object;
The first threshold, the second threshold and the third threshold are sequentially increased, the moving early warning mode is to send out photoelectric alarms, and the moving intervention mode is to set roadblock.
The conditions corresponding to the above (2) and (3) are that the dynamic object is in a position range capable of being intervened to avoid too close to the crane, so that danger can be avoided in advance through early warning and mobile intervention, and additional working risks caused by frequent braking of the crane, such as shaking caused by inertia of suspended objects, mechanical parts and parts matched abrasion caused by equipment braking, and the like, are avoided.
On the basis of fig. 1 and fig. 2, and further referring to fig. 3, the solution of this embodiment further includes:
s04, according to the dynamic object positioning result generated in the preset time, estimating the action track of the dynamic object in the future preset time, and generating a dynamic object action track prediction result;
s05, estimating the action track of the crane in the future preset time according to the running information and the pose information of the crane in the preset time, and generating a crane running track prediction result;
s06, acquiring a crane running track prediction result and a dynamic object running track prediction result, dynamically judging the relative positions of the crane and the dynamic object within a preset time, and generating a predicted position judgment result;
S07, according to the judgment result of the predicted position, starting an active braking unit or a redundant braking unit of the crane to intervene in the operation of the starter and/or to perform mobile early warning or mobile intervention on the dynamic object.
As a preferred implementation choice, the dynamic object in this solution is preferably a moving object on the ground of a construction site.
In the operation monitoring method according to the present embodiment S04, according to a dynamic object positioning result generated in a preset time, the step of estimating a motion track of a dynamic object in a future preset time, the step of generating a dynamic object motion track prediction result includes:
s041, acquiring a dynamic object positioning result generated in a preset time, extracting coordinates of the dynamic object, converting coordinate two-dimensional processing of the dynamic object into two-dimensional coordinate information by taking the ground of a construction site as a two-dimensional coordinate plane, wherein the formula is as follows:
D j ’=(X j ,Y j )
wherein D is j ' projecting position coordinates of a dynamic object in a three-dimensional digital twin model to a two-dimensional coordinate plane with the ground of a construction site as a two-dimensional coordinate plane, and j is the ID of different dynamic objects;
s042, labeling two-dimensional coordinate information which is generated in preset time and corresponds to the two-dimensional processing of the dynamic object positioning result in a two-dimensional coordinate system, sequentially connecting the two-dimensional coordinate information to form a two-dimensional coordinate curve, constructing trend lines to generate a plurality of mathematical models matched with the trend lines, and selecting a prediction model with a correlation coefficient meeting preset requirements;
S043, calculating the moving speed V of the dynamic object according to the two-dimensional coordinate information of the dynamic object at different time points, and calculating the movable distance R of the dynamic object by combining the future time point T to be predicted, wherein R=VT;
s044, combining with the diagram 4, obtaining a prediction model, taking the tail end of the curve as the center of the circle, and establishing the circle with the radius of R as the possible position range of the dynamic object at the time point T to obtain the action track prediction result of the dynamic object.
In this scheme, since the dynamic objects mostly walk on the ground or a fixed platform of the construction site, in order to improve the calculation efficiency, the scheme only extracts the x-axis and y-axis position information of the dynamic objects to calculate the action track thereof, and the S042 builds the mathematical model to predict the possible area range by means of the mathematical curve when the predicted track time point is at the time point when the positioning result of the dynamic objects is not fed back, for example, the predicted area where the mark 2 in fig. 4 is located, and then combines the movable area of the dynamic objects to assist in predicting the possible area range.
In the present solution S5, according to operation information and pose information of a crane within a preset time, predicting a movement track of the crane within a future preset time, generating a crane operation track prediction result includes:
S051, acquiring pose information of the crane within preset time, and generating track information of the crane within the corresponding preset time;
s052, acquiring running information of a current crane, acquiring running speed information of a load trolley on a crane arm and rotating speed information of a crane rotating tower body, taking the running speed information and the rotating speed information as fixed parameters, calculating positions of the crane arm, a balance arm, the load trolley, a lifting hook and a suspended object of the crane at a future time point T by combining current pose information of the crane, comparing the pose information of the crane at the future time point T with the pose information of the current crane, and setting a movement track range between the pose information as a crane running track prediction result.
The step 06 of obtaining a crane running track prediction result and a dynamic object running track prediction result, dynamically judging the relative positions of the crane and the dynamic object within a preset time, and generating a predicted position judgment result includes:
s061, acquiring a crane running track prediction result and a dynamic object running track prediction result;
s062, projecting the position of the suspended object in the predicted result of the crane running track to a two-dimensional coordinate plane of the ground of a construction site, and then dynamically calculating the relative spacing S between the suspended object and a dynamic object in a preset time;
S063, comparing the relative distance S with a preset threshold value according to the relative distance S, and generating a predicted position judgment result.
The scheme mainly aims at avoiding the situation that the suspended object of the crane possibly moves from the position right above the construction ground dynamic object in the moving process, and avoiding potential safety hazards caused by the fact that the suspended object moves from the position right above the dynamic object, especially a person.
According to the scheme S07, according to the predicted position judgment result, starting the active braking unit or the redundant braking unit of the crane to intervene in the operation of the starter and/or to perform mobile early warning or mobile intervention on the dynamic object includes:
acquiring a predicted position judgment result, and outputting a first instruction when the predicted position judgment result points to a preset area above the dynamic object when the relative spacing S is smaller than a preset threshold value, or outputting a second instruction when the suspended object passes through the preset area above the dynamic object;
according to the first instruction, an active braking unit or a redundant braking unit of the crane is started to intervene in the operation of the starter and/or to perform movement early warning or movement intervention on the dynamic object.
In the above scheme, the intermittent participation operation of the redundant brake units can be realized by setting the operation participation frequency of the main brake unit and the redundant brake unit, for example, after the active brake unit intervenes 20 times, the 21 st redundant brake unit intervenes to brake and then switches back, in this way, the problem that the redundant brake unit suddenly needs to intervene to participate in operation after long-term 'sleep', and malfunctions can be avoided, that is, the effect of daily spot check can be achieved by intermittently starting the redundant brake unit to operate, and at the moment, the state of the redundant brake system can be more comprehensively recorded by recording the switching intermittence and the brake parameters of the redundant brake system during the intervention operation.
In the aspect of early warning and intervention, the moving early warning mode is to send out a photoelectric alarm, and the moving intervention mode is to set up a roadblock.
With reference to fig. 5, based on the foregoing solution, this embodiment further provides a crane anti-collision person redundancy system, where the crane has a main brake unit and a power drive unit, where the crane anti-collision person redundancy system is loaded with the crane operation monitoring method described above, where the dynamic object includes a person, and where the crane anti-collision person redundancy system includes:
the positioning units are a plurality of lifting arms, balance arms, load-carrying trolleys, lifting hooks and suspended articles which are arranged on the crane;
the starting induction unit is used for inducing a work starting signal of the crane;
the operation monitoring unit is used for acquiring operation information and pose information of the crane in real time;
the image monitoring unit is used for capturing images of an open-air area in a preset range of a construction site where the crane is located, and generating a monitoring image;
the neural network unit is used for positioning the dynamic object in the monitoring image in real time according to the monitoring image and generating a dynamic object positioning result;
the data processing unit is used for acquiring the relative position data of the crane and the dynamic object according to the real-time running information and the pose information of the crane and the dynamic object positioning result generated in real time, and outputting an intervention instruction according to the relative position data and a preset condition;
The redundant braking unit is used for braking the crane;
the brake switching unit is used for switching the braking of the main braking unit and the redundant braking unit to work and intervene the crane;
the command receiving unit is used for acquiring the intervention command and starting an active braking unit or a redundant braking unit of the crane to intervene in the operation of the starter according to the intervention command.
In addition, each functional unit in each embodiment of the present invention may be integrated in one processing unit, each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in essence or a part contributing to the prior art or all or part of the technical solution in the form of a software product stored in a storage medium, including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) or a processor (processor) to execute all or part of the steps of the methods of the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The foregoing description is only a partial embodiment of the present invention, and is not intended to limit the scope of the present invention, and all equivalent devices or equivalent processes using the descriptions and the drawings of the present invention or directly or indirectly applied to other related technical fields are included in the scope of the present invention.
Claims (10)
1. A crane operation monitoring method having a main brake unit and a redundant brake unit, and a brake switching unit for switching operation interventions of the main brake unit and the redundant brake unit, characterized by comprising:
responding to a work starting signal of the crane, and acquiring running information and pose information of the crane in real time;
responding to a work starting signal of the crane, and carrying out real-time positioning on a dynamic object in an open air area of a preset range of a construction site where the crane is positioned, so as to generate a dynamic object positioning result;
according to the real-time running information and pose information of the crane and the real-time generated dynamic object positioning result, the relative position data of the crane and the dynamic object are obtained, and an active braking unit or a redundant braking unit of the crane is started according to the relative position data and a preset condition to intervene in the running of the starter and/or to perform movement early warning or movement intervention on the dynamic object.
2. The crane operation monitoring method according to claim 1, further comprising:
according to the dynamic object positioning result generated in the preset time, predicting the action track of the dynamic object in the future preset time to generate a dynamic object action track prediction result;
according to the running information and pose information of the crane in the preset time, predicting the action track of the crane in the future preset time, and generating a crane running track prediction result;
acquiring a crane running track prediction result and a dynamic object running track prediction result, dynamically judging the relative positions of the crane and the dynamic object within a preset time, and generating a predicted position judgment result;
and according to the predicted position judgment result, starting an active braking unit or a redundant braking unit of the crane to intervene in the operation of the starter and/or to perform movement early warning or movement intervention on the dynamic object.
3. The crane operation monitoring method according to claim 2, wherein the crane is a tower crane, and the crane operation information includes: travelling speed information of a loading trolley on a crane arm, rotation speed information of a crane rotary tower body, lifting speed information of a crane lifting hook and load information;
The pose information of the crane comprises the following steps: the crane comprises boom position information, balance arm position information, position information of a load trolley on the boom, position information of a lifting hook and position information of a suspended object on the lifting hook, wherein a plurality of positioning units which are mutually spaced and used for marking positions are arranged on the boom, the balance arm, the load trolley, the lifting hook and the suspended object of the crane, and the positioning units on the boom, the balance arm, the load trolley, the lifting hook and the suspended object are distributed at intervals along the length direction of the positioning units.
4. The crane operation monitoring method according to claim 3, wherein a construction site where the crane is located is provided with a plurality of image capturing units, and images captured by the plurality of image capturing units cover an open area within a preset range of the construction site;
responding to a work starting signal of the crane, carrying out real-time positioning on a dynamic object in an open air area of a preset range of a construction site where the crane is located, and generating a dynamic object positioning result comprises the following steps:
the image shooting unit responds to a work starting signal of the crane, performs image shooting on an open air area in a preset range of a construction site where the crane is located, and generates an image data file;
Acquiring image data files generated at different times, selecting an initial reference image data file according to preset conditions, then deriving an image frame from the initial reference image data file, positioning, identifying and marking elements in the image frame through a trained neural network, and generating baseline reference data;
the method comprises the steps of calling image data files generated after initial reference of the image data files according to preset time intervals, respectively deriving image frames, positioning, identifying and marking elements in the image frames through a trained neural network, and determining dynamic objects in the image frames by combining reference data;
constructing a three-dimensional digital twin model corresponding to a construction site where a crane is located, defining the ground where the construction site is located as an x-axis plane, defining the y-axis plane in the model, defining the z-axis plane as a vertical direction, selecting a preset position as a reference origin (0, 0), constructing elements in an image data file into the three-dimensional digital twin model in a corresponding digital simulation mode according to the reference data and the determined dynamic object, obtaining dynamic object coordinate data correspondingly, and setting the dynamic object coordinate data as a dynamic object positioning result, wherein the dynamic object and the non-dynamic object in the three-dimensional digital twin model have different rendering strategies and marks.
5. The crane operation monitoring method according to claim 4, wherein elements in the reference data corresponding image frames are each marked with a unique ID and a recognition result, the recognition result including: when generating basic reference data, performing secondary definition on elements in an image according to a recognition result to obtain a dynamic object and a non-dynamic object;
the method comprises the steps of calling image data files generated after initial reference of the image data files according to preset time intervals, respectively deriving image frames, positioning, identifying and marking elements in the image frames through a trained neural network, and determining dynamic objects in the image frames by combining reference data, wherein the steps of:
the method comprises the steps of calling image data files generated after an initial reference image data file according to preset time intervals, and then respectively guiding out image frames;
positioning, identifying and marking elements in the image frame through the trained neural network, comparing the elements with elements in the reference data, judging the moving condition of the same elements in the image frame, and redefining a non-dynamic object with changed position in the image frame as a dynamic object;
And collecting information of elements defined as dynamic objects in all the image data, and finishing the determination of the dynamic objects.
6. The crane operation monitoring method according to claim 5, wherein the acquiring the relative position data of the crane and the dynamic object according to the real-time operation information and pose information of the crane and the real-time generated dynamic object positioning result, and the starting the active braking unit or the redundant braking unit of the crane according to the relative position data to intervene in the operation of the starter and/or perform movement early warning or movement intervention on the dynamic object according to the preset condition comprises:
acquiring real-time running information and pose information of the crane, and defining coordinates corresponding to the pose information as:
Q i =(X i ,Y i ,Z i )
wherein Q is i Is a lifting arm, a balance arm, a load trolley and a lifting hook of a craneThe position coordinates of the positioning units on the suspended object in the three-dimensional digital twin model are i preset numbers corresponding to the positioning units on the lifting arm, the balance arm, the load trolley, the lifting hook and the suspended object;
the method comprises the steps of obtaining a dynamic object positioning result generated in real time, and defining the coordinates of a dynamic object as:
D j =(X j ,Y j ,Z j )
wherein D is j The method comprises the steps that the position coordinates of different dynamic objects in a three-dimensional digital twin model are defined, j is the ID of the different dynamic objects, and in addition, a datum point defined by the dynamic object coordinates is a preset geometric position of a contour positioned in an image frame;
Calculating the relative position data of each part positioning unit of the crane and the dynamic object, wherein the formula is as follows:
S ijx =|X i -X j |
S ijy =|Y i -Y j |
S ihz =|Z i -Z j |
wherein S is ijx 、S ijy 、S ijy 、S ij The relative spacing between the positioning unit and the dynamic object in the x, y and z directions on each part of the crane and the relative spacing in the three-dimensional space are respectively;
comparing the relative position data of each part of the dynamic object and the crane with a preset distance threshold value, and starting an active braking unit or a redundant braking unit of the crane to intervene in the running of the starter according to preset conditions when the relative position data is smaller than or equal to a preset first threshold value, and meanwhile, performing movement early warning or movement intervention on the dynamic object;
when the moving pre-warning or moving intervention is performed on the dynamic object, the moving pre-warning or moving intervention is performed on the dynamic object when the moving pre-warning or moving intervention is performed on the dynamic object and the moving pre-warning or moving intervention is performed on the dynamic object;
when the relative position data is larger than a preset second threshold value and smaller than or equal to a preset third threshold value, acquiring the relative position data of the dynamic object and each part of the crane at the last preset time point, comparing, and when the relative position data is reduced, carrying out movement early warning on the dynamic object;
the first threshold, the second threshold and the third threshold are sequentially increased, the moving early warning mode is to send out photoelectric alarms, and the moving intervention mode is to set roadblock.
7. A crane operation monitoring method as claimed in claim 6, characterized in that,
in the operation monitoring method, according to a dynamic object positioning result generated in a preset time, a motion track of a dynamic object in a future preset time is estimated, and the generation of a dynamic object motion track prediction result comprises the following steps:
the method comprises the steps of obtaining a dynamic object positioning result generated in a preset time, extracting coordinates of the dynamic object, converting coordinate two-dimensional processing of the dynamic object into two-dimensional coordinate information by taking the ground of a construction site as a two-dimensional coordinate plane, wherein the formula is as follows:
D j ’=(X j ,Y j )
wherein D is j ' projecting position coordinates of a dynamic object in a three-dimensional digital twin model to a two-dimensional coordinate plane with the ground of a construction site as a two-dimensional coordinate plane, and j is the ID of different dynamic objects;
labeling two-dimensional coordinate information which is generated in preset time and corresponds to the two-dimensional processing of the dynamic object positioning result in a two-dimensional coordinate system, sequentially connecting the two-dimensional coordinate information to form a two-dimensional coordinate curve, constructing trend lines to generate a plurality of mathematical models matched with the two-dimensional coordinate information, and selecting a prediction model with a correlation coefficient meeting preset requirements;
calculating the moving speed V of the dynamic object according to the two-dimensional coordinate information of the dynamic object at different time points, and calculating the movable distance R of the dynamic object by combining the future time point T to be predicted, wherein R=VT;
Obtaining a prediction model, taking the tail end of a curve of the prediction model as a circle center, and establishing a circle with the radius of R as a possible position range of a dynamic object at a time point T to obtain a dynamic object action track prediction result;
in the operation monitoring method, according to operation information and pose information of a crane in preset time, a motion track of the crane in future preset time is estimated, and the generation of a crane operation track prediction result comprises the following steps:
acquiring pose information of the crane within preset time, and generating track information of the crane within corresponding preset time;
acquiring running information of a current crane, calling running speed information of a load trolley on a crane arm and rotating speed information of a crane rotating tower body, taking the running speed information and the rotating speed information as fixed parameters, calculating positions of the crane arm, a balance arm, the load trolley, a lifting hook and a suspended object at a future time point T by combining current pose information of the crane, comparing the pose information of the crane with the pose information of the current crane at the future time point T, and setting a movement track range between the pose information as a crane running track prediction result.
8. The crane operation monitoring method according to claim 7, wherein the dynamic object is a moving object on the ground of a construction site;
In the operation monitoring method, obtaining a crane operation track prediction result and a dynamic object action track prediction result, dynamically judging the relative positions of a crane and a dynamic object in preset time, and generating a prediction position judgment result comprises the following steps:
acquiring a crane running track prediction result and a dynamic object running track prediction result;
projecting the position of the suspended object in the predicted result of the crane running track to a two-dimensional coordinate plane of the ground where the construction site is located, and then dynamically calculating the relative spacing S between the suspended object and the dynamic object within preset time;
comparing the relative distance S with a preset threshold value according to the relative distance S to generate a predicted position judgment result;
in the operation monitoring method, according to the judgment result of the predicted position, starting an active braking unit or a redundant braking unit of the crane to intervene in the operation of the starter and/or to perform mobile early warning or mobile intervention on a dynamic object comprises the following steps:
acquiring a predicted position judgment result, and outputting a first instruction when the predicted position judgment result points to a preset area above the dynamic object when the relative spacing S is smaller than a preset threshold value, or outputting a second instruction when the suspended object passes through the preset area above the dynamic object;
According to the first instruction, an active braking unit or a redundant braking unit of the crane is started to intervene in the operation of the starter and/or to perform movement early warning or movement intervention on the dynamic object.
9. Crane anti-collision human redundancy system, the crane having a main brake unit and a power drive unit, characterized in that it is loaded with a crane operation monitoring method according to one of claims 1 to 8, the dynamic object comprising a human, comprising:
the positioning units are a plurality of lifting arms, balance arms, load-carrying trolleys, lifting hooks and suspended articles which are arranged on the crane;
the starting induction unit is used for inducing a work starting signal of the crane;
the operation monitoring unit is used for acquiring operation information and pose information of the crane in real time;
the image monitoring unit is used for capturing images of an open-air area in a preset range of a construction site where the crane is located, and generating a monitoring image;
the neural network unit is used for positioning the dynamic object in the monitoring image in real time according to the monitoring image and generating a dynamic object positioning result;
the data processing unit is used for acquiring the relative position data of the crane and the dynamic object according to the real-time running information and the pose information of the crane and the dynamic object positioning result generated in real time, and outputting an intervention instruction according to the relative position data and a preset condition;
The redundant braking unit is used for braking the crane;
the brake switching unit is used for switching the braking of the main braking unit and the redundant braking unit to work and intervene the crane;
the command receiving unit is used for acquiring the intervention command and starting an active braking unit or a redundant braking unit of the crane to intervene in the operation of the starter according to the intervention command.
10. A computer-readable storage medium, characterized by: the storage medium stores at least one instruction, at least one program, a code set, or an instruction set, and the at least one instruction, the at least one program, the code set, or the instruction set is loaded by a processor and executed to implement the crane operation monitoring method according to one of claims 1 to 8.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202310111346.8A CN116253248B (en) | 2023-02-13 | 2023-02-13 | Crane operation monitoring method, crane anti-collision human redundancy system and storage medium |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202310111346.8A CN116253248B (en) | 2023-02-13 | 2023-02-13 | Crane operation monitoring method, crane anti-collision human redundancy system and storage medium |
Publications (2)
Publication Number | Publication Date |
---|---|
CN116253248A true CN116253248A (en) | 2023-06-13 |
CN116253248B CN116253248B (en) | 2023-10-03 |
Family
ID=86678831
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN202310111346.8A Active CN116253248B (en) | 2023-02-13 | 2023-02-13 | Crane operation monitoring method, crane anti-collision human redundancy system and storage medium |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN116253248B (en) |
Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN118052441A (en) * | 2024-04-15 | 2024-05-17 | 山东奥深智能工程有限公司 | Intelligent community management method and system based on Internet of things |
Citations (10)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN111063026A (en) * | 2019-12-26 | 2020-04-24 | 南京悠淼科技有限公司 | Intelligent production process accurate modeling simulation system and method based on digital twins |
CN111709973A (en) * | 2020-06-16 | 2020-09-25 | 北京百度网讯科技有限公司 | Target tracking method, device, equipment and storage medium |
CN114549766A (en) * | 2022-04-24 | 2022-05-27 | 成都纵横自动化技术股份有限公司 | Real-time AR visualization method, device, equipment and storage medium |
KR20220087688A (en) * | 2020-12-18 | 2022-06-27 | 한국과학기술원 | Geo-spacial data estimation method of moving object based on 360 camera and digital twin and the system thereof |
CN114821257A (en) * | 2022-04-26 | 2022-07-29 | 中国科学院大学 | Intelligent processing method, device and equipment for video stream and natural language in navigation |
CN115100387A (en) * | 2022-07-08 | 2022-09-23 | 深圳云途数字创意科技有限公司 | Three-dimensional scene efficient visual editing method and equipment based on digital twins |
CN115268254A (en) * | 2022-08-04 | 2022-11-01 | 江苏省特种设备安全监督检验研究院 | Method, device and system for distributing reliability redundancy of control system |
CN115303946A (en) * | 2022-09-16 | 2022-11-08 | 江苏省特种设备安全监督检验研究院 | Digital twin-based tower crane work monitoring method and system |
CN115457479A (en) * | 2022-09-28 | 2022-12-09 | 江苏省特种设备安全监督检验研究院 | Crane operation monitoring method and system based on digital twinning |
KR20230004280A (en) * | 2021-06-30 | 2023-01-06 | 옥재윤 | System for tracking motion using deep learning technic |
-
2023
- 2023-02-13 CN CN202310111346.8A patent/CN116253248B/en active Active
Patent Citations (10)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN111063026A (en) * | 2019-12-26 | 2020-04-24 | 南京悠淼科技有限公司 | Intelligent production process accurate modeling simulation system and method based on digital twins |
CN111709973A (en) * | 2020-06-16 | 2020-09-25 | 北京百度网讯科技有限公司 | Target tracking method, device, equipment and storage medium |
KR20220087688A (en) * | 2020-12-18 | 2022-06-27 | 한국과학기술원 | Geo-spacial data estimation method of moving object based on 360 camera and digital twin and the system thereof |
KR20230004280A (en) * | 2021-06-30 | 2023-01-06 | 옥재윤 | System for tracking motion using deep learning technic |
CN114549766A (en) * | 2022-04-24 | 2022-05-27 | 成都纵横自动化技术股份有限公司 | Real-time AR visualization method, device, equipment and storage medium |
CN114821257A (en) * | 2022-04-26 | 2022-07-29 | 中国科学院大学 | Intelligent processing method, device and equipment for video stream and natural language in navigation |
CN115100387A (en) * | 2022-07-08 | 2022-09-23 | 深圳云途数字创意科技有限公司 | Three-dimensional scene efficient visual editing method and equipment based on digital twins |
CN115268254A (en) * | 2022-08-04 | 2022-11-01 | 江苏省特种设备安全监督检验研究院 | Method, device and system for distributing reliability redundancy of control system |
CN115303946A (en) * | 2022-09-16 | 2022-11-08 | 江苏省特种设备安全监督检验研究院 | Digital twin-based tower crane work monitoring method and system |
CN115457479A (en) * | 2022-09-28 | 2022-12-09 | 江苏省特种设备安全监督检验研究院 | Crane operation monitoring method and system based on digital twinning |
Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN118052441A (en) * | 2024-04-15 | 2024-05-17 | 山东奥深智能工程有限公司 | Intelligent community management method and system based on Internet of things |
Also Published As
Publication number | Publication date |
---|---|
CN116253248B (en) | 2023-10-03 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN115303946B (en) | Digital twinning-based tower crane operation monitoring method and system | |
US20210040713A1 (en) | System and method for determining work of work vehicle, and method for producing trained model | |
JP2013131100A (en) | Number of persons prediction method, number of persons prediction device, movable robot, and program | |
CN113469115B (en) | Method and device for outputting information | |
JP2020093890A (en) | Crane work monitoring system, crane work monitoring method, dangerous state determination device, and program | |
CN116253248B (en) | Crane operation monitoring method, crane anti-collision human redundancy system and storage medium | |
CN117533956A (en) | Crane hoisting operation safety monitoring and early warning method and system | |
CN111879308A (en) | Intelligent tower crane safety monitoring system based on pose perception technology and implementation method | |
CN113269008B (en) | Pedestrian track prediction method and device, electronic equipment and storage medium | |
WO2017062079A2 (en) | Device and method for detecting non-visible content in a non-content manner | |
US12024837B2 (en) | Railway weed control vehicle | |
CN117238100A (en) | Intelligent monitoring method and system for warehouse safety based on image recognition | |
CN114757218B (en) | Bar information identification method, device, equipment and medium | |
CN112001936B (en) | Visual positioning processing method and device, electronic equipment and storage medium | |
CN113781564B (en) | Steel coil material point cloud filtering method and crown block control system based on same | |
CN116051493A (en) | Contact net suspension state monitoring method, device, equipment and storage medium | |
CN115215221A (en) | Tower crane and control method, control device and controller thereof | |
CN114120583B (en) | Driving safety early warning device based on machine vision | |
CN118270655A (en) | Digital twinning-based tower crane operation monitoring method and application thereof | |
CN115941909B (en) | Driving safety monitoring system, method and device | |
CN116873772A (en) | Crane running track control method and application thereof | |
CN117208772A (en) | Portal crane safety intelligent early warning method and early warning system based on image recognition | |
JP7440009B2 (en) | Crane monitoring device and method and overhead crane | |
CN117690189B (en) | Charging station dangerous behavior identification method and monitoring system based on artificial intelligence | |
US11983891B2 (en) | Moving target tracking device, moving target tracking method, moving target tracking system, learning device, and program |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
GR01 | Patent grant | ||
GR01 | Patent grant |