CN116022673A - Tower crane driving assisting system based on cloud edge cooperative technology - Google Patents
Tower crane driving assisting system based on cloud edge cooperative technology Download PDFInfo
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Abstract
The invention provides a tower crane auxiliary driving system based on cloud edge cooperative technology, which comprises an industrial control computer module, a tower crane pose sensing module, a radar-based anti-collision module, a lifting hook visualization module, a fault diagnosis acquisition module, a driver behavior monitoring module, an edge computing system and an industrial center cloud data platform, wherein the industrial control computer module is used for acquiring the position and the pose of a tower crane; through cloud edge cooperation, the advantages of cloud computing and edge computing are fully integrated, and the method is a key for digitalization and intellectualization of the tower crane. Through the omnidirectional monitoring to the tower crane including the driver to provide auxiliary driving function, guarantee tower crane and driver whole journey work in the safe situation, greatly reduced the danger of tower crane work. According to the cloud edge collaborative optimization method, cloud edge collaborative is combined with powerful resource capacity of cloud computing and ultra-low time delay characteristics of edge computing, and the goal of collaborative optimization is achieved.
Description
Technical Field
The invention relates to the technical field of tower crane construction, in particular to a tower crane auxiliary driving system based on cloud edge cooperative technology.
Background
The tower crane (tower crane for short) is the most commonly used hoisting equipment on the building site, and the characteristics of large working range, flexible lifting height and the like greatly improve the construction work efficiency, but various safety accidents caused by high-altitude operation are frequent, the casualty rate is extremely high, and great life and property loss is easily caused. How to ensure the safety while the tower crane operates efficiently and avoid the accident occurrence is a problem which needs to be solved in the building industry.
In the wind gap era of digital transformation of engineering machinery at present, a domestic tower crane safety system is still growed in the level of the traditional primary internet of things, an anti-collision method still stays in passive calculation according to coordinates, false alarm is serious, efficiency is greatly reduced, functions are incomplete, and a series of functions of detecting abnormal behaviors of people, diagnosing remote faults and the like are lacked.
Aiming at the current situation, a set of auxiliary driving system with comprehensive safety and efficiency considered by functional consideration is needed in the tower crane industry, and the auxiliary driving system can be used for monitoring the basic state of the tower crane, visualizing a lifting hook, and identifying fatigue and judging abnormal behaviors of a driver.
Disclosure of Invention
The invention aims to: aiming at the defects of the prior art, the invention provides a tower crane auxiliary driving system based on cloud edge cooperative technology, provides a tower crane auxiliary driving system based on cloud edge cooperative technology and hardware equipment thereof, introduces a brand new generation encoder and nine-axis sensor and performs redundancy algorithm verification, adopts an active anti-collision algorithm based on radar and pose parameter data fusion, combines with advanced technologies such as wireless lifting hook visualization, remote fault diagnosis, driver identification, driver abnormal behavior early warning, cloud data multiplexing calculation and the like, and has convenient and reliable overall operation, thereby realizing high-efficiency, high-safety and high-intellectualization operation of the tower crane.
The system comprises an industrial control computer module, a tower crane pose sensing module, a radar-based anti-collision module, a lifting hook visualization module, a fault diagnosis acquisition module, a driver behavior monitoring module, an edge computing system and an industrial center cloud data platform;
the system comprises a tower crane pose sensing module, a radar-based anti-collision module, a lifting hook visualization module, a fault diagnosis acquisition module and a driver behavior monitoring module, wherein the tower crane pose sensing module, the radar-based anti-collision module, the lifting hook visualization module, the fault diagnosis acquisition module and the driver behavior monitoring module are all connected to a computer module in parallel, the computer module is connected to an edge computing system, and the edge computing system is in communication connection with an industrial center cloud data platform.
The industrial control computer module includes: the system comprises an industrial control computer, an input signal conversion module, a local data storage module, a weak current signal output unit, a 4G communication module, a wireless network bridge receiving module and a high-brightness resistance touch display screen;
the input signal conversion module, the local data storage module, the weak current signal output unit, the 4G communication module and the high-brightness resistance touch display screen are connected and expanded on the periphery of the industrial control computer in a wired mode and are arranged in the cab; the wireless network bridge receiving module is connected in a wired mode and is arranged at the root of the crane boom to receive video data from the lifting hook visualization module;
the tower crane pose sensing module comprises:
the lifting height encoder is used for collecting the lifting height value of the lifting hook and is arranged at the root of the lifting winch shaft;
the trolley amplitude changing encoder is used for acquiring amplitude values of the amplitude changing trolley and is arranged at the root of the amplitude changing winch shaft;
the nine-axis sensor is used for collecting the rotation angle value of the tower crane and is arranged at the coaxial position of the rotation center;
the wind speed sensor is used for collecting real-time wind speed values at the height of the tower body and is arranged outside the cab;
the weight sensor is used for collecting the weight value of the hoisted goods and is arranged at the fixed pulley of the hoisting steel cable;
the inclination sensor is used for collecting real-time inclination values of the tower body and is arranged at the coaxial position of the rotation center;
the radar-based anti-collision module comprises 6 laser radars, wherein the installation positions are respectively arranged on an arm end and an arm support and are connected to an industrial control computer through an Ethernet twisted pair, one laser radar is respectively arranged at the balance arm end and the crane arm end, and the forward direction of the laser radars is outwards along the extension line of the arm support; the four laser radars are arranged on the arm frame, 2 laser radars are respectively arranged on three equal dividing points of the arm frame, and the positive direction is vertical to the arm frame outwards.
The lifting hook visualization module comprises a gunshot camera, a lithium battery module, a wireless network bridge transmitting module, a wireless charging receiving module and a wireless charging transmitting module, wherein the gunshot camera, the lithium battery module, the wireless network bridge transmitting module and the wireless charging receiving module are all arranged at the position of the amplitude-variable trolley through wired connection, and the direction of the gunshot camera is downward; the wireless charging transmitting module is arranged at the root of the crane boom, and charges the lithium battery module when the amplitude-variable trolley returns to the root of the crane boom.
The fault diagnosis acquisition module comprises a PLC expansion module and a frequency converter expansion module, wherein the PLC expansion module and the frequency converter expansion module are both installed in a tower crane electrical cabinet and are connected to an industrial control computer through wires. The PLC represents Programmable Logic Controller, programmable logic controller.
The driver behavior monitoring module comprises a USB wide-angle camera, is installed in a cab and is connected to an industrial control computer through a USB interface in a wired mode.
The input signal conversion module is used for integrating various sensor data, PLC data and frequency converter data into a data bus and inputting the data into the industrial control computer.
The local data storage module is used for storing local end data in real time, and comprises:
basic sensor data, including real-time tower crane lifting height, tower crane amplitude, tower crane rotation angle, tower crane lifting weight, tower crane lifting moment, tower crane inclination angle, wind speed, amplitude real-time speed, lifting real-time speed and rotation real-time speed, are used for carrying out real-time data display in a tower crane cab to assist a driver to master the posture of the tower crane, carrying out tower crane alarming or stopping operation on values exceeding a safety range, and carrying out remote operation state monitoring of the tower crane in an industrial center cloud data platform;
the operation data of the driver in the tower crane PLC comprises handle gear data and electrical equipment state data, wherein the handle gear data reflects the operation process of lifting, amplitude-changing and rotating of the tower crane by the driver, and is used for judging whether the driver performs illegal operations such as slamming and returning, and the like, and the electrical equipment state data reflects whether the operation of a circuit breaker in a tower crane electric control cabinet is normal or not, so that the maintenance process of maintenance personnel maintenance is simplified;
real-time state data of the lifting frequency converter, the rotary frequency converter and the variable amplitude frequency converter comprise real-time current, and are used for monitoring working states of the frequency converter and the motor and judging whether overload work exists or not;
if the video data of the personnel behavior and action expression of the wide-angle camera of the cab are analyzed in real time, fatigue expressions such as yawning, inattention and the like of the driver are analyzed, reminding and alarming are carried out;
the real-time scanning data of the laser radar sensor comprises the distance between a collider and a crane arm positioning point of the tower crane, and is used for carrying out collision early warning reminding or stopping operation;
the video data of the camera of the gun camera is visualized by the lifting hook and used for analyzing the overlook size of the suspended object and the surrounding environment of the suspended object, and reminding and alarming are carried out if the possibility of personnel mistouching the surrounding of the suspended object occurs.
The weak current output unit is connected to an electrical cabinet of the tower crane through a wire, comprehensively judging according to basic sensor data, driver operation data in a PLC (programmable logic controller) of the tower crane, real-time state data of a lifting frequency converter, a rotary frequency converter, a variable amplitude frequency converter, video data of a personnel behavior and action expression of a wide-angle camera of a cab, real-time scanning data of a laser radar sensor and video data of a visual gun camera of a lifting hook, and if one item of data reaches a dangerous area, stopping operation of a part of a mechanism or the whole machine of the tower crane;
the 4G communication module utilizes wireless communication to upload local database information in the local data storage module to an edge computing system of the local area, and transmits information to an industrial center cloud data platform while carrying out pose information interaction of the local tower crane, the cloud data platform can carry out online monitoring on various information of the tower crane, and the data storage of the full life cycle is carried out for carrying out the data storage of the lifting working condition and the service life of the tower crane from factory use to obsolete of the tower crane of a certain model;
the wireless network bridge receiving module is used for receiving the hook visual video information from the wireless network bridge transmitting module end in a near-field wireless communication mode;
the high-brightness resistance touch display screen adopts a long screen with the proportion of 21:9, is used for displaying various real-time data in an industrial control computer, assisting a driver in high-efficiency operation, providing tower crane pose and anti-collision protection in a visual field blind area, displaying real-time state information (such as lifting height, amplitude length, rotation angle, lifting weight, tower body inclination angle, wind speed grade, lifting moment, lifting characteristic real-time curve and the like) of a tower crane, lifting hook visual video information, radar-based anti-collision information and multi-tower crane rotation top view, and displaying 3D tower crane animation;
based on radar anti-collision information such as the conditions of primary and secondary early warning areas, the multi-tower crane rotates a top view;
the radar anti-collision module forms an early warning area around the arm support by using the laser radar, and performs anti-collision early warning when a collision object approaches the tower crane and enters the early warning area formed by the laser radar.
The lifting hook visualization module focuses and enlarges the picture in real time along with the change of the lifting height of the goods through a real-time zooming technology, transmits the collected video signals to an industrial control computer and displays the video signals through a high-brightness resistance touch display screen, and gives a driver a view of lifting the goods when a view blind area condition occurs;
the fault diagnosis acquisition module is used for acquiring handle gear data and electrical equipment state data in the PLC, and real-time current and frequency conversion information of the lifting, amplitude changing and rotating frequency converter;
the driver behavior monitoring module collects video data through a USB wide-angle camera in a cab, on one hand, the face fatigue characteristics are extracted and identified by utilizing a visual discrimination algorithm, the face and body behaviors of a driver are monitored in real time, distraction behaviors of the driver such as mobile phone playing or fatigue behaviors such as dozing are reminded or alarmed, on the other hand, face identity information of an operator is loaded into an industrial control computer in advance through an industrial center cloud data platform, and identity verification of the driver is carried out before a tower crane is started;
the edge computing system consists of edge computing nodes in each tower crane group region, the tower crane pose data interaction in the region is carried out through the edge computing nodes arranged in the tower crane groups to realize tower crane group anti-collision, the classified integration of the data is realized at the edge nodes to improve the transmission speed, lighten the cloud pressure, and the processed tower crane group data are sent to an industrial center cloud data platform;
the industrial center cloud data platform can perform remote online monitoring, perform tower crane historical data on remote equipment, perform real-time data access and remotely complete data loading modification. Carrying out data mining analysis on full life cycle data generated in the period from factory use to elimination of scrapping of a certain type of tower crane, namely carrying out big data processing and analysis, establishing a lifting working condition and service life related model of the tower crane, finishing training and upgrading an algorithm model, pushing the updated model to an industrial control computer to update equipment of the same type, realizing real-time service life prediction of the tower crane, analyzing the full life cycle of the old tower crane in the process, and providing support for maintenance and service decision of the tower crane by utilizing data sharing;
failure of the edge computing nodes in the area can not affect the work and data collection state of the tower crane group outside the area, and stored information on the industrial center cloud data platform can not be lost;
the industrial center cloud data platform is updated or fails without interference to the operation of the edge computing nodes, and information interaction between the tower crane and the tower crane is uninterrupted.
Cloud edge cooperation is to connect cloud and edge, extend cloud end capacity to the edge node close to equipment, edge calculation is closer to the tower crane, delay is lower, efficiency is higher, cloud end and edge side data are linked, and remote control, data analysis, intelligent decision and the like of the edge node are achieved. Cloud computing is good at, and edge computing has the advantages of high instantaneity, wide connection, data security, privacy protection and the like, and is suitable for real-time and short-period data processing and analysis.
The invention has the following beneficial effects:
through cloud edge cooperation, the advantages of cloud computing and edge computing are fully integrated, and the method is a key for digitalization and intellectualization of the tower crane. Through the omnidirectional monitoring to the tower crane including the driver to provide auxiliary driving function, guarantee tower crane and driver whole journey work in the safe situation, greatly reduced the danger of tower crane work. According to the cloud edge collaborative optimization method, cloud edge collaborative is combined with powerful resource capacity of cloud computing and ultra-low time delay characteristics of edge computing, and the goal of collaborative optimization is achieved.
Drawings
The foregoing and/or other advantages of the invention will become more apparent from the following detailed description of the invention when taken in conjunction with the accompanying drawings and detailed description.
Fig. 1 is a schematic diagram of the arrangement of the various hardware of the present invention on a tower crane.
Fig. 2 is a schematic diagram of the system composition of the present invention.
Detailed Description
Fig. 1 is a marked illustration:
the system comprises a laser radar point 1, a lifting encoder point 2, an inclination sensor point 3, a nine-axis sensor point 4, an anemometer point 5, a weight sensor point 6, a wireless charging transmitting end point 7, a laser radar point 8, a luffing encoder point 9, a wireless charging receiving end point 10, a gunshot camera point 11, a wireless network bridge transmitting end point 12, a laser radar point 13, a laser radar point 14, a weak current output unit point 15, a wireless network bridge receiving end point 16, an industrial control computer point 17, a USB wide-angle camera point 18 and a high-brightness resistance touch display screen point 19;
FIG. 2 is a schematic diagram of the system components of the present invention;
fig. 2 label description:
the industrial control computer module 100, the industrial control computer 110, the input signal conversion module 120, the local data storage module 130, the weak current output unit 140, the 4G communication module 150, the wireless network bridge receiving module 160, the high-brightness resistance touch display screen 170, the pose sensing module 200, the wind speed sensor 210, the lifting encoder 220, the weight sensor 230, the amplitude changing encoder 240, the inclination angle sensor 250, the nine-axis sensor 260, the radar anti-collision module 300, the lifting hook visualization module 400, the gunshot camera 410, the wireless network bridge transmitting module 420, the lithium battery module 430, the wireless charging receiving module 440, the wireless charging transmitting module 450, the fault diagnosis module 500, the driver behavior detection module 600, the USB wide-angle camera 610, the edge computing system 700 and the industrial center cloud data platform 800.
As shown in fig. 1 and 2.
The invention provides a tower crane auxiliary driving system based on cloud edge cooperative technology, which comprises an industrial control computer module 100, a tower crane pose sensing module 200, a radar-based anti-collision module 300, a lifting hook visualization module 400, a fault diagnosis acquisition module 500, a driver behavior monitoring module 600, an edge computing system 700 and an industrial center cloud data platform 800;
the tower crane pose sensing module 200, the radar-based anti-collision module 300, the lifting hook visualization module 400, the fault diagnosis acquisition module 500 and the driver behavior monitoring module 600 are all connected to the computer module 100 in parallel, the computer module 100 is connected to the edge computing system 700, and the edge computing system 700 is in communication connection with the industrial center cloud data platform 800.
The industrial control computer module 100 includes: an industrial control computer (for short, industrial control computer) 110, an input signal conversion module 120, a local data storage module 130, a weak current signal output unit 140, a 4G communication module 150, a wireless network bridge receiving module 160 and a high-brightness resistance touch display screen 170;
the input signal conversion module 120, the local data storage module 130, the weak current signal output unit 140, the 4G communication module 150, and the high brightness resistance touch display screen 170 are all connected and expanded around the industrial control computer 110 in a wired manner and are arranged in the cab; the wireless network bridge receiving module 160 is connected in a wired manner and is installed at the root of the boom to receive video data from the hook visualization module 400;
the tower crane pose sensing module 200 comprises a lifting height encoder 220, wherein the lifting height encoder is used for collecting lifting height values of a lifting hook and is arranged at the root of a lifting winch shaft; the trolley amplitude-changing encoder 240 is used for collecting amplitude values of the amplitude-changing trolley and is arranged at the root of the amplitude-changing winch shaft; the nine-axis sensor 260 is used for collecting the rotation angle value of the tower crane and is arranged at the coaxial position of the rotation center; the wind speed sensor 210 is used for collecting real-time wind speed values at the height of the tower body and is arranged outside the cab; the weight sensor 230 is used for collecting the weight value of the hoisted goods and is arranged at the fixed pulley of the hoisting steel cable; the inclination sensor 250 is used for acquiring real-time inclination values of the tower body and is arranged at the coaxial position of the rotation center;
the radar-based anti-collision module 300 includes 6 lidars 310 mounted at respective positions on the arm end and the arm rest, connected to the industrial control computer 110 via an ethernet twisted pair, wherein:
the balance arm end and the crane arm end are respectively provided with one, and the positive direction is outwards along the extension line of the arm support.
The four arms are respectively arranged on the three bisectors of the arm support, 2 equal bisectors are respectively arranged on each bisector, and the positive direction is vertical to the arm support outwards.
The hook visualization module 400 comprises a gunshot camera 410, a lithium battery module 430, a wireless network bridge emission module 420, a wireless charging receiving module 440 and a wireless charging emission module 450, wherein the gunshot camera 410, the lithium battery module 430, the wireless network bridge emission module 420 and the wireless charging receiving module 440 are all installed at the position of the luffing trolley through wired connection, and the direction of the gunshot camera 410 is downward; the wireless charging and transmitting module 450 is arranged at the root of the crane boom, and charges the lithium battery module 430 when the amplitude-variable trolley returns to the root of the crane boom;
the fault diagnosis acquisition module 500 comprises a PLC expansion module 510 and a frequency converter expansion module 520, is installed in a tower crane electrical cabinet and is connected to the industrial control computer 110 through a wire;
the PLC is Programmable Logic Controller and is a programmable logic controller.
The driver behavior monitoring module 600 is a USB wide-angle camera 610 installed in the cab and connected to the industrial control computer 110 by a USB interface;
in the industrial control computer module 100:
the signal conversion module 120 is configured to integrate various sensor data, PLC data, and inverter data into a data bus, and input the data into the industrial control computer 110 at an extremely high frequency;
the local data storage module 130 is configured to store local data in real time, including:
basic sensor data such as real-time tower crane lifting height, tower crane amplitude, tower crane rotation angle, tower crane lifting weight, tower crane lifting moment, tower crane inclination angle, wind speed, amplitude real-time speed, lifting real-time speed and rotation real-time speed are used for displaying real-time data in a tower crane cab to assist a driver to master the posture of the tower crane, carrying out tower crane alarming or stopping operation on values exceeding a safety range, and carrying out remote operation state monitoring on the tower crane in an industrial center cloud data platform;
the operation data of the driver in the tower crane PLC, such as handle gear data and electrical equipment state data, wherein the handle gear data reflects the operation process of lifting, amplitude-changing and rotating of the tower crane by the driver, so that whether the driver performs illegal operations such as slamming and returning can be judged, the electrical equipment state data reflects whether the operation of a circuit breaker in a power control cabinet of the tower crane is normal, and the maintenance process of maintenance personnel maintenance can be simplified;
real-time state data such as real-time current of the lifting frequency converter, the rotary frequency converter and the variable amplitude frequency converter are used for monitoring working states of the frequency converter and the motor and whether overload work exists or not;
if the video data of the personnel behavior and action expression of the wide-angle camera of the cab are analyzed in real time, fatigue expressions such as yawning, inattention and the like of the driver are analyzed, and reminding and alarming are carried out;
real-time scanning data of the laser radar sensor such as the distance between a collider and a crane arm positioning point of the tower crane can be used for collision early warning reminding or stopping operation;
the video data of the camera of the gun camera can be visualized by the lifting hook, so that the overlook size of the suspended object can be analyzed, and the surrounding environment of the suspended object can be reminded and alarmed if the possibility of personnel mistouch around the suspended object occurs.
The weak current output unit 140 is connected to an electrical cabinet of the tower crane through a wire, and comprehensively judges according to basic sensor data, driver operation data in the PLC of the tower crane, real-time state data of a lifting frequency converter, a turning frequency converter, a variable amplitude frequency converter, video data of a personnel behavior and action expression of a wide-angle camera of a cab, real-time scanning data of a laser radar sensor and video data of a visual gun camera of a lifting hook, namely, one item of data reaches a dangerous area to perform shutdown operation of a part of a mechanism or the whole machine of the tower crane;
the 4G communication module 150 uploads the local database information in the local data storage module 130 to the edge computing node 710 of the local area by using wireless communication, performs pose information interaction of the local tower crane and simultaneously transmits the information to the industrial center cloud data platform 800, and the front end of the cloud data platform can perform online monitoring of each item of information of the tower crane, and performs full life cycle data storage for a certain model of tower crane from factory use to obsolete use so as to correlate the lifting working condition with the service life of the tower crane;
the wireless bridge receiving module 160 receives the hook visual video information from the wireless bridge transmitting end 420 through a near field wireless communication mode;
the high-brightness resistive touch display 170 adopts a long screen with a ratio of 21:9, is used for displaying various real-time data of 110 in an industrial control computer, assisting a driver to efficiently work, and providing tower crane pose and anti-collision protection in a blind area of a visual field, and comprises the following display contents:
real-time state information of the tower crane such as lifting height, amplitude length, rotation angle, lifting weight, tower body inclination angle, wind speed grade, lifting moment, lifting characteristic real-time curve and the like, and displaying 3D tower crane animation;
the hook visualizes video information;
based on radar anti-collision information such as the conditions of primary and secondary early warning areas, the multi-tower crane rotates a top view;
the radar anti-collision module 300 forms an early warning area around the arm support by using a laser radar, and performs anti-collision early warning when a collision object approaches the tower crane and enters the early warning area formed by the laser radar.
The hook visualization module 400 focuses and enlarges the picture in real time along with the change of the lifting height of the goods through a real-time enlarging and zooming technology, transmits the collected video signal to an industrial control computer and displays the video signal on the high-brightness resistance touch display screen, and gives a driver a view of lifting the goods when a view blind area condition occurs;
the fault diagnosis acquisition module 500 is used for acquiring handle gear data and electrical equipment state data in the PLC, and real-time current and variable frequency information of the lifting, variable-amplitude and rotary frequency converter. The handle gear data reflects the operation process of lifting, amplitude-changing and rotating of the tower crane by a driver, whether the driver performs illegal operations such as slapping and returning can be judged, the state data of the electrical equipment reflects whether the operation of a circuit breaker in the electric control cabinet of the tower crane is normal, and the maintenance process of maintenance personnel maintenance can be simplified. Real-time state data such as real-time current of the lifting frequency converter, the rotary frequency converter and the variable amplitude frequency converter are used for monitoring working states of the frequency converter and the motor and whether overload work exists or not;
the driver behavior monitoring module 600 collects video data through the USB wide-angle camera 610 in the driver cab, on one hand, the extraction and recognition of facial fatigue characteristics are realized by using a visual discrimination algorithm, the facial and body behaviors of the driver are monitored in real time, the distraction behaviors of the driver such as mobile phone playing or fatigue behaviors such as dozing off are reminded or alarmed, on the other hand, the face identity information of the operator is loaded into the industrial control computer 110 in advance through the industrial center cloud data platform 800, and the identity verification of the driver is performed before the tower crane is started;
according to the present invention, the edge computing system 700 is preferably composed of edge computing nodes 710 in each tower group region, and performs inter-regional tower pose data interaction through the edge computing nodes 710 arranged in the tower group to realize tower group collision prevention, and performs classification integration on data at the edge nodes to improve transmission speed, reduce cloud pressure, and send the processed tower group data to the industrial center cloud data platform 800;
according to the invention, the industrial center cloud data platform 800 can perform remote online monitoring, perform tower crane historical data on remote equipment, perform real-time data access and remotely complete data loading modification. Carrying out tower crane data mining analysis on full life cycle data generated in the period from factory use to elimination of scrapping of a certain type of tower crane, namely carrying out big data processing and analysis, establishing a lifting working condition and service life related model of the tower crane, completing training and upgrading of an algorithm model, pushing the updated model to an industrial control computer 110 to update equipment of the same type, realizing real-time life prediction of the tower crane, analyzing the full life cycle of the old tower crane in the process, and providing support for maintenance and service decision of the tower crane by utilizing data sharing;
the failure of the edge computing node 710 in a certain area does not affect the work and data collection state of the tower clusters outside the area, and the stored information of the industrial center cloud data platform center 800 is not lost;
the upgrade or failure of the industrial center cloud data platform 800 does not interfere with the operation of the edge computing node 710, and the information interaction between the tower crane and the tower crane is uninterrupted;
cloud edge cooperation is to connect cloud and edge, extend cloud capacity to edge nodes 710 close to equipment, enable edge calculation to be closer to a tower crane, enable delay to be lower, enable efficiency to be higher, enable cloud and edge side data to be linked, and enable remote control, data analysis, intelligent decision making and the like of the edge nodes to be achieved. Cloud computing is good at, and edge computing has the advantages of high instantaneity, wide connection, data security, privacy protection and the like, and is suitable for real-time and short-period data processing and analysis.
In a specific implementation, the application provides a computer storage medium and a corresponding data processing unit, wherein the computer storage medium can store a computer program, and the computer program can run the invention content of the tower crane auxiliary driving system based on the cloud edge cooperative technology and part or all of the steps in each embodiment when being executed by the data processing unit. The storage medium may be a magnetic disk, an optical disk, a read-only memory (ROM), a random-access memory (random access memory, RAM), or the like.
It will be apparent to those skilled in the art that the technical solutions in the embodiments of the present invention may be implemented by means of a computer program and its corresponding general hardware platform. Based on such understanding, the technical solutions in the embodiments of the present invention may be embodied essentially or in the form of a computer program, i.e. a software product, which may be stored in a storage medium, and include several instructions to cause a device (which may be a personal computer, a server, a single-chip microcomputer MUU or a network device, etc.) including a data processing unit to perform the methods described in the embodiments or some parts of the embodiments of the present invention.
The invention provides a tower crane driving assisting system based on cloud edge cooperative technology, which has a plurality of methods and approaches for realizing the technical scheme, the above description is only a preferred embodiment of the invention, and it should be noted that, for a person skilled in the art, a plurality of improvements and modifications can be made without departing from the principle of the invention, and the improvements and modifications should also be regarded as the protection scope of the invention. The components not explicitly described in this embodiment can be implemented by using the prior art.
Claims (10)
1. The tower crane driving assisting system based on the cloud edge cooperative technology is characterized by comprising an industrial control computer module (100), a tower crane pose sensing module (200), a radar-based anti-collision module (300), a lifting hook visualization module (400), a fault diagnosis acquisition module (500), a driver behavior monitoring module (600), an edge computing system (700) and an industrial center cloud data platform (800).
The intelligent monitoring system comprises a tower crane pose sensing module (200), a radar-based anti-collision module (300), a lifting hook visualization module (400), a fault diagnosis acquisition module (500) and a driver behavior monitoring module (600), wherein the tower crane pose sensing module, the lifting hook visualization module, the fault diagnosis acquisition module and the driver behavior monitoring module (600) are all connected to a computer module (100) in parallel, the computer module (100) is connected to an edge computing system (700), and the edge computing system (700) is in communication connection with an industrial center cloud data platform (800).
2. The system of claim 1, wherein the industrial control computer module (100) comprises: the system comprises an industrial control computer (110), an input signal conversion module (120), a local data storage module (130), a weak current signal output unit (140), a 4G communication module (150), a wireless network bridge receiving module (160) and a high-brightness resistance touch display screen (170);
the input signal conversion module (120), the local data storage module (130), the weak current signal output unit (140), the 4G communication module (150) and the high-brightness resistance touch display screen (170) are connected and expanded on the periphery of the industrial control computer (110) in a wired mode and are arranged in a cab; the wireless network bridge receiving module (160) is connected in a wired mode and is arranged at the root of the lifting arm so as to receive video data from the lifting hook visualization module (400).
3. The system of claim 2, wherein the tower pose awareness module (200) comprises:
a lifting height encoder (220) for collecting the lifting height value of the lifting hook and being arranged at the root of the lifting winch shaft;
the trolley amplitude-changing encoder (240) is used for acquiring amplitude values of the amplitude-changing trolley and is arranged at the root of the amplitude-changing winch shaft;
the nine-axis sensor (260) is used for collecting the rotation angle value of the tower crane and is arranged at the coaxial position of the rotation center;
the wind speed sensor (210) is used for collecting real-time wind speed values at the height of the tower body and is arranged outside the cab;
the weight sensor (230) is used for collecting the weight value of the hoisted goods and is arranged at the fixed pulley of the hoisting steel cable;
and the inclination angle sensor (250) is used for acquiring real-time inclination values of the tower body and is arranged at the coaxial position of the rotation center.
4. A system according to claim 3, wherein the radar-based anti-collision module (300) comprises 6 lidars mounted at respective arm ends and arm supports, connected to the industrial control computer by means of ethernet twisted pair wires, wherein the balance arm end and the crane arm end are each mounted with one lidar, the forward direction being outwards along the extension of the arm supports; the four laser radars are arranged on the arm frame, 2 laser radars are respectively arranged on three equal dividing points of the arm frame, and the positive direction is vertical to the arm frame outwards.
5. The system of claim 4, wherein the hook visualization module (400) comprises a gunshot camera (410), a lithium battery module (430), a wireless network bridge transmitting module (420), a wireless charging receiving module (440), and a wireless charging transmitting module (450), wherein the gunshot camera (410), the lithium battery module (430), the wireless network bridge transmitting module (420), and the wireless charging receiving module (440) are all installed at the luffing trolley through wired connection, and the gunshot camera (410) is downward; the wireless charging transmitting module (420) is arranged at the boom root of the crane boom, and charges the lithium battery module (430) when the variable-amplitude trolley returns to the boom root.
6. The system of claim 5, wherein the fault diagnosis acquisition module (500) comprises a PLC extension module (510) and a frequency converter extension module (520), the PLC extension module (510) and the frequency converter extension module (520) are both installed in a tower crane electrical cabinet and connected to the industrial control computer (110) by wires.
7. The system of claim 6, wherein the driver behavior monitoring module (600) comprises a USB wide angle camera (610) mounted in the cab and wired to the industrial control computer (110) via a USB interface.
8. The system of claim 7, wherein the input signal conversion module (120) is configured to aggregate various sensor data, PLC data, and inverter data into a single data bus and input the data bus to the industrial control computer (110).
9. The system of claim 8, wherein the local data storage module (130) is configured to store local side data in real time, comprising:
basic sensor data, including real-time tower crane lifting height, tower crane amplitude, tower crane rotation angle, tower crane lifting weight, tower crane lifting moment, tower crane inclination angle, wind speed, amplitude real-time speed, lifting real-time speed and rotation real-time speed, are used for carrying out real-time data display in a tower crane cab to assist a driver to master the posture of the tower crane, carrying out tower crane alarming or stopping operation on values exceeding a safety range, and carrying out remote operation state monitoring of the tower crane in an industrial center cloud data platform;
the operation data of the driver in the tower crane PLC comprises handle gear data and electrical equipment state data, wherein the handle gear data reflects the operation process of lifting, amplitude-changing and rotating of the tower crane by the driver, and is used for judging whether the driver performs illegal operations such as slamming and returning, and the like, and the electrical equipment state data reflects whether the operation of a circuit breaker in a tower crane electric control cabinet is normal or not, so that the maintenance process of maintenance personnel maintenance is simplified;
real-time state data of the lifting frequency converter, the rotary frequency converter and the variable amplitude frequency converter comprise real-time current, and are used for monitoring working states of the frequency converter and the motor and judging whether overload work exists or not;
video data of the human behavior and action expression of the wide-angle camera of the cab are analyzed in real time, and if the driver has fatigue performance, reminding and alarming are carried out;
the real-time scanning data of the laser radar sensor comprises the distance between a collider and a crane arm positioning point of the tower crane, and is used for carrying out collision early warning reminding or stopping operation;
the video data of the camera of the gun camera is visualized by the lifting hook and used for analyzing the overlook size of the suspended object and the surrounding environment of the suspended object, and reminding and alarming are carried out if the possibility of personnel mistouching the surrounding of the suspended object occurs.
10. The system according to claim 9, wherein the weak current output unit (140) is connected to an electrical cabinet of the tower crane by a wire, and performs comprehensive judgment according to basic sensor data, driver operation data in the PLC of the tower crane, real-time status data of a lifting frequency converter, a turning frequency converter, a luffing frequency converter, video data of a human behavior and action expression of a wide-angle camera of a cab, real-time scanning data of a laser radar sensor, and video data of a visual camera of a hook gun crane, and performs a machine shutdown operation of a part of the tower crane or the whole machine if one item of data reaches a dangerous area;
the 4G communication module (150) utilizes wireless communication to upload local database information in the local data storage module (130) to the edge computing system (700) of the local area, and transmits information to the industrial center cloud data platform (800) when carrying out pose information interaction of the regional tower crane, and the cloud data platform (800) can carry out online monitoring on various information of the tower crane;
the wireless network bridge receiving module (160) is used for receiving the hook visual video information from the wireless network bridge transmitting module (420) through a near-field wireless communication mode;
the high-brightness resistance touch display screen (170) is used for displaying various real-time data in an industrial control computer, assisting a driver in operation, providing tower crane pose and anti-collision protection in a visual field blind area, displaying real-time state information of a tower crane, hook visual video information, radar-based anti-collision information and multi-tower crane rotation top view, and displaying 3D tower crane animation;
the radar anti-collision module (300) forms an early warning area around the arm support by utilizing a laser radar, and performs anti-collision early warning when a collision object approaches the tower crane and enters the early warning area formed by the laser radar;
the lifting hook visualization module (400) focuses and enlarges images in real time along with the change of lifting height of goods through a real-time zooming technology, transmits collected video signals to the industrial control computer (110) and displays the video signals through the high-brightness resistance touch display screen (170), and gives a driver a view of lifting the goods when a view blind area condition occurs;
the fault diagnosis acquisition module (500) is used for acquiring handle gear data and electrical equipment state data in the PLC, and real-time current and frequency conversion information of the lifting, amplitude-changing and rotation frequency converter;
the driver behavior monitoring module (600) collects video data through the USB wide-angle camera (610) in the cab, on one hand, the face fatigue characteristics of the driver are extracted and identified by utilizing a visual discrimination algorithm, the face and body behaviors of the driver are monitored in real time, the distraction behaviors of the driver such as mobile phone playing or fatigue behaviors such as dozing off are reminded or alarmed, on the other hand, the face identity information of the operator is loaded into an industrial control computer (110) in advance through the industrial center cloud data platform (800), and the identity verification of the driver is carried out before the tower crane is started;
the edge computing system (700) consists of edge computing nodes in each tower crane group area, tower crane pose data interaction in the area is carried out through the edge computing nodes arranged in the tower crane groups to realize tower crane anti-collision, classification integration of data is realized at the edge nodes to improve transmission speed, cloud pressure is relieved, and processed tower crane group data are sent to the industrial center cloud data platform (800);
the industrial center cloud data platform (800) can perform remote online monitoring, perform tower crane historical data on remote equipment, perform real-time data access and remotely complete data loading modification;
failure of the edge computing nodes in the area does not affect the work and data collection state of the tower clusters outside the area, and stored information on the industrial center cloud data platform (800) is not lost;
the industrial center cloud data platform (800) is updated or fails without interfering with the operation of the edge computing nodes, and information interaction between the tower crane and the tower crane is uninterrupted.
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310127423.9A CN116022673A (en) | 2023-02-17 | 2023-02-17 | Tower crane driving assisting system based on cloud edge cooperative technology |
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| Application Number | Priority Date | Filing Date | Title |
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| CN202310127423.9A CN116022673A (en) | 2023-02-17 | 2023-02-17 | Tower crane driving assisting system based on cloud edge cooperative technology |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116679726A (en) * | 2023-08-01 | 2023-09-01 | 山东中建众力设备租赁有限公司 | Unmanned tower crane autonomous decision-making system based on edge calculation |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116679726A (en) * | 2023-08-01 | 2023-09-01 | 山东中建众力设备租赁有限公司 | Unmanned tower crane autonomous decision-making system based on edge calculation |
| CN116679726B (en) * | 2023-08-01 | 2023-11-03 | 山东中建众力设备租赁有限公司 | Unmanned tower crane autonomous decision-making system based on edge calculation |
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Application publication date: 20230428 |