Compared with traditional cranes, intelligent cranes have artificial intelligence, which replaces or assists human mental labor on the basis of replacing human physical labor. By integrating sensors and intelligent decision-making software with cranes, sensing, analysis, reasoning, decision-making and control functions are achieved, enabling interaction and integration between humans, objects and machines, replacing manual on perception, decision-making, and execution, enabling cranes to adapt in different working environment. Its workflow is the same as that of traditional crane, but added intelligent control can replace human perception organs such as vision, hearing, smell, and limbs, replacing operator judgment to make corresponding actions, and complete recognition, perception, operation, and management during crane operation.
2. Key Technologies of Intelligent Crane
In the process of replacing the operator's perception, decision-making, and execution, cranes need to automatically perceive the position of the lifted object, automatically identify and verify the lifted object, automatically pick and place the lifted object, automatically select the running route, automatically optimize the running path and overcome the swing of the flexible lifting system, accurately start and stop the corresponding location for storing items, record and monitor the working status of their own equipment during automatic operation, automatically diagnose faults and alarm. Therefore, the artificial intelligence cranes needs to break through several key technologies.
2.1 Identification, verification, feedback, and information storage technology for lifting objects
According to the shape, packaging method, storage and transportation method of the lifted object, common lifted objects include: coils (steel coils, paper coils, film coils, etc.), boxes (containers, material boxes, transfer boxes, etc.), blocks (steel plates, steel billets, shield tunnel components, etc.), bundles (steel pipes, threads, etc.) Steel, rails, profiles, etc., reels (cables, coils, etc.), components (buckets, bags, etc.), pieces (rails, I-beams, H-beams, etc.).
The automatic recognition, inspection, and feedback of various status objects are standardized means of data coding, collection, identification management, and transmission, they are the foundation of intelligent cranes. This technology involves process of encoding, collecting, labeling, managing, and transmitting of items information data. It includes specific format information recognition technologies such as barcode recognition, RFID radio frequency recognition, speech recognition, optical character recognition, magnetic recognition, as well as image and graphic format information recognition technologies, biometric recognition information recognition technologies. The stored information after identification and inspection must have universality, uniqueness, stability, and non replicability.
wire rod imaging picture
deformed steel bar imaging picture
loose material imaging picture
loose material software picture
2.2 Space positioning technology
Although some high-end products have applied 3D positioning technology, but the positioning level is limited by the accumulated error of the entire system and cannot achieve high-precision positioning. At present, there are two types of commonly used positioning methods: one is relative address recognition, generally achieved by using rotary encoders, laser or radar ranging, visual recognition, and other methods; The other one is absolute address recognition, achieved usually by ausing position limit switches, coding cables (Gray bus), linear encoders, BPS barcode, gear rack, and real-time absolute address recognition radio, infrared, wireless radio frequency GPS and other methods.
With the advancement of wireless communication technology, the positioning accuracy of indoor wireless positioning technology is getting higher and higher, such as cellular positioning and Wi Fi, Bluetooth infrared, ultra wideband, RFID, and ultrasound in communication networks, it has gradually been applied in mechanical equipment positioning and promoting applications.
Crane positioning technology not only involves the appearance monitoring of the lifted object, vacancy detection, one-dimensional, two-dimensional, and three-dimensional identification and positioning methods of the actual storage location, but also involves the one-dimensional, two-dimensional, and three-dimensional identification and positioning methods of the crane's retrieval devices (hooks, forks, suction cups, grabs, grab buckets, etc.). Due to the large operating range of cranes, a single positioning method is difficult to achieve the required positioning accuracy, therefore, precise positioning in large areas and complex environments often adopts a comprehensive positioning technology of "relative proximity addressing+absolute positioning identification". Compared with simple absolute identification or relative identification positioning methods, it has more accuracy, stability, economy, lower requirements for civil engineering quality, and is more suitable for lifting equipment.
Working in harsh environments
2.3 Intelligent retrieval device
More than 95% of crane pick-up devices use hooks, which can only be manually lifted and hung to lift a specific type of item. The poor universality restricts the improvement of the automation level of lifting and handling equipment. In the process of lifting and handling different items such as loose materials, boxes, bundles, and rolls, intelligent cranes need to be equipped with automatic retrieval devices or intelligent lifting tools, including automatic removing/hanging hooks, C-shaped hooks, electromagnetic suction chunks, vacuum suction chunks, clamps, hanging beams, box type lifting tool tanks, grab buckets, grabbing tools, etc. Developing automatic retrieval devices or intelligent lifting tools suitable for crane applications based on the status of various lifted items is the most crucial step in achieving intelligent crane access.
2.4 Path planning and electronic sway control technology for flexible lifting systems
Running path planning and sway control positioning control of flexible lifting systems are crucial conditions for achieving crane operation. During the operation of a crane, the acceleration and deceleration of cross travel and long travel, as well as the lifting and lowering of the load, can cause the load to swing back and forth, which not only affects the efficiency of the crane operation but also leads to accidents. At present, open-loop and closed-loop control technologies are commonly used to achieve crane path planning and sway control. The open-loop control methods mainly include input shaping based positioning sway control and trajectory planning based positioning sway control. There are many closed-loop control methods for implementing path planning and anti sway, such as feedback linearization, gain scheduling control, sliding mode control, predictive control, fuzzy control, neural network control, passive control, and other control methods.
For lifting and handling environments with fixed obstacle locations, static path planning can meet the requirements. However, when obstacles in the environment cannot be determined in advance or when multiple cranes are mixed for operation, it is necessary to use dynamic path planning methods to obtain a safe path in real-time online. Path planning for lifting and handling In recent years, scholars have proposed some effective planning algorithms for crane path planning, such as artificial potential field method, probabilistic landmark algorithm, fast random spanning tree algorithm, genetic algorithm, ant colony algorithm, etc. With the development of wireless mobile communication technology, sensors (gyroscopes, acceleration sensors, orientation sensors, etc.) will be installed on lifting equipment or retrieval devices to achieve three-dimensional positioning, path planning, and sway control based on the lifted object, which will be widely applied.
2.5 State detection and automatic fault diagnosis technology
State monitoring refers to understanding and mastering the operating status of equipment through certain channels; Fault diagnosis is based on the information obtained from state monitoring, combined with the working principle, structural characteristics, operating parameters, and historical conditions of the equipment, to analyze and predict possible faults, analyze and judge existing or ongoing faults, in order to determine the nature, category, degree, location, and trend of the faults. The significance of status monitoring and fault diagnosis lies in their effective containment of fault losses and equipment maintenance costs.
The commonly used monitoring parameters that need to be monitored during the monitoring process include lifting weight; lifting torque; lifting height/descent depth; traveling stroke, amplitude; long travel deviation and levelness; Wind speed; rotation angle; safe distance of traveling mechanism on the same or different rails; verticality of supporting legs; working time; calculation of working time; each working cycle, etc. Common monitoring states include motor status; Brake status; Frequency converter status; Wind resistant and anti slip state; Interlocking protection: door limit and traveling interlocking between mechanisms; Working condition setting status; The status of the power cable reel; Through hole state; Real time self detection system for video system, bridge stiffness, strength, etc.
2.6 Real time online monitoring and remote diagnosis technology
The system includes technologies such as sensor monitoring, real-time wireless transmission, data management, information inquiry, root cause analysis of faults, trend analysis, expert diagnosis, state prediction and prediction, and remote monitoring of the Internet of things. By installing monitoring gateways on existing devices and transmitting data through Wi Fi or 3G networks to collect operational status and fault conditions, remote monitoring and visual management can be achieved;Integrate the remote management system that comes with the new device and establish a unified device management platform; Integrate with asset maintenance management system to improve maintenance efficiency and equipment performance. Provide a networked emergency maintenance coordination mechanism, obtain real-time equipment status through wireless meter reading, automatically generate maintenance and inspection plans, and gradually achieve state based predictive maintenance based on data analysis. The predictive maintenance achieved through computer networks is based on condition monitoring and fault diagnosis technology, and is based on the actual condition of equipment. It is a maintenance system that formulates predictive maintenance plans according to production needs. Its goal is to achieve real-time parking, corresponding replacement, and maintenance of determined projects. From current fault maintenance and regular planned maintenance, to achieve future predictive maintenance, distinguish the authenticity of faults, determine the type, degree, and specific location of faults, and predict the trend of fault development.
Timely detect early signs of faults in order to take corresponding measures to avoid, slow down, and reduce the occurrence of major accidents; Once a fault occurs, it can automatically record the complete information of the fault process, so as to analyze the cause of the fault afterwards and avoid similar accidents from happening again; By analyzing the abnormal operation status of equipment, revealing the cause, degree, location, and trend of faults, providing scientific basis for online adjustment and shutdown maintenance of equipment, extending the operating cycle, and effectively curbing fault losses and equipment maintenance costs; Based on the information obtained from state monitoring, combined with the working principle, structural characteristics, operating parameters, and historical conditions of the equipment, analyzing and predicting possible faults can fully understand the performance of the equipment and provide strong evidence for improving design, manufacturing, and maintenance levels.
2.7 Monitoring and management of complete equipment
Based on the stacking forms and storage requirements of different items such as bulk materials, boxes, bundles, and rolls, combined with the key technologies of identification, positioning, access, and monitoring mentioned above, a monitoring and management system MWS for intelligent cranes has been developed, including interface subsystem, storage location inventory management subsystem, material identification subsystem, scheduling and crane operation subsystem, spatial positioning subsystem, etc., to achieve intelligent, efficient, and safe operation of cranes.
3. conclusion
The demand to various intelligent cranes in fields of intelligent manufacturing, intelligent logistics, and intelligent maintenance is expanding day by day, with broad application prospects. The above key technologies will be integrated into intelligent crane application solutions in the form of software, new products, new technologies, etc, forming a complete engineering equipment, applied in intelligent manufacturing fields, such as metallurgy, papermaking, and automobiles fields for station transportation, and logistics field for warehousing and handling.
The intelligent crane automatically completes the operation and process flow, and can monitor and record crane operating status in real time, providing higher work efficiency and lower operating costs. Intelligent monitoring and operating systems provide intelligent maintenance services for in-service lifting machinery, that is, through remote online detection, big data statistical analysis, predictive maintenance and remaining life assessment. The accumulated big data can provide data basis for the design of cranes, improve the overall cranes design level, and effectively and targetedly improve crane’s intrinsic safety and performance.
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deceleration of cross travel and long travel, as well as the lifting and lowering of the load, can cause the load to swing back and forth, which not only affects the efficiency of the crane operation but also leads to accidents. At present, open-loop and closed-loop control technologies are commonly used to achieve crane path planning and sway control. The open-loop control methods mainly include input shaping based positioning sway control and trajectory planning based positioning sway control. There are many closed-loop control methods for implementing path planning and anti sway, such as feedback linearization, gain scheduling control, sliding mode control, predictive control, fuzzy control, neural network control, passive control, and other control methods.
