Portal Crane Research Articles

A geometric model with stochastic error for abnormal motion detection of portal crane bucket grab

Abnormal swing angle detection of bucket grabs is crucial for efficient harbor operations. In this study, we develop a practically convenient swing angle detection method for crane operation, requiring only a single standard surveillance camera at the fly-jib head, without the need for sophisticated sensors or markers on the payload. Specifically, our algorithm takes the video images from the camera as input. Next, a fine-tuned ‘the fifth version of the You Only Look Once algorithm’ (YOLOv5) model is used to automatically detect the position of the bucket grab on the image plane. Subsequently, a novel geometric model is constructed, which takes the pixel position of the bucket grab, the steel rope length provided by the Programmable Logic Controller (PLC) system, and the optical lens information of the camera into consideration. The key parameters of this geometric model are statistically estimated by a novel iterative algorithm. Once the key parameters are estimated, the algorithm can automatically detect swing angles from video streams. Being analytically simple, the computation of our algorithm is fast, as it takes about 0.01 s to process one single image generated by the surveillance camera. Therefore, we are able to obtain an accurate and fast estimation of the swing angle of an operating crane in real-time applications. Simulation studies are conducted to validate the model and algorithm. Real video examples from Qingdao Seaport under various weather conditions are analyzed to demonstrate its practical performance.

Application and Realization of Fully Automatic Portal Crane

Application and Realization of Fully Automatic Portal Crane

Effects of Floating States on Collision Forces of Drifting Containers Caused by Solitary Wave Inundation

The overtopping-inundation process of a tsunami results in the collisions of drifting objects on the coast, which damage structures, thereby increasing the risk of collapse. This study conducted laboratory experiments on the collision between a drifting container caused by the overtopping-inundation process of a solitary wave and a fixed port crane’s leg. The movement trajectory and velocity of the container as well as the collision velocity by solitary wave inundation, were analyzed using motion analysis software. Overall, increasing solitary wave scale, collision velocity, and drifting object weight and decreased distance between the two objects tended to increase the collision force. However, different experiment results were also obtained due to pitching in objects that fully floated without bottom friction owing to the solitary wave bore. This resulted in line-to-surface collisions. Thus, surface-to-surface contact occurred under the incomplete floating condition owing to the difficulty because of interference with the bottom; however, the collision force decreased under complete floating conditions owing to line-to-surface contact. Therefore, the contact condition according to the floating behavior must be considered a parameter while predicting the collision forces of drifting objects. Thus, surface-to-surface contact occurred under the incomplete floating condition owing to the difficulty because of interference with the bottom; however, the collision force decreased under complete floating conditions owing to line-to-surface contact. Therefore, the contact condition according to the floating behavior must be considered a parameter while predicting the collision forces of drifting objects.

Characterization of dust emission during ore unloading and analysis of its influencing factors

Dry bulk terminals at ports generate dust in the process of ore loading / unloading and transfer, and these particulate matters disperse to the atmospheric environment causing pollution and endangering human health. This study focuses on the funnel unloading point of a portal crane at a port terminal, and the variation characteristics of dust emission under different mass flow rates, ambient wind speeds, and moisture contents are investigated. The microscopic features of ore powders, i.e., wetting time, contact angle, particle size, specific surface area and pore structure, as well as microscopic morphology, are also determined to explore the intrinsic mechanism between wettability, moisture content, and dust emission. The impact of mass flow rate, ambient wind speed, and moisture content on dust emission is evaluated by employing the orthogonal test range method and response surface method. The experimental data reveals that the dust at the unloading point is dominated by coarse particles of total suspended particulate (TSP), and increasing the moisture content effectively reduced the dust emissions, with a suppression efficiency of TSP > PM10 > PM2.5. The experimental results on the microscopic features of the ore powders indicate that the above difference is attributed to wettability, which weakens with diminishing particle diameter. It is also concluded that the wettability of Australian ore 1 is determined to be superior to bauxite 394. Therefore, Australian ore 1 exhibits an excellent dust suppression effect at a moisture content of 4% ∼ 5%, whereas bauxite 394 requires a moisture content of approximately 5% ∼ 7% to achieve the same dust suppression. By conducting the orthogonal test range method, the three factors on the dust emission, in descending order, are moisture content > ambient wind speed > mass flow rate. According to the response surface method, the optimal parameter combination is determined and the dust emission is minimized as 4.149 μg/s, which corresponds to 0.386 mg TSP/ton, with the conditions of mass flow rate 10.356 kg/s, ambient wind speed 4.289 m/s, moisture content 6.983%.

An improved algorithm for solving inverse problems of the dynamics of robotic devices at SCAS KIDYM

The paper presents the results of studies of an analytical algorithm for constructing a resolving system of linear equations to determine the driving forces and moments in the links of robotic devices of arbitrary structure during movement. This algorithm is implemented as an analytical algorithm in a special computer algebra system (SCAS) KiDyM, on the basis of which numerical calculations of the specified forces and moments are generated in the process of performing work processes, positioning mechanisms in the required positions, parking movements, etc. The KiDyM software package is used to solve mechanics problems of a wide class of discrete mechanical systems of arbitrary structure and type of motion for engineering and scientific calculations. A theoretical justification for the developed new approach, analytical and numerical proof of its effectiveness from the point of view of the process of automatically obtaining resolving equations, computational efficiency and accuracy of results are presented. The proposed algorithm is the result of the development of an algorithm that was previously implemented in SCAS KiDyM and was similar in purpose. Unlike the previously implemented algorithm, which generates a resolving system of equations after constructing the dynamic equations, the new algorithm is built into the process of generating dynamic equations - it sorts the model elements - inertial, dissipative, elastic and force elements of known forces and moments form the right side, and force elements with unknown forces and moments, they form a matrix of the left side of equations that solve the inverse problem of dynamics. The article gives a comparative analytical conclusion of one and another algorithm and shows the coincidence of the resulting equations. Also, using examples of calculations of the inverse problem of the dynamics of a portal crane and two 6-degree manipulators, the advantages of the new approach are shown.

Bearing Fault Diagnosis Method Based on Adversarial Transfer Learning for Imbalanced Samples of Portal Crane Drive Motor

Due to their unique structural design, portal cranes have been extensively utilized in bulk cargo and container terminals. The bearing fault of their drive motors is a critical issue that significantly impacts their operational efficiency. Moreover, the problem of imbalanced fault samples has a more pronounced influence on the application of novel fault diagnosis methods. To address this, the paper presents a new method called bidirectional gated recurrent domain adversarial transfer learning (BRDATL), specifically designed for imbalanced samples from portal cranes’ drive motor bearings. Initially, a bidirectional gated recurrent unit (Bi-GRU) is used as a feature extractor within the network to comprehensively extract features from both source and target domains. Building on this, a new Correlation Maximum Mean Discrepancy (CAMMD) method, integrating both Correlation Alignment (CORAL) and Maximum Mean Discrepancy (MMD), is proposed to guide the feature generator in providing domain-invariant features. Considering the real-time data characteristics of portal crane drive motor bearings, we adjusted the CWRU and XJTU-SY bearing datasets and conducted comparative experiments. The experimental results show that the accuracy of the proposed method is up to 99.5%, which is obviously higher than other methods. The presented fault diagnosis model provides a practical and theoretical framework for diagnosing faults in portal cranes’ field operation environments.

Vibration Analysis of the Damaged Bearing Unit of the Port Crane Lifting Mechanism

Vibration Analysis of the Damaged Bearing Unit of the Port Crane Lifting Mechanism

Development of an Optimal Port Crane Trajectory for Reduced Energy Consumption

This paper is concerned with the development of an optimal load-handling trajectory for port cranes. The objective is to minimize load cycle time and reduce energy consumption. Energetic macroscopic representation formalism is used to model a port crane load-handling mechanism. The crane model developed includes the mathematical model, the crane’s local control system, and a MATLAB/Simulink model for simulation. The particle swarm optimization algorithm is used to find the set of pareto optimal crane trajectories given the variation in crane size, ship size, and wind speed. Experimental validation of the crane model is conducted by comparing it with a real-world crane. Simulation results show that the optimal crane load trajectory is 38% faster and more productive than the nonoptimal crane load trajectory. Furthermore, the results show that the optimal trajectory reduces the cranes’ peak power and energy consumption by 36% when compared with the nonoptimal trajectory.

Modified Gradient Projection Neural Network for Multiset Constrained Optimization

To solve nonlinear optimization problems under multiple set constraints, a modified gradient projection neural network (MGPNN) is proposed and investigated. Different from existing approaches specialized for linear constrained optimizations, such as the gradient-based recurrent neural network or dynamic-parameter zeroing neural network, the MGPNN is intrinsically designed from the perspective of the multiple set constrained optimization (MSCO), which is a more generalized form for the linear constrained optimization. The MGPNN is able to efficiently and conveniently provide a feasible solution to the MSCO problem. Ultimately, compared with existing solution methods, numerical simulations and applications to the control of an underactuated portal crane system are provided for verifications of the robust stability and preponderance of the proposed MGPNN model.

Study on Stress Intensity Factor of the Pit-Crack Model for Portal Crane Girders

In shipbuilding gantry cranes in long-term service in the coastal humid salt-spray environment, the main beam is affected in many places by corrosion fatigue-formed corrosion pits, affecting the structural strength of the main beam. This paper focuses on the impact of corrosion-generated pits under the conditions of crack nucleation. Corrosion fatigue crack nucleation is a local damage evolution process and the stress intensity factor criterion is one of the critical conditions to discern whether a crack sprouts at the corrosion pit. This paper establishes a corrosion pit-crack model based on the overall finite element model of the portal crane, and uses ANSYS software to simulate the stress intensity factor under complex boundary conditions. The results show that the different sizes and depth-to-diameter ratio of the pits greatly affect the value of the stress intensity factor and the stress concentration phenomenon may be the main factor causing the emergence of cracks; the change in the size of the pits on the stress intensity factor is not obvious, but with the increase in the depth-to-diameter ratio of the pits, the stress intensity factor of the pit-crack model is significantly increased. According to the hypothesis of semi-ellipsoidal pitting, the relationship between the stress intensity factor and the stress concentration factor at the pit is proposed, and its calculation results are within 5% error compared with the finite element method, and it is found that the effect of the etch pit on the stress intensity factor is positively correlated with the stress concentration factor; with the increase in the etch pit depth–diameter ratio, the crack budding location changes with the change in the stress concentration location, and the crack is more likely to be generated from the shoulder of the etch pit when the depth–diameter ratio of etch pit exceeds 1.

Specimen Size Effect on the Tensile Properties of Rolled Steel of Long-Term-Operated Portal Crane.

This paper presents the research results on the mechanical behavior of the low-carbon rolled steel of a sea portal crane after a 33-year operation depending on the operational stresses and rolling direction in order to assess its serviceability. The tensile properties of steels were investigated using rectangular cross-section specimens with different thicknesses and the same width. Strength indicators were slightly dependent on the considered factors (operational conditions, the cutting direction, and thickness of specimens). However, a clear trend of higher ultimate strength for thinner specimens was noticed, especially in the case of more brittle material due to its operational degradation. Plasticity of the tested steel specimens was more sensitive to the influence of the above-mentioned factors than strength but less sensitive than impact toughness. Uniform elongation was slightly less for thinner specimens regardless of the investigated steel state or the orientation of specimens relative to the rolling direction. The post-necking elongation was lower for transversal specimens compared with longitudinal ones, and the effect was more significant when testing steel with the lowest brittle fracture resistance. Among the tensile properties, non-uniform elongation was demonstrated to be the most effective for assessing the operational changes in the state of rolled steels.

Detection of distributed and localized faults in rotating machines using periodically non-stationary covariance analysis of vibrations

The covariance structure for vibrations of the noising mechanism for a port crane and a wind turbine with gear tooth breakage are studied on the basis of their models in the form of periodically non-stationary random processes (PNRPs). The investigation is performed by the authors using PNRP statistical analysis methods. The estimations of the basic frequencies of the vibration’s deterministic components and the time changes of the power for the stochastic part (the PNRP variance) are the key issues of this analysis. In the present paper, the basic frequency estimators are obtained using the least squares technique which are characterized by the maximum of the signal-to-noise ratio as compared with techniques known in the literature. Using the basic frequency, values for the Fourier coefficients for the mean and covariance functions are calculated and the dependencies of the forenamed moment functions on time and lag are ascertained. The amplitude spectra of the deterministic oscillations and the time changes of the power of the stochastic part are presented. These spectra are considered as the symptomatic features of the mechanism’s state of health. It is revealed that the high-frequency modulation of PNRP carrier harmonics is narrow-band for both distributed and localized faults. Using bandpass filtering and Hilbert transform, the quadratures for each high-frequency component are separated and analyzed. It is shown that the auto- and cross-covariance structure of the high-frequency component quadratures characterizes the specific features of the different types of faults. Using the cross-covariance map for high-frequency components, the peculiarities of the bandpass filtering of vibrations for a damaged wind turbine’s gearbox as a PNRP’s is considered. It is shown that the filtering bandwidth cannot be narrower than 14 times the basic frequency. This bandwidth essentially exceeds that recommended in the literature (two to three times the basic frequency).

EVALUATION OF THE RELIABILITY OF «GANZ» PORTAL CRANE MECHANISMS

Portal cranes are widely used in various ports for transhipment operations. However, today in the river and sea ports of Ukraine, more than 88% of cranes have fulfilled the standard service life and continue to be operated. Since portal cranes are the main link in the technological process, therefore, the productivity of Port lines depends on their reliable and trouble-free operation. The analysis of statistical data shows that the processing and long-term operation of portal cranes in the mode of intense cyclic loading leads to the formation of fatigue defects and the subsequent failure of their components and accidents [1-9]. Therefore, ensuring safe and reliable operation is one of the main tasks in the design, modernization and operation of cranes. The analysis of works] showed that the reliability of portal crane mechanisms that have been soldered for more than 35 years in sea and river ports has not been sufficiently studied. For research, 24 identical Ganz cranes with a lifting capacity of 16 tons were selected, which operate in clamshell mode in sea and river ports. The analysis uses information contained in the respective maintenance and repair logs of the respective cranes from 2008 to 2021. Data analysis shows that the greatest number of failures is observed in the mechanisms of movement, lifting, changing the boom departure and metal structures of cranes. It should be noted that up to 75% of all time is spent on restoring the operation of reducers. The reasons for the failure of movement mechanisms are: wear of gears and shafts of gearboxes, destruction and wear of bearings in gearboxes, cracks in gearbox housings. The failures of the mechanisms for changing the reach of the boom are caused by wear of the teeth of the racks and gears, bearings and gear housings of the mechanism.

The methodical peculiarities of the investigation of portal crane rolled steels degradation

Rolled structural steels of port structures, operating under intensive cyclic loading, are particularly susceptible to the degradation of their mechanical properties. Advantages of the investigation of operational degradation of steels based not on fatigue strength characteristics, but on characteristics of resistance to brittle fracture using the example of determining the impact strength of longitudinal and transverse Charpy samples in relation to the rolling direction of sheet metal for 10 local areas at different structural nodes of portal crane are analyzed. This is caused to a great extend by micro-layering along the stretched fibers in the rolling direction of the rolled product. Accordingly, the mechanical properties of the metal become particularly sensitive to the direction of samples cutting in relation to the direction of rolling. Therefore, in order to evaluate the steel operational degradation it is recommended to use transverse samples in which the direction of micro-laayering coincides with the direction of rolling. Possible role of the marine environment in enhancing the degradation of steel due to its flooding properties is also considered in this paper.

Simulation of the operation of a non-linear control system for moving cargo by a gantry crane

The process of creating a mathematical model of a portal crane is considered. Two types of nonlinear controllers can be used to control this process. Numerical simulation of the operation of this system was carried out. A virtual physical model of a portal crane in the C++ language with using environment the Unreal Engine 4 was developed Keywords numerical simulation, mathematical model, nonlinear controller, control theory

Structural Strength Analysis and Stress Testing of Portal Crane based on Finite Element Method

In order to ensure the safety of the long-term service shipbuilding portal crane, this paper analyzes the stress distribution of the crane metal structure by using the finite element analysis method, which plays an auxiliary role in the crane safety assessment. The working condition at the most dangerous working position of the crane is selected as the stress test condition for analysis, and compared with the simulation calculation. The finite element calculation results show that the stress distribution of the whole machine is relatively reasonable. The overall stress is basically less than 100 MPa, and the maximum stress value is 131 MPa, which is less than the allowable stress value of the material. And through the comparison with the actual stress testing data, they are also basically consistent, and the structure of the crane can be used safely.

Stress analysis of gantry crane cylinder structure

By building three finite element analysis models for its four-bar metal structure under different amplitudes (the boom span is 13.5m, 22.5m and 34.5m), the relationship between stress, amplitude and load at key parts is established by linear interpolation method; At the same time, the relationship between the measured strain data of key parts and the load and amplitude is linearly fitted. The analysis and comparison between the finite element calculation data and the measured data are well verified. In order to provide a feasible analysis method for solving the working performance of four-bar linkage structure of portal crane. At the same time, it provides a more convenient method for the compilation of typical load, which is the important basic data for the calculation and analysis of residual fatigue life of later structures.

Mechanical Wits Used in the America Colonization: Engineering Assessment

The first European settlements in the new world faced technical issues with the help of the XVI century scientific advances. Besides briefly exposing the scientific and technological situation, this paper explores, with the help of reverse engineering, two singular mechanical wits representative of the technological advances introduced in America to overcome different problems. Firstly, a pump, based on an alternative movement system through crankshafts and pistons used against the continuous flooding suffered in the Ciudad de México valley. Although flooding remained a problem (it was solved in the XX century), hydraulic pumps were essential for continuous soil drainage. Secondly, a port crane for handling cannons, military devices, and construction materials during the Lima fortification in the XVII century. For both cases, reverse engineering, through engineering methods, Computer-Aided Design CAD programs, and additive manufacturing, provides virtual and/or tangible mockups that help to analyze and improve our knowledge about the dimensions, materials, and functions of used (and currently lost) mechanical systems during the American colonization.

Approach for the structural reliability analysis by the modified sensitivity model based on response surface function - Kriging model

The sensitivity analysis model is widely used to describe the impacts of condition parameters on structural reliability. However, the classical sensitivity analysis model is limited to the small number of influence parameters and has no high prediction accuracy. Integrating the response surface function - Kriging model with Sobol sensitivity algorithm, a revised sensitivity model is proposed in this paper. And the quantitative sensitivity analysis for the influence of condition parameters on structural reliability are achieved through combining the revised sensitivity model with the experimental design of coupling parameters, range verification, the multi-body dynamics analysis and the structural statics analysis. The proposed analysis model is mainly applied in large structures with multiple influence parameters. Finally, a typical port crane is adopted to verify the accuracy and effectiveness of the proposed model. The results reveal that among the multiple parameters, the biggest sensitivity influence is the trolley position, while the least one is the lifting speed. The average prediction accuracy of the quantitative structural reliability index for the influencing parameters is up to 95.91%. The revised sensitivity model enables the accurate assessment of structural relativity with plenty of coupling condition parameters.

Multisensor-Based Heavy Machine Faulty Identification Using Sparse Autoencoder-Based Feature Fusion and Deep Belief Network-Based Ensemble Learning

Faulty identification plays a vital role in the area of prognostic and the health management (PHM) of the industrial equipment which offers great support to the maintenance strategy decision. Owing to the complexity of the machine internal component-system structure, the precise prediction of the heavy machine is hard to be obtained, thus full of uncertainty. Moreover, even for a single component, the feature representation of the acquired conditional monitoring signal can be different due to the different deployment of the sensor location and environmental inference, causing difficulty in feature selection and uncertainty in faulty identification. In order to improve the model identification reliability, a novel hybrid machine faulty identification approach based on sparse autoencoder- (SAE-) and deep belief network- (DBN-) based ensemble learning is proposed in this paper. First, six kinds of statistical features are extracted and normalized from multiple sensors monitoring the same target component. Second, the six extracted features are fused by the two-stage SAE proposed in this paper from the sensor dimension and feature dimension, respectively. The composite feature fused in the feature dimension is regarded as the comprehensive representation of the corresponding component. Finally, the fused features containing comprehensive representation of different components are utilized to predict the machine health condition by the ensemble of multiple deep belief classifiers. The effectiveness of the proposed method is validated by the two case studies of wind turbine gearbox and industrial port crane. The experimental result shows that the proposed ensemble learning approach outperforms other traditional deep learning approaches in terms of the prediction accuracy and the prediction stability when dealing with multisensor feature fusion and the precise faulty identification of the industrial heavy machine.