Zhimeng Luo, Jianzhong Zhou, Xiuqiao Xiang, Yaoyao He and Shan Peng
Shaft orbit is an important characteristic for vibration monitoring and diagnosing system of hydroelectric generating set. Because of the low accuracy and poor reliability of…
Abstract
Purpose
Shaft orbit is an important characteristic for vibration monitoring and diagnosing system of hydroelectric generating set. Because of the low accuracy and poor reliability of traditional methods in identifying the shaft orbit moving direction (MD), the purpose of this paper is to present a novel automatic identification method based on trigonometric function and polygon vector (TFPV).
Design/methodology/approach
First, some points on shaft orbit were selected with inter‐period acquisition method and joined together orderly to form a complex plane polygon. Second, by using the coordinate transformation and rotation theory, TFPV were applied comprehensively to judge the concavity or convexity of the polygon vertices. Finally, the shaft orbit MD is identified.
Findings
The simulation and experiment demonstrate that the method proposed can effectively identify the common shaft orbit MD.
Originality/value
In order to identity the shaft orbit MD effectively, a novel automatic identification method based on TFPV is proposed in this paper. The problem of identifying the shaft orbit MD is transformed into the problem about orientation of complex polygons, which are formed orderly by points on orbit shaft, and TFPV are applied comprehensively to judge the concavity or convexity of the polygon vertices.
Details
Keywords
Wang Junguo, Zhou Jianzhong and Peng Bing
The purpose of this paper is to improve forecasting accuracy for short‐term load series.
Abstract
Purpose
The purpose of this paper is to improve forecasting accuracy for short‐term load series.
Design/methodology/approach
A forecasting method based on chaotic time series and optimal diagonal recurrent neural networks (DRNN) is presented. The input of the DRNN is determined by the embedding dimension of the reconstructed phase space, and adaptive dynamic back propagation (DBP) algorithm is used to train the network. The connection weights of the DRNN are optimized via modified genetic algorithms, and the best results of optimization are regarded as initial weights for the network. The new method is applied to predict the actual short‐term load according to its chaotic characteristics, and the forecasting results also validate the feasibility.
Findings
For the chaos time series, the hybrid neural genetic method based on phase space reconstruction can carry out the short‐term prediction with the higher accuracy.
Research limitations/implications
The proposed method is not suited to medium and long‐term load forecasting.
Practical implications
The accuracy of the load forecasting is important to the economic and secure operation of power systems; also, the neural genetic method can improve forecasting accuracy.
Originality/value
This paper will help overcome the defects of traditional neural network and make short‐term load forecasting more accurate and fast.
Details
Keywords
Junguo Wang, Jianzhong Zhou and Bing Peng
The purpose of this paper is to detect the periodic signal under strong noise background, and estimate its amplitude/phase.
Abstract
Purpose
The purpose of this paper is to detect the periodic signal under strong noise background, and estimate its amplitude/phase.
Design/methodology/approach
Melnikov method is adopted as calculating the threshold value when chaos occurs, and the detected signal is taken as a system parameter. The system's output state is changed if the parameter has a slight change near the threshold. Meantime, the phase of system's output is recognized to judge whether the output state changes, and the signal parameter is estimated according to the necessary condition.
Findings
A small periodic signal in noise can be detected by Duffing oscillator via a transition from chaotic motion to periodic motion.
Research limitations/implications
The paper shows how to calculate the amplitude/phase in low signal‐to‐noise ratios.
Practical implications
The Duffing system is sensitive to the weak periodic signal and has definite immunity to noise, so it is easy to construct a system composed of many oscillators that could process complex signals, even though the environmental noise is intense.
Originality/value
This paper presents a nonlinear method for detecting and extracting the weak signal.
Details
Keywords
Ranran Zhou, Jianzhong Xu, Jiaqi Zhai and Qingwei Kong
This study examines how responsible leadership drives sustainable reconfiguring in multi-tier supply chains, addressing the recognized challenges of implementing sustainable…
Abstract
Purpose
This study examines how responsible leadership drives sustainable reconfiguring in multi-tier supply chains, addressing the recognized challenges of implementing sustainable practices in complex, global value chains, particularly in the face of the management challenges posed by the high complexity of multi-tier supply chains.
Design/methodology/approach
Data were collected from 475 Chinese manufacturing firms between December 2023 and June 2024. Structural equation modeling with maximum likelihood estimation was used to assess linear relationships, followed by least-squares linear regression to verify model robustness. Neural network modeling was then applied to explore potential nonlinear relationships among variables.
Findings
The study empirically confirms that responsible leadership was a direct driver of sustainable reconfiguring, and social capital partially mediated the relationship between responsible leadership and sustainable reconfiguring. In addition, it was found that in highly complex supply chains, responsible leadership has a more significant driving effect on sustainable reconfiguring, i.e. supply chain complexity positively moderates the relationship between responsible leadership and sustainable reconfiguring.
Originality/value
This study contributes to the field by uniquely examining responsible leadership as a driver of sustainable supply chain reconfiguration, highlighting its role in resource acquisition through social capital from a resource dependence perspective. Unlike prior studies that treat supply chain complexity primarily as a management obstacle, this research uncovers its role as a “demand driver” in sustainable reconfiguration, offering fresh insights into complexity’s strategic impact. This approach provides a novel framework for understanding the nuanced pathways through which leadership style and situational factors collectively shape sustainable practices in supply chains.
Details
Keywords
Bing Liu, Hongyao Shen, Rongxin Deng, Zeyu Zhou, Jia’ao Jin and Jianzhong Fu
Additive manufacturing based on arc welding is a fast and effective way to fabricate complex and irregular metal workpieces. Thin-wall metal structures are widely used in the…
Abstract
Purpose
Additive manufacturing based on arc welding is a fast and effective way to fabricate complex and irregular metal workpieces. Thin-wall metal structures are widely used in the industry. However, it is difficult to realize support-free freeform thin-wall structures. This paper aims to propose a new method of non-supporting thin-wall structure (NSTWS) manufacturing by gas metal arc welding (GMAW) with the help of a multi-degree of freedom robot arm.
Design/methodology/approach
This study uses the geodesic distance on the triangular mesh to build a scalar field, and then the equidistant iso-polylines are obtained, which are used as welding paths for thin-wall structures. Focusing on the possible problems of interference and the violent variation of the printing directions, this paper proposes two types of methods to partition the model mesh and generate new printable iso-polylines on the split meshes.
Findings
It is found that irregular thin-wall models such as an elbow, a vase or a transition structure can be deposited without any support and with a good surface quality after applying the methods.
Originality/value
The experiments producing irregular models illustrate the feasibility and effectiveness of the methods to fabricate NSTWSs, which could provide guidance to some industrial applications.
Details
Keywords
Zhengtuo Wang, Yuetong Xu, Guanhua Xu, Jianzhong Fu, Jiongyan Yu and Tianyi Gu
In this work, the authors aim to provide a set of convenient methods for generating training data, and then develop a deep learning method based on point clouds to estimate the…
Abstract
Purpose
In this work, the authors aim to provide a set of convenient methods for generating training data, and then develop a deep learning method based on point clouds to estimate the pose of target for robot grasping.
Design/methodology/approach
This work presents a deep learning method PointSimGrasp on point clouds for robot grasping. In PointSimGrasp, a point cloud emulator is introduced to generate training data and a pose estimation algorithm, which, based on deep learning, is designed. After trained with the emulation data set, the pose estimation algorithm could estimate the pose of target.
Findings
In experiment part, an experimental platform is built, which contains a six-axis industrial robot, a binocular structured-light sensor and a base platform with adjustable inclination. A data set that contains three subsets is set up on the experimental platform. After trained with the emulation data set, the PointSimGrasp is tested on the experimental data set, and an average translation error of about 2–3 mm and an average rotation error of about 2–5 degrees are obtained.
Originality/value
The contributions are as follows: first, a deep learning method on point clouds is proposed to estimate 6D pose of target; second, a convenient training method for pose estimation algorithm is presented and a point cloud emulator is introduced to generate training data; finally, an experimental platform is built, and the PointSimGrasp is tested on the platform.
Details
Keywords
Jianzhong Li, Alhanouf Alburaikan and Rita de Fátima Muniz
The main purpose of this paper is to create a suitable structure based on neutrosophic numbers to evaluate the safety performance in construction projects in such a way that the…
Abstract
Purpose
The main purpose of this paper is to create a suitable structure based on neutrosophic numbers to evaluate the safety performance in construction projects in such a way that the shortcomings can be highlighted with the reasoned measurement and possible strategies can be recommended.
Design/methodology/approach
Data envelopment analysis (DEA), which is a useful tool for performance appraisal, along with neutrosophic logic, which is one of the most complete tools for handling uncertainty phenomenon, has been used to evaluate the safety performance of construction projects. With this hybrid model, a new strategy is considered as an indicator for safety performance and comparisons are made between different units.
Findings
A total of 35 Chinese organizations with construction projects lasting between 1.5 and 2 years were selected for comparison. After processing the data into neutrosophic numbers and using the NN-DEA model, it can be found that projects that pay more attention to safety issues such as training and equipment are more efficient.
Originality/value
Since in the real world, there are uncertainties with different contradictions, and neutrosophical data can handle many of these challenges, using DEA model with neutrosophic numbers to evaluate the performance of construction projects from a safety perspective, can provide significantly better results. Therefore, considering that no study has been presented in this field so far, the authors will deal with this topic.
Details
Keywords
Jiawei Feng, Jianzhong Fu, Zhiwei Lin, Ce Shang and Bin Li
T-spline is the latest powerful modeling tool in the field of computer-aided design. It has all the merits of non-uniform rational B-spline (NURBS) whilst resolving some flaws in…
Abstract
Purpose
T-spline is the latest powerful modeling tool in the field of computer-aided design. It has all the merits of non-uniform rational B-spline (NURBS) whilst resolving some flaws in it. This work applies T-spline surfaces to additive manufacturing (AM). Most current AM products are based on Stereolithograph models. It is a kind of discrete polyhedron model with huge amounts of data and some inherent defects. T-spline offers a better choice for the design and manufacture of complex models.
Design/methodology/approach
In this paper, a direct slicing algorithm of T-spline surfaces for AM is proposed. Initially, a T-spline surface is designed in commercial software and saved as a T-spline mesh file. Then, a numerical method is used to directly calculate all the slicing points on the surface. To achieve higher manufacturing efficiency, an adaptive slicing algorithm is applied according to the geometrical properties of the T-spline surface.
Findings
Experimental results indicate that this algorithm is effective and reliable. The quality of AM can be enhanced at both the designing and slicing stages.
Originality/value
The T-spline and direct slicing algorithm discussed here will be a powerful supplement to current technologies in AM.
Details
Keywords
Rong Wang, Jianzhong Shang, Xin Li, Zhuo Wang and Zirong Luo
This paper aims to present a new topology method in designing the lightweight and complex structures for 3D printing.
Abstract
Purpose
This paper aims to present a new topology method in designing the lightweight and complex structures for 3D printing.
Design/methodology/approach
Computer-aided design (CAD) and topology design are the two main approaches for 3D truss lattices designing in 3D printing. Though these two ways have their own advantages and have been used by the researchers in different engineering situations, these two methods seem to be incompatible. A novel topology method is presented in this paper which can combine the merits of both CAD and topology design. It is generally based on adding materials to insufficient parts in a given structure so the resulting topology evolves toward an optimum.
Findings
By using the topology method, an optimized-Kagome structure is designed and both 3D original-Kagome structure and 3D optimized-Kagome structure are manufactured by fused deposition modeling (FDM) 3D printer with ABS and the compression tests results show that the 3D optimized-Kagome has a higher specific stiffness and strength than the original one.
Originality/value
The presented topology method is the first work that using the original structure-based topology algorithm other than a boundary condition-based topology algorithm for 3D printing lattice and it can be considered as general way to optimize a commonly used light-weight lattice structure in strength and stiffness.
Details
Keywords
Bin Li, Jianzhong Fu, Yongjie Jessica Zhang, Weiyi Lin, Jiawei Feng and Ce Shang
Majority of the existing direct slicing methods have generated precise slicing contours from different surface representations, they do not carry any interior information…
Abstract
Purpose
Majority of the existing direct slicing methods have generated precise slicing contours from different surface representations, they do not carry any interior information. Whereas, heterogeneous solids are highly preferable for designing and manufacturing sophisticated models. To directly slice heterogeneous solids for additive manufacturing (AM), this study aims to present an algorithm using octree-based subdivision and trivariate T-splines.
Design/methodology/approach
This paper presents a direct slicing algorithm for heterogeneous solids using T-splines, which can be applied to AM based on the fused deposition modeling (FDM) technology. First, trivariate T-splines are constructed using a harmonic field with the gradient direction aligning with the slicing direction. An octree-based subdivision algorithm is then used to directly generate the sliced layers with heterogeneous materials. For FDM-based AM applications, the heterogeneous materials of each sliced layer are discretized into a finite number of partitions. Finally, boundary contours of each separated partition are extracted and paired according to the rules of CuraEngine to generate the scan path for FDM machines equipped with multi-nozzles.
Findings
The experimental results demonstrate that the proposed algorithm is effective and reliable, especially for solid objects with multiple materials, which could maintain the model integrity throughout the process from the original representation to the final product in AM.
Originality/value
Directly slicing heterogeneous solid using trivariate T-splines will be a powerful supplement to current technologies in AM.