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Fault-related monitoring variables selection is a process of obtaining a subset of variables from the original set, which is of great significance for reducing information redundancy and improving the performance of the fault diagnosis models. This paper aims to propose a novel variables selection approach based on complex networks.

Firstly, a dual-layer correlation networks (DlCN) which consists of mechanism-oriented correlation sub-network (MoCSN) and data-oriented correlation sub-network (DoCSN) is constructed. Secondly, an algorithm for identifying critical fault-related monitoring variables based on dual correlations is introduced. In the algorithm, the topological attributes of the MoCSN and correlation threshold of the DoCSN are used successively.

In the experiments of vertical elevator fault diagnosis, the critical fault-related monitoring variables selected by the DlCN-based approach is more effective than the traditional approaches. It indicates that fusion mechanism-oriented correlation can enhance the comprehensiveness of variable correlation analysis. Moreover, the approach has been proved to be adaptable to different fault diagnosis models.

In the DlCN-based variables selection approach, the mechanism-oriented correlation and data-oriented correlation are comprehensively considered. It improves the precision of variables selection. Meanwhile, it is an unsupervised and model-agnostic approach which addresses the shortcomings of some conventional approaches that require data labels and have insufficient adaptability for fault diagnosis models.

This paper aims to investigate the effect of unknown noise parameters of Kalman filter on velocity and displacement and to enhance the measured accuracy using adaptive Kalman filter with particle swarm optimization algorithm.

A novel method based on adaptive Kalman filter is proposed. Combined with the displacement measurement model, the standard Kalman filtering algorithm is established. The particle swarm optimization algorithm fused with Kalman is used to obtain the optimal noise parameter estimation using different fitness function.

The simulations and experimental results show that the adaptive Kalman filter algorithm fused with particle swarm optimization can improve the accuracy of the velocity and displacement.

The adaptive Kalman filter algorithm fused with particle swarm optimization can serve as a new method for optimal state estimation of moving target.

Regarding the important roles of accuracy and robustness of tightly-coupled micro inertial measurement unit (MIMU)/global navigation satellite system (GNSS) for unmanned aerial vehicle (UAV). This study aims to explore the efficient method to improve the real-time performance of the sensors.

A covariance shaping adaptive Kalman filtering method is developed. For optimal performance of multiple gyros and accelerometers, a distribution coefficient of precision is defined and the data fusion least square method is applied with fault detection and identification using the singular value decomposition. A dual channel parallel filter scheme with a covariance shaping adaptive filter is proposed.

Hardware-in-the-loop numerical simulation was adopted, the results indicate that the gain of the covariance shaping adaptive filter is self-tuning by changing covariance weighting factor, which is calculated by minimizing the cost function of Frobenius norm. With the improved method, the positioning accuracy with tightly-coupled MIMU/GNSS of the adaptive Kalman filter is increased obviously.

The method of covariance shaping adaptive Kalman filtering is efficient to improve the accuracy and robustness of tightly-coupled MIMU/GNSS for UAV in complex and dynamic environments and has great value for engineering applications.

A covariance shaping adaptive Kalman filtering method is presented and a novel dual channel parallel filter scheme with a covariance shaping adaptive filter is proposed, to improve the real-time performance in complex and dynamic environments.

This paper aims to explore the damage mechanism of a lubricating film on the worn surface of solid self-lubricating composites under different loads.

By comparing the actual stress with the strength, it is possible to determine the approximate wear state of the lubricating film. To prove the validity of the mathematical model that can predict the initiation of micro cracks or even the failure of the lubricating film, M50-5 Wt.% Ag self-lubricating composites (MA) was prepared. Tribological tests of the composites against Si₃N₄ ceramic balls were conducted at room temperature from 2 to 8 N. The electron probe microanalysis images of the lubricating film verify the wear state of the lubricating film.

The study found that the back edge of the contact area is the most vulnerable to destruction. The tensile stress and the equivalent shear stress have a positive correlation with load and friction coefficient. When the load is 4 N, an intact lubricating film covers the worn surface because the tensile stress and the equivalent shear stress are below the tensile strength and the shear strength, respectively; under other working conditions, the lubricating film is destroyed.

This paper has certain theoretical guidance for the study of tribological properties of solid self-lubricating composites. Moreover, this mathematical model is appropriate to be applied for the other composites.

This study aims to present multi-layered embeddedness and explore the main and interaction effects of political embeddedness on the performance of private enterprises in China. This study tests multi-layered embeddedness through interaction effects between three layers, namely, political, territorial and inter-firm embeddedness. Political embeddedness is related at the personal and the firm levels.

The authors used secondary data of four non-panel waves (2002, 2008, 2010 and 2016) of large samples having identical questions based on the Chinese private enterprises’ survey. The accumulated number of business owners’ responses is a total of 10,686.

The main effects of each of the layers of embeddedness showed a positive influence on enterprise performance consistently and unchanged over time which fits the Chinese Guanxi regardless of the immense macro-economic transition. However, unexpectedly some interactions showed negative significant effects on performance.

First, business owners should be aware of the specific contribution to the performance of political embeddedness at both the firm level and the personal level. Second, the pursuit of exercising simultaneously several layers of embeddedness may be detrimental to company performance. This study provides generalizable lessons regarding different embeddedness layers beyond the context of China’s transition economy.

First, the authors extend political embeddedness to the firm level whilst in previous research this construct had been mostly related to the personal level. Second, building on the resource-based view and redundant resources the authors present the disadvantage of “over-embeddedness” as related to multi-layered embeddedness which has been understudied.

Given the unique cultural-political context of China, this paper aims to investigate two research questions: What has been the development trajectory of policy-making on consumer privacy protection in China, and what factors have shaped its development over the years?

This paper adopts a historical approach and examines the development of Chinese consumer privacy policy during four periods: 1980s, 1990s, 2000s and 2010-present.

Chinese policy-making on consumer privacy protection has made steady advancement in the past few decades due to factors such as technological development, elite advocacy and emulation of other markets; however, the effects of these factors are conditioned by local forces.

To date, most studies of consumer privacy issues have focused on Western countries, especially the European Union and the USA. A better understanding of how consumer privacy policy has developed in China provides important lessons on the promotion of consumer privacy protection in other developing countries.

To clarify divergent conclusions on the impact of alliances on green innovation (GI), this study aims to examine the non-linear relationships between dual alliance and GI, as well as the mediation of green knowledge reconstruction (GKR) and the moderation of alliance tie strength.

Based on the theory of knowledge-based view, a moderated intermediary model is constructed by introducing GKR and alliance tie strength. The hypotheses are validated by using hierarchical regression analysis and bootstrapping method, with questionnaire survey data collected from 316 manufacturing firms in China.

Empirical results show that both exploratory alliance and exploitative alliance have an inverted U-shaped effect on GI, in which GKR plays a mediating role in the above relationship. Moreover, alliance tie strength weakens the intermediary role of GKR in the relationship between exploratory alliance and GI, whereas it enhances the intermediary role of GKR in the relationship between exploitative alliance and GI.

Findings reveal the non-linear effects of dual alliance on GI and clarify the inconsistent conclusions by proposing the moderated intermediary effect model. Moreover, this research reveals the mechanism of dual alliance on GI through the mediation of GKR and enriches the boundary conditions by integrating the moderating role of alliance tie strength.

To address the gap of divergent conclusions on the impact of knowledge search (KS) on performance, this paper aims to discuss the nonlinear relationships between KS and reverse internationalization enterprise (RIE) performance, and the co-moderation of causation and effectuation (C&E) on KS–performance.

The proposed theoretical model is developed by integrating the theory of knowledge-based view and decision rationality theory. The empirical study is based on survey data collected from 245 RIEs of the Yangtze River Delta and Pearl River Delta regions in China. Hierarchical multiple regression and the appropriate U-test method are used to test the hypotheses.

Empirical results suggest that both focused and multi-focus searches have inverted U-shaped effects on RIE performance. Furthermore, causation weakens the curvilinear effect between multi-focus search and RIE performance, whereas effectuation strengthens the curvilinear effect but weakens the inverted U-shaped relationship between focused search and RIE performance. Results also indicate that the integration of C&E positively moderates the relationship between focused or multi-focus searches and RIE performance.

Findings reveal the nonlinear effects of focused and multi-focus searches on RIE performance and clarify the dispute over the mechanism of KS on performance by proposing the different moderating role of C&E. Moreover, this research provides deeper insight into contingency mechanisms between KS and performance by integrating the co-moderating role of C&E in RIEs.

This paper aims to solve the nonlinear problem in the uncertainty evaluation of the measurement of the positioning repeatability (RP) of industrial robots and provide guidance to restrict the uncertainty of measurement of RP (u_RP).

Firstly, some uncertain sources existing in the measurement procedure of RP are identified. Secondly, the probability distribution function (PDF) of every source is established on the basis of its measurements. Some spatial combined normal distributions are adopted. Then, a method, based on Monte Carlo method (MCM) and established measurement model, is developed for the estimation of u_RP. Thirdly, some tests are developed for the identification and validation of the selected PDFs of uncertain sources. Afterwards, the proposed method is applied for the evaluation and validation of the u_RP. Finally, influence analyses of some key factors are proposed for the quantification of their relative contributions to u_RP.

Results show that the proposed method can reasonably and objectively estimate the u_RP of the selected industrial robot, and changes of the industrial robots’ position and the laser trackers measurement are correlated. Additionally, the u_RP of the selected industrial robot can be restricted by using the results of its key factors on u_RP.

This paper proposes the spatial combined normal distribution to model the uncertainty of the repeatability of the laser tracker and industrial robot. Meanwhile, the proposed method and influence analyses can be used in estimating and restricting the u_RP and thus useful in determining whether the RP of a tested industrial robot meets its requirements.

The purpose of this study is to find out the influence degree of harmonic current on the generator operating parameters. In practical operation of the salient-pole synchronous generator, the heat generated by eddy current loss may lead to the breaking of damper winding, and the damper winding is a key component for ensuring the reliable operation of generators. Therefore, it is important to study the distribution characteristics and the influence factors of eddy current loss. Taking a 24-MW bulb tubular turbine generator as a reference, the influence factors that affect the eddy current loss of damper winding are analyzed.

A two-dimensional (2-D) electromagnetic field model of the generator is established, and the correctness of the model is verified by comparing simulation results and experiment data. The eddy current losses of damper winding in various conditions are calculated by using the finite element method.

It is identified that the cogging effect, pole shoe magnetic saturation degree, pole arc coefficient and armature reaction are the main factors that affect the eddy current loss of the generator rotor. When the generator is installed with magnetic slot wedges, the distribution characteristic of eddy current loss is obtained through the study of the eddy current density distributions in the damper bars. The variations of eddy current losses with time are gained when the generator has different permeability slot wedges, pole arc coefficients and pole shoe magnetic saturation degrees.

The study of this paper provides a theoretical reference for the design and optimization of bulb tubular turbine generator structure.

The research can help enhance the understanding of eddy current distribution characteristics and influence factors of eddy current loss in bulb tubular turbine generator.