The influence of perceived Human Resource strength on safety performance among high-speed railway drivers: The role of organizational identification and psychological capital.

INTRODUCTION: Under the Chinese railway system reform background, high-speed railway drivers face continuous organizational change. As a communication channel between organizations and employees, the implementation of Human Resource Management (HRM) requires urgent attention. The present study explored the impacts of perceived Human Resource (HR) strength on safety outcomes premised on social identity theory. The relationships among perceived HR strength, organizational identification, psychological capital, and safety performance were investigated. METHOD: This study gathered 470 sets of paired data from Chinese high-speed railway drivers and their direct supervisors. RESULTS: The results indicated that perceived HR strength positively affects safety performance via organizational identification, directly and indirectly. The findings also revealed that psychological capital promotes the direct effect of perceived HR strength on drivers' safety performance. PRACTICAL APPLICATIONS: Railway organizations were suggested to not only focus on the HR content but also consider the HR process, especially in an organizational change context.

Finite Element Modeling and Vibration Control of Plates with Active Constrained Layer Damping Treatment.

An enhanced lightness and thinness is the inevitable trend of modern industrial production, which will also lead to prominent low-frequency vibration problems in the associated structure. To solve the vibration problem of thin plate structures in various engineering fields, the active constrained layer damping (ACLD) thin plate structure is taken as the research object to study vibration control. Based on the FEM method, energy method, and Hamilton principle, the dynamic model of an ACLD thin plate structure is derived, in which the Golla-Hughes-McTavish (GHM) model is used to characterize the damping characteristics of the viscoelastic layer, and the equivalent Rayleigh damping is used to characterize the damping characteristics of the base layer. The order of the model is reduced based on the high-precision physical condensation method and balance reduction method, and the model has good controllability and observability. An LQR controller is designed to actively control the ACLD sheet, and the controller parameters and piezoelectric sheet parameters are optimized. The results show that the finite element model established in this paper is accurate under different boundary conditions, and the model can still accurately and reliably describe the dynamic characteristics of the original system in the time and frequency domain after using the joint reduction method. Under different excitation and boundary conditions, LQR control can effectively suppress structural vibration. Considering the performance and cost balance, the most suitable control parameter for the system is: Q-matrix coefficient is between 1 × 104 and 1 × 105, the R-matrix coefficient is between 1 and 10, and the thickness of the piezoelectric plate is 0.5 mm.

Modeling and Vibration Control of Sandwich Composite Plates.

A finite element dynamic model of the sandwich composite plate was developed based on classical laminate theory and Hamilton's principle. A 4-node, 7-degree-of-freedom three-layer plate cell is constructed to simulate the interaction between the substrate, the viscoelastic damping layer, and the piezoelectric material layer. Among them, the viscoelastic layer is referred to as the complex constant shear modulus model, and the equivalent Rayleigh damping is introduced to represent the damping of the substrate. The established dynamics model has too many degrees of freedom, and the obtained dynamics model has good controllability and observability after adopting the joint reduced-order method of dynamic condensation in physical space and equilibrium in state space. The optimal quadratic (LQR) controller is designed for the active control of the sandwich panel, and the parameters of the controller parameters, the thickness of the viscoelastic layer, and the optimal covering position of the sandwich panel are optimized through simulation analysis. The results show that the finite element model established in this paper is still valid under different boundary conditions and different covering methods, and the model can still accurately and reliably represent the dynamic characteristics of the original system after using the joint step-down method. Under different excitation signals and different boundary conditions, the LQR control can effectively suppress the vibration of the sandwich plate. The optimal cover position of the sandwich plate is near the solid support end and far from the free-degree end. The parameters of controller parameters and viscoelastic layer thickness are optimized from several angles, respectively, and a reasonable optimization scheme can be selected according to the actual requirements.

An Environmentally Adaptive and Contrastive Representation Learning Method for Condition Monitoring of Industrial Assets.

Condition monitoring of assets is significant to the efficiency and reliability of industrial automation systems. However, the accuracy of condition monitoring results is easily impaired by variational environments and volatile operations, especially for complex automation systems. In this article, an environmentally adaptive and contrastive representation learning method is proposed to address the problem. To suppress the unexpected effects of environmental variations on operating data, a regression model between the operational and environmental variables is developed. The variable regression adjustment is achieved by solving a penalized optimization problem based on spline functions, and the solution is explicitly derived. Then, negative samples and pseudo labels are generated based on the designed pattern of data augmentation, and valid data representations for asset condition monitoring can be obtained by contrastive learning. Moreover, the reference statue of healthy assets is established by kernel density estimation, and control charts are employed for online monitoring with alarm thresholds. Taking wind turbine blades as examples, the remarkable performance of the developed method is demonstrated with real-world measurements from wind farms. Furthermore, comparative analysis with benchmark approaches and ablation study are conducted to reveal the superiority and effectiveness of the proposed method.

Active Vibration Control of Piezoelectric Sandwich Plates.

This paper deals with the active vibration control of piezoelectric sandwich plate. The structure consists of a substrate plate layer sandwiched between two layers of piezoelectric sensor and actuator. Based on laminate theory and constitutive equation of piezoelectric material, the vibration active control dynamic equation of the sandwich structure is established by using hypothetical mode method and Hamilton principle. The Rayleigh-Ritz method is used to solve it. The form of hypothetical solution is used for approximate solution, which is simple and accurate. The method of this paper is verified by several examples. The parametric studies of the sandwich plate structures are carried out. The results show that applying different boundary conditions and piezoelectric patch positions to the structures have a great influence on the natural frequency. When the driving voltage increases, the deflection of the plate structures increase approximately linearly. The active vibration control studies are investigated as well. The results show that within a certain range, the larger the value of the speed feedback coefficient, the better the active control effect. The positions of the piezoelectric patches affect the effectiveness and cost of active control. When the piezoelectric plate is located at the fixed end, the effect and cost of active control are better than that at the midpoint and free end of the plate.

Group strength in safety performance: the effects of group characteristics on individual personality expression in high-speed railway operators.

Objectives. In diverse working situations, the predictive effect of individual personality on job performance is not always the same. Thus, how to best understand and use personality in the workplace has been an important issue in recent years. Methods. Based on trait activation theory, the present study provides initial evidence from high-risk organizations (high-speed railway organizations) regarding interactionist effects of group-level characteristics on the relationship between individual personality (Big Five model) and safety performance (both safety compliance and safety participation). Data were obtained from a sample of high-speed rail operators from nine railway bureaus (N = 1012 from 86 working groups). Results. The results indicate that group conscientiousness, agreeableness and neuroticism enhance the relationship between individual personality and safety performance, while group openness weakens the relationship between individual personality and safety performance, and group extraversion has no effect on their relationship. Conclusion. These results suggest that high-risk organizations should focus not only on individual factors but also on the interactions between individual factors and group situations in individuals' safety performance.

Active Vibration Control of Composite Cantilever Beams.

This paper deals with the active vibration control of composite cantilever beam. Based on the finite element method and Golla-Hughes-McTavish (GHM) model, the system dynamics equation is established. Models are simplified in physical and modal space because of unobservable and uncontrollable. Based on the particle swarm optimization (PSO) algorithm, the linear quadratic regulator (LQR) feedback gain was optimized. The effect of system vibration damping under different controller parameters, piezoelectric-constrained layer position and excitation signal was studied. The study show that the optimal feedback gain of the controller can effectively balance the control effect and the control cost. The closer the piezoelectric layer and viscoelastic layer are to the fixed end, the better the system control effect and the smaller the control cost. The reduced-order model has a good control effect on different excitation signals.

Transverse Vibration of Viscoelastic Sandwich Structures: Finite Element Modeling and Experimental Study.

In the present work, the nonlinear vibration behavior of elastic-viscoelastic-elastic sandwich (EVES) beams is studied. A finite element (FE) equation taking intoaccount the transverse compression deformation of the viscoelastic core for the EVES beams is derived. In order toaccurately characterize the frequency-dependent feature of the viscoelastic materials layer, athird-order seven-parameter Biot model isused. A 2-node 8-DOF element is established to discretize the EVES beams. The experimental testing onEVES beams validates the numerical predication of the FE model. Numerical and analytical investigations are carried on a series of EVES beams with different thicknesses. The results indicate that the presented FE model has better accuracy in predicting the natural frequency of the sandwich beams, and in predicting damping, the accuracy is related to the thickness of each layer. The results of this paper have important reference values for the design and optimization of the viscoelastic sandwich structure.

Novel Method for Vibration Sensor-Based Instantaneous Defect Frequency Estimation for Rolling Bearings Under Non-Stationary Conditions.

It is proposed a novel instantaneous frequency estimation technology, multi-generalized demodulation transform, for non-stationary signals, whose true time variations of instantaneous frequencies are unknown and difficult to extract from the time-frequency representation due to essentially noisy environment. Theoretical bases of the novel instantaneous frequency estimation technology are created. The main innovations are summarized as: (a) novel instantaneous frequency estimation technology, multi-generalized demodulation transform, is proposed, (b) novel instantaneous frequency estimation results, obtained by simulation, for four types of amplitude and frequency modulated non-stationary single and multicomponent signals under strong background noise (signal to noise ratio is -5 dB), and (c) novel experimental instantaneous frequency estimation results for defect frequency of rolling bearings for multiple defect frequency harmonics, using the proposed technology in non-stationary conditions and in conditions of different levels of noise interference, including a strong noise interference. Quantitative instantaneous frequency estimation errors are employed to evaluate performance of the proposed IF estimation technology. Simulation and experimental estimation results show high effectiveness of the proposed estimation technology.

TheFinite Element Modeling and Experimental Study of Sandwich Plates with Frequency-Dependent Viscoelastic Material Model.

Athree-layer composite plate element is developed for finite element modeling and vibration analysis of sandwich plate with frequency-dependent viscoelastic material core. The plate element is quadrilateral element bounded by four-node with 7-degree-of-freedom per node. The frequency-dependent characteristics of viscoelastic material parameters are described using the Biot model. The method of identifying the parameters of the Biot model is given. By introducing auxiliary coordinates, the Biot model is combined with the finite element equation of the viscoelastic sandwich plate. Through a series of mathematical transformations, the equation is transformed into a standard second-order steady linear system equation form to simplify the solution process. Finally, the vibration characteristics of the viscoelastic sandwich plate are analyzed and experimentally studied. The results show that the method in this paper is correct and reliable, and it has certain reference and application value for solving similar engineering vibration problems.

A Finite Element Model for the Vibration Analysis of Sandwich Beam with Frequency-Dependent Viscoelastic Material Core.

In this work, a finite element model was developed for vibration analysis of sandwich beam with a viscoelastic material core sandwiched between two elastic layers. The frequency-dependent viscoelastic dynamics of the sandwich beam were investigated by using finite element analysis and experimental validation. The stiffness and damping of the viscoelastic material core is frequency-dependent, which results in complex vibration modes of the sandwich beam system. A third order seven parameter Biot model was used to describe the frequency-dependent viscoelastic behavior, which was then incorporated with the finite elements of the sandwich beam. Considering the parameters identification, a strategy to determine the parameters of the Biot model has been outlined, and the curve fitting results closely follow the experiment. With identified model parameters, numerical simulations were carried out to predict the vibration and damping behavior in the first three vibration modes, and the results showed that the finite model presented here had good accuracy and efficiency in the specific frequency range of interest. The experimental testing on the viscoelastic sandwich beam validated the numerical predication. The experimental results also showed that the finite element modeling method of sandwich beams that was proposed was correct, simple and effective.

Corrigendum: Spiritual Leadership on Proactive Workplace Behavior: The Role of Organizational Identification and Psychological Safety.

[This corrects the article DOI: 10.3389/fpsyg.2019.01206.].

Spiritual Leadership on Proactive Workplace Behavior: The Role of Organizational Identification and Psychological Safety.

This study investigates whether and why spiritual leadership may contribute to enhanced proactive employee workplace behavior. Based on self-determination theory (SDT), we examine the effects of two sequential mediators (i.e., organizational identification and psychological safety) on the relationship between spiritual leadership and proactive workplace behavior. Data collected from 188 subordinate-leader dyads in Chinese firms suggested that spiritual leadership has a significant positive effect on proactive workplace behavior. In addition, both organizational identification and psychological safety mediate the relationship between spiritual leadership and proactive workplace behavior. Furthermore, spiritual leadership positively influences organizational identification, and such identification nurtures psychological safety, which, in turn, fosters the proactive behavior of employees. It extends the existing impact of spiritual leadership to proactive workplace behavior and shed lights on the mediating mechanisms through which spiritual leadership exerts influences on proactive workplace behavior. Finally, it considers the important roles played by leaders in modern organizations.

Bearing fault diagnosis under time-varying rotational speed via the fault characteristic order (FCO) index based demodulation and the stepwise resampling in the fault phase angle (FPA) domain.

Time-frequency representation (TFR) based order tracking algorithm can help to realize rolling bearing fault diagnosis under time-varying rotational speed without using a tachometer. Among this TFR based algorithm, however, two important steps, determining the optimal resonance band and realizing the TFR based resampling with high accuracy, are not well addressed. As such, a new criterion called fault characteristic order index (FCOindex) is designed to select the optimal filter band to enhance the fault-related components under time-varying rotational speed, and a new stepwise resampling algorithm is proposed based on the fine instantaneous fault characteristic frequency (IFCF) trend extracted from the STFT and CWT based envelope TFRs. The proposed algorithm contains five main steps: (a) Band-pass filtering the raw signal with several specially designed filter bands, (b) Constructing the FCOindex as the criterion and selecting the filter band with the highest FCOindex as the optimal filter band, (c) extracting the fine IFCF trend from the CWT based envelope TFR of the filter signal and the STFT based rough IFCF trend, (d) resampling the filter signal with the fine IFCF trend using a new stepwise resampling algorithm, and (e) realizing the fault detection using the FCO spectrum. The effectiveness of the proposed method has been validated using the simulated and experimental signals.

Organization is also a "life form": Organizational-level personality, job satisfaction, and safety performance of high-speed rail operators.

Although studies have suggested that personality can forecast safety performance at the individual level, the link between organizational-level personality and safety performance is rarely considered. On the basis of the Attraction-Selection-Attrition (ASA) theory, the present study investigated the direct and indirect effects of the organizational emergence of personality (Five-Factor Model) on individual-level outcomes (safety performance) in the high-speed rail industry. The sample consisted of 1035 high-speed rail operators in China. The results indicated that the effects of organizational-level personality on safety performance are similar to or stronger than the effects of individual-level personality. Specifically, organizational-level extraversion, agreeableness, and conscientiousness have significantly positive relationships with individual-level safety compliance and safety participation, while neuroticism has a significantly negative relationship with safety compliance and safety participation; the effect of openness to experience was not significant. Moreover, in terms of indirect effects, job satisfaction mediated the links of the four personality constructs (extraversion, agreeableness, neuroticism, and conscientiousness) with safety compliance and safety participation. These findings highlight the importance of organizational personality to improving employees' safety performance in safety-critical organizations.

Fault diagnosis for wind turbine planetary ring gear via a meshing resonance based filtering algorithm.

Identifying the differences between the spectra or envelope spectra of a faulty signal and a healthy baseline signal is an efficient planetary gearbox local fault detection strategy. However, causes other than local faults can also generate the characteristic frequency of a ring gear fault; this may further affect the detection of a local fault. To address this issue, a new filtering algorithm based on the meshing resonance phenomenon is proposed. In detail, the raw signal is first decomposed into different frequency bands and levels. Then, a new meshing index and an MRgram are constructed to determine which bands belong to the meshing resonance frequency band. Furthermore, an optimal filter band is selected from this MRgram. Finally, the ring gear fault can be detected according to the envelope spectrum of the band-pass filtering result.

The impact of personality on driving safety among Chinese high-speed railway drivers.

This study explored the impact of personality traits on driving safety in high-speed railway drivers. A sample of high-speed railway drivers in Beijing (N=214) completed a questionnaire, including information on personality traits and background variables. The NEO Five Factor Inventory (NEO-FFI) was administered to characterize participants based on five personality traits: Neuroticism, Extraversion, Agreeableness, Openness to Experience, and Conscientiousness. The survey data were combined with naturalistic data of accident involvement and risky driving behavior in China. Poisson regression results show that drivers with high Conscientiousness and Extraversion caused fewer accidents. Higher Conscientiousness and lower Agreeableness were related to less frequent risky driving behavior. Education level and age negatively moderated the relation between certain personality traits and driving safety. The findings suggest that personality traits should be considered when selecting and training high-speed railway drivers.

A sclerotic rim provides mechanical support for the femoral head in osteonecrosis.

Osteonecrotic collapse of the femoral head is a common refractory disease in orthopedics, and the occurrence of collapse is an important factor in the prognosis of this condition. Osteonecrotic collapse of the femoral head can be delayed or prevented by the formation of a sclerotic rim. This study used finite element analysis to evaluate the mechanical role of a proximal sclerotic rim on stress on the femoral head. The study used a healthy man who underwent computed tomography of both hips to generate 3-dimensional finite element models with different proportions of proximal rim sclerosis (0%, 30%, 50%, and 100%). Using a negative directional mechanical load of 400 N along the Z-axis, total deformation, deformation in the negative Z-axial direction (ie, direction of longitudinal compression), maximum principal stress, minimum principal stress, and contact pressure on necrotic tissue were evaluated. For 0%, 30%, 50%, and 100% rim sclerosis, total femoral head deformation was 0.21, 0.205, 0.20, and 0.19 mm, respectively, and maximum principal stress in compression was 9.83, 9.67, 9.16, and 9.05 MPa, respectively. Increases in proximal rim sclerosis decreased all of the measured outcomes. These results suggest that proximal rim sclerosis provides effective mechanical support for the femoral head, offers mechanical protection for necrotic tissue, decreases deformation of the femoral head, and delays or prevents collapse in osteonecrosis.