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This paper aims to provide an effective method so that the ultrasonic technique can be applied to the online debris particle detection. It proposes utilizing the waveshape features in discriminating the debris particle in lubricant.

The finite element model has been developed to investigate the scattering of the ultrasonic waves in lubricant containing single scatterer, such as the debris particle and the air bubble. The simulation results show that the results verify that different scatterers differ in the waveshape features. The static experiments were carried out on a specially fixture. The single spherical debris, long debris and air bubble were measured. The fast Fourier transform (FFT) method was applied to the analysis of the echo signals to obtain the features implicated in the waveshape.

The research of this paper verifies that different scatterers differ both in their shape features and in the FFT analysis features.

The rapid movement of the debris particles as well as the lubricant temperature may influence the measuring signals. Besides, the measuring signals are usually corrupted by noise, especially for the tiny debris. Therefore, researchers are encouraged to solve those problems further.

The paper includes implications for the improvement in the online debris detection and the development of the ultrasonic technique applied in online debris detection.

The paper provides a promising way that the ultrasonic waveshape features can be utilized to the identify debris particle online.

This paper aims to establish an organizational learning system model based on both western and Chinese management thoughts.

The approach is a conceptual model which is based on research within the field.

The model consists of nine interrelated organizational learning sub‐systems including “discovering”, “innovating”, “selecting”, “executing”, “transferring”, “reflecting”, “acquiring knowledge from environment”, “contributing knowledge to environment”, and “building organizational memory” ones. The evidences in some famous Chinese traditional cultural classics (including Great Learning, Doctrine of the Mean, The Analects of Confucius, Book of Change, Tao‐Te‐Ching, The Art of War and Chuan‐Xi‐Lu) that support the rationale of the model are described and analyzed.

Several propositions are developed and it is hoped that the model is applicable in both eastern and western business environments.

Composite cellular structures have wide application in advanced engineering fields due to their high specific stiffness and strength. As an emerging technology, continuous fiber-reinforced polymer additive manufacturing provides a cost-effective solution for fabricating composite cellular structures with complex designs. However, the corresponding path planning methods are case-specific and have not considered any manufacturing constraints. This study aims to develop a generally applicable path planning method to fill the above research gap.

This study proposes a path planning method based on the graph theory, yielding an infill toolpath with a minimum fiber cutting frequency, printing time and total turning angle. More specifically, the cellular structure design is converted to a graph first. Then, the graph is modified to search an Eulerian path by adding an optimal set of extra edges determined through the integer linear programming method. Finally, the toolpath with minimum total turning angle is obtained with a constrained Euler path search algorithm.

The effectiveness of the proposed method is validated through the fabrication of both periodic and nonperiodic composite cellular structures, i.e. triangular unit cell-based, Voronoi diagram-based and topology optimized structures. The proposed method provides the basis for manufacturing planar thin-walled cellular structures of continuous fiber-reinforced polymer (CFRP). Moreover, the proposed method shows a notable improvement compared with the existing method. The fiber cutting frequency, printing time and total turning angle have been reduced up to 88.7%, 52.6% and 65.5%, respectively.

A generally applicable path planning method is developed to generate continuous toolpaths for fabricating cellular structures in CFRP-additive manufacturing, which is an emerging technology. More importantly, manufacturing constraints such as fiber cutting frequency, printing time and total turning angle of fibers are considered within the process planning for the first time.

This paper aims to theoretically investigate a knowledge management model from the combined perspective of knowledge acquisition and knowledge application and its effect on organizational performance.

This study reviews prior research on knowledge acquisition and knowledge application, puts forward the concepts of “the extensiveness of knowledge acquisition” and “the concentration of knowledge application” and more importantly proposes an integrated model by combining these two dimensions. Four case examples of enterprises are subsequently described and analyzed to illustrate the sources of knowledge acquisition, the objects of knowledge application and their influences on organizational performance.

Four knowledge management modes and their impacts are confirmed in this study. Specifically, the organization of the turbojet engine mode (high extensiveness of knowledge acquisition and high concentration of knowledge application) can achieve good performance. The pipeline mode (high extensiveness of knowledge acquisition and low concentration of knowledge application) is the second, which has limited influence on good organizational performance. Organizations with the flashlight mode (low extensiveness of knowledge acquisition and high concentration of knowledge application) can achieve limited performance under the appropriate environment. The candle mode (low extensiveness of knowledge acquisition and low concentration of knowledge application) is the worst, performance of which is poor due to the break of the knowledge chain.

This paper holds that organizations should actively use the turbojet engine mode, adopt the pipeline mode and the flashlight mode cautiously, and avoid falling into the candle mode.

To the best of the authors’ knowledge, this study is among the first to propose the concepts of “the extensiveness of knowledge acquisition” and “the concentration of knowledge application,” and provides a combined model for analyzing differences in organizational performance from the perspective of knowledge.

The differential magnetic gradient tensor system is usually constructed from the three-axis magnetic sensor array. While the effects of measurement error, sensor performance and baseline distance on localization performance of such systems have been widely reported, the research about the effect of spatial design of sensor array is less presented. This paper aims to provide a spatial design method of sensor array and corresponding optimization strategy to localization based on magnetic tensor gradient to get the optimum design of the sensor array. Based on the results of simulation, magnetic localization systems constructed from the proposed array and the traditional array have been built to carry out a localization experiment. The results of experiment have verified the effectiveness of magnetic localization based on the proposed array.

The authors focus on the localization of the magnetic target based on magnetic gradient by using three-axis magnetic sensor array and combine a design method with corresponding optimization strategy to get the optimum design of the sensor array.

This paper provides an array design and optimization method for magnetic target localization based on magnetic gradient to improve the localization performance.

In this paper, the authors focus on the magnetic localization based on magnetic gradient by using three-axis magnetic sensors and study the effect of the spatial design of sensor array on localization performance.

This paper aims to focus on the tracking of a moving magnetic target by using total field magnetometers and to present a tracking method based on the gradient of a magnetic anomaly. In the tracking, it is assumed that the motion of the target is equivalent to a first-order Markov process. And the unit direction vector of the magnetic moment from the gradient of the magnetic anomaly can be obtained. According to the unit direction vector, the inverse problem is turned into an optimization problem to estimate the parameters of the target. The particle swarm optimization algorithm is used to solve this optimization problem. The proposed method is validated by the numerical simulation and real data. The parameters of the target can be calculated rapidly using the proposed method. And the results show that the estimated parameters of the mobile target using the proposed method are very close to the true values.

The authors focus on the tracking of a moving magnetic target by using total field magnetometers and present a tracking method based on the gradient of a magnetic anomaly.

The paper provides an effective method for tracking the magnetic target based on an array with total field sensors.

Comparing with a vector magnetic sensor, the measurement of the scalar magnetic sensor is almost not influenced by its orientation. In this paper, a moving magnetic target was tracked by using total field magnetometers and a tracking method presented based on the gradient of a magnetic anomaly.