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The purpose of this paper is to propose cuckoo optimization algorithm (COA)-based back propagation neural network (BPNN) to reduce the effect of the nonlinearities presented in laser triangulation displacement sensors. The 3D positioning and posture sensor allows access to the third dimension through depth measurement; the performance of the sensor varies according to the level of nonlinearities presented in the system, which leads to inaccuracies in measurement.

While applying optimization approach, the mathematical model and the relationship between the key parameters in the laser triangulation ranging and the indexes of the measuring system were analyzed.

Based on the performance of the parametric optimization method, the measurement repeatability reached 0.5 µm with an STD value within 0.17 µm, an expanded uncertainty of measurement was within 5 µm, the angle error variation of the object’s rotational plane was within 0.031 degrees and nonlinearity was recorded within 0.006 per cent in a full scale. The proposed approach reduced the effect of the nonlinearity presented in the sensor. Thus, the accuracy and speed of the sensor were greatly increased. The specifications of the optimized sensor meet the requirements for high-accuracy devices and allow wide range of industrial application.

In this paper, COA-based BPNN is proposed for laser triangulation displacement sensor optimization, on the basis of the mathematical model, clarifying the working space and working angle on the measurement system.

Although a laser profile sensor (LPS) can be used to measure dimensions, the “shadow region” generally degrades the accuracy and precision of width measurements. The accuracy and precision of such measurements should be improved.

In this paper, the authors propose herein a technique that combines high dynamic range (HDR) imaging with logistic fitting. First, a HDR image is composed of several images acquired with different exposure times, which augments the grayscale of the object profile and significantly reduces overexposure. Next, the profile is fit to a logistic function, which provides accurate and precise edge coordinates. Finally, given the edge coordinates, the object width is calculated.

To verify the stability of this logistic algorithm, the authors simulate different noise conditions and different degrees of incomplete edge data. In addition, the progressiveness of the algorithm is demonstrated by comparing the results with those of other algorithms and with the height measurement. Furthermore, the suitability of the system is verified experimentally.

Because of the limitation of the condition of laboratory, in the experimental section, this paper cannot represent perfectly the industrial situation. It makes this section limited in demonstration.

In this paper, the results show that the measurement accuracy and precision of the width is improved and exceeds that of the height measurement. The proposed HDR imaging method with logistic fitting may be applied to LPS width measurements, which should significantly aid the development of LPSs.

The purpose of this paper is to analyze the lubrication behavior of misaligned water-lubricated polymer bearings with axial grooves.

A lubrication model considering journal misalignment, bush deformation and grooves is established. In dynamic analyses of shaft systems, bearings are usually simplified as supporting points. Thus, an approach for solving the equivalent supporting point location is presented. The influence of misalignment angle and groove number on film thickness, hydrodynamic pressure distribution, load-carrying capacity and ESP location is investigated.

As the misalignment angle increases, the location of the maximum pressure and ESP are shifted toward the down-warping end, and the load-carrying capacity of the bearing decreases. In comparison to the nine-groove bearing, the six grooves bearing has a higher load-carrying capacity and the ESP is located closer to the down-warping end for an equivalent misalignment angle.

The results of this study can be applied to marine propeller shaft systems and other systems with misaligned bearings.

A study on the lubrication behavior of misaligned water-lubricated polymer bearings with axial grooves is of significant interest to the research community.

This paper aims to introduce the history and major achievement of the Chinese private enterprise survey (CPES), which is one of the most enduring large-scale nationwide sample surveys in China, providing important micro firm-level data for understanding and studying the development of Chinese enterprises and entrepreneurs over the past 26 years.

The main body of this paper is based on a bibliometric analysis of all literature using CPES until 2017.

This paper discusses problems that users may encounter during data mining. By doing so, it can assist other researchers to get a better understanding of what has been done (e.g. journals, topics, scholars and institutions) and do their research in a more targeted way.

As members of the survey project team, the authors also take a prospect of the future data design and use, as well as offer some suggestions about how to use the CPES data to improve high-quality development and business environment evaluation in China.

This paper is the first to provide an overall picture of academic papers in China and abroad that have used the CPES data.

This paper considers a maintenance problem for a queueing system. The arrival rate decreases as the server state becomes worse. The system can be recovered by maintenance, though the system is closed until the end of maintenance. A semi‐Markov decision process is formulated to find the optimal policy that maximizes the total expected discounted income from customers.

Penetration state is one of the most important factors for judging the quality of a gas tungsten arc welding (GTAW) joint. The purpose of this paper is to identify and classify the penetration state and welding quality through the features of arc sound signal during robotic GTAW process.

This paper tried to make a foundation work to achieve on‐line monitoring of penetration state to weld pool through arc sound signal. The statistic features of arc sound under different penetration states like partial penetration, full penetration and excessive penetration were extracted and analysed, and wavelet packet analysis was used to extract frequency energy at different frequency bands. The prediction models were established by artificial neural networks based on different features combination.

The experiment results demonstrated that each feature in time and frequency domain could react the penetration behaviour, arc sound in different frequency band had different performance at different penetration states and the prediction model established by 23 features in time domain and frequency domain got the best prediction effect to recognize different penetration states and welding quality through arc sound signal.

This paper tried to make a foundation work to achieve identifying penetration state and welding quality through the features of arc sound signal during robotic GTAW process. A total of 23 features in time domain and frequency domain were extracted at different penetration states. And energy at different frequency bands was proved to be an effective factor for identifying different penetration states. Finally, a prediction model built by 23 features was proved to have the best prediction effect of welding quality.

The purpose of this paper is to study the relationship between arc sound signal and arc height through arc sound features of GTAW welding, which is aimed at laying foundation work for monitoring the welding penetration and quality by using the arc sound signal in the future.

The experiment system is based on GTAW welding with acoustic sensor and signal conditioner on it. The arc sound signal was first processed by wavelet analysis and wavelet packet analysis designed in this research. Then the features of arc sound signal were extracted in time domain, frequency domain, for example, short‐term energy, AMDF, mean strength, log energy, dynamic variation intensity, short‐term zero rate and the frequency features of DCT coefficient, also the wavelet packet coefficient. Finally, a ANN (artificial neural networks) prediction model was built up to recognize different arc height through arc sound signal.

The statistic features and DCT coefficient can be absolutely used in arc sound signal processing; and these features of arc sound signal can accurately react the modification of arc height during the GTAW welding process.

This paper tries to make a foundation work to achieve monitoring arc length through arc sound signal. A new way to remove high frequency noise of arc sound signal is produced. It proposes some effective statistic features and a new way of frequency analysis to build the prediction model.

Surface forming control of welding bead is the fundamental study in automated welding. Considering that the vision sensing system cannot extract the height information of weld pool in pulsed GTAW process, so this paper designed a set of automatic measurement and control technology to achieve real-time arc height control via audio sensing system. The paper aims to discuss these issues.

The experiment system is based on GTAW welding with acoustic sensor and signal conditioner. A combination denoising method was used to reduce the environmental noise and pulse interference noise. After extracting features of acoustic signal, the relationship between arc height and arc sound pressure was established by linear fitting. Then in order to improve the prediction accuracy of that model, the piecewise linear fitting method was proposed. Finally, arc height linear model of arc sound signal and arc height is divided into two parts and built in two different arc height conditions, which are arc height 3-4 and 4-5-6 mm.

The combination denoising method was proved to have great effect on reducing the environmental noise and pulse interference noise. The experimental results showed that the prediction accuracy of linear model was not stable in different arc height changing state, like 3-4 and 4-5-6 mm. The maximum error was 0.635588 mm. And the average error of linear model was about 0.580487 mm, and the arc sound signal was accurately enough to meet the requirement for real-time control of arc height in pulse GTAW.

This paper tries to make a foundation work to achieve controlling of depth of welding pool through arc sound signal, then the welding quality control. So a new idea of arc height control based on automatic measuring and processing system through arc sound signal was proposed. A new way to remove environmental noise and pulse interference noise was proposed. The results of this thesis had proved that arc sound signal was an effective features and precisely enough for online arc height monitoring during pulsed GTAW.

This paper sets out to analyze the determinants of foreign direct investment (FDI) on both the country and regional level through the extensive review of past research studies, as well as through the development of a multiple regression model for identifying key determinants of FDI at the regional level in China during the critical year of 2002.

The development of a multiple regression model to identify statistically significant determinants of FDI by region in China.

As reforms continue to take place, FDI in China has been unevenly distributed. This paper examines five potential determinants of FDI in 30 regions (including provinces, centrally controlled municipalities, and semi‐autonomous regions) of China using a regression model. The specific focus is on 2002, as it is the first full year after China's accession to the World Trade Organization, and the first year in which China exceeded the USA in attracting FDI. From this initial study, one can conclude that the government should consider encouraging capital‐intensive FDI through the further development of a skilled workforce. This means increasing funding for higher education, and infrastructure, while also encouraging more openness in state‐owned enterprises. This paper sets up further research that may help expose regions with greater potential for FDI, as well as identifying regions which need to improve certain conditions in order to receive more FDI.

This paper analyzes the determinants of FDI by region in China in 2002. This year is particularly interesting as it is both the first full year after China's accession to the World Trade Organization, as well as the first year in which FDI was greater in China than in the USA While this research study is only a snap shot of a topic that is of increasing importance to China, it has direct relevance to the FDI development efforts of the individual regions. This study provides evidence that GDP that proxies for the market size and potential is shown to be a big attraction for FDI. Labor quality and the progress of reform or the degree of openness are also important determinants of the distribution of FDI. There is some mild evidence that high labor cost deters the inflow of FDI and the level of infrastructure has positive relation to FDI. These results have important implications for both the central and regional governments as they can be useful in helping the authorities to allocate funds and resources which will help attract FDI.

This study aims to address the challenge of the real-time state of charge (SOC) estimation for lithium-ion batteries in robotic systems, which is critical for monitoring remaining battery power, planning task execution, conserving energy and extending battery lifespan.

The authors introduced an optimal observer based on adaptive dynamic programming for online SOC estimation, leveraging a second-order resistor–capacitor model for the battery. The model parameters were determined by fitting an exponential function to the voltage response from pulse current discharges, and the observer's effectiveness was verified through extensive experimentation.

The proposed optimal observer demonstrated significant improvements in SOC estimation accuracy, robustness and real-time performance, outperforming traditional methods by minimizing estimation errors and eliminating the need for iterative steps in the adaptive critic and actor updates.

This study contributes a novel approach to SOC estimation using an optimal observer that optimizes the observer design by minimizing estimation errors. This method enhances the robustness of SOC estimation against observation errors and uncertainties in battery behavior, representing a significant advancement in battery management technology for robotic applications.