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1 – 10 of 577Wei Fang, Mingyu Fu and Lianyu Zheng
This paper aims to perform the real-time and accurate ergonomics analysis for the operator in the manual assembly, with the purpose of identifying potential ergonomic injuries…
Abstract
Purpose
This paper aims to perform the real-time and accurate ergonomics analysis for the operator in the manual assembly, with the purpose of identifying potential ergonomic injuries when encountering labor-excessive and unreasonable assembly operations.
Design/methodology/approach
Instead of acquiring body data for ergonomic evaluation by arranging many observers around, this paper proposes a multi-sensor based wearable system to track worker’s posture for a continuous ergonomic assessment. Moreover, given the accurate neck postural data from the shop floor by the proposed wearable system, a continuous rapid upper limb assessment method with robustness to occasional posture changes, is proposed to evaluate the neck and upper back risk during the manual assembly operations.
Findings
The proposed method can retrieve human activity data during manual assembly operations, and experimental results illustrate that the proposed work is flexible and accurate for continuous ergonomic assessments in manual assembly operations.
Originality/value
Based on the proposed multi-sensor based wearable system for posture acquisition, a real-time and high-precision ergonomics analysis is achieved with the postural data arrived continuously, it can provide a more objective indicator to assess the ergonomics during manual assembly.
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P. van Zee, K.G. Günther, R. Poleschinski and N. Roth
A new approach to programming and operating multi‐sensor systems in flexible assembly automation has been developed. The concepts and strategies are described together with its…
Abstract
A new approach to programming and operating multi‐sensor systems in flexible assembly automation has been developed. The concepts and strategies are described together with its application to a depalletising task.
Zengrui Zheng, Kainan Su, Shifeng Lin, Zhiquan Fu and Chenguang Yang
Visual simultaneous localization and mapping (SLAM) has limitations such as sensitivity to lighting changes and lower measurement accuracy. The effective fusion of information…
Abstract
Purpose
Visual simultaneous localization and mapping (SLAM) has limitations such as sensitivity to lighting changes and lower measurement accuracy. The effective fusion of information from multiple modalities to address these limitations has emerged as a key research focus. This study aims to provide a comprehensive review of the development of vision-based SLAM (including visual SLAM) for navigation and pose estimation, with a specific focus on techniques for integrating multiple modalities.
Design/methodology/approach
This paper initially introduces the mathematical models and framework development of visual SLAM. Subsequently, this paper presents various methods for improving accuracy in visual SLAM by fusing different spatial and semantic features. This paper also examines the research advancements in vision-based SLAM with respect to multi-sensor fusion in both loosely coupled and tightly coupled approaches. Finally, this paper analyzes the limitations of current vision-based SLAM and provides predictions for future advancements.
Findings
The combination of vision-based SLAM and deep learning has significant potential for development. There are advantages and disadvantages to both loosely coupled and tightly coupled approaches in multi-sensor fusion, and the most suitable algorithm should be chosen based on the specific application scenario. In the future, vision-based SLAM is evolving toward better addressing challenges such as resource-limited platforms and long-term mapping.
Originality/value
This review introduces the development of vision-based SLAM and focuses on the advancements in multimodal fusion. It allows readers to quickly understand the progress and current status of research in this field.
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K. Arshak, A. Arshak, E. Jafer, D. Waldern and J. Harris
To develop a wireless sensor micro‐systems containing all the components of data acquisition system, such as sensors, signal‐conditioning circuits, analog‐digital converter…
Abstract
Purpose
To develop a wireless sensor micro‐systems containing all the components of data acquisition system, such as sensors, signal‐conditioning circuits, analog‐digital converter, embedded microcontroller unit (MCU), and RF communication modules. This has now become the focus of attention in many biomedical applications.
Design/methodology/approach
The system prototype consists of miniature FSK transceiver integrated with MCU in one small package, chip antenna, and capacitive interface circuitry based on Delta‐sigma modulator. At the base station side, an FSK receiver/transmitter is connected to another MCU unit, which send the received data or received instructions from a PC through a graphical user interface GUI. Industrial, scientific and medical band RF (433 MHz) was used to achieve half duplex communication between the two sides. A digital filtering has been used in the capacitive interface to reduce noise effects forming capacitance to digital converter. All the modules of the mixed signal system are integrated in a printed circuit board of size 22.46 × 20.168 mm.
Findings
An innovation circuits and system techniques for building advanced smart medical devices have been discussed. Low‐power consumption and high reliability are among the main criteria that must be given priority when designing such wirelessly powered microsystems. Switched capacitors readout circuits have been found to be suitable for pressure sensing low‐power applications.
Research limitations/implications
The presented wireless prototype needs a second phase of development that will lead to a further reduction in both size and power consumption. Currently, the main limitation of the RF system is the number of working hours according to the selected battery.
Practical implications
The developed system was found to be useful in terms of measuring pressure and temperature in a system of either slow or fast physical change. It would be a good idea to explore the system performance in human or animal trials.
Originality/value
This paper fulfils useful information for capacitive interface circuitries and presents a new short‐range wireless system that has different design features.
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Rong Wang, Jianye Liu, Zhi Xiong and Qinghua Zeng
The Embedded GPS/INS System (EGI) has been used more widely as central navigation equipment of aircraft. For certain cases needing high attitude accuracy, star sensor can be…
Abstract
Purpose
The Embedded GPS/INS System (EGI) has been used more widely as central navigation equipment of aircraft. For certain cases needing high attitude accuracy, star sensor can be integrated with EGI to improve attitude performance. Since the filtering‐correction loop has already built in finished EGI product, centralized or federated Kalman filter is not applicable for integrating EGI with star sensor; it is a challenge to design multi‐sensor information fusion algorithm suitable for this situation. The purpose of this paper is to present a double‐layer fusion scheme and algorithms to meet the practical need of constructing integrated multi‐sensor navigation system by star sensor assisting finished EGI unit.
Design/methodology/approach
The alternate fusion algorithms for asynchronous measurements and the sequential fusion algorithms for synchronous measurements are presented. By combining alternate filtering and sequential filtering algorithms, a kind of double‐layer fusion algorithms for multi‐sensors is proposed and validated by semi‐physical test in this paper.
Findings
The double‐layer fusion algorithms represent a filtering strategy for multiple non‐identical parallel sensors to assist INS, while the independent estimation‐correction loop in EGI is still maintained. It has significant benefits in updating original navigation system by integrating new sensors.
Practical implications
The approach described in this paper can be used in designing similar multi‐sensor information fusion navigation system composed by EGI and various kinds of sensors, so as to improve the navigation performance.
Originality/value
Compared with conventional approach, in the situation that centralized and federated Kalman filter are not applicable, the double‐layer fusion scheme and algorithms give an external filtering strategy for measurements of finished EGI unit and star sensors.
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Kai Zhao, Li-Guo Tan and Shen-Min Song
This paper aims to give the centralized and distributed fusion estimator for nonlinear multi-sensor networked systems with packet loss compensation and correlated noises and give…
Abstract
Purpose
This paper aims to give the centralized and distributed fusion estimator for nonlinear multi-sensor networked systems with packet loss compensation and correlated noises and give the corresponding square-root cubature Kalman filter.
Design/methodology/approach
Based on the Gaussian approximation recursive filter framework, the authors derive the centralized fusion filter and using the projection theorem, the authors derive the centralized fusion smoother. Then, based on the fast batch covariance intersection fusion algorithm, the authors give the corresponding results for distributed fusion estimators.
Findings
Designing the fusion estimators for nonlinear multi-sensor networked systems with packet loss compensation and correlated noises is necessary. It is useful for general nonlinear systems.
Originality/value
Throughout the whole study, the main highlights of this paper are as follows: packet loss compensation and correlated noises are considered in nonlinear multi-sensor networked systems. There are no relevant conclusions in the existing literature; centralized and distributed fusion estimators are derived based on the above system; for the posterior covariance with compensation factor and correlated noises, a new square-root factor of the error covariance is derived; and the new square-root factor of the error covariance is used to replace the numerical implementation of the covariance in cubature Kalman filter (CKF), which simplified the problem in calculating the posterior covariance in CKF.
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Bo Chen, Jifeng Wang and Shanben Chen
Welding sensor technology is the key technology in welding process, but a single sensor cannot acquire adequate information to describe welding status. This paper addresses arc…
Abstract
Purpose
Welding sensor technology is the key technology in welding process, but a single sensor cannot acquire adequate information to describe welding status. This paper addresses arc sensor and sound sensor to acquire the voltage and sound information of pulsed gas tungsten arc welding (GTAW) simultaneously, and uses multi‐sensor information fusion technology to fuse the information acquired by the two sensors. The purpose of this paper is to explore the feasibility and effectiveness of multi‐sensor information fusion in pulsed GTAW.
Design/methodology/approach
The weld voltage and weld sound information are first acquired by arc sensor and sound sensor, then the features of the two signals are extracted, and the features are fused by weighted mean method to predict the changes of arc length. The weights of each feature are determined by optional distribution method.
Findings
The research findings show that multi‐sensor information fusion technology can effectively utilize the information of different sensors and get better result than single sensor.
Originality/value
The arc sensor and sound sensor are first used at the same time to get information about pulsed GTAW and the fusion result shows its advantages over single sensor; this reveals that multi‐sensor fusion technology is a valuable research area in welding process.
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Per Holmbom, Ole Pedersen, Bengt Sandell and Alexander Lauber
By tradition, sensors are used to measure one desired parameter; all other parameters influencing the sensor are considered as interfering inputs, to be eliminated if possible…
Abstract
By tradition, sensors are used to measure one desired parameter; all other parameters influencing the sensor are considered as interfering inputs, to be eliminated if possible. Hence most of existing sensors are specifically intended for measuring one parameter, e.g. temperature, and the ideal temperature sensor should be as immune to all other parameters as possible. True, we sometimes use primitive sensor fusion, e.g. when calculating heat flow by combining separate measurements of temperature difference and of fluid flow.
Mohammad Ghesmat and Akbar Khalkhali
There are high expectations for reliability, safety and fault tolerance are high in chemical plants. Control systems are capable of potential faults in the plant processing…
Abstract
Purpose
There are high expectations for reliability, safety and fault tolerance are high in chemical plants. Control systems are capable of potential faults in the plant processing systems. This paper proposes is a new Fault Tolerant Control (FTC) system to identify the probable fault occurrences in the plant.
Design/methodology/approach
A Fault Diagnosis and Isolation (FDI) module has been devised based on the estimated state of system. An Unscented Kalman Filter (UKF) is the main innovation of the FDI module to identify the faults. A Multi-Sensor Data Fusion algorithm is utilized to integrate the UKF output data to enhance fault identification. The UKF employs an augmented state vector to estimate system states and faults simultaneously. A control mechanism is designed to compensate for the undesirable effects of the detected faults.
Findings
The performance of the Nonlinear Model Predictive Controller (NMPC) without any fault compensation is compared with the proposed FTC scheme under different fault scenarios. Analysis of the simulation results indicates that the FDI method is able to identify the faults accurately. The proposed FTC approach facilitates recovery of the closed loop performance after the faults have been isolated.
Originality/value
A significant contribution of the paper is the design of an FTC system by using UKF to estimate faults and enhance the accuracy of data. This is done by applying a data fusion algorithm and controlling the system by the NMPC after eliminating the effects of faults.
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