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The purpose of this paper is to study the potential advantages of aircraft formation flight (FF) and to exploit further benefits through exchanging the leading positions.

The detailed and robust methodologies concerning FF mission analysis including the leading aircraft rotation strategies are developed in this paper to study the fuel burn benefit and the additional bonus of formation rotation.

Switch of FF leading positions can offset the undesired weight ratios between the leading and trailing aircraft within FF missions, which further alleviates the deviations from design flight conditions. The case studies on two long-range civil transport aircraft in FF show that the leading and trailing aircraft can achieve almost equal fuel benefit through rotations. As compared to FF without rotation, the fuel efficiency can be improved by more than 11 per cent.

The work can bring benefit the research communities as a fundamental basis for operational studies of FF, such as FF airspace management in the future, which is significant for a future real-world implementation of FFs.

According to the authors’ study, equal or quasi-equal fuel savings can be achieved if the rotation is properly arranged. For the real-world FF application, fuel consumption (FC) or cost redistribution problem for leading and trailing aircraft belonging to two different operating airlines can therefore be resolved through the concept proposed by the paper.

The methods developed in the paper have the advantage to give more reliable estimations of the achievable fuel burn savings of FF. The concept proposed in the paper has significant meaning with respect to offset the undesired weight ratios between the leading and trailing aircraft within FF missions and redistributing FC or cost redistribution of different operating airlines.

The purpose of this paper is to present a detection method based on computer vision for automatic flexible printed circuit (FPC) defect detection.

This paper proposes a new method of watershed segmentation based on morphology. A dimensional increment matrix calculation method and an image segmentation method combined with a fuzzy clustering algorithm are provided. The visibility of the segmented image and the segmentation accuracy of a defective image are guaranteed.

Compared with the traditional one, the segmentation result obtained in this study is superior in aspects of noise control and defect segmentation. It completely proves that the segmentation method proposed in this study is better matches the requirements of FPC defect extraction and can more effectively provide the segmentation result. Compared with traditional human operators, this system ensures greater accuracy and more objective detection results.

The extraction of FPC defect characteristics contains some obvious characteristics as well as many implied characteristics. These characteristics can be extracted through specific space conversion and arithmetical operation. Therefore, more images are required for analysis and foresight to establish a more widely used FPC defect detection sorting algorithm.

This paper proposes a new method of watershed segmentation based on morphology. It combines a traditional edge detection algorithm and mathematical morphology. The FPC surface defect detection system can meet the requirements of online detection through constant design and improvement. Therefore, human operators will be replaced by machine vision, which can preferably reduce the production costs and improve the efficiency of FPC production.

This paper aims to introduce a method based on the optimizer of the particle swarm optimization (PSO) algorithm to improve the efficiency of a Kriging surrogate model.

PSO was first used to identify the best group of trend functions and to optimize the correlation parameter thereafter.

The Kriging surrogate model was used to resolve the fuselage optimization of an unmanned helicopter.

The optimization results indicated that an appropriate PSO scheme can improve the efficiency of the Kriging surrogate model.

Both the STANDARD PSO and the original PSO algorithms were chosen to show the effect of PSO on a Kriging surrogate model.

The purpose of this paper is to analyze and figure out the temperature field and thermal stress field with the calculation model of thermal insulation material and composite material.

The paper adopted the three-dimensional finite element algorithm.

The simulated results showed great shearing strength between the chipset and the printed circuit board. The position of chip exerts great influence on the distribution of temperature field and thermal stress field of circuit board. The reasonable distribution of chip will effectively reduce the temperature extremum and stress extremum of circuit board.

The paper analyzes and presents a discussion of the problems relating to the density of electronic packaging. The analysis process and the method of the paper provide essential help in resolving electronic device heat problems.

This paper aims to conduct soft fault diagnosis of dual-redundancy sensors. An innovative fault diagnosis method, which combines a tracking differentiator and a sequential probability ratio test, is proposed.

First, two tracking differentiators are used to track and predict the two original signals, and determine their residuals. These residuals are used to calculate one quadratic residual. Then, a sequential probability ratio test is carried out on this quadratic residual to obtain log-likelihood ratio. A fault can be detected through comparing the log-likelihood ratio value with the threshold value. Finally, analyses of the difference in the residuals, which locates the fault, and of the difference in the original signals, which reveals the fault level and type, are completed successively.

Results from experimentation show that this method can realise soft fault diagnosis for dual-redundancy sensors.

The method proposed in the paper gives a new idea to study hybrid redundancy. The method provides a new application mode for tracking differentiators and sequential probability ratio test. The method can be used in robots, such as unmanned aerial vehicles and unmanned ground vehicles, to improve their fault tolerance. It can also be applied to the key parts of industrial production lines to decrease financial losses caused by sensor faults.