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The purpose of this paper is to demonstrate the non-destructive methods for detection and localization of interconnection structure discontinuities based on the signal analysis in the frequency and time domain.

The paper deals with the discontinuity characterization of interconnection structures created on substrates used for electronics, and methods for their detection and localization, based on the frequency analysis of transmitted signals. Used analyses are based on the theoretical approach for the solution of discontinuity electrical parameters and are the base for diagnostic methods of discontinuity identification.

The measurement results of reflection parameters, frequency spectrums of transmitted signals and characteristic impedance values are presented on test samples containing multiple line cracks and their width reduction.

Obtained results can be used practically, not only for the detection of transmission lines discontinuities on printed circuit boards but also in other applications, such as the quality assessment of bonded joints.

Developed methods allow the quick identification and localization of particular discontinuities without the destruction of tested devices.

The purpose of this paper is to provide a knowledge-enabled digital twin for smart design (KDT-SD) of aircraft assembly line (AAL) to enhance the AAL efficiency, performance and visibility. Modern AALs usually need to have capabilities such as digital-physical interaction and self-evaluation that brings significant challenges to traditional design method for AAL. The digital twin (DT) combining with reusable knowledge, as the key technologies in this framework, is introduced to promote the design process by configuring, understanding and evaluating design scheme.

The proposed KDT-SD framework is designed with the introduction of DT and knowledge. First, dynamic design knowledge library (DDK-Lib) is established which could support the various activities of DT in the entire design process. Then, the knowledge-driven digital AAL modeling method is proposed. At last, knowledge-based smart evaluation is used to understand and identify the design flaws, which could further improvement of the design scheme.

By means of the KDT-SD framework proposed, it is possible to apply DT to reduce the complexity and discover design flaws in AAL design. Moreover, the knowledge equips DT with the capacities of rapid modeling and smart evaluation that improve design efficiency and quality.

The proposed KDT-SD framework can provide efficient design of AAL and evaluate the design performance in advance so that the feasibility of design scheme can be improved as much as possible.

The paper presents the application of self‐organizing neural network for the location of the fault in the transmission line and estimation of the parameter of the faulty element. The location of fault is done on the basis of the measurement of some node voltages of the line and appropriate preprocessing it to enhance the differences between different faults. The hybrid neural network is used to solve the problem. The self‐organizing layer of this network is used as the classifier. The output postprocessing MLP structure realizes the association of the place of the fault and its parameter with the measured set of node voltages. The results of computer experiments are given in the paper and discussed.

The industrial robot has high repeatability but low accuracy. With the industrial robot being widely used in complicated tasks, e.g. arc welding, offline programming and surgery, accuracy of the robot is more and more important. Robot calibration is an efficient way to improve the accuracy. Previous methods such as using coordinate measurement machines, laser trackers or cameras are limited by the cost, complex operation or the resolution. The purpose of this paper is to propose an approach and calibration equipment to address these issues.

The proposed method relies mainly upon a laser pointer attached on the end‐effector and single position‐sensitive devices (PSD) arbitrarily located on the workcell. The automated calibration procedure (about three minutes) involves aiming the laser lines loaded by the robot towards the center of the PSD surface from various robot positions and orientations. The localization is guaranteed by precise PSD feedback servoing control, which means physically the intersections of each pair of laser lines (virtual lines) are on the same point. Based on the untouched single‐point constraint, the robot joint offset calibration is implemented. Using the authors' proposed approach, a portable, low‐cost, battery‐powered, wireless and automated calibration system was implemented. Error analysis was conducted on the system.

The localization error of the developed calibration system is within 2 μm. The errors in joint space are magnified in PSD plane, and consequently the resolution in the joint space is improved. The standard deviation of the identified parameters was small (10‐2), indicating the stability of the calibration method. Both simulation and experimental results verify the feasibility of the proposed method and demonstrate the developed calibration system can identify joint offset with uncalibrated laser tool parameters.

The paper shows how a portable calibration system for joint offset of industrial robots was developed and how the goal of fast, automated, low‐cost, portable, and high precision calibration methods for joint offset was achieved.

The purpose of this paper is to design a new sliding mode control algorithm for the second order dynamic system subject to input signal and velocity constraints.

The proposed algorithm employs a time‐varying switching line. At the initial time t=t₀, the line passes through the representative point of the system in the error state space. Afterwards, the line moves with a constant velocity and a constant angle of inclination to the origin of the space and having reached the origin it stops moving. Parameters of the line are selected in such a way that the integral of the time multiplied by the absolute error is minimized with the input signal and the system velocity constraints. First, each of the constraints is taken into account separately, and then both of them are considered at the same time.

The algorithm introduced in this paper ensures insensitivity of the controlled system with respect to external disturbance and model uncertainty since the very beginning of its motion. Furthermore, the algorithm guarantees fast tracking error convergence to zero without overshoots or oscillations.

In this paper, new systematic methods of the switching line design for the second order system are presented. Input signal and velocity constraints are explicitly taken into account in the design process.

The purpose of this study is to obtain the optimal frequency for low-frequency transmission lines while minimizing losses and maintaining the voltage stability of low-frequency systems. This study also emphasizes a reduction in calculations based on mathematical approaches.

Telegrapher’s method has been used to reduce large calculations in low-frequency high-voltage alternating current (LF-HVac) lines. The static compensator (STATCOM) has been used to maintain voltage stability. For optimal frequency selection, a modified Jaya algorithm (MJAYA) for optimal load flow analysis was implemented.

The MJAYA algorithm performed better than other conventional algorithms and determined the optimum frequency selection while minimizing losses. Voltage stability was also achieved with the proposed optimal load flow (OLF), and statistical analysis showed that the proposed OLF reduces the frequency deviation and standard error of the LF-HVac lines.

The optimal frequency for LF-HVac lines has been achieved, Telegrapher’s method has been used in OLF, and STATCOM has been used in LF-HVac transmission lines.

As a common transmission line, the microstrip line plays an important role in high-speed circuits. The purpose of this paper was to investigate the effects of the circuit design of microstrip lines on the signal integrity (SI). In addition, the influence of the type and thickness of the solder resist ink on SI was analyzed to provide guidance for the related producing process design of printed circuit boards (PCBs).

Microstrip line properties consisting of shape, line-width/line-space ratio, reference layer design and as-covered solder resist ink were designed to measure the insertion loss (S₂₁) in high-speed PCB.

The study showed that the insertion loss (S₂₁) of straight, meander, snake-shaped and wavy microstrip lines was approximately consistent. A microstrip line with width/space ratio less than 0.96 is necessary, as the differential line closing produces a mutual interference. Reference layer including the discontinuous area should be repaired by adjusting the microstrip line parameters. With regard to the solder resist ink, the insertion loss of novel solder resist ink decreased by 0.163 dB/in at 12.9 GHz and 0.164 dB/in at 14 GHz, compared with traditional solder resist ink. Accordingly, the insertion loss effectively improved at a lower thickness of solder resist.

This paper demonstrated that the common designing factors of line shape, line/space ratio, reference layer and solder resist influence microstrip line SI in the significant reference of designer-making PCB layout.

One of the most challenging problems facing the package designer today is how to predict electrical performance before committing a design to fabrication. One means of accomplishing this task is to employ computer‐aided design (CAD) tools that analyse performance from simulations done on models derived from the physical package structures. These models, when combined with the chip models, allow interactive simulation and timing analysis of an entire multilayer package. This paper describes a CAD approach for evaluating interconnect performance within multilayer package structures and presents several examples to show how the approach is applied.

The loading and power variations in the power system, especially for the peak hours have abundant concussion on the loading patterns of the open access transmission system. During such unconditional state of loading the transmission line parameters and the line voltages show a substandard profile, which depicts exaction of congestion management of the power line in such events. The purpose of this paper is to present an uncomplicated and economical model for congestion management using flexible AC transmission system (FACTS) devices.

The approach desires a two-step procedure, first by optimal placement of thyristor controlled series capacitor (TCSC) and static VAR compensator (SVC) as FACTS devices in the network; second tuning the control parameters to their optimized values. The optimal location and tuning of TCSC and SVC represents a hectic optimization problem, due to its multi-objective and constrained nature. Hence, a reassuring heuristic optimization algorithm inspired by behavior of cat and firefly is employed to find the optimal placement and tuning of TCSC and SVC.

The effectiveness of the proposed model is tested through simulation on standard IEEE 14-bus system. The proposed approach proves to be better than the earlier existing approaches in the literature.

With the completed simulation and results, it is proved that the proposed scheme has reduced the congestion in line, thereby increasing the voltage stability along with improved loading capability for the congested lines.

The usefulness of the proposed scheme is justified with the computed results, giving convenience for implementation to any practical transmission network.

This paper fulfills an identified need to study exaction of congestion management of the power line.

The paper sets out to deal with the off‐line identification of induction motor (IM) parameters at standstill. Determination of values of the IM parameters is essential in sensorless drives with regard to accuracy and quality of the control system.

The presented identification method is based on the reconstruction of stator current response to the forced stator voltage step change; thus the cost function is defined in the classical form of the mean squared error between the computed and experimental data. The identification via evolutionary algorithms (EAs) is presented. The considered problem is continuous and thus a continuous version of EA is suggested as more suitable.

This approach has been shown to have several advantages over classical optimisation methods like the ability to cope with ill‐behaved problem domains exhibiting attributes such as: discontinuity, time‐variance, randomness, and, what is particularly important in this application, the ability to cope with the signals disturbed by noises. Owing to this ability the EAs could be implemented directly for the identification of IM parameters not only in simulations but also in the industrial applications for the motor control, though the electrical signals acquired from real motor and used as input data in the identification procedures are to a large extent disturbed by the electrical noises.

Two versions of the suggested approach are compared: the EA with hard selection and with soft selection. Both algorithms were tested in a simulation and experimental set‐up using digital signal processor for control and signal processing of the voltage inverter‐fed IM drive. Satisfactory results were obtained for the identification procedure based on the selected EA.