Parameter Setting Method Research Articles

A Frequency-Adaptive Improved Moving-Average-Filter-Based Quasi-Type-1 PLL for Adverse Grid Conditions

The moving-average-filter-based quasi-type-1 phase-locked loop (MAF-QT1 PLL) can provide zero steady-state phase error in the presence of frequency drifts, achieving a high filtering capability. However, in the presence of an MAF and frequency drift, MAF-QT1 PLL cannot achieve a fast transient response and frequency-dependent characteristic under adverse grid conditions. To overcome this drawback of the MAF-QT1 PLL, this paper proposes a frequency-adaptive improved moving-average-filter-based quasi-type-1 PLL (FAIMAF-QT1 PLL). Aiming at the shortcoming of the slow dynamic response of the MAF-QT-1 PLL, a correction link is introduced, and an improved moving-average-filter-based quasi-type-1 PLL (IMAF-QT1 PLL) is obtained. To improve the anti-interference ability of the IMAF-QT1 PLL in response to grid frequency changes, a FAIMAF-QT1 PLL and a corresponding digital implementation scheme are proposed. The regulator parameter setting method is proposed based on the small-signal model of the FAIMAF-QT1 PLL. Simulation and experimental results show that the FAIMAF-QT1 PLL can accurately track the grid voltage phase in the presence of power grid frequency fluctuations, phase angle jumps, distorted harmonic injections and unbalanced voltage drops and has good steady-state and dynamic performance.

A methodology for setting the injection moulding process parameters for polymer rapid tooling inserts

Purpose Polymer rapid tooling (PRT) inserts can be used as injection moulding (IM) cavities for prototyping and low volume production but lack the robustness of metal inserts. Metal inserts can withstand high injection pressure and temperature required, whereas PRT inserts may fail under similar parameters. The current method of parameter setting starts with using the highest pressure setting on the machine and then fine-tuning to optimize the process parameters. This method needs modification, as high injection pressures and temperatures can damage the PRT inserts. There is a need for a methodical process to determine the upper limits of moulding parameters that can be used without damaging the PRT inserts. Design/methodology/approach A case study analysis was performed to investigate the causes of failure in a PRT insert. From this, a candidate set-up process was developed to avoid start-up failure and possibly prolong tool life. This was then tested on a second mould, which successfully avoided start-up failure and moulded 54 parts before becoming unusable due to safety issues. Findings Process parameters that are critical for tool life are identified as mould temperature, injection pressure, injection speed, hold pressure and cooling time. Originality/value This paper presents a novel method for setting IM process parameters for PRT inserts. This has the potential to prevent failure at start up when using PRT inserts and possibly extend the operating life of the PRT inserts.

GAAP: A Genome Assembly + Annotation Pipeline.

Genomic analysis begins with de novo assembly of short-read fragments in order to reconstruct full-length base sequences without exploiting a reference genome sequence. Then, in the annotation step, gene locations are identified within the base sequences, and the structures and functions of these genes are determined. Recently, a wide range of powerful tools have been developed and published for whole-genome analysis, enabling even individual researchers in small laboratories to perform whole-genome analyses on their objects of interest. However, these analytical tools are generally complex and use diverse algorithms, parameter setting methods, and input formats; thus, it remains difficult for individual researchers to select, utilize, and combine these tools to obtain their final results. To resolve these issues, we have developed a genome analysis pipeline (GAAP) for semiautomated, iterative, and high-throughput analysis of whole-genome data. This pipeline is designed to perform read correction, de novo genome (transcriptome) assembly, gene prediction, and functional annotation using a range of proven tools and databases. We aim to assist non-IT researchers by describing each stage of analysis in detail and discussing current approaches. We also provide practical advice on how to access and use the bioinformatics tools and databases and how to implement the provided suggestions. Whole-genome analysis of Toxocara canis is used as case study to show intermediate results at each stage, demonstrating the practicality of the proposed method.

Sliding mode extremum seeking control based on improved invasive weed optimization for MPPT in wind energy conversion system

The sliding mode extremum seeking control (SMESC) could track the maximum power point (MPP) of wind energy conversion system (WECS) without wind speed or wind turbine parameters. Inappropriate SMESC parameters would cause steady-state oscillation and increase tracking time. This paper proposed an improved invasive weed optimization (IIWO) to optimize the SMESC parameters. The algorithm developed a new stochastic reproductive strategy to enhance its robustness and simplify the coding. Meanwhile, IIWO optimized double parameters coordinately to replace traditional parameter setting methods of SMESC, which could make the parameters meet the different requirements simultaneously for high efficiency. Simulation results showed that proposed IIWO-SMESC method yielded a better transient response, steady-state stability, and robustness than traditional hill-climbing search (HCS) and SMESC method.

IIWO Based Sliding Mode Extremum Seeking Control for MPPT in Wind Energy Conversion System

Abstract The sliding mode extremum seeking control (SMESC) could track the maximum power point (MPP) of wind energy conversion system (WECS) without wind speed or wind turbine parameters. Inappropriate SMESC parameters would cause steady-state oscillation and increase tracking time. This paper proposed an improved invasive weed optimization (IIWO) to optimize the SMESC parameters. The algorithm developed a new stochastic reproductive strategy to enhance its robustness and simplify the coding. Meanwhile, IIWO optimized double parameters coordinately to replace traditional parameter setting methods of SMESC, which could make the parameters meet the different requirements simultaneously for high efficiency. Simulation results showed that proposed IIWO-SMESC method yielded a better transient response, steady-state stability, and robustness than conventional hill-climbing search (HCS) and SMESC method.

An Efficient Adjustment of Genetic Algorithm for Pareto Front Determination

Abstract The Pareto front determination is an important part of multiobjective problem solving when two or more contradictory objectives must be considered. This paper deals with the emergency service system design problem where the demand for minimal average response time stands in opposition to the demand that maximal travel time over all users should be as small as possible. On the contrary to the iterative approach employing mathematical programming, we focus on adjustment of genetic algorithm which builds the Pareto front by updating an elite set of individuals. As the genetic algorithm belongs to the family of metaheuristics, it is commonly awaited that its performance is very sensitive to setting of its parameters. That is why the focus of this paper is devoted to such method of parameter setting, which is most suitable for efficient estimate Pareto front determination by the genetic algorithm.

Face hallucination through differential evolution parameter map learning with facial structure prior

Current learning based face hallucination approaches mainly focus on how to design a reasonable objective function, such as using different assumptions and incorporating different regularization terms, but do not give a reasonable way of selecting the model parameters. In this paper, we propose to exploit the facial structure prior to learn a parameter map based on differential evolution. Specifically, we claim that different position patches have different parameter settings because of their different statistical properties, and patches from the same position of different face images should have similar parameter settings. As a result, we first learn a parameter map for each training sample by leveraging an evolutionary algorithm based on differential evolution, and then fuse these learned parameter maps to an optimal parameter map for testing via mean-pooling strategy. Finally, we use the predicted parameter map to guide the co-occurrence relationship modeling in different regions of the input low-resolution (LR) face image. Experimental results demonstrate that, even without seeing the ground truth, results of proposed parameter map learning method are comparable to or better than those traditional unified parameter setting methods and some recently proposed deep learning methods.

An image segmentation method of a modified SPCNN based on human visual system in medical images

An image segmentation method of a modified simplified pulse-coupled neural network (MSPCNN) based on human visual system (HVS) is proposed for medical images. The method successfully determines the stimulus input of the MSPCNN according to the characteristics of PCNN and HVS. In order to accomplish the goal, we attempt to deduce the sub-intensity range of central neurons firing by introducing neighboring firing matrix Q and calculating intensity distribution range based on a new MSPCNN(NMSPCNN), and then reveal the way how sub-intensity range parameter Sint generates the stimulus input Sioij closer to HVS. Besides, we try to substitute the above stimulus input into the MSPCNN to extract more suitable lesions for medical images. In contrast to prevalent PCNN models, the MSPCNN has higher segmentation accuracy rates and lower computational complexity because of the parameter setting method. Finally, a good proposed method comparing with the state-of-the-art methods has a better performance, presenting the overall metric OEM with MIAS of 0.8784, DDSM of 0.8606 and gallstones of 0.8585.

Optimizing Neural Network Parameters Using Taguchi’s Design of Experiments Approach: An Application for Equivalent Stress Prediction Model of Automobile Chassis

Artificial neural networks (ANNs) have been successfully applied to problems in different fields including medicine, management, and manufacturing. One major disadvantage of ANNs is that there is no systematic approach for model design. Most literature suggests a trial-and-error method for parameter setting which requires more time. The accuracy of the ANN model greatly depends on the network parameter settings including the number of neurons, momentum, learning rate, transfer function, and training algorithm. In this paper, we apply Taguchi’s design of experiments approach to determine the optimum set of parameters for an ANN trained using feed forward back-propagation. We present a case study of an equivalent stress prediction model for an automobile chassis to demonstrate the implementation of the approach. After training the network, the optimum values of the ANN parameters are determined according to the performance statistics. The performance of the ANN is superior using the Taguchi method to optimize the parameters compared with random parameter values.

Studies on test technique of stress concentration for ferromagnetic component based on permeability

The stress concentration detection technology based on the permeability is an evaluating method on the stress concentration which is according to the induction voltage signal of the closed magnetic circuit composed of the probe and the specimen. The permeability is related to the detection signal, but also to the degree of stress concentration. Through the permeability parameter, the relation between the detection signal and the degree of stress concentration can be established. The permeability measurement technique can be used to detect various micro-structural changes of component related to permeability, such as stress concentration, fatigue damage, aging and transformation. The basic principle of permeability measurement technology is analyzed, and the optimum setting method of detection parameters is discussed. Taking steel 20 as an example, the relationships between the detected signal and the tensile stress, tensile residual stresses have been studied experimentally which is based on the measured signals data. It is found that the change of detection signal caused by tensile stress can reach 33.3%, and the change of detection signal caused by residual stress after unloading can reach 35.8%. It is also found that the detection signal is particularly sensitive to the yield strength, and the signal will decrease sharply when the stress exceeds the yield strength. According to the characteristics of the detected signal, it can effectively detect the stress state in a certain area of the specimen, and has a broad application prospect.

One Parameters Optimization Setting Method of PSS4B and Test Verification

As a new type of multiband power system stabilizer, PSS4B has good engineering application prospects due to the huge potential of its inhibition of oscillation in different frequency bands. Aim at the shortcoming of lacking general applicability for PSS4B typical parameters, a hybrid particle swarm optimization algorithm is introduced into the optimization process for PSS4B parameters based on the method of center frequency in this paper, and good phase compensation effect is obtained. By testing the phase frequency characteristic without compensation of self shunt excitation system of Sanjiangkou No.1 generator, PSS4B functional verification test is carried out on the new generation of excitation regulator EXC9200 for the first time. Finally, PSS4B field parameter setting method and the process is summarized, which provides an effective way for PSS4B putting into operation.

Research on the Inductance/Capacitance Switch Model for an LCC-HVDC Converter in an AC/DC Hybrid Grid

In order to improve the simulation speed of the AC/DC hybrid grid, the inductance/capacitance (L/C) switch model for line-commutated converter of high-voltage direct current (LCC-HVDC) is presented in this study. The time domain modeling method is used to analyze the circuit of L/C switch model for the six-pulse system in LCC-HVDC in a switching period. A parameter setting method of L/C switch model is proposed considering the transient response, the steady state performance, switching losses and simulation error of the switch. The inductance/capacitance (L/C) switch model for LCC-HVDC has the advantage of keeping the admittance matrix unchanged regardless of the change of switching state, which improves the simulation efficiency. Finally, the validity of the parameter setting method is verified. Compared with the test results of PSCAD/EMTDC, the accuracy of the proposed LCC-HVDC simulation model is proved. The model is suitable for real-time or offline simulation of AC/DC hybrid grid.

Research on the PID control of the ESP system of tractor based on improved AFSA and improved SA

The paper uses the electronic stability program (ESP) on tractors in order to improve their trafficability and steering stability. The paper builds a full-tractor model with an ESP system, as well as a steering-by-wire system based on Matlab and Carsim with the aim to research and improve the ESP system’s control performance. The paper investigated the optimization and the setting method of the PID control parameters. The paper applied the speed and the position update mode of the particle swarm optimization (PSO), the probability judgment Metropolis rule of simulated annealing algorithm (SA), the non-uniform mutation idea of genetic algorithm (GA), and the custom initial swarm implantation method into the artificial fish swarm algorithm (AFSA) in order to improve the AFSA. This paper proposes a new method based on the improved AFSA and the improved SA that would simulate the artificial setting of the PID parameters. This method alters the concurrent optimization process of the PID parameters into a process that is initially serial and then becomes concurrent. The new method is then compared with the parameter setting methods based standard AFSA and the improved AFSA. The comparison results showed that the improved AFSA had a faster rate of convergence and a better precision of optimization. The new setting method for the PID parameters improved the PID’s control result more effectively and enabled a tractor with an ESP system to change directions at the expected yaw velocity.

Hardware detection and parameter tuning method for speed control system of PMSM

In this paper, the development of permanent magnet synchronous motor AC speed control system is taken as an example, aiming to expound the principle and parameter setting method of the system hardware, and puts forward the method of using software or hardware to eliminate the problem.

Consideration for application of central pattern generator to pneumatic anti-vibration apparatus (Parameter setting of CPG, change of switch input, and comparison of both inversion and non-inversion CPG)

For pneumatic anti-vibration apparatus (AVA) used in the precision positioning field, the authors have pursued the possibility of applying Central Pattern Generator (CPG) and realized its application in order to suppress flow disturbance caused by the pressure variation of the compressed air supplied to the pneumatic AVA. In the past, CPG has been mainly used for generation of desired values, such as analysis of biological movement and motion control of a quadruped walking robot. On the other hand, CPG has been implemented in the loop of the control system to improve the damping ability of the structure by the mass damper. The authors have also tried to improve the suppression effect of the disturbance by implementing CPG in the same way. However, the background of determining the parameters of CPG is not shown in any relevant documents. Therefore, this paper describes the parameter setting method for implementing CPG to the pneumatic AVA in detail. In addition, the characteristics and performances of CPG which have not been mentioned so far are revealed. Concretely, when switch input and signs for CPG input stage are changed, the influence of these is verified. These are summarized as consideration for application of CPG to the pneumatic AVA.

Application of dynamic milling in stainless steel processing

This paper mainly introduces the method of parameter setting for NC programming of stainless steel parts by dynamic milling. Stainless steel is of high plasticity and toughness, serious hard working, large cutting force, high temperature in cutting area and easy wear of tool. It is difficult to process material. Dynamic motion technology is the newest NC programming technology of Mastercam software. It is an advanced machining idea. The tool path generated by the dynamic motion technology is more smooth, more efficient and more stable in the machining process. Dynamic motion technology is very suitable for cutting hard machining materials.

SNR Enhancement in Phase-Sensitive OTDR with Adaptive 2-D Bilateral Filtering Algorithm

An adaptive image restoration algorithm based on 2-D bilateral filtering has been proposed to enhance the signal-to-noise ratio (SNR) of the intrusion location for phase-sensitive optical time domain reflectometry (Ф-OTDR) system. By converting the spatial and time information of the Ф-OTDR traces into 2-D image, the proposed 2-D bilateral filtering algorithm can smooth the noise and preserve the useful signal efficiently. To simplify the algorithm, a Lorentz spatial function is adopted to replace the original Gaussian function, which has higher practicability. Furthermore, an adaptive parameter setting method is developed according to the relation between the optimal gray level standard deviation and noise standard deviation, which is much faster and more robust for different types of signals. In the experiment, the SNR of location information has been improved over 14 dB without spatial resolution loss for a signal with original SNR of 6.43 dB in 27.6 km sensing fiber. The proposed method has the potential to precisely extract intrusion location from a harsh environment with strong background noise.

The Research on Application of Cadna/A Software in Noise Prediction of Urban Substation

Nowadays, the environmental protection problem which is caused by urban substation noise is getting more and more serious. Before substation noise management, we should understand substation noise value at boundary or sensitive point and be able to reasonably judge noise para-normal area, distribution form, etc. In this paper, the Cadna/A calculation software is adopted to establish the substation prediction model. Through analyzing the characteristics of the urban substation, we compare actual test value and predictive value and verify the accuracy of the prediction. According to the real situation of substation, the parameter settings of noise prediction software were analyzed, and the basic principles of layout optimization based on noise control in substation were determined. After the layout optimization design of substations, the adjustment measures of main transformer, reactor, firewall and buildings were proposed. In this study, the parameter setting method in analysis of noise prediction was proposed. And it also provides technical basis for substation noise prediction. The layout optimization design method based on noise control was proposed.

Research of Fuzzy-PID Controller Based on Nonlinear Optimization Method

The time delay often exists in the industrial process. Its control effect by conventional PID controller needs to be improved. In this paper, a method of parameter setting based on nonlinear optimization is proposed. Combined with Fuzzy-PID, the robustness of the control system is improved. Compared with traditional PID, the proposed controller shows better control effect with the variation of controlled object.

符合法测量<sup>60</sup>Co放射源活度的精度研究

本文介绍了γ-γ符合法测量放射源活度的基本原理，阐述实验过程中为达到最高精度，各个插件参数的设置方法；详细讨论了测量时间对测量结果的影响，并讨论在该条件下符合法测量源活度能够达到的精度。实验结果表明：最佳测量时间为100 s；符合法实验测得60Co放射源的活度为142,620 ± 924 Bq，测量精度为308 Bq，测量结果的相对偏差为0.217%；实验所得的源活度与实验时源的参考活度相对偏差为1.09%，在误差范围内一致。 This paper introduces the basic principle of γ-γ coincidence method for measuring the activity of radioactive source, and the setting method of each plug-in parameter is described in order to achieve the highest precision. The influence of the measurement time on the measurement results is discussed in detail, and the accuracy of the measurement method can be achieved under the condition of the method. The experimental results show that the best measurement time is 100 s. The activity of the 60Co radioactive source is 142,620 ± 924 Bq, the measurement accuracy is 308 Bq, and the relative deviation of the measurement result is 0.217%. The experiment turns out that the activity and experimental time the relative deviation of the reference activity of the source is 1.09%, which is consistent within the error range.