Search results

1 – 10 of over 1000
To view the access options for this content please click here
Article
Publication date: 24 January 2019

Tian Lei, Nan Gong, Li Wang, Qin Qin Li and Heng Wei Wang

Because of the logic delay in the converter, the minimum turn on time of the switch is influenced by the constant time. When the inductor current gets to the threshold of…

Abstract

Purpose

Because of the logic delay in the converter, the minimum turn on time of the switch is influenced by the constant time. When the inductor current gets to the threshold of the chip, the control signal will delay for a period. This makes the inductor current rising with the increasing of the clock and leads to the load current out of control. Thus, this paper aims to design an oscillator with a variable frequency protection function.

Design/methodology/approach

This paper presents an oscillator with the reducing frequency applied in the DC-DC converter. When the converter works normally, the operating frequency of the oscillator is 1.5 MHz. So the inductor current has enough time to decay and prevent the power transistor damaging. After the abnormal condition, the converter returns to the normal operating mode automatically.

Findings

Based on 0.5 µm CMOS process, simulated by the HSPICE, the simulation results shows that the frequency of the oscillator linearly decreases from 1.5 MHz to 380 KHz when the feedback voltage less than 0.2 V. The maximum deviation of the oscillator frequency is only 6 per cent from −50°C to 125°C within the power supply voltage of 2.7-5.5 V.

Originality/value

When the light load occurs at the output stage, the oscillator frequency will decrease as the load voltage drops. The test results shows that when the circuit works in the normal condition, the oscillator frequency is 1.5 MHz. When the load decreased, the operating frequency is dropped dramatically.

Details

Circuit World, vol. 45 no. 2
Type: Research Article
ISSN: 0305-6120

Keywords

To view the access options for this content please click here
Article
Publication date: 2 November 2017

Jiliang Mu, Zhang Qu, Zongmin Ma, Shaowen Zhang, Yunbo Shi, Jian Gao, Xiaoming Zhang, Huiliang Cao, li Qin, Jun Liu and Yanjun Li

This study aims to fabricate and manipulate ensemble spin of negative nitrogen-vacancy (NV) centres optimally for future solid atomic magnetometers/gyroscope. Parameters…

Abstract

Purpose

This study aims to fabricate and manipulate ensemble spin of negative nitrogen-vacancy (NV) centres optimally for future solid atomic magnetometers/gyroscope. Parameters for sample preparation most related to magnetometers/gyroscope are, in particular, the concentration and homogeneity of the NV centres, the parameters’ microwave antenna of resonance frequency and the strength of the microwave on NV centres. Besides, the abundance of other impurities such as neutral NV centres (NV0) and substitutional nitrogen in the lattice also plays a critical role in magnetic sensing.

Design/methodology/approach

The authors succeeded in fabricating the assembly of NV centres in diamond and they determined its concentration of (2-3) × 1016 cm−3 with irradiation followed by annealing under a high temperature condition. They explored a novel magnetic resonance approach to detect the weak magnetic fields that takes advantage of the solid-state electron ensemble spin of NV centres in diamond. In particular, the authors set up a magnetic sensor on the basis of the assembly of NV centres. They succeeded in fabricating the assembly of NV centres in diamond and determined its concentration. They also clarified the magnetic field intensity measured at different positions along the antenna with different lengths, and they found the optimal position where the signal of the magnetic field reaches the maximum.

Findings

The authors mainly reported preparation, initialization, manipulation and measurement of the ensemble spin of the NV centres in diamond using optical excitation and microwave radiation methods with variation of the external magnetic field. They determined the optimal parameters of irradiation and annealing to generate the ensemble NV centres, and a concentration of NV centres as high as 1016 cm−3 in diamond was obtained. In addition, they found that sensitivity of the magnetometer using this method can reach as low as 5.22 µT/Hz currently.

Practical implications

This research can shed light on the development of an atomic magnetometer and a gyroscope on the basis of the ensemble spin of NV centres in diamond.

Social implications

High concentration spin of NV in diamond is one of the advantages compared with that of the atomic vapor cells, because it can obtain a higher concentration. When increasing the spin concentration, the spin signal is easy to detect, and macro-atomic spin magnetometer become possible. This research is the first step for solid atomic magnetometers with high spin density and high sensitivity potentially with further optimization. It has a wide range of applications from fundamental physics tests, sensor applications and navigation to detection of NMR signals.

Originality/value

As has been pointed out, in this research, the authors mainly worked on fabricating NV centres with high concentration (1015-1016 cm−3) in diamond by using optimal irradiation and annealing processes, and they quantitatively defined the NV concentration, which is important for the design of higher concentration processes in the magnetometer and gyroscope. Until now, few groups can directly define the NV concentration. Besides, the authors optimized the microwave antenna parameters experimentally and explored the dependence between the splitting of the magnetic resonance and the magnetic fields, which dictated the minimum detectable magnetic field.

Details

Sensor Review, vol. 37 no. 4
Type: Research Article
ISSN: 0260-2288

Keywords

To view the access options for this content please click here
Article
Publication date: 1 October 2003

Zhou Baiqing, Wang Xiaowei, Li Qin and Peng Yisheng

Corrosion of carbon steel and copper is a troublesome problem in low hardness cooling water systems. A new kind of water stabiliser containing hydroxy phosphonocarboxylic…

Abstract

Corrosion of carbon steel and copper is a troublesome problem in low hardness cooling water systems. A new kind of water stabiliser containing hydroxy phosphonocarboxylic acid, zinc salts and molybdate has been developed. Its performance has been proved by means of weight loss tests and a static state scale‐inhibiting test method. The mechanism was also studied using polarisation tests, scanning electron microscope examination and XPS analysis. The test results showed that the corrosion rate of carbon steel and copper could be reduced to 0.0136 and 0.0010 mm/a, respectively. A compact film containing P, Mo and Zn was formed on the surface of carbon steel, by means of which the steel was protected.

Details

Anti-Corrosion Methods and Materials, vol. 50 no. 5
Type: Research Article
ISSN: 0003-5599

Keywords

To view the access options for this content please click here
Article
Publication date: 23 September 2020

Qin Li, Huifeng Zhu, Guyue Huang, Zijie Yu, Fei Qiao, Qi Wei, Xinjun Liu and Huazhong Yang

The smart image sensor (SIS) which integrated with both sensor and smart processor has been widely applied in vision-based intelligent perception. In these applications…

Abstract

Purpose

The smart image sensor (SIS) which integrated with both sensor and smart processor has been widely applied in vision-based intelligent perception. In these applications, the linearity of the image sensor is crucial for better processing performance. However, the simple source-follower based readout circuit in the conventional SIS introduces significant nonlinearity. This paper aims to design a low-power in-pixel buffer circuit applied in the high-linearity SIS for the smart perception applications.

Design/methodology/approach

The linearity of the SIS is improved by eliminating the non-ideal effects of transistors and cancelling dynamic threshold voltage that changes with the process variation, voltage and temperature. A low parasitic capacitance low leakage switch is proposed to further improve the linearity of the buffer. Moreover, an area-efficient SIS architecture with a sharing mechanism is presented to further reduce the number of in-pixel transistors.

Findings

A low parasitic capacitance low leakage switch and a gate-source voltage pre-storage method are proposed to further improve the linearity of the buffer. Nonlinear effects introduced by parasitic capacitance switching leakage, etc., have been investigated and solved by proposing low-parasitic and low-leakage switches. The linearity is improved without a power-hungry operational amplifier-based calibration circuit and a noticeable power consumption increment.

Originality/value

The proposed design is implemented using a standard 0.18-µm CMOS process with the active area of 102 µm2. At the power consumption of 5.6 µW, the measured linearity is −63 dB, which is nearly 27 dB better than conventional active pixel sensor (APS) implementation. The proposed low-power buffer circuit increase not only the performance of the SIS but also the lifetime of the smart perception system.

Details

Sensor Review, vol. 40 no. 5
Type: Research Article
ISSN: 0260-2288

Keywords

To view the access options for this content please click here
Article
Publication date: 6 July 2015

Jiahuan Du, Qiang Li, Chuanli Qin, Xugang Zhang, Zheng Jin and Xuduo Bai

– The purpose of this paper is to develop nitrogen-enriched carbon (NC) with high conductivity and specific capacitance as electrode materials for supercapacitors.

Abstract

Purpose

The purpose of this paper is to develop nitrogen-enriched carbon (NC) with high conductivity and specific capacitance as electrode materials for supercapacitors.

Design/methodology/approach

Graphene oxide (GO) was synthesized by the modified Hummers–Offeman method. NC was synthesized by carbonization of melamine formaldehyde resin/graphene oxide (MF/GO) composites. Supercapacitors based on Ni(OH)2/Co(OH)2 composites as the positive electrode and NC as the negative electrode were assembled. The electrochemical performances of NC and supercapacitors are studied.

Findings

The results show that obtained NC has high nitrogen content. Compared to NC-GO0 without GO, high conductivity and specific capacitance were obtained for NC with GO due to the introduction of layered GO. The presence of pseudocapacitive interactions between potassium cations and the nitrogen atoms of NC was also proposed. When the weight ratio of GO to MF is 0.013:1, the obtained NC-GO3 has the highest specific capacitance of 154.07 F/g due to GO and its highest content of N-6. When the P of the asymmetric supercapacitor with NC-GO3 as the negative electrode is 1,326.70 W/kg, its Cps and Ep are still 23.84 F/g and 8.48 Wh/Kg, respectively. There is only 4.4 per cent decay in Cps of the supercapacitor over 1,000 cycles.

Research limitations/implications

NC is a suitable electrode material for supercapacitors. The supercapacitors can be used in the field of automobiles and can solve the problems of energy shortage and environmental pollutions.

Originality/value

NC based on MF/GO composites with high nitrogen content and conductivity was novel and its electrochemical properties were excellent.

Details

Pigment & Resin Technology, vol. 44 no. 4
Type: Research Article
ISSN: 0369-9420

Keywords

To view the access options for this content please click here
Article
Publication date: 6 April 2020

Zheng-Xin Wang, Ji-Min Wu, Chao-Jun Zhou and Qin Li

Seasonal fluctuation interference often affects the relational analysis of economic time series. The main purpose of this paper is to propose a new grey relational model…

Abstract

Purpose

Seasonal fluctuation interference often affects the relational analysis of economic time series. The main purpose of this paper is to propose a new grey relational model for relational analysis of seasonal time series and apply it to identify and eliminate the influence of seasonal fluctuation of retail sales of consumer goods in China.

Design/methodology/approach

First, the whole quarterly time series is divided into four groups by data grouping method. Each group only contains the time series data in the same quarter. Then, the new series of four-quarters are used to establish the grey correlation model and calculate its correlation coefficient. Finally, the correlation degree of factors in each group of data was calculated and sorted to determine its importance.

Findings

The data grouping method can effectively reflect the correlation between time series in different quarters and eliminate the influence of seasonal fluctuation.

Practical implications

In this paper, the main factors influencing the quarterly fluctuations of retail sales of consumer goods in China are explored by using the grouped grey correlation model. The results show that the main factors are different from quarter to quarter: in the first quarter, the main factors are money supply, tax and per capita disposable income of rural residents. In the second quarter are money supply, fiscal expenditure and tax. In the third quarter are money supply, fiscal expenditure and per capita disposable income of rural residents. In the fourth quarter are money supply, fiscal expenditure and tax.

Originality/value

This paper successfully realizes the application of grey relational model in quarterly time series and extends the applicable scope of grey relational model.

Details

Grey Systems: Theory and Application, vol. 10 no. 2
Type: Research Article
ISSN: 2043-9377

Keywords

To view the access options for this content please click here
Article
Publication date: 3 April 2018

Lingling Pei, Qin Li and Zhengxin Wang

The purpose of this paper is to propose a new method based on nonlinear least squares (NLS) for solving the parameters of nonlinear grey Bernoulli model (NGBM(1,1)) and to…

Abstract

Purpose

The purpose of this paper is to propose a new method based on nonlinear least squares (NLS) for solving the parameters of nonlinear grey Bernoulli model (NGBM(1,1)) and to verify the proposed model using the case of employee demand prediction of high-tech enterprises in China.

Design/methodology/approach

First of all, minimising the square sum of fitting error of grey differential equation of NGBM(1,1) is taken as the optimisation target and the parameters of classic grey model (GM(1,1)) are set as the initial value of parameter vector. Afterwards, the structural parameters and power exponents are solved by using the Gauss-Newton iteration algorithm so as to calculate the parameters of NGBM(1,1) under given rules for ceasing the algorithm. Finally, by taking the employee demand of high-tech enterprises in the state-level high-tech industrial development zone in China as examples, the validity of the new method is verified.

Findings

The results show that the parameter estimation algorithm based on the NLS method can effectively identify the power exponents of NGBM(1,1) and therefore can favourably adapt to the nonlinear fluctuations of sequences. In addition, the algorithm is superior to the GM(1,1) model, grey Verhulst model, and Quadratic-Exponential smoothing algorithm in terms of the simulation and prediction accuracy.

Research limitations/implications

Under the framework of solving parameters based on NLS, various aspects of NGBM(1,1) remain to be further investigated including background value, initial condition and variable structural modelling methods.

Practical implications

The parameter estimation algorithm based on NLS can effectively identify the power exponent of NGBM(1,1) and therefore it can favourably adapt to the nonlinear fluctuation of sequences.

Originality/value

According to the basic principle of NLS, a new method for solving the parameters of NGBM(1,1) is proposed by using the Gauss-Newton iteration algorithm. Moreover, by conducting the modelling case about employees demand in high-tech enterprises in China, the effectiveness and superiority of the new method are verified.

Details

Grey Systems: Theory and Application, vol. 8 no. 2
Type: Research Article
ISSN: 2043-9377

Keywords

Content available
Article
Publication date: 8 July 2020

Yang Li, Yaochen Qin, Liqun Ma and Ziwu Pan

The ecological environment of the Loess Plateau, China, is extremely fragile under the context of global warming. Over the past two decades, the vegetation of the Loess…

Abstract

Purpose

The ecological environment of the Loess Plateau, China, is extremely fragile under the context of global warming. Over the past two decades, the vegetation of the Loess Plateau has undergone great changes. This paper aims to clarify the response mechanisms of vegetation to climate change, to provide support for the restoration and environmental treatment of vegetation on the Loess Plateau.

Design/methodology/approach

The Savitsky–Golay (S-G) filtering algorithm was used to reconstruct time series of moderate resolution imaging spectroradiometer (MODIS) 13A2 data. Combined with trend analysis and partial correlation analysis, the influence of climate change on the phenology and enhanced vegetation index (EVI) during the growing season was described.

Findings

The S-G filtering algorithm is suitable for EVI reconstruction of the Loess Plateau. The date of start of growing season was found to gradually later along the Southeast–Northwest direction, whereas the date of the end of the growing season showed the opposite pattern and the length of the growing season gradually shortened. Vegetation EVI values decreased gradually from Southeast to Northwest. Vegetation changed significantly and showed clear differentiation according to different topographic factors. Vegetation correlated positively with precipitation from April to July and with temperature from August to November.

Originality/value

This study provides technical support for ecological environmental assessment, restoration of regional vegetation coverage and environmental governance of the Loess Plateau over the past two decades. It also provides theoretical support for the prediction model of vegetation phenology changes based on remote sensing data.

Details

International Journal of Climate Change Strategies and Management, vol. 12 no. 4
Type: Research Article
ISSN: 1756-8692

Keywords

To view the access options for this content please click here
Article
Publication date: 7 August 2017

Jinjin Wang, Zhengxin Wang and Qin Li

In recent years, continuous expansion of the scale of the new energy export industry in China caused a boycott of American and European countries. Export injury early…

Abstract

Purpose

In recent years, continuous expansion of the scale of the new energy export industry in China caused a boycott of American and European countries. Export injury early warning research is an urgent task to develop the new energy industry in China. The purpose of this paper is to build an indicator system of exports injury early warning of the new energy industry in China and corresponding quantitative early warning models.

Design/methodology/approach

In consideration of the actual condition of the new energy industry in China, this paper establishes an indicator system according to four aspects: export price, export quantity, impact on domestic industry and impact on macro economy. Based on the actual data of new energy industry and its five sub-industries (solar, wind, nuclear power, smart grid and biomass) in China from 2003 to 2013, GM (1,1) model is used to predict early warning index values for 2014-2018. Then, the principal component analysis (PCA) is used to obtain the comprehensive early warning index values for 2003-2018. The 3-sigma principle is used to divide the early warning intervals according to the comprehensive early warning index values for 2003-2018 and their standard deviation. Finally, this paper determines alarm degrees for 2003-2018.

Findings

Overall export condition of the new energy industry in China is a process from cold to normal in 2003-2013, and the forecast result shows that it will be normal from 2014 to 2018. The export condition of the solar energy industry experienced a warming process, tended to be normal, and the forecast result shows that it will also be normal in 2014-2018. The biomass and other new energy industries and nuclear power industry show a similar development process. Export condition of the wind energy industry is relatively unstable, and it will be partially hot in 2014-2018, according to the forecast result. As for the smart grid industry, the overall export condition of it is normal, but it is also unstable, in few years it will be partially hot or partially cold. The forecast result shows that in 2014-2018, it will maintain the normal state. In general, there is a rapid progress in the export competitiveness of the new energy industry in China in the recent decade.

Practical implications

Export injury early warning research of the new energy industry can help new energy companies to take appropriate measures to reduce trade losses in advance. It can also help the relevant government departments to adjust industrial policies and optimize the new energy industry structure.

Originality/value

This paper constructs an index system that can measure the alarm degrees of the new energy industry. By combining the GM (1,1) model and the PCA method, the problem of warning condition detection under small sample data sets is solved.

Details

Grey Systems: Theory and Application, vol. 7 no. 2
Type: Research Article
ISSN: 2043-9377

Keywords

To view the access options for this content please click here
Book part
Publication date: 5 October 2018

Long Chen and Wei Pan

With numerous and ambiguous sets of information and often conflicting requirements, construction management is a complex process involving much uncertainty. Decision…

Abstract

With numerous and ambiguous sets of information and often conflicting requirements, construction management is a complex process involving much uncertainty. Decision makers may be challenged with satisfying multiple criteria using vague information. Fuzzy multi-criteria decision-making (FMCDM) provides an innovative approach for addressing complex problems featuring diverse decision makers’ interests, conflicting objectives and numerous but uncertain bits of information. FMCDM has therefore been widely applied in construction management. With the increase in information complexity, extensions of fuzzy set (FS) theory have been generated and adopted to improve its capacity to address this complexity. Examples include hesitant FSs (HFSs), intuitionistic FSs (IFSs) and type-2 FSs (T2FSs). This chapter introduces commonly used FMCDM methods, examines their applications in construction management and discusses trends in future research and application. The chapter first introduces the MCDM process as well as FS theory and its three main extensions, namely, HFSs, IFSs and T2FSs. The chapter then explores the linkage between FS theory and its extensions and MCDM approaches. In total, 17 FMCDM methods are reviewed and two FMCDM methods (i.e. T2FS-TOPSIS and T2FS-PROMETHEE) are further improved based on the literature. These 19 FMCDM methods with their corresponding applications in construction management are discussed in a systematic manner. This review and development of FS theory and its extensions should help both researchers and practitioners better understand and handle information uncertainty in complex decision problems.

Details

Fuzzy Hybrid Computing in Construction Engineering and Management
Type: Book
ISBN: 978-1-78743-868-2

Keywords

1 – 10 of over 1000