Virtual Sound Intensity Analyzer

The Virtual Sound Intensity Analyzer is a new instrument which has more advantages than the traditional Sound Analyzer. This Analyzer is based on fast Fourie transformation and virtual instrument technique.As an application, combining software and hardware, all kinds of weight noise sound level measurement and real-time noise octave analyzes realized synchronously. The design method has been introduced from three ways, which includes hardware, software and panel. An applied example and error analyze of Virtual Sound Intensity Analyzer are given.This Analyzer is low cost, small volume. and it is also easy to operate. It can be widely used in actual applications.     

Error Analysis and Modification of Virtual Instrument System

The errors of each parts of virtual instrument system, which are produced in the signals transfer process, are introduced. These errors include sensor error, signal conditioning error, data acquisition error and data dealing error, etc. The main error can be found by analyzing the influence of these errors on different virtual instrument system. The methods of errors modification are also discussed. It's an effective method that modifying system errors, especially nonlinear errors, by software. At last, as a good example, the error analysis and modification of Virtual Noise Analysis Instrument is given.     

Error Description and Modification of Virtual Measuring Instrument

When measuring, virtual instruments are inevitable to cause error damaging the precision of measuring resuits. It presents error constitution, methods of error transfer and synthesis of virtual measuring instrument. Based on the analysis of error transfer and synthesis of virtual measuring tual measuring instrument and gets the method of dealing instrument, it generalizes the error constitution formula of virwith errors. Then, errors can be modifyed.     

用模糊神经网络提高洪峰预报精度的研究

在大量研究的基础上,提出了基于模糊理论的神经网络改进算法,用来提高对洪峰的预报精度。该方法在网络训练时引入模糊理论来确定网络误差修改的程度。引入的算法增大了大值输出样本和期望输出的误差,使得网络向着提高洪峰拟合精度的方向修改权重。应用表明,改进的模糊BP神经网络能够较好的反映洪水演进机理,提高了神经网络洪水预报模型对洪峰的预报精度,保证了洪峰预报的可靠性。     

Virtual FFT Spectrum Analyzer Based on DSP Technology

Virtual Instrument has become an important direction of instrument development, now it has been widely used in many fields. FFT analysis is a widely used method in mechanical engineering, fault detection and many other fields. However, the traditional FFT analyzer is expensive and is not easy to upgraded. The birth of virtual FFT Spectrum Analyzer gets rid of the limit of traditional FFT analyzer, and paves the way for the application of FFT analyzer. The uses of DSP technology make the future broadened of Virtual Instrument. This article ,based on the deep study of DSP system, designs a virtual FFT Spectrum analyzer based on DSP technology. The design is new and of great practicality, which indicates the important role of Virtual Instrument in the development of instruments.     

Design of Virtual Instrument for Automobile Based on PC/104

The design of virtual instrument for automobile based on PC/104 has been presented by comparing with the traditional auto meter. The paper focuses on the development environment, system construction and operation principle. The data of the virtual instrument is transported by CAN bus, and this system can monitor in real-time, display in digit and fire the alarm to the super-speed, save the record.     

A Virtual Wavelet Transform Analyzer for the Signal Analysis Based on the Direct Algorithm

A virtual wavelet transform analyzer for the signal analysis based on the direct algorithm is introduced so that the discrete wavelet transform and continuous wavelet transform is maken to signal in the direct algorithm. The authors first introduce the direct algorithm of the WT, which is numerical algorithm obtained from the original formula of the wavelet transform by directly numericalizing. Then some conclusions are drawn on the direct algorithm. The examples are the sampling principle and technology for the wavelets, the limitation of the scale range of the wavelets and the measures to solve the edge phenomenal in the direct algorithm of the discrete wavelet transform, and some conclusions in the direct algorithm of the continuous wavelet transform. The virtual wavelet transform analyzer for the signal analysis based on the direct algorithm explored based on these studies and combined with virtual instrument technique can make the discrete wavelet transform and continuous wavelet transform to signal with any basic wavelet. It can be applied in studying the property of any basic wavelet and learning the theory on the wavelet transform, and also in making some engineering signal analysis. In the end, the authors give some typical examples for the application of the virtual analyzer. These examples show that the analyzer can be applied in many situations.     

Junction stiffness analysis and vibration noise prediction of wind power speed-increase gearbox

In order to study the vibration characteristics and radiation noise of wind power speed-increase gearbox, a torsional vibration model of wind power speed-increase gearbox is established based on the analysis of supporting stiffness of bearing and contact stiffness of gear pairs. By solving the vibration differential equation with the help of Matlab, the frequency and corresponding vibration mode are obtained. With taking stiffness excitation, error exaction and meshing impact exaction into account, the dynamic finite element model of speed-increase gearbox is set up, and the dynamic response simulation is carried out. Regarding vibration displacement of the nodes on gearbox surface as boundary condition, an acoustic boundary element model of speed-increase gearbox is built. The surface acoustic pressure of gearbox and the radiation noise of field points are solved by the direct boundary element method. The results show that there is a great difference between torsion frequency and excitation frequency of wind power speed-increase gearbox, and so the resonance doesn't occur. The maximum structural noise and radiation noise mainly appear near the double octave of the gears meshing frequency of high-speed grade.     

Calculation Method of Hydraulic Characteristics for Direct-Return Chilled Water System

In order to optimize design and operation, it is necessary to calculate accurately hydraulic characteristics large central air-conditioning systems. Simplified Model can not be applied to hydraulic calculation of large pipe network topological structure for its large calculation error. Taking into account the regulating characteristics of terminal branch temperature regulating valve, a direct-return chilled water system is studied, an accurate mathematical model of pipe network hydraulic characteristics has been established and a computer logic algorithm with virtual flow has been given. A direct-return pipe network with ten AHU branches is used as simulation calculation object, the pipe network supply-return water pressure difference is calculated, and also the temperature regulating valve opening and actual flow of each branch are calculated in the condition of different supply-return water pressure difference. The calculated results accord with the natural characteristics of high pressure difference unbalanced for direct-return pipe network. The calculation method can ensure calculation convergence.     

PDA Based Virtual Instrument

Test and Measurement task can be done without limit of time and space by PDA with virtual instrument technology. The structure of PDA based virtual instrument is described firstly. Then PMDS(PDA Measurement Develop System) which can construct virtual instruments efficiently using component technology is introduced, it can enhance quality and efficiency of instruments. Finally, portable spectrum analyzer and mobile temperature monitor is built with PMDS to illuminate the usage of PMDS.     

Analysis on the Effect of Harmonic on the Instruments with Average Value Principle

The application of non-linear load produces a mass of harmonics. The AC voltage meter and the AC current meter used in power system are usually rectifying instruments, which adopt principle of responding to the average value of voltage and current and get the virtual value by using of the proportion between the average value and it. Because they are designed based on the 50 Hz standard sinuous wave, the principle error will occur when the voltageof power system and the current of loads include harmonic. Based on their working principle, this kind of error is analyzed quantificationally. And the result shows that it can not be neglected. The voltage and current meters with real virtual value are proposed.     

Drift error compensation algorithm for fiber optic gyro based on T-S fuzzy modeling

A drift error nonlinear compensation algorithm for Fiber Optic Gyro (FOG) is presented based on T-S fuzzy model with the antecedent parameters identified by G-K clustering algorithm and the error model of T-S fuzzy model with the consequent parameters identified by least square algorithm. The computed results show that this model can compensate the original data effectively, while the error principles of FOG do not need to be understood well. Comparing with the original data, compensation with linear fitting and compensation with neural network, the absolute error of the proposed model reduces by 99%, 96% and 10%, respectively. The error variance reduces by 99%, 98% and 20%, respectively. The results indicate that this proposed algorithm can be simply operated with high precision and easy to realize in engineering.     

Research and Development of the Network Virtual Instrument

This paper introduces a basic concept of network virtual instrument and presents a solving scheme based on the .net framework for web network virtual instrument in which the component technology are used to construct UI component, data-service component, signal-processing component, DB-component, controlling component and data-acquiring component, in accordance to demand these component above can be flexibly put on the right place to realize remote test and control. In the light of the scheme, a set of network oscilloscope based on web is designed to remotely sampling data, and the technology of data base is successfully used to administer the saving and taking of signals in network virtual instrument .     

元动作装配单元误差传递模型及有效路径求解方法

在对机械产品进行"功能-运动-动作"结构化分解的基础上,将影响元动作装配单元装配精度的误差源分为零部件的形状误差、位置误差、装配位置误差和运动误差等四类误差源。引入误差链接模型作为元动作装配单元误差关联关系的基本封装单元,构建结构化误差关联模型——链接网络和链接矩阵,形象描述误差间的耦合嵌套关系。提出基于误差链接模型的装配误差传递路径求解方法,用老鼠迷宫算法搜索所有可能的误差传递路径,以装配精度最高作为判别依据,得到各误差分量的有效传递路径。以蜗杆转动元动作装配单元蜗杆轴线平行度误差有效传递路径为目标,对上述方法进行验证,结果表明该方法能够高效地搜索到所有误差传递路径,并快速获得有效传递路径。该方法的提出为整机装配过程质量预测与控制提供了理论依据。     

The application of rough sets-neural network theory to mine ventilation system evaluation

To solve the instability problem of established sample in the neural network evaluation method for mine ventilation system, a comprehensive evaluation of the ventilation system is carried out based on rough sets and BP neural networks. Taking the ventilation system of a mine as an example, the classification quality of raw data samples are tested by using rough set data analysis system. Then, based on artificial neural network theory, a rough sets-neural network evaluation model of a mine ventilation system is established and a new rough sets-neural network evaluation method of mine ventilation system is formed. The results show that, after the model validation of data and application, its theoretical evaluation results are in line with the actual situation, and the network total error is less than 0.004. It shows that the comprehensive evaluation method based on rough sets-neural networks has a good effect in evaluating mine ventilation system in practical application.     

Applying of the DSP Technology in the Virtual Instrument System

The hardware architecture and instruction set of the digital signal processor leads to its high speed and precision in processing data. Aiming at the virtual instrument's deficiency in speed and precision resulting from the limit of the computers' development, the author brings forward a method to promote the performance of the virtual instruments using the DSP technology. Implementing the complex algorithms in DSP and using the principal and subordinate DSP structure or DMA technology in the data acquisition card of the virtual instrument can promote the virtual instrument's real-time characteristic greatly. Several key technologies are introduced in realizing the data acquisition and processing card. The experiment shows that the digital signal processors have higher speed and precision than the computers when implementing complex algorithms, and that using the DSP to implement the algorithms is an effective method to promote the virtual instrument's performance.     

An improved localization algorithm based on RSSI for landslide monitoring

In order to overcome the existing problems of low automation, high cost and difficult to implement in the area of landslide monitoring, this paper presents a new method of RSSI (Received Signal Strength Indicator)based positioning technology without any one-off instruments to monitor landslide surface displacement. By adding weighted factors, the improved positioning algorithm can estimate the parameters of the path loss model dynamically and calculates the communication distance of network nodes in real-time, which can improve positioning precision and reduce the impact of environmental changes on it. The MATLAB experiments show that, compared with the traditional RSSI based localization algorithm using fixed pass loss model, the improved algorithm could significantly reduce the average error.     

山西日光温室逐日极端气温预测模型研究

利用山西省忻州市日光温室的室内小气候观测数据及气象站资料,用BP神经网络及逐步回归法建立以多种输入变量的不同天气条件下的日光温室内最高温度、最低温度的模型。结果表明,利用BP神经网络及逐步回归法建立的模型R2均在0.96以上,RMSE与AE大部分在2℃之下。利用逐步回归方法在模拟日光温室内晴天最高、最低温度和寡照的最高温度精度较高,利用BP神经网络模型在多云的最高、最低温度与寡照的最低温度模拟的精度较高。选择精度更好的模型对日光温室的极端气温做准确的预测,可为山西省设施农业的管理和调控及小气候预报提供支持。     

Prediction and Analyses of Residual Chlorine Based on Support Vector Regression in Urban Water Distribution System

Support vector regression(SVR) algorithm is an application of structural risk minimization principle in function regression.In this paper,a residual chlorine prediction model based on SVR is established by using the data of manual sampling residual chlorine of water distribution system in a certain city in the north of China.SVR model is compared with the artificial neural network and multivariate linear regression.The result shows that SVR model has better generalization ability for small samples,the predicted average relative error of all monitoring points is 1.80%~8.73%,and can achieve unique and globally optimal solutions.It is practical and can solve the problem for small samples of residual chlorine when the fit precision of model is good but the predicted effect is worse.     

Intelligent Extracting Method for Feature Mode of Electric Days Load

Generally there have a number of bad data in the electric load data and it affects the precision of load forecasting,so it is necessary for extracting the feature mode of days load data,then cleaning the load data before it is used to forecasting electric load or performing power system analysis.Inspired by soft clustering thought,a intelligent feature mode of days load data extracting method is proposed based on the mutual offset of fuzzy c-means clustering arithmetic and Kohonen self organization feature map neural network.With the merits of not only high extracting precision and convergent speed but also dynamic calculation capability,the method proposed can supply load forecasting or system analysis procedure with due data.Test results using actual data of Chengqu power supply bureau in Chongqing demonstrate the effectivity and feasibility of the method.