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According to this algorithm, if is the discrete sampling data of original signals , then the decomposition formula of orthogonal wavelet transform of the signal is: (5) In the formula, is the approximate coefficient; is the detail coefficient; and are respectively low-pass filter and high-pass filter; is the number of decomposition layer; is number of the discrete sampling point.
Data Description Sample data come from the bearing data center of Case Western Reserve University [6].
In order to obtain the characteristic frequency, the relevant program is developed based on MATLAB platform, and relevant analysis on fault data is completed by using discrete wavelet transform.
Wavelet Analysis Data Processing Using the discrete wavelet transform, the vibration acceleration signals of rolling bearing are converted to time-scale domain, then, the power spectrum analysis of the high frequency detail signal is completed.
After that, such processing are completed, including wavelet decomposition, noise reduction, reconstruction, Hilbert transform, etc, the characteristics frequency of rolling bearing is accurately found from its power spectrum, which shows the accuracy and effectiveness of this method.

Introduction Main factor analysis is a very useful statistical analysis method,it can through the dimensional reduction and data simplification to research the inner dependent relationship of many variables.
Moreover,this mathematical method is to find a basic structure relationship of the observation data and to use a few abstract variable to express the relationship of data.This few abstract variables are called factors,furthermore,these few factors are capable of reflecting the main information of many of the original variables.The original variables can be observed in the show variable,however,the main factor is potential variables that cannot be observed.
Factor analysis and modeling process Factor analysis steps The main factor analysis steps is as follows,firstly according to the research problem and aim to select the original variables and then standardize the original variables and calculate the original variables and data,then in search of initial common factor and factor loading matrix,and the important step is factor rotating and factor scoring.
zx16-0.052zx17-0.032zx18 Z3=-0.075zx1-0.216zx2-0.013zx3-0.022zx4-0.051zx5+0.001zx6+0.081zx7+0.260zx8+0.196zx9-0.206 zx10-0.336zx11+0.072zx12-0.001zx13-0.001zx14+0.141zx15-0.001zx16-0.042 zx17-0.043zx18 Z4=-0.018zx1+0.012zx2+0.042zx3+0.339zx4+0.357zx5+0.187zx6-0.104zx7-0.085zx8-0.133zx9 -0.181zx10-0.030zx11-0.050zx12+0.053zx13+0.053zx14-0.032zx15+0.053zx16-0.053zx17-0.036zx18 Conclusion Through the main factor mathematical analysis method and respectively testing the eighteen index of physical and mechanical performance,internal structure performance,filtration performance of the automobile engine oil filter materials,such as nominal filtration precision, thickness, weight, average pore diameter,maximum pore diameter,actual filtration precision, maximum fiber diameter, minimum fiber diameter,average fiber diameter,porosity,air permeability, breaking strength, breaking elongation,elongation at break,fracture work,breaking time,bursting strength,bursting elongation.After modeling and data
[4] Sorensen B.L.and Sorensen P.B.Applying cake filtration theory on membrane filtration data.

Equally important is the choice of the method of processing of raw data of sedimentation analysis, ie choice of the method of processing of the sedimentation curve [3].
The data of sedimentation analysis are in good agreement with the results of measurements of the dependence of electrokinetic potential of particles of coal powder in an aqueous medium on the duration of grinding.
Further reduction of z-potential may be due to the consolidation of fine powder particles of coal, which is confirmed by the differential distribution curves of coal particles by size.
In addition, data from the IR spectra can provide information about the link between different structural groups.
These data suggest that during the mechano-chemical processing of coal the profound degradation of coal macromolecules occurs, which affects the yield of distillate of coal.

Hardness curve of laser remelting coating presented three gradients, namely high hardness area, hardness reduction area and low hardness area.
It was evident that the fracture mode of plasma spraying samples was the fracture between coating and substrate, so the experimental data shown in Table 1 were bond strength of coating and substrate.
So data shown in Table 2 were not the bond strength of laser remelting coating and substrate, it was just the bond strength of adhesive.
But through the observation of coating fracture mode and the comparison analysis data of experiment data, we could draw the conclusion that bond strength of coatings after laser remelting treatment was far greater than the bond strength of adhesive as well as the bond strength of plasma spraying coating.
Table 1 Tensile testing data of plasma spraying coating N1-1 N2-2 N3-3 N4-4 N5-5 AVG Maximum fracture load [KN] 7.653 7.546 7.725 7.664 7.708 7.659 Bond strength [Mpa] 24.3 24.0 24.6 24.4 24.5 24.36 Table 2 Tensile testing data of laser re-melting coating N1-1 N2-2 N3-3 N4-4 N5-5 AVG Maximum fracture load [KN] 20.9 21.2 20.5 21.6 21.0 21.04 Bond strength [Mpa] 66.6 67.5 65.3 68.8 66.9 67.02 Analysis of Wear Resistance Test.

Through reasonable use of these collected data, you can draw floor plans, topographic maps, ortho photo images and so on in details, which can also identify ground targets, the distribution of the growth of facilities and resources.
At present, the GPS measuring the aerial mapping can be divided into four steps pictures, namely select GPS observation are nodded, choose GPS observation time observing the assignments, and processing, GPS measurement data
The Processing and Analysis of Glaciers Image As one of the important data sources of spatial information, remote sensing image acquisition equally becomes mature with the development of science and technology.
It broke through the difficulties of access to data, and is in the direction of the positive full application development.
Generally speaking, the reduction of as latitude, which motivates snowline high, the zonal quite obvious that the latitude.

Findings Defaults of Z-R relationship Radar calibration by using data from other measurement system Identification of uncertainty and calibration by errors reduction Radar signal attenuation.
[44] did not believe that radar signal attenuation is effective in data quality.
Data from radar after removing ground clutter are transferred to the polar Cartesian system [62], to perform the data calibration.
Hill, “Automated Bayesian quality control of streaming rain gauge data,” Environ.
Santosa, “Data mining techniques for improved WSR-88D rainfall estimation,” Comput.

Bayesian theory was applied into the damage problems of military engineering, adapted to the uncertain, incomplete damage problem, but whose flaws and hidden information was difficult to show in the sample data [1].
Set the damage sample data of component units as , in which described the physical damage value of component unit, and then could be expressed as a set form, namely .
Set as the threshold of the damage measurement about any component unit of military engineering, and carry on the knowledge reduction about the component units in accordance with the compare from the damage sample to threshold, namely: (6) Here, denoted the improved entropy value of component unit, called "rough entropy", which derived the classification of component units from the damage sample data.
Thus, carry on the metamorphic power weight of component unit under the damage sample data, namely: , (7) Where, showed the weight parameters under this particular damage environment, whose set was erected as , namely .
From the model, simulation, evaluation point, the damage simulation and effect assessment system was designed for military engineering, which provided the sample data for the functional damage reason on the system level

Hong et.al [4] used Lipchitz exponents for the detection of singularities in beam modal data.
Hoelder Exponent (or) Lipschitz Constant The Hoelder exponent (HE) is a mathematical tool that can provide degree of change in distributed data.
Daubachies wavelets were found extremely compatible with data.
Slope of Lipchitz equation v/s crack depth Conclusions Different damage cases are simulated and modal analysis data is processed by wavelet transforms.
The peaks corresponding to edges appeared in 3D-plots are clearly visible in case of strain mode data than displacement mode data.

Introduction Lightweight metals are increasingly utilized in automobile and aerospace industries to satisfy the requirement of weight reduction, improvement in fuel efficiency, and the omission decrease of greenhouse gas.
All of these six fracture criteria were calibrated firstly, and then both of 2D and 3D fracture loci were constructed and compared with the experimental fracture data.
Experimental data of AA2024-T351 Bao and Wierzbicki [7] performed a series of tests on AA2024-T351, which covered a wide range of stress triaxiality from -0.3 to 0.9.
Comparison and Evaluation The accuracy of each fracture criterion discussed above is schematically assessed by comparing the constructed fracture loci to experimental data points as presented in Fig. 1.
The error between predicted EPSF and experimental data is calculated by using the least square method and compared in Table 2.

At the same time, efforts to improve the efficiency of energy usage and the reduction of energy consumption will be carried out.

Power expansion planning model outline 3.2 Input data and basic premise Information in 5th Power Expansion Planning was used for input data for analysis and 2015~2030 were target period to derive Power Expansion Planning.
Then, based on these data, energy supply cost was derived.
Detailed input data are as follows
- Review period : 2015~2030 (16years) - Discount Rate : 7.5% - Demand Data : Using the standard demand prospectivity of the 5th Power Expansion Planning (Demand after 2024 is estimated by applying 2.3% which is the average demand increasing rate) Data for each electric power source Fuel cost (won/kWh) O&M cost (won/kW) Construction cost (won/kW) Unit capacity (MW) avail-ability rate (%) LNG 64.4 - 784,000 700 - Oil 88.1 - 1,254,000 800 - Coal 23.0 - 1,134,000 1000 - Nuke 3.3 - 2,042,000 1400 - IGCC 33.8 44,708 2,905,539 300 - Wind 0 35,038 2,223,546 100 34 Solar 0 13,504 6,979,401 50 25 Scenario for analysis were composed with disposal/maintenance of nuclear-power plants and the proportion of renewable energy in the total power generation based on 2015.

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