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Based on the recent measured noise data of 220 kV, 500 kV and 750 kV substations, the noise source characteristics of transformer and the attenuation laws in noise transmission are analyzed.
However, transformer noise reduction measures can make manufacturing cost rising sharply along with the increase of the noise reduction effects.
For example, setting the spring or pad vibration reduction in the bottom of transformer can reduce vibration and make noise decreased.
The noise reduction effects is around 20～30dB(A) and can achieve environmental protection limits.
The measured data shows that the BOX-IN structure has a better noise reduction effect than the tradition acoustical enclosure[3].

However, the network needs experimental data to be trained and any configuration outside the experimental range makes the prediction to be not reliable.
For these reasons, here we propose a different approach based on model reduction, particularly in the Proper Generalized Decomposition (PGD) method [3].
And it can be shown (e.g. [6]) that solving a nonlinear problem with standard model reduction techniques and standard linearization schemes is intrinsically inefficient because the complexity of evaluating the nonlinear term remains comparable to that of the original problem.
Cueto: A short review in Model Order Reduction based on Proper Generalized Decomposition, Archives of Computational Methods in Engineering, 18, 395-404, 2011
Sorensen: Nonlinear model order reduction via discrete empirical interpolation, SIAM J.

Using the video detection device, one of the traffic flow information collecting devices, a large number of data in the period of ice-snow of cold area are collected, which is the research base of this paper.
To regression analysis the data relation with the FC of snowy road and the relative humidity and compaction degree of snow, as follows: (3) Through the correlation test obtained R2=0.8806, and the correlation meet the residual requirement.
Through the analysis of traffic data, we can see that the frequency of time headway under the ice-snow condition is close to the negative exponential distribution.
Using 5 minutes as a statistical interval, the traffic flow data such as flow volume and speeds are collected under the non-ice-snow and the ice-snow road surface at the same site.
“Traffic volume reductions due to winter storm conditions.”

This paper has designed a gyro dynamic data generator for simulation according to the gyro signal characteristics.The signal produced by the generator is specified as the gyro data and the optimal estimator for data fusion is designed by using the Kaman filter algorithm.The multi-segment data is analyzed and identified while the optimal data is estimated .The results show no matter how the correlation of the data is, the fusion data has attenuation of 10dB in noise, with its signal-to-noise ratio being enhanced more than 2 times at least.
At present, apart from improving the design and produce technique, the noise reduction processingt is an efficiency method to enhance the MEMS gyro precision[3,4,5].
Towards to the MEMS dynamic data, the optimal estimator for data fusion is designed by using the Kalman filter algorithm .The multi-segment data is analyzed and identified while the optimal data is estimated.
In order to adjust the collecting data , generator install the framing buffer to observe the data in different time.
In order to observe the energy and the frequency of the data, the data is transformed by FFT.

In order to realize simulation modeling of complex particle like corn, change the original rough and approximation methods, with the help of outer outline 3D scanning of the corn granule, scanning data are processed into the data that can be identified by Pro/ENGINEER, which are saved in the data base in this paper; through data mining, approximation simulation of ball filling is done to corn granule with cavity in the working environment of Pro/ENGINEER, which offers real, accurate and workable data for analysis and calculation of discrete element software behind the service.
By using the rotary table, six times of scanning for the corn seed are finished, at last the data of six times of scanning are combined to form the complete scanning data of the corn seed, which is shown in Figure 3.
Fig.3 Combination and Completion of Corn Seed Scanning Data Processing of the Corn Seed Data (1) Import the scanning document of the above corn seed into Geomagic Studio software
Use (reducing noise) command for automatic noise reduction, the level of noise reduction can be chosen according to the practical situation and generally default setting is used
Fig. 4 Geomagic Data Processing Process of the Corn Seed Corn Granule Auto-Filling Modeling Algorithm Ball is used to represent for the particle in the most of 3D DEM models because the contact, detection and calculation of balls are more convenient than those of other shapes.

It analysed the change regulation about the two parameters which are rate of wheel load reduction and overturning coefficient during running of the train.
Two dynamic parameters is selected to analyze which are rate of wheel load reduction and overturning coefficient.
From the figure 3, we can see that when the vehicle runs at the speed of 50km/h cross the curves, the rate of wheel load reduction of the 1st wheelset is 0.0038.
From the data and figure 6, we can get the result that the impact of the lower speed passed the surplus superelevation is better than the higher speed passed the deficient superelevation.
For the absolute value of these data, the overturning coefficient of the deficient superelevation is the biggest.

This paper analyzes the characteristics of the dam on the basis of measured data, using wavelet decomposition and reconstruction method, taking advantage of wavelet transform to do different frequency bands and signal denoising for dam measured data, effectively extracting original information from the measured data sequence with interference error, introducing a effective method to eliminate errors of measured data.
So when using dam safety monitoring data, we should judge and deal with the noise, eliminate the false and save the truth, make the analysis based on reliable data.
Figure 1 is a comparison between original settle measured data and denoised data with soft-threshold.
As can be seen from the figure, after denoising, the data graph becomes smoother.
Fig.1 Comparison of the signal before and after de-noising Conclusion Dealing with dam safety monitoring data with wavelet analysis, analyzing denoise of monitoring data series.

As the main aluminosilicate precursor already used in AASC is a waste product of the metal industry (i.e. slag), the incorporation of waste as aggregate into the AASC will lead to further reduction in the cost of the concrete coupled with significant reduction in its embodied energy and carbon.
With most studies showing a reduction in mechanical properties with the incorporation of wastes as aggregate in concrete [4-7].
And the continuous reduction in the workability was observed with increasing RCA content.
Figure 1: 28 day's mechanical properties of AASC incorporating copper slag as a fine aggregate (data from [10]) Increase in the compressive strength was observed in AASC when RCA was used as a replacement of natural coarse aggregate up to 50%, after which there is a reduction in its compressive strength [15].
Sulphate attack on the AASC mixtures leads to a reduction in their compressive strength, with more reduction in strength observed with increasing RCA content [16].

The renewal of data in each computation is limited because of the time of data transfer unlike the shared memory type workstation.
This brings about the delay of data renewal.
Data Transfer.
Data transfer Imbalanced stress <0.0001MPa Subroutine 1 Subroutine 1 Data transfer All steps ?
Data transfer Imbalanced stress <0.0001MPa Subroutine 1 Subroutine 1 Data transfer All steps ?

At present, there is more storm waterlogging in our urban, one of the main reasons is that there are many disadvantages in rainwater pipe network design, this paper in the pipe network design must be reasonable to determine the ground water runoff coefficient, The ground water time, reduction coefficient, catchment area and position and quantity of gully according to the measured data, and appropriately increasing the recurrence interval according to the actual in engineering, hydraulic calculation as much as possible to select data sets larger diameter, accurate calculation time of flow, to reduce the urban storm waterlogging fundamentally.
If designer select a set of data of smaller diameter corresponding as result, which will cause storm waterlogging easily.
If the design data provided by the construction unit, the designer must be verified, especially terrain, topography, landforms , Ground surface mulch and soil.
These accurate measured data or verify data can provide the basis for the determination of design parameters or important reference: ①runoff coefficient. ②inlet time . ③reduction factor. ④water catchment .
(4)To ensure safety of rainwater transportation, select data groups of larger diameter during hydraulic calculation of rainwater pipes, while ensuring calculation accurate of, These are also important factors to avoid storm waterlogging.