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However, additional difficulties arise, if only experimental fatigue life data from unnotched smooth material specimens is available.
Then a fatigue life estimation approach is needed, that transfers this data from smooth to notched specimen and accumulates the damage with respect to load sequence effects.
Within the current investigation a fatigue life estimation approach based on the FEA results and experimental data is applied to predict residual durability of power steam turbine disk with take into account of operating time.
Fatigue life time prediction for power steam turbine traditionally has involved numerical study in real structure components in order to determine the stress-strain fields and crack modeling based on the theoretical relationship and experimental data.
As follows from these data, the minimal endurance limit corresponds to the upper row of disk and blade rivet attachment.

The data in Figure 3 shows contact resistances in n+ and p+ contact chains while held continuously at 300°C for over 9000 hours.
The data shows a high level of stability with a total change in resistance of below 10%.
With a capacity of 5 off 16 pin DIL devices in a thermal cavity the system is used to collect significant amounts of ageing data.
The well-known SiC MOS transistor instability [2], due to near interface trapping is evident in this data.
The data in Figure 5 shows the leakage current in the offstate as a function of temperature between room 23°C and 400°C.

Several wrappers for the post-processing and data sorting are also made to perform the iterative analysis automatically caused by geometrical changes of transom support bracket attached in the bogie frame.
Data and output files are managed by EDM (Engineering Data Management) in this system.
Whole data used in the implementation are managed in the EDM as three schemes, i.e. project, job and task.
The NominalPost task converts the extracted values to specified input data for the task of NominalBFAP.
I-DEAS, ANSYS and BFAP, iterative analysis and data management can be performed automatically.

Of course, comprehensive data on weld residual stress profiles also deepen our understanding of welding processes, and so improve our capability to achieve high quality welds.
Basically, employment of the contour method involves four steps: specimen cut, contour measurement, data reduction and finite element analysis.
The remainder was valid for further data reduction.
A spline function was employed again to extrapolate the deleted measurements, aiming to generate full data covering the whole plane.
The results in the shaded area in Figure 5 cannot be relied on since it is derived from extrapolated data in the recut region, rather than actual measurements.

The data analysis varies depending on the excitation source and excitation type.
In combination with advanced data analysis methods of classical pulse thermography, the signal to noise ratio can be significantly increased.
Data Processing.
Further data reduction was realized by summarizing the amplitude information for defined time periods.
Figure 4: Data reduction using FFT and sum up of amplitude information to one single frame, which shows the total damaging map.

With accelerations data acquired continuously by a wearable wireless device, a motion pattern recognition method based on acceleration time series analysis of human activity states is proposed.
The system composes by two parts: data sampling module and data processing module, the data sampling module was used to transmit acceleration data that acquired from microprocessor , while the data processing module was used to recognize the activity types by HMM algorithm on computer.
Because of body shaking and other factors, output data contains some pulse signal.
Features are extracted from the raw data using a window length of 128 with 64 samples overlapping between consecutive windows.
Figure.3 is the window process of the resultant accelerations data of walking.

The machining experimental results show that the proposed algorithms are satisfying in reduction of machining time and improvement of machining quality.
But cutting path generation is a very complicated and specialized area, and industry prefers the mature commercial CAM system for cutting path generation; thus most researchers study machining parameter optimization problems with existing cutting path data.
Results showed that the proposed algorithms based on controlling cutting force are both effective and efficient in case of reduction of machining time and improvement of machining quality.

The experimental data can provide the necessary basic data for the design and operation of the practical desulfurization equipments.
The experimental data can provide the reliable design basis for industrial applications of the process.
That means the absorption is strongly enhanced by the very fast reactions(At this time the enhancement factor is high.) and therefore the gas side resistance to mass transfer becomes important[8].The reaction (2) is largely completed when pH drops to about 6, where [SO3-] and the enhancement factor decrease rapidly with pH reduction, whereas the mass transfer resistance increases, so that the desulfurization rate falls quickly.
And the experimental data can testify to the sodium alkali desulfurization process whose essential element is a packed column has its significant technological advance and vast application prospect.
“SO2 Emission reduction and flue gas desulfurization project ,” Bei Jing:Metallurgy Industry Press, 2004, pp.151

Based on the mathematical-statistical analysis of the obtained data the suitable predicting model was developed for determining the thickness of deposited zinc coating reflecting the technological conditions of the acid zinc plating process.
Compared with the references mentioned above, the contribution deals with the determination of the dependence of coating thickness on the factors-level changes and combinations based on the mathematical-statistical analysis experimentally obtained data.
Zinc cations react with electrons and a reduction occurs (Eq. 2).
The values of adjusted index of determination of the data variability for this model are shown in Table 2.
Table 2 Adjusted index of determination of the data variability for chosen calculated model and regression coefficients of factors x[mm] 40,00 35,00 30,00 25,00 20,00 15,00 10,00 5,00 ADJ[%] 59,38 46,64 54,01 53,58 54,24 48,11 39,56 41,47 Abs[-] 16,03 16,89 14,22 15,09 15,00 14,26 14,91 15,30 Zn[g.l-1] 0,36 0,44 0,51 0,21 0,28 0,37 0,36 -0,02 (Zn[g.l-1])2 -0,67 -0,84 -0,33 -0,33 -0,39 -0,42 -0,17 -0,12 Cl-[g.l-1] 0,29 0,57 0,15 -0,18 0,00 -0,16 -0,42 -0,38 (Cl-[ g.l-1])2 0,26 0,16 0,33 -0,20 -0,23 0,02 0,08 0,07 H3BO3[g.l-1] -0,10 -0,25 0,12 0,18 -0,10 -0,24 -0,07 -0,11 (H3BO3[g.l-1])2 -0,52 -0,11 0,10 -0,05 0,01 0,25 -0,07 -0,04 U[V] 0,97 0,99 0,86 0,88 0,96 0,37 0,39 0,37 (U[V])2 0,06 -0,05 0,47 0,33 0,34 0,35 0,32 0,27 T[°C] 0,38 0,96 0,75 0,64 0,43 0,24 0,45 0,69 (T[°C])2 0,65 0,26 0,80 0,67 0,44 0,42 0,41 0,47 t[min] 2,25 2,13 2,04 1,95 1,77 1,61 1,49 1,40 (t[min])2 0,00 -0,57 0,14 -0,26 -0,05 0,12 -0,26 -0,36 The Pareto diagram of the factors significance (Fig. 2) for the quadratic

Round center hole of two cycloid wheel is roller way of arm bearing in the eccentric sleeve, which composed by a circular array meshing needle teeth of cycloid and pin gear, forming internal gear reduction mechanism with a tooth spacing.
When getting stable operation system, the AC signals produced by torque and revolution speed transducer was processed into digital signals through the data acquisition card.
Working principle of test bed Experimental data and analysis In this study, using the 1/9 reduction ratio of cycloid cam speed reducer as test transmission machinery.
During experiment, adjusts the motor speed and load size mainly by industrial computer. 1) Adjust rotational speed to a certain value by industrial computer, then change the load, the experiment data is shown in table 1 and table 2. 2) Keep constant load, then change motor rotational speed, experimental data is shown in table 3.
Since with the increase of speed, the mixing oil power of transmission loss correspondingly, the loss of coupling and bearing power also will increase, which lead to decrease of transmission efficiency, it also can be declined from the data of table 1 and table 2; the same input torque , high speed get low efficiency[5].