Search results

It can store data and the result of data analysis.
When the process of rap traversal end, The data analysis module will be performed and we will get the final impedance data and graphics. 1.3 Data Acquisition System The data acquisition part of the system uses USB data acquisition card MPS-010601.
The entire data analysis system, we use LabVIEW + Matlab.
Fig. 2 shows the block diagram of the data analysis system.
Fig. 3 Data analysis panel 2.

The EBSD data reveal that these bands are separated by high angle grain boundaries.
The TEM observations revealed that the highest reduction in the (sub)grain size (~ 0.7 µm) has already occurred after 1 ECAP pass and the subsequent ECAP passes have only negligible effect on the (sub)grain size.
The EBSD data indicate that the number of high-angle grain boundaries (θ>15°) measured in the samples after ECAP and subsequent creep exposure is strongly dependent on the number of ECAP passes (Fig. 7).
Conclusions ECAP pressing of coarse-grained Al-0.2wt.% alloy led to the reduction in the grain size to the submicrometer range.

Figure 1 shows the communication process between simulation tool and data acquisition.
As a first step, data obtained from the simulation is passed to the data acquisition.
LabVIEW performs measurement and control tasks and returns data to the building simulation software.
Weather data are accessible by Type 15, which enables reading data at regular time intervals, interpolate them in time steps less than one hour and making them available for other components.
In majority of the test, weather data from Graz was used.

Obtained relationships between the microstructure characteristics and mechanical properties were described using physically based models and used to establish a material specific database for prediction of the mechanical properties from X-ray diffraction data.
Therefore, a number of reference data had to be created experimentally referring to the technological boundary conditions that may occur during wire production and the microstructural and mechanical properties achievable during processing via hot rolling and wire drawing.
The experimental data for filling the database and adapting the corresponding microstructure models have all been generated from material of the same steel batch, smelted and cast in an industrial scale process.
The measurement itself can be performed in relatively short time with sufficient precision and sensing depth and can also be done automated, as well as the evaluation of the data.
Therefore, a set of reference data will be necessary for each steel grade based on the technological background.

The system also contains GPRS data acquisition gateway subsystem, and data processing subsystem.
Data acquisition gateway performance indicators I.
The maximum data transfer rate X. 250Kbps XI.
The server mainly realizes functions of communication, monitoring, parameter setting, data storage, playback, data statistical analysis, tracking through the Internet receiving data sent by data gateway.
Figure.4 The strain gauges acquisition data curve Figure.5 Wireless strain sensing node data acquisition curve Regarding the achievement and shortage of the research, the work of efficiency improvement of node energy collection and power consumption reduction need to be done.

The data shows the average misorientations between the 'parent' and 'daughter' grains are 30º, this value seems too high for only subgrain rotation recrystallisation to be taking place.
From the data it can be seen that the subgrain size and the recrystallised 'daughter' grain size are not the same, the 'daughter' grains are significantly smaller than the subgrains.
The data shows that there is no transition from subgrains to recrystallised 'daughter' grains and the angle of misorientation is too great to have been produced by subgrain rotation alone.
The four crystal orientations for the parent grain are showing nearly exactly the same orientation, which is what we expect from the stereonet data.
The data is showing that the recrystallised 'daughters' on each side of the 'parent' grain show both orientations, so its not one side creating one clusters, but that each side creates a part of each cluster.

The regression equation coefficients were calculated and the data fitted to a second-order polynomial equation for removal of Pb (II), Cu(II),Zn (II) and Cd (II) ions with ME.
The optimal conditions for Pb(II), Cu(II), Zn(II) and Cd(II) removal were also obtained from the model obtained via experimental data.
Experimental data were analyzed with Design-Expert 7.1.3 program including ANOVA to obtain the interaction between the process variables and the response.
Non-significant lack-of-fit is good for data fitness in the model.
The predicted R2 of 0.9991 and adjusted R2 of 0.9980, which are higher than 0.80 and closer to 1.0, indicate the better fitness of model in the experimental data.

The most common one is represented by the reduction of the limit tensions used during the design phase; reductions of up to 70% of the initial value of the allowables.
The amplitude of the delamination zone, obtained from the numerical analysis, was compared with the experimental data; also this comparison showed a correct interpretation of the real phenomenon.
In Tables 2, for the case at 10 J, the comparison between the numerical and experimental data, for the various support fixtures, in terms of peak value of the impact contact force, is shown.
In particular, the correlation of numerical and experimental data were shown in Table 3.
Comparison between numerical and experimental data for the 10 J impact test.

Using again the data of sil54d2 engine for ExtractionMain03 Fig. 4.
The generalization here depends also on the use of more experiment - oriented data concerning the described group under study.
One must interpret these new indices in term of machine damage and operational data.
The whole idea was illustrated by data processing taken from real diagnostic measurements on some Diesel engines.
At the end of the paper, it is postulated that some generalization of SVD is needed, in order to include some other data and matrices concerning the external and internal condition of machine operation.

To improve the performance of PTHE, the fulid should flow to any position in the heat exchanger and reduce the dead zone.Fig.5 3.3 Data reduction and analysis The whole ORC systems was take for reaching the steady condition when all the sensor not to change.
The test data are recordered by data acquisition systems, which the sample rate is 0.2HZ.
To more clear analysis the thermodynamic process, the data reduction are expressed by the list eqution: 1）The total quantity of engine waste heat ,Q Q=Qw+Qe 2）The working fluid absorb heat quantity, Q: Q=m×h1-h4 3）The work of expander do ,W：W=m×(h1-h2) 4） Isentropic efficiency of expander ：ηs=h1-h2h1-h2s 5) Heat rejection for the condenser, Qc： Qc=m×h3-h4 6) Generating efficiency of ORCη=EQ 7) Net generate efficiency of ORC systems： ηe=E-E1Q In the above equation, the Qw,Qe are the heat quantity of coolant and exhaust gas; the h1, h2, h3, h4, hs are respectively the enthalpy of the corresponding location.
Form the ORC systems begin generate elecrity to the steady condition, the test data recorder time is about 2hours and 24minuts.