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It finds application in ore processing which involves size reduction, generation of large surface area and/or liberation of valuable minerals from their matrices.
It consisted of mill base, an adjustable-speed motor driven by direct current with reduction gear, a rotating joint made by nylon cord, a ball mill and three sensors.
A special computer software was developed using C-language for performing signal acquisition, signal amplification, signal standardization, analog-to-digital conversion, data calculation, measurement result display, data storage and printout.
In order to obtain representative experimental data which can reflect the relationship between the external responses of ball mill and different operation parameters, such as rotation speed, ball load, the ratio of ground materials to grinding balls and pulp density, A 34 factorial design was used to arrange the grinding experiments.
The data were recorded at various time intervals after the mill was run continuously for 15min.

This consideration reflects increasing demand of the rolled products of enlarged dimensions, in particular, because of feasible reduction of welded joints in end items.
Assessment of working capacity of the rolling mill machinery should be initiated with statistical analysis of its breakdowns and failure locations in the course of initial billets mass rolling and the data on production technology indicated in certificate of the machinery, original rolling schemes and accepted rules for production.
The due analysis of published data [6-8] indicates the high rate of breakdowns and outage time of existing rolling mills.
The data given in Table 1 analysis shows that the weakest component of the MDL is the gear reducer, and there is notable difference between operating torque values in details and elements of the line.
According to the [16, 17] data the graphs of the dynamic factors, kd , dependence on the time of filing the deformation zone, tb, for the mill stand No.1 of CWM 1700 HR are plotted corresponding to rolling of the billets differing by weight (Fig. 3 and 4).

According to the experiment data, the relationship between expansion pressure and pull-out strength of Zr/16MnR joints can be derived as follows: Ungrooved joints: S(p)=2928.025-257.65p+7.53p2-0.07p3 (2) Grooved joints: S(p)=-24.56+0.004p+0.096p2-0.0018p 3 (3) Where S is the pull-out strength, MPa, p is the expansion pressure, MPa.
It shows that thermal loading causes significant linearity reduction in the pull-out strength of three kinds of joints.
The proper expansion pressure can obtained high quality connection joint, which consistent with the experiment results. 0 50 100 150 200 250 300 6 8 10 12 14 16 18 Pull-out strength, MPa Temperature, o C Finite element results Experiment data Zr/16MnR 24MPa 0 50 100 150 200 250 300 4 6 8 10 12 14 Pull-out strength,MPa Temperature, o C Finite element results Experiment data Zr/316L 34MPa Fig. 12 Pull-out strength of Zr/16MnR joints at different temperature Fig. 13 Pull-out strength of Zr/316L joints at different temperature Fig. 12, Fig. 13 and Fig.14 show the effect of the temperature on the pull-out strength of three kinds of joints.
It also shows that thermal loading causes significant reduction in the pull-out strength due to the significant difference in the coefficient of thermal expansion between the material of tube and tubesheet.
The expansion joint could become weaker when the temperature is increased, which is also consistent with the experiment observation. 0 50 100 150 200 250 300 350 4 5 6 7 8 9 10 11 12 Pull-out strength, MPa Temperature, o C Finite element results Experiment data Ti/16MnR 34MPa Fig. 14 Pull-out strength of Ti/16MnR joints at different temperature Conclusions In this paper, experiment and finite element analysis were conducted to investigate the connection strength of expanded tube-to- tubesheet joints of different material (zirconium tubes, titanium tubes and 16MnR tubesheets, 316L tubesheet).

To this end, the non-linear restoring force can be represented through a polynomial, whose degree must be chosen sufficiently high to approximate the actual behavior of the system under investigation, on the basis of the available experimental data [11-13]
In such a way it is possible to find at any instant the optimal polynomial representation, through which it is possible to reproduce the experimental data and that involves the minimum number of terms in Eq. 2.
In practical applications, it is possible to start from a linear representation (only α1 and α2 different from zeros) and, if needed, successively increase the polynomial degree till a sufficiently good representation of the experimental data is obtained.
In Fig. 4 the stability diagrams of the modal frequencies and the fitness of the identified model, as a function of the order, are plotted: the fitness is evaluated through Eq. 5 and constitutes a parameter that gives a measure of how good is the identified model at reproducing the experimental data. 2 4 6 8 10 12 14 16 18 20 75 76 77 78 79 80 81 82 83 84 85 System order Fitness (%) 0 5 10 15 20 10 20 30 40 50 60 70 Frequency (Hz) System order Modal damping < 0.15 (a) (b) Fig. 4.
It can be observed that the frequency instantaneous estimator is characterized by a general reduction with time (up to about -40%), except in the interval 21-22 s.

And such data connected with well logging data can be used for predictions of rock properties distribution to delineate sedimentologic heterogeneity.
The derivation of stratigraphic insights from seismic data originated in early 1970s based on 2D seismic data [1].
Seismic stratigraphy into the next millennium; a focus on 3D seismic data.
Stratal slicing, partII: Real 3-D seismic data [J].Geophysics, 1998, 63(2): 514-522
Imaging elements of depositional systems with 3-D seismic data: a case study.

The forming limit curves predicted by the Marciniak-Kuczynski model in each of the cases previously mentioned are compared with experimental data.
The difference between them consists in the number of material parameters needed as input data (four, six, seven and eight different parameters, respectively).
The predicted curves will be compared with experimental data.
The following relationships express the continuity of the strain-rate along the necking band: (8) The mechanical equilibrium at the interface of regions A and B is described by the equations (9) The implicit scheme allows the reduction of the M-K model to the numerical solution of a single non-linear equation [6].
Forming limit curve predicted with Marciniak-Kuczynski model for DC04 steel Conclusions The aim of this paper consists in evaluating the influence of the identification procedure of the BBC2005 yield criterion (use of different sets of mechanical parameters as input data) on the quality of the forming limit curves predicted by the M-K model.

The definition of the material modifications due to processes is based on the expert knowledge and/or experimental data.
Flowchart for the SWORFISH concept/model for assessment of the timber structures safety In that peculiar case, the initial RAW MATERIAL properties cannot be scrutinized from the existing structures, but rather are related to literature or proprietary data collections.
An example of such comprehensive data base is shown on Fig. 3 where weathered structural beams were scanned by means of active (Fig. 3a) and passive (Fig. 3b) thermography [3, 5].
A dedicated research campaign was performed therefore in collaboration with Laboratory of Wood Drying and Thermal Treatment at IVALSA/CNR in order to collect necessary data to characterize both treatment process and resulting products.
Models of changes to the larch wood (Larix sp.) due to treatment in a thermo-vacuum reactor; mass loss (a), hygroscopicity reduction (b), predicted color (c) Conclusions The concept and potential of the novel algorithms for modeling and predicting processes developed under SWORFISH project is shown here.

X rays powder diffraction data were collected for the sintered samples in order to a structural and microstructural analysis.
The first one of the advantages is the cost reduction.
Special samples for electrical conductivity studies were measured using an Agilent 4338B Milliohmmeter; x rays powder diffraction data were collected with a conventional Rigaku Multiplex II diffractometer with a fixed monocromator.
Results and Discussion The important data with copper-nickel-tin samples is shown in Table 2 concerning mixing, compacting, sintering, homogenizing treatments and also values of hardness and electrical conductivity.
The powder diffraction data indicate that the utilized amounts of dopants do not distorted the copper matrix structure significantly.

Constrained independent component analysis (cICA) is a new theory and new method derived from the independent component analysis (ICA).It can extract the desired independent components (ICs) from the data based on some prior information, thus overcoming the uncertainty of the traditional ICA.
Experiments with real-world data The main parameters of the third reducer gearbox are as follows: The actual inputting speed is 975r / min; Matching motor power is 400 kw; reduction ratio is 20; The number of teeth on the gears are: Z1=23,Z2=53,Z3=19,Z4=67,Z5=19,Z6=67.We can calculate the speed of each shaft: n1=975 r / min, n2=423.1 r / min n3=120 r / min n4=34.0 r / min; the rotation frequency: fr1=16.25 Hz, fr2=7.05 Hz , fr3=2.0 Hz, fr4=0.57 Hz； the meshing frequency :fg1=374.0 Hz, fg2=134.1Hz fg3=38.0Hz.
Using DASP2003 whose has Automatic data acquisition and signal processing system to collect vertical, horizontal and axial vibration acceleration signals of three directions.
T., et al:Employing spatially constrained ICA and wavelet denoising, for automatic removal of artifacts from multichannel EEG data.

Studies on stresses around hole-edge and comparisons with test values show that simulated results of xσ and yσ agree well with test data and the relative errors are no more than 15%.
Fig.1 Test principle Test Results Test data are shown in table 1.Least-squares fitting method is used to determine coefficient k .
Table 1. data from direct measurement and electric measurement methods Torque （Nm） Direct measurement Electric measurement k Pre-tightening force of force sensor[KN] pre-tightening strain[×10-6 ] pre-tightening force[KN] 0 0 0 0 Direct measurement: 0.1439 Electric measurement: 0.1472, correlation coefficient is 0.9984. 2 1.45 126 1.23 4 3.12 312 3.05 6 5.22 528 5.16 8 7.20 735 7.18 10 9.43 914 8.94 12 10.89 1001 9.78 14 12.58 1238 12.11 16 13.73 1379 13.49 18 16.05 1627 15.91 Test Conclusions (1) The relationship between pre-tightening torque and force is approximately linear.
The two groups of data are very close indicating credible test results
The main reason is that the reduction of pre-tightening torque coefficient increases pre-tightening force, causing higher interface pressure between bolt and connecting part and larger load component transmitted by friction.