Search results

Key grinding relationships were analysed along with experimental data in developing the crankshaft pin force grinding models.
Experimental Verification The required data to experimental validate the force crankshaft pin grinding models was obtained on a Landis 6 pin cylindrical crankshaft pin grinder using a Norton 53A54LVS specified grinding wheel.
The analog signals from the strain gauges were converted to digital signals and then converted to computer format by a data-logging card.
The data was later processed to a force reading.
It should also be noted that a reduction in system stiffness also decreases the actual grinding velocity produced, hence the actual distance being ground, which explains why the lower system stiffness values in Fig. 7 take longer to grind the crankshaft pin then the higher values.

Table 1 Skeleton dense type aggregate synthetic grading Mesh size mm) 31.5 19 9.5 4.75 2.36 0.6 0.075 synthetic grading 99.6 81.1 50.5 26.4 17.6 9.0 3.1 upper limit 100 86 58 32 28 15 3 Lower limit 100 68 38 22 16 8 0 Figure 1 Synthetic grading curve Data Analysis The test uses a plurality of cement dosage, to stabilize the powder and mixed with 20% gravel with 1%, 2%, 3 %, 5%, 6%, five cement dosage, of gravel mixed with 40% of 1%, 3%, 5%, 6% four cement dose, determined by heavy compaction test cement dose optimum moisture content and maximum dry density as follows in Table 2 and figure 2.
Table 3 Unconfined compressive strength test results (Mpa) cement dosage（%） 1 2 3 5 6 stable powder 0.95 1.91 2.69 4.04 5.17 gravel mixed with 20% 1.27 2.47 3.39 5.46 6.22 gravel mixed with 40% 1.48 3.66 6.58 7.58 Figure 3 The relationship between unconfined compressive strength and cement dose and gravel mixing amount Table 4 Unconfined compressive strength and cement dose linear relationship linear relation correlation coefficient R2 stable powder Y=0.8067X+0.2091 0.9937 gravel mixed with 20% Y=0.991X+0.3924 0.9971 gravel mixed with 40% Y=1.2519X+0.1305 0.9957 Jilai highway subbase design strength is 2 Mpa[1], and cement stabilized powder in a dose of 3 % cement according to the test results that can meet the design requirements, gravel mixed with 20% or gravel mixed with 40% in a dose of 2 % cement also be able to meet the requirements, that is mixed with a certain amount of gravel can meet the design strength of the cement dose reduction.
Cost Analysis Obtained by the analysis of the test data to meet the requirements of the design strength by mixing a certain amount of gravel, and adding a certain amount of gravel can make the cement dosage reduced, gravel unit price is higher than the powder price, so the need for a variety mixed material cost analysis, the unit price of the various materials is based on the end of 2005 surveys.
According to the analysis of the production of raw materials, mixed with 20% gravel still can not solve the problem of insufficient powder production, and affect the stability of the mixture when mixed with small amount of gravel above data analysis, and therefore do not recommend mixing 20% of the amount of gravel .If mixed with 30% gravel, through the unconfined compressive strength of the interpolation show that when the cement dose is 3%, the unconfined compressive strength can meet the design requirements, the interpolation can be obtained maximum dry density of the maximum dry density of 2.281g/cm3, its cost analysis results is 42.75 yuan/ m3 (only consider the price of materials), a slight increase compared to cement stable powder cost, materials prices increased by 1.512 yuan.
Figure 4 Construction site Summary On the face of the cement stabilized powder and mixed with 20%, 40% gravel test data analysis, and various cost analysis, preliminary conclusions are as follows: (1) instead of powder mixed with a certain amount of gravel is feasible, the same cement dose mixed with gravel mixture unconfined compressive strength than stable powder , cement doses meet the strength requirements slightly there are reduced; (2) With the increasing amount of gravel mixed with within a certain range, the maximum dry density and unconfined compressive strength are also increasing, and the trend is more and more obvious, when the mixing amount is small due to mixture distribution of the gravel mixture larger changes likely to cause the mixture quality unstable; (3)The cost analysis, mixed with a certain amount of gravel has little effect on the material cost, the comprehensive technical and economic factors, recommend adding gravel content is 30%, cement dosage is 2%

Introduction In recent years the emergence of new structural concepts, in particular, frame-monolithic construction required the development of new innovative materials and technologies to strengthen the above-mentioned structures, under the condition of the necessary energy and materials consumption reduction of new developments.
Experimental Program and Research Results The main objective of this study is to conduct a detailed analysis of the test data, based on the experimental samples made reinforced and tested by the authors on a single technique.
Materials employed characteristics and other data are detailed in [16-18].
Their ratio is called the  amplification coefficient - Summary The data analysis given in columns 5, 6, 7, 9 of table 1 allows to mark the following: - For flexible struts, each of the variable factors-the options for transverse and longitudinal reinforcement and, in particular, the eccentricity of the load application, had a greater impact than the short struts on the change in bearing capacity.
The obtained experimental data show that flexible reinforced concrete elements strengthened by external composite reinforcement and tested under the eccentricity of load application , which is not reflected in the requirements (i.e. within the inequality 0.1h<<0.3h), showed the possibility of the composite amplification within 20-30% compared to standard samples depending on the amplification options.

“Skeleton-based Dynamic hand gesture recognition by Quentin De Smedt, Haze Wannous, Jean-Philippe Vandeborre Tel´ ecom Lille this work suggests the advantages of using 3D hand skeleton data to describe hand gestures and represents a promising direction for performing gesture recognition tasks using skeleton-like information.
Cameras, gloves and data gloves are the most prevalent ways for capturing and identifying railings.
Better techniques for implementing mouse events will be developed in the future, as well as a reduction in lag during cursor movement to almost zero.
Deep learning for hand gesture recognition on skeletal data.
Sign language recognition based on hand and body skeletal data.

The control potential "a" can be determined after each engine test in the moment  1 using data obtained during the test in the moment  0 and data obtained during the test in the moment  1 as well as data concerning carried out adjustment actions u.
In the case of maintenance actions based only on "tracking" transfer functions (4) and (5), and carried out in the moments  0 and  1 from (15) we get the practical formula:  a  y1  y0 1  0 res y0  ˆ a u1  (16) where: 1Θy - value of the functional signal for  1 before adjustment (for the investigated example 1Θy =0,8), 0Θy - value of the functional signal for  0 and  1 after adjustment (for the investigated example 0Θy =1), resΘ - service life,  ˆ a - intensity of influence of the control unit on the functional signal (e.g. 20% y for 2.5 revolutions of the setting unit u), 1Θu - number of revolutions of the setting unit required for reduction of 1Θy to 0Θy (e.g. 2.5 revolutions of the setting unit u).
For above presented exemplary data the value of the parameter  a=0.17 means that the engine, which before adjustment lost 0.2 of its functional value, lost also 0.17 of its control potential.

Furthermore, SiO2 is used in the production of sensors and light signal converters. [2] Nano and micro-wires silicon oxide are synthesized using several techniques as laser ablation [3], chemical vapor deposition [4], vapor-liquid-solid (VLS) [5], oxide assisted growth mechanism [6], hydrothermal synthesis [7], carbo-thermal reduction synthesis catalytic thermal decomposition [8], bamboo pyrolysis thermal evaporation and thermal oxidation [9], catalytic pyrolysis with polymeric precursor [10], thermic evaporation [11], and metal thin film catalysis [12].
The XRD data is obtained for the amorphous SiO2 powder that depends on the etchant (KOH) concentration and the sonication time).
That's assured by XRD data.
The Raman spectrum of the as-synthesized material confirmed SiO2 formation that is in line with XRD and FTIR data.
SEM data revealed that the SiO2 nanoparticles and nano-clusters are present, in addition, micro-wires and micro-ribbons which is depending on the connection time between the precipitated powder and the etching solution.

In order to establish the accuracy and reliability of the collected data, the pH value was adjusted by the same volume of solutions: 0.2 mL HCl (1%) +0.8 mL deionized water, 1.0 mL deionized water, 0.2 mL NaOH (1%)+0.8 mL deionized water, 0.6 mL NaOH (1%)+0.4 mL deionized water and 1 mL NaOH (1%) solutions, respectively.
Lagergren pseudo-first order model (Lagergren and Svenska, 1898) and the pseudo-second-order model (Ho and McKay, 1998) shown as Eqs.(1) and (2).are employed to interpret the experimental data. appears after the equation but before the equation number, e.g
Table 1 Parameters of kinetic models for acid dyes adsorption onto CTSN As seen in Table 1, both pseudo-first-order and pseudo-second-order rate models fit well to experimental data, but the pseudo- second-order rate model shows a better fit than the pseudo-first-order.
Except for RP2P for all the three dyes onto CTSN are higher, the qBmaxB calculated from the pseudo-second-order rate models are closer to the experimental data.
This rapid reduction of dye adsorption at severe basic conditions may be attributed to the electrostatic repulsion between the deprotonated –NHB2B of CTSN and negatively charged dye molecules.

.), in order to obtain relatively accurate experimental data.
The force hammer and the data logger are connected with the acceleration sensor, each of the exciting force signal and the impulse response signal is transmitted to a data logger, and then passed by the data collection instrument into the signal analysis system.
Vibration Analysis and Reduction in Switched Reluctance Motors[D]．Ph.

Data show that in 2013 the annual total electricity consumption grew by 7.5% , increased by 1.9% over the previous year, at the end of the year ranked the first and the national power capacity reaching 1.25 billion kilowatts for the first time, the annual total power grid investment accounted for 51.2% of power engineering investment[1] .By the end of 2014, an increase of about 7.0% in electricity consumption and national power generation capacity of approximately 13.4 million kilowatts with the whole society will be excepted.
Power material supplier evaluation index system Supplier Evaluation Indicator System A First layer indexes Second layer indexes Weights (AHP) Quality A1 0.1965 Rate of qualified products A11 0.4240 Product lifetime A12 0.2270 Quality System Certification pass rate A13 0.1220 Product failure rates A14 0.2270 Cost A2 0.1966 Equipment maintenance costs A21 0.1090 Price A22 0.5640 Price reduction of space A23 0.2580 Transportation costs A24 0.1090 Supply capacity and flexibility A3 0.1610 Delivery (agility) A31 0.2765 Order completion rate A32 0.2559 Number of flexible A33 0.0999 Flexible time A34 0.2765 Variety of flexible A35 0.0922 competitiveness of enterprises A4 0.1610 Enterprise management level A41 0.0574 R & D capabilities A42 0.1870 The level of information A43 0.1870 Financial position A44 0.0974 Corporate Culture A45 0.0974 After-sales service and attitude A46 0.1870 Cooperation and development force and customers A47 0.1870 level of carbon A5
After the original data pretreatment, the paper establishes the index system as shown in table 1.
Experts have scored the average results, the original data as shown in table 2.
Second layer indexes of expert scoring data Qi A Q1 Q2 Q3 Q4 Q5 Q6 A1 3 2 3 4 4 2 A2 1 4 2 1 3 2 A3 2 3 1 4 1 3 A4 4 3 3 2 2 1 A5 1 3 3 3 1 4 A6 4 1 2 2 3 2 In this case,m = 6, k = 1/ln6, by the formula (1) and (2) it is concluded that the entropy value and differential coefficient, and then by the formula (3) get the revised weight value, and the normalized to obtain the final weight value, as shown in table 3.

After the test, choose the valid data without instability, then fit resistance curvse, and judg the effectiveness of the characteristic values of CTOD finally, such as δ0.05, δi, δc and δu. 2 Results and discussion 2.1 Resistance curves of crack propogation Fig.2 shows the resistance curves of base metal, HAZ and weld of X80 pipe at different temperatures.
There is no available data of the crack propagation resistance and tear modulus at the HAZ of X100 pipe when the experimental temperature is -10℃ and -30℃.
Table 1 Specimens and experimental temperature Table 2 Chemical composition Grade Size /mm Temperature/℃ B /mm W /mm X70 1016×21 -5℃ 12 24 X80 1219 ×18.4 Room temperature, -10℃, -30℃ 12 24 X100 1016×16 Room temperature, -10℃, -30℃ 11 22 Grade C Si Mn Cr Mo Ni Nb+V+Ti X70 0.048 0.10 1.55 0.083 0.20 0.19 0.072 X80 0.051 0.26 1.83 0.043 0.30 0.30 0.09 X100 0.059 0.23 1.96 0.53 0.0036 0.39 0.043 Table 3 Mechanical property Grade Tensile property (at room temperature) Charp impact energy (－10℃) Rm /MPa Rt0.5 /MPa A / % Akv / J SA / % X70 625 622 625 547 558 553 26 26 27 449 441 435 100 100 100 X80 713 715 709 565 561 562 25 26 26 345 340 338 100 100 100 X100 873 878 880 834 843 840 20 17 21 250 252 255 98 98 100 Fig.1 Position of cracks The data for the HAZ of X70 pipe is decentralized because of the instability.
As to the specimens of HAZ of X100 pipe, some of them are instable at room temperature; all of them are instable at -10℃ and -30℃; and the data of δ0.05 and δm is missing at -10℃ and -30℃.
High strength line pipe for project cost reduction [J].