On-line dead-time compensation method using disturbance observer

A new on-line dead-time compensation method for a permanent magnet (PM) synchronous motor drive is proposed. Using a simple disturbance observer without any additional circuit and off-line experimental measurement, disturbance voltages in the rotor reference dq frame caused by the dead time and nonideal switching characteristics of power devices are estimated in an on-line manner and fed to voltage references in order to compensate the dead-time effects. The proposed method is applied to a PM synchronous motor drive system and implemented by using software of a digital signal processor (DSP) TMS320C31. Simulations and experiments are carried out for this system and the results well demonstrate the effectiveness of the proposed method.     

A unified group technology implementation using the backpropagation learning rule of neural networks

Two engineering problems in implementing Group Technology are part family formation and part classification. Regardless of the approach adopted for the formation and classification, a critical problem is how to maintain consistency. The consistency problem can be addressed most effectively if the formation and classification is a single procedure rather than two separate procedures. A feedforward neural network using the Backpropagation learning rule is adopted to automatically generate part families during the part classification process. The spontaneous generalization capability of the neural network is utilized in classifying the parts into the families and creating new families if necessary. A heuristic algorithm using the neural network is described with an illustrative example.     

A 0.8-V accurately tuned linear continuous-time filter

An accurately tuned low-voltage linear continuous-time filter is presented in this paper. Accurate tuning is achieved using time-constant matched master-slave tuning combined with power-up mismatch calibration. A low-pass biquad designed for a corner frequency of 115 kHz achieves better than -80-dB total harmonic distortion with a 250-mV/sub pp/ 10-kHz input signal. The prototype implemented in 0.18-/spl mu/m CMOS process occupies an area of 0.4 mm/sup 2/ and dissipates 4.6 mW (2.6 mW for the filter and 2 mW for tuning) of power.     

Computer modeling of the continuous annealing furnace

A computer program to calculate the strip temperature heated in the continuous annealing furnace was developed, using the zone method for radiative heat transfer analysis with the measured gas temperature in the furnace. Using theF _E Operator, the present study considered the effects of soot and transient species, in addition to the H₂O−CO₂ gas mixture on the gas radiative heat transfer. The predicted strip temperature distribution forF _E=1.05 represented well the measured data. The maximum difference in the heat flux transfered to the strip from the combustion gas forF _E=1.0 (without soot and transient species gas radiation) and 1.05 (with soot and transient species gas radiation) was about 15%. The present study also investigated the effects of line speed and thickness variations on the strip temperature, establishing the bases for the on-line computer model.     

Feature selection techniques and comparative studies for large-scale manufacturing processes

In order to efficiently and effectively control an overall process in the process industry, a few important parameters should be identified from high-dimensional, non-linear, and correlated data. Feature selection techniques can be employed to extract a subset of process parameters relevant to product quality. The performance of these techniques depends on the precision of the prediction model formulated to quantify the relationship between the process parameters and the quality characteristics. Although the neural network-based partial least squares (NNPLS) method has been proven to be effective in prediction models for the aforementioned industrial process data, feature selection techniques appropriate for NNPLS models have yet to appear. Here, several techniques for scoring the relevance of process parameters to product quality are proposed and validated by applying three datasets. These experiments show that the proposed techniques can discriminate relevant process parameters from irrelevant ones.     

Effect of Annealing on the Surface Microstructure of Y-Ba-Cu-O Superconducting Ceramics

Precusors to the YBa₂Cu₃O_7-δ material were prepared by both the oxalate precipitation method and conventional ceramic processing. Second-phase grains were observed to develop on the exposed fracture surface during annealing at 500° to 600°C in an ambient atmosphere. The second-phase grains were identified to be BaCO₃ using EDX and XRD. The liquid phase, which was formed because of local chemical inhomogeneity in the Y-Ba-Cu-O system, contributed to the formation of second-phase grains as a source of Ba.     

Preparation of aligned polyetherimide fiber by electrospinning

Fifteen to 20 wt % polyetherimide (PEI) solutions with 1-methyl-2-pyrrolidinone (NMP) were prepared. The electrical conductivity and surface tension of the solutions were determined. The fiber spinning technique of electrospinning was optimized in order to prepare unidirectionally aligned, structurally oriented nanofiber tows. The morphology of the PEI fibers was investigated using field emission scanning electron microscopy (FESEM). The well-aligned fibers with diameters between 0.58 and 0.90 μm (FESEM) were collected by electrospinning 20 wt % PEI solutions with NMP in the range of 8–10 kV onto a target rotating with a surface velocity 9.8 m/s. © 2008 Wiley Periodicals, Inc. J Appl Polym Sci, 2008     

Effects of tube rupture modeling and the parameters on the analysis of multiple steam generator tube rupture event progression in APR1400

A multiple steam generator tube rupture (MSGTR) event in APR1400 has been investigated using the best estimate thermal hydraulic system code, MARS1.4. The effects of the parameters such as the number of ruptured tubes, rupture location, affected steam generator on the analysis of the MSGTR event in APR1400 are examined. In particular, tube rupture modeling methods, single tube modeling (STM) and double tube modeling (DTM), are compared. The APR1400 is found to have the capability of allowing more than 30 min to operators for the MSGTR event of five tubes. The effects of rupture location on the MSSV lift time is not significant in the case of STM, but the MSSV lift time for tube-top rupture is found to be 25.3% larger than that for rupture at the hot-leg side tube sheet in the case of DTM. The MSSV lift time for the cases that both steam generators are affected (4C5x, 4C23x) are found to be larger than that of the single steam generator cases (4A5x, 4B5x) due to a bifurcation of the primary leak flow. The discharge coefficient of Cd is found to affect the MSSV lift time only for a smaller value of 0.5. It is found that the most dominant parameter governing the MSSV lift time is the leak flow rate. Whether any modeling method is used, it gives the similar MSSV lift time if the leak flow rate is close, except in the case where both steam generators are affected. Therefore, the system performance and the MSSV lift time of the APR1400 are strongly dependent on the break flow model used in the best estimate system code.