介紹了一種基于MSP430系列單片機和ADXL203加速度傳感器的數字式傾角儀，它不僅可以實現水平度檢測，而且可以測量00～3600范圍內的任意傾角，分辨率可達O．1。。此外，由于該傾角儀輸出為數字結果，因此它也可以與其他的數字設備結合起來，組合成一個功能更加強大的儀器。該數字傾角儀可廣泛應用于建筑、機械、道路、橋梁、石油、煤礦和地質勘探等各種需要測量重力參考系下傾角的場合。關鍵詞：MSP430F133單片機；力敏傳感器；ADXL203加速度計；角度測量
Abstract：This paper presents a new style digital inclinometer which is developed on the basis of the MSP430F133 MCU and the ADXL203 dual axis aeeelerometer．This inclinometer not only can test levelness，but also can measure any angle between 0。and 360。with an accuracy of 0．1 O．In addition，its output is a digital result，which makes it possible to integrate itself with other digital devices to form a more functional unit．This inclinometer can be widely used in any construction site，oil field，coal-mine or geologic survey and SO on where it will provide the working people with convenience to measure any angles．Key words：MSP430F133 MCU；force sensor；ADXL203 accelerometer；angle measurement
為了提高直接轉矩控制（DTC）系統定子磁鏈估計精度，降低電流、電壓測量的隨機誤差，提出了一種基于擴展卡爾曼濾波（EKF）實現異步電機轉子位置和速度估計的方法。擴展卡爾曼濾波器是建立在基于旋轉坐標系下由定子電流、電壓、轉子轉速和其它電機參量所構成的電機模型上，將定子電流、定子磁鏈、轉速和轉子角位置作為狀態變量，定子電壓為輸入變量，定子電流為輸出變量，通過對磁鏈和轉速的閉環控制提高定子磁鏈的估計精度，實現了異步電機的無速度傳感器直接轉矩控制策略，仿真結果驗證了該方法的可行性,提高了直接轉矩的控制性能。
Abstract:
In order to improve the Direct Torque Control（DTC） system of stator flux estimation accuracy and reduce the current， voltage measurement of random error， a novel method to estimate the speed and rotor position of asynchronous motor based on extended Kalman filter was introduced. EKF was based on d-p axis motor and other motor parameters （state vector: stator current， stator flux linkage， rotor angular speed and position； input: stator voltage； output: staror current). EKF was designed for stator flux and rotor speed estimation in close-loop control. It can improve the estimated accuracy of stator flux. It is possible to estimate the speed and rotor position and implement asynchronous motor drives without position and speed sensors. The simulation results show it is efficient and improves the control performance.
Rotating shafts experience a an elliptical motion called whirl. It is important to decompose this motion into a forward and backward whil orbits. The current function makes use of two sensors to generate a bi-directional spectrogram. The method can be extended to any time-frequency distribution
％
％ compute the forward/backward Campbell/specgtrogram
％
％ INPUT:
％ y (n x 2) each column is measured from a different sensor
％ ///////
％ __
％ |s1| y(:,1)
％ |__|
％ __
％ / \ ________|/
％ | | | s2 |/ y(:,2)
％ \____/ --------|/
％
％ Fs Sampling frequnecy
％
％ OUTPUT:
％ B spectrogram/Campbel diagram
％ x x-axis coordinate vector (time or Speed)
％ y y-axis coordinate vector (frequency [Hz])
％WAVETEST Example Matlab script for WAVELET, using NINO3 SST dataset
％
％ See "http://paos.colorado.edu/research/wavelets/"
％ Written January 1998 by C. Torrence
％
％ Modified Oct 1999, changed Global Wavelet Spectrum (GWS) to be sideways,
％ changed all "log" to "log2", changed logarithmic axis on GWS to
％ a normal axis.
Intro/: Directory containing introductory examples.
HelloWorld.c A simple program that draws a box and writes "Hello World" in
HelloWorld.f it.
data The data file for the introductory progressive example.
Lines.c Reads the data from file "data" and plots just the curve with
Lines.f no labels, viewport or anything indicating quantity or units.
Viewport.c Restricts the graph to a viewport and frames the viewport,
Viewport.f leaving the remainder of the area for labels, etc.
CharLbls.c Adds labels for the chart title, X-axis title, and Y-axis
CharLbls.f title.
Tics.c Adds tic marks to the viewport edges, but since clipping was
Tics.f not set correctly, tics extend outside the viewport.
Clip.c Sets clipping such that tic marks are clipped at the viewport
Clip.f boundaries.
TicLabels.c Adds numeric tic labels to the graph this is the final
TicLabels.f installment of the progressive example.
PlotSphereIntensity(azimuth, elevation)
PlotSphereIntensity(azimuth, elevation, intensity)
h = PlotSphereIntensity(...)
Plots the intensity (as color) of a number of points on a unit sphere.
Input:
azimuth (phi), in degrees
elevation (theta), in degrees
intensity (optional, if not provided, a green sphere is produced)
All inputs must be vectors or matrices of the same size. Data does not have to be evenly spaced. When there aren t enough points to draw a smooth sphere, additional points (with color) are interpolated.
Output:
h - a handle to the patch object
The axes are also plotted:
positive x axis is red
positive y axis is green
positive z axis is blue
A .zip file contains a series of scripts that were used in the MathWorks webinar "Using MATLAB to Develop Portfolio Optimization Models." The scripts generate 3D efficient frontiers for a universe of 44 stocks with time as the third axis. Additional scripts perform various ex-ante and ex-post analyses. Results are generated with and without market adjustments in the data. A readme.txt. file in the .zip folder describes each script and how to use it
Input : A set S of planar points
Output : A convex hull for S
Step 1: If S contains no more than five points, use exhaustive searching to find the convex hull and return.
Step 2: Find a median line perpendicular to the X-axis which divides S into SL and SR SL lies to the left of SR .
Step 3: Recursively construct convex hulls for SL and SR. Denote these convex hulls by Hull(SL) and Hull(SR) respectively.
Step 4: Apply the merging procedure to merge Hull(SL) and Hull(SR) together to form a convex hull.
Time complexity:
T(n) = 2T(n/2) + O(n)
= O(n log n)
