電路仿真程序 Classic ladder is coded 100％ in C.It can be used for educational purposes or anything you want...
The graphical user interface uses GTK.
In the actual version, the following elements are implemented :
* Booleans elements
* Rising / falling edges
* Timers
* Monostables
* Compare of arithmetic expressions
便攜式B型超聲診斷儀具有無創傷、簡便易行、相對價廉等優勢，在臨床中越來越得到廣泛的應用。它將超聲波技術、微電子技術、計算機技術、機械設計與制造及生物醫學工程等技術融合在一起。開展該課題的研究對提高臨床診斷能力和促進我國醫療事業的發展具有重要的意義。 便攜式B型超聲診斷儀由人機交互系統、探頭、成像系統、顯示系統構成。其基本工作過程是：首先人機交互系統接收到用戶通過鍵盤或鼠標發出的命令，然后成像系統根據命令控制探頭發射超聲波，并對回波信號處理、合成圖像，最后通過顯示系統完成圖像的顯示。 成像系統作為便攜式B型超聲診斷儀的核心對圖像質量有決定性影響，但以前研制的便攜式B型超聲診斷儀的成像系統在三個方面存在不足：第一、采用的是單片機控制步進電機，控制精度不高，導致成像系統采樣不精確；第二、采用的數字掃描變換算法太粗糙，影響超聲圖像的分辨率；第三、它的CPU多采用的是51系列單片機，測量速度太慢，同時也不便于系統升級和擴展。 針對以上不足，提出了基于FPGA的B型超聲成像系統解決方案，采用Altera公司的EP2C5Q208C8芯片實現了步進電機步距角的細分，使電機旋轉更勻速，提高了采樣精度；提出并采用DSTI-ULA算法（Uniform ladder Algorithm based on Double Sample and Trilinear Interotation）在FPGA內實現數字掃描變換，提高了圖像分辨率；人機交互系統采用S3C2410-AL作為CPU，改善了測量速度和系統的擴展性。 通過對系統硬件電路的設計、制作，軟件的編寫、調試，結果表明，本文所設計的便攜式B型超聲成像系統圖像分辨率高、測量速度快、體積小、操作方便。本文所設計的便攜式B型超聲診斷儀可在野外作業和搶險（諸如地震、抗洪）中發揮作用，同時也可在鄉村診所中完成對相關疾病的診斷工作。
AUTOMGEN runtime is an open source royalty free runtime for open PLCs. By using this runtime, any target systems can become compatible with the AUTOMGEN automation workshop: IEC1131 languages (ladder, SFC, etc.), 2D and 3D scada, WEB SCADA, etc
The ADC0803 family is a series of three CMOS 8-bit successive
approximation A/D converters using a resistive ladder and
capacitive array together with an auto-zero comparator. These
converters are designed to operate with microprocessor-controlled
buses using a minimum of external circuitry. The 3-State output data
lines can be connected directly to the data bus.
observable distribution grid are investigated. A distribution
grid is observable if the state of the grid can be fully determined.
For the simulations, the modified 34-bus IEEE test feeder is used.
The measurements needed for the state estimation are generated
by the ladder iterative technique. Two methods for the state
estimation are analyzed: Weighted Least Squares and Extended
Kalman Filter. Both estimators try to find the most probable
state based on the available measurements. The result is that
the Kalman filter mostly needs less iterations and calculation
time. The disadvantage of the Kalman filter is that it needs some
foreknowlegde about the state.
