An in-house developed 2D ultrasound computerized Tomography system is fully automated. Performance analysis of instrument and software interfacing soft tools, namely the LabVIEW, MATLAB, C, and Python, is presented. The instrument interfacing algorithms, hardware control algorithms, signal processing, and analysis codes are written using above mentioned soft tool platforms. Total of eight performance indices are used to compare the ease of (a) realtime control of electromechanical assembly, (b) sensors, instruments integration, (c) synchronized data acquisition, and (d) simultaneous raw data processing. It is found that C utilizes the least processing power and performs a lower number of processes to perform the same task. In runtime analysis (data acquisition and realtime control), LabVIEW performs best, taking 365.69s in comparison to MATLAB (623.83s), Python ( 1505.54s), and C (1252.03s) to complete the experiment. Python performs better in establishing faster interfacing and minimum RAM usage. LabVIEW is recommended for its fast process execution. C is recommended for the most economical implementation. Python is recommended for complex system automation having a very large number of components involved. This article provides a methodology to select optimal soft tools for instrument automation-related aspects.
翻译:内部开发的2D超声波计算机地形学系统已完全自动化,对仪器和软件接口软工具,即LabVIEW、MATLAB、C和Python进行性能分析,发现C利用最少的处理力和较少的程序来完成同样的任务,在运行时分析(数据获取和实时控制),LabVIEW表现最佳,与MATLAB(623.83s)、Python(1505.54s)和C(1252.03s)相比,共使用8个性能指数来比较(a)电机组件实时控制、(b)传感器、仪器集成、(c)同步数据获取和(d)同步原始数据处理,发现C利用最少的处理力和较少的流程来完成相同的任务。在运行时分析(数据获取和实时控制),LabVIEW表现最佳,与MATLAB(623.83s)、Python(1505.54s)和C(1252.03s)相比,完成试验的方便程度。Pyson更好地建立更快的内插器和最小使用。LAVIEW是建议快速执行的最软化工具。