高效的瞬态测试程序,使用一种新颖的体验回放粒子群优化器,用于工业4.0中基于thd的自x传感电子设备的鲁棒设计和优化

IF 0.8 Q4 INSTRUMENTS & INSTRUMENTATION Journal of Sensors and Sensor Systems Pub Date : 2021-01-01 DOI:10.5194/jsss-10-193-2021
Q. Zaman, S. Alraho, A. König
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引用次数: 3

摘要

摘要本文旨在改进传统的可重构自x(自校准、自修复、自优化等)传感器接口读出电路的校准方法,以适应工业4.0。在被测器件上施加一种经济有效的测试激励,并分析系统的瞬态响应以关联电路的特性参数。针对智能传感电子的搜索和目标空间的复杂性,提出了一种新的体验重放粒子群优化算法,并证明了该算法比现有的一些粒子群优化算法具有更好的搜索能力。新提出的ERPSO通过引入经验重放缓冲(ERB)来减少陷入局部极小值的概率,从而扩展了经典粒子群算法的选择生产者。ERB反映了先前访问过的全局最佳粒子的存档,而其选择基于速度更新模型中的自适应epsilon贪心方法。通过使用8种不同的常用基准函数验证了所提出的ERPSO算法的性能。此外,在可重构宽摆幅间接电流反馈仪表放大器(CFIA)上对ERPSO算法进行了外在评价。在后期的测试中,我们提出了一种高效的优化程序,利用CFIA输出的总谐波失真分析来减少测量的总次数,节省大量的优化时间和成本。所提出的优化方法大约比经典优化过程快3倍。该电路采用Cadence设计工具和奥地利微系统公司(AMS)的CMOS 0.35µm技术实现。效率和鲁棒性是为工业4.0应用实现可靠的传感电子系统所提出的方法的关键特征。
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Efficient transient testing procedure using a novel experience replay particle swarm optimizer for THD-based robust design and optimization of self-X sensory electronics in industry 4.0
Abstract. This paper aims to improve the traditional calibration method for reconfigurable self-X (self-calibration, self-healing, self-optimize, etc.) sensor interface readout circuit for industry 4.0. A cost-effective test stimulus is applied to the device under test, and the transient response of the system is analyzed to correlate the circuit's characteristics parameters. Due to complexity in the search and objective space of the smart sensory electronics, a novel experience replay particle swarm optimization (ERPSO) algorithm is being proposed and proved a better-searching capability than some currently well-known PSO algorithms. The newly proposed ERPSO expanded the selection producer of the classical PSO by introducing an experience replay buffer (ERB) intending to reduce the probability of trapping into the local minima. The ERB reflects the archive of previously visited global best particles, while its selection is based upon an adaptive epsilon greedy method in the velocity updating model. The performance of the proposed ERPSO algorithm is verified by using eight different popular benchmarking functions. Furthermore, an extrinsic evaluation of the ERPSO algorithm is also examined on a reconfigurable wide swing indirect current-feedback instrumentation amplifier (CFIA). For the later test, we proposed an efficient optimization procedure by using total harmonic distortion analyses of CFIA output to reduce the total number of measurements and save considerable optimization time and cost. The proposed optimization methodology is roughly 3 times faster than the classical optimization process. The circuit is implemented by using Cadence design tools and CMOS 0.35 µm technology from Austria Microsystems (AMS). The efficiency and robustness are the key features of the proposed methodology toward implementing reliable sensory electronic systems for industry 4.0 applications.
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来源期刊
Journal of Sensors and Sensor Systems
Journal of Sensors and Sensor Systems INSTRUMENTS & INSTRUMENTATION-
CiteScore
2.30
自引率
10.00%
发文量
26
审稿时长
23 weeks
期刊介绍: Journal of Sensors and Sensor Systems (JSSS) is an international open-access journal dedicated to science, application, and advancement of sensors and sensors as part of measurement systems. The emphasis is on sensor principles and phenomena, measuring systems, sensor technologies, and applications. The goal of JSSS is to provide a platform for scientists and professionals in academia – as well as for developers, engineers, and users – to discuss new developments and advancements in sensors and sensor systems.
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