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Low-Cost Smart Embedded Sensor for Single Throw Mechanical Equipment

机译:用于单掷机械设备的低成本智能嵌入式传感器

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This research builds on the work carried out in the area of developing a smart sensor for Single Throw Mechanical Equipment (STME). Limits sensors are the best candidate for observing throw trajectories although their limitation to detect a continuous change in residuals, restricts their usage to discrete applications. Thus research and academia maintains focus on continuous sensors, while industry keeps the limit switches as their key sensor. The paper attempts to bridge the gulf and formally presents a framework for deploying optimal number of limit switches to capture the process dynamics with increased degree of freedom and use them as model based multi sensor residual generator. The energy distribution of Residual Spectra generated by such Model Based Parity Space relationship results in drifts in the form of Eigen value. The Eigen vector in such a multi-dimensional Residual Space is used to maintain the degree and polarity of drift. This paper presents investigations into the issues related to such Eigen analysis. It was found that normalized residuals from multiple sources and parity space relations are neutralized in the form of unified representation of energy that can be used to form a generic framework for fault detection and isolation. It is being investigated, how the proper modeling of quantitative entities as energy, could lead to unified and neutral residual space while keeping the implementation cost reasonably low. Higher degree of freedom allows robust model based self diagnostics to cater for sensor, actuators and system failures isolation model based self diagnostics. An FPGA based implementation of the algorithm is underway based on MEMS to ensure compact very high degree freedom of sensor within financial constraints for Embedded STMEs embedded fault Diagnostics system.
机译:该研究建立在开发用于单掷机械设备(STME)的智能传感器领域中的工作之上。极限传感器是观察抛掷轨迹的最佳候选者,尽管它们的极限是检测残差的连续变化,但将它们的使用限制在离散应用中。因此,研究和学术界将重点放在连续传感器上,而工业界将限位开关作为其关键传感器。本文试图弥合鸿沟,并正式提出了一个框架,该框架用于部署最佳数量的限位开关以捕获具有更大自由度的过程动态,并将其用作基于模型的多传感器残差生成器。由这种基于模型的奇偶空间关系产生的残留谱的能量分布导致特征值形式的漂移。在这样的多维残差空间中,本征向量用于保持漂移的程度和极性。本文介绍了与这种本征分析有关的问题。已发现,来自多个来源的标准化残差和奇偶性空间关系以能量的统一表示形式被中和,该能量可用于形成故障检测和隔离的通用框架。正在研究如何将定量实体作为能量进行正确建模,如何在保持实施成本合理较低的同时,实现统一和中性的剩余空间。较高的自由度允许基于鲁棒的基于模型的自诊断功能来满足传感器,执行器和系统故障基于隔离模型的自诊断功能。基于MEMS的算法的基于FPGA的实现正在进行中,以确保在嵌入式STME嵌入式故障诊断系统的财务限制内,传感器具有紧凑的高度自由度。

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