Extended Kalman filter-based prognostic of actuator degradation in two tank system

D. Jayaprasanth, J. Arul Melissa
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Abstract

Rapid growth in the industries need an effective predictive maintenance policy. Failure in the equipment decreases the production rate and thereby, causing a loss to the industry. The equipment especially, the actuator is operated continuously in the industries in order to achieve the desired production rate. Actuator is the key element which undergoes degradation due to frequent control actions. However, degradation is mainly influenced by different operating conditions and other environmental factors. This decreases the lifetime of the equipment and also it increases the maintenance cost. This problem is addressed by carrying out the reliability studies on the actuator by using Gamma process. It is used to describe the system  degradation. In this work, Gamma process based actuator modelling is used to study the deterioration in the actuator. The gamma parameters such as shape and scale parameters are the deciding factors describing the level of degradation in the system. It is then applied to two tank feedback control system. Extended version of Kalman filter estimates the state of noisy measurements which describes the fault trend characteristics in the system. Finally, the evolution of actuator capacity in presence of fault is analyzed and simulated in MATLAB environment.
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基于扩展卡尔曼滤波的双罐系统执行器退化预测
快速增长的行业需要有效的预测性维护策略。设备故障降低了生产率,从而给行业造成了损失。设备特别是执行器在工业中连续运行,以达到预期的生产率。执行机构是由于频繁的控制动作而导致性能退化的关键元件。然而,降解主要受不同操作条件和其他环境因素的影响。这减少了设备的使用寿命,也增加了维护成本。利用伽玛过程对作动器进行了可靠性研究,解决了这一问题。它用来描述系统退化。在这项工作中,采用基于伽玛过程的执行器建模来研究执行器的劣化。gamma参数如形状和尺度参数是描述系统退化程度的决定性因素。并将其应用于双槽反馈控制系统。扩展版的卡尔曼滤波估计了噪声测量的状态,描述了系统中的故障趋势特征。最后,在MATLAB环境中对故障情况下执行器容量的演变进行了分析和仿真。
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