This paper reports the application of Taguchi optimization technique in determining process condition for synthetic lightweight aggregates by incorporating waste liquid crystal displays (LCD) glass with reservoir sediments. In the study the waste LCD glass cullet was used as an additive. It was incorporated with reservoir sediments to produce lightweight aggregates. Taguchi method with an L16(45) orthogonal array and five controllable 4-level factors (i.e., cullet content, preheat temperature, preheat time, sintering temperature, and sintering time) was adopted. Then, in order to optimize the selected parameters, the analysis of variance method was used to explore the effects of the experimental factors on the performances (particle density and water absorption) of the produced lightweight aggregates. The results showed that it is possible to produce high performance lightweight aggregates by incorporating waste LCD glass cullet with reservoir sediments.

This study proposed an intelligent rotary fault diagnosis systems for motors. A sensorless rotational speed detection method and a dynamic structural neural network (DSNN) were used. This method can be employed to detect the rotary frequencies of motors with varying speeds and can enhance the discrimination of motor faults. To conduct the experiments, this work used wireless sensor nodes to transmit vibration data, and employed MATLAB to write codes for functional modules, including signal processing, sensorless rotational speed estimation, and neural networks. Additionally, Visual Basic was used to create an integrated human-machine interface. The experimental results regarding test equipment faults indicated that the proposed method can effectively estimate rotational speeds and provide superior discrimination of motor faults.

No abstract

This study implemented fuzzy control theory with a cerebellar controller to design a fuzzy cerebellar model articulation controller (FCMAC), ensuring system stability by deriving an adaptive FCMAC weight update rule from the Lyapunov theory. The speed estimator design in this study is based on the structure of an adaptive stator flux observer (ASFO) to achieve rapid sensorless control. According to results from experiments, installing the adaptive FCMAC speed controller in the induction motor’s direct torque control system demonstrates excellent speed dynamic response.