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Capacitors are critical in voltage regulator modules (VRMs) which contribute to store energy and stabilize the output voltage during load transients. Usually, VRMs work with consecutive load transients, which would bring more electrothermal stress to capacitors and affect the reliability of capacitors compared with the steady-state operation. Recently, some efforts have been made to investigate the reliability of capacitors in power electronic converters. Unfortunately, transient processes are commonly ignored, which can impair the accuracy of the lifetime estimation. Regarding this issue, this paper investigates the influence of transients on the damage of capacitors in VRMs. A 150 W VRM is introduced as a case study. Firstly, the electrothermal stresses during steady state and transients are analyzed.Then, the lifetime calculation is considered from a single capacitor to hybrid capacitor banks. In addition, a suitable capacitor configuration of capacitor banks is also provided, in order to maximize its lifetime.

Wireless sensor networks (WSNs) have been expected to improve the capability of capturing mechanical vibration dynamic behaviors and evaluating the current health status of equipment. While the expectation for mechanical vibration monitoring using WSNs has been high, one of the key limitations is the limited lifetime of batteries for sensor node. The energy harvesting technologies have been recently proposed. One of them shares the same main idea, that is, energy harvesting from ambient vibration can be converted into electric power. Employing the vibration energy harvesting, a novel self-powered wireless sensor node has been developed to measure mechanical vibration in this paper. The overall architecture of node is proposed. The wireless sensor node is described into four main components: the energy harvesting unit, the microprocessor unit, the radio transceiver unit, and accelerometer. Moreover, the software used to control the operation of wireless node is also suggested. At last, in order to achieve continuous self-powered for nodes, two operation modes including the charging mode and discharging mode are proposed. This design can effectively solve the problem of continuous supply power of sensor node for mechanical vibration monitoring.

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We synthetically applied computer vision, genetic algorithm and artificial neural network technology to automatically identify the tomatoes that had physiological diseases. Firstly, the tomatoes' images were captured through a computer vision system. Then to identify cavernous tomatoes, we analyzed the roundness and detected deformed tomatoes by applying the variation of fruit's diameter. Secondly, we used a Genetic Algorithm (GA) trained artificial neural network. Experiments show that the above methods can accurately identify tomatoes' shapes and meet requests of classification; the accuracy rate for the identification for tomatoes with physiological diseases was up to 100%. tomato with physiological disease; computer vision; artificial neural network; genetic algorithms 1.

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Abstract:Although the flowerpot is widely used for indoor flowers, it cannot meet the needs of intelligent management during the uncared-for period. The objective of this study was to design a new microcontroller-based smart flowerpot. Its overall system was composed of three parts: information collection layer, automatic control layer and data transmission layer. Firstly, in the process of collecting information, the Laiyite criterion and the normalized weighted average algorithm were adopted to improve the accuracy of information collection. Secondly, for making precise control decisions, the fuzzy control was used to achieve automatic on-demand watering. Finally, the method for comparative analysis of regional light intensity was utilized to achieve light-seeking and light-supplementing. Experimental results showed that the smart flowerpot had strong anti-jamming performance for information collection, the relative soil moisture of flowers could be stably maintained near the optimum humidity (65%), and the light was well-distributed on the flower with the error angle of light-supplementing ranged from -3° to 3°.