• Journal of Sensor Science and Technology
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• v.32 no.1
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• pp.10-15
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• 2023

It is well known that polycrystalline ceramics fabricated via the templated grain growth method along a desired crystallographic direction, generally along [001], exhibits enhanced piezoelectric response. Generally, the piezoelectric properties of textured ceramics depend on the degree of texture, as piezoelectric properties peak in single crystals. Therefore, understanding the relationship between the degree of texture and piezoelectric properties is fundamental. Here, we present state-of-the-art textured piezoceramics by focusing on critical issues such as the quality of templates used for texturing and proper evaluation of the degree of texture analysis. The relationship between the degree of texture and its impact on the properties of textured materials is exclusively defined by the Lotgering factor (L.F.) calculated from the X-ray diffraction profiles. Additionally, we show that L.F. is not a suitable indicator of the degree of texture, contrary to previous interpretations. This statement was further supported by the fact that the true degree of texture can be better quantified by the multiples of random distribution. This argument was justified by comparing the quantitative values of the degree of texture obtained from both methods to those of the piezoelectric charge coefficient of textured and random ceramics.

• Journal of Korea Water Resources Association
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• v.51 no.8
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• pp.703-711
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• 2018

Water distribution system (WDS) pipe bursts are caused from excessive pressure, pipe aging, and ground shift from temperature change and earthquake. Prompt detection of and response to the failure event help prevent large-scale service interruption and catastrophic sinkhole generation. To that end, this study proposes a improved Western Electric Company (WECO) method to improve the detection effectiveness and efficiency of the original WECO method. The original WECO method is an univariate Statistical Process Control (SPC) technique used for identifying any non-random patterns in system output data. The improved WECO method multiples a threshold modifier (w) to each threshold of WECO sub-rules in order to control the sensitivity of anomaly detection in a water distribution network of interest. The Austin network was used to demonstrated the proposed method in which normal random and abnormal pipe flow data were generated. The best w value was identified from a sensitivity analysis, and the impact of measurement frequency (dt = 5, 10, 15 min etc.) was also investigated. The proposed method was compared to the original WECO method with respect to detection probability, false alarm rate, and averaged detection time. Finally, this study provides a set of guidelines on the use of the WECO method for real-life WDS pipe burst detection.

• Journal of IKEEE
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• v.23 no.4
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• pp.1360-1365
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• 2019

In this paper, we describe a sound source localization(SSL) system which can be applied to mobile robot and automatic control systems. Usually the SSL method finds the Interaural Time Difference, the Interaural Level Difference, and uses the geometrical principle of microphone array. But here we proposed another approach based on the deep neural network to obtain the horizontal directional angle(azimuth) of the sound source. We pick up the sound source signals from the two microphones attached symmetrically on both sides of the robot to imitate the human ears. Here, we use difference of spectral distributions of sounds obtained from two microphones to train the network. We train the network with the data obtained at the multiples of 10 degrees and test with several data obtained at the random degrees. The result shows quite promising validity of our approach.