Biblio
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Inter-Batch Gap Filling Using Compressive Sampling for Low-Cost IoT Vibration Sensors. 2021 IEEE International Instrumentation and Measurement Technology Conference (I2MTC). :1—6.
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2021. To measure machinery vibration, a sensor system consisting of a 3-axis accelerometer, ADXL345, attached to a self-contained system-on-a-chip with integrated Wi-Fi capabilities, ESP8266, is a low-cost solution. In this work, we first show that in such a system, the widely used direct-read-and-send method which samples and sends individually acquired vibration data points to the server is not effective, especially using Wi-Fi connection. We show that the micro delays in each individual data transmission will limit the sensor sampling rate and will also affect the time of the acquired data points not evenly spaced. Then, we propose that vibration should be sampled in batches before sending the acquired data out from the sensor node. The vibration for each batch should be acquired continuously without any form of interruption in between the sampling process to ensure the data points are evenly spaced. To fill the data gaps between the batches, we propose the use of compressive sampling technique. Our experimental results show that the maximum sampling rate of the direct-read-and-send method is 350Hz with a standard uncertainty of 12.4, and the method loses more information compared to our proposed solution that can measure the vibration wirelessly and continuously up to 633Hz. The gaps filled using compressive sampling can achieve an accuracy in terms of mean absolute error (MAE) of up to 0.06 with a standard uncertainty of 0.002, making the low-cost vibration sensor node a cost-effective solution.
Research on Correlation Analysis of Vibration Signals at Multiple Measuring Points and Black Box Model of Flexible-DC Transformer. 2020 IEEE 4th Conference on Energy Internet and Energy System Integration (EI2). :3238–3242.
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2020. The internal structure of the flexible-DC transformer is complicated and the lack of a reliable vibration calculation model limits the application of the vibration analysis method in the fault diagnosis of the flexible-DC transformer. In response to this problem, this paper analyzes the correlation between the vibration signals of multiple measuring points and establishes a ``black box'' model of transformer vibration detection. Using the correlation analysis of multiple measuring points and BP neural network, a ``black box'' model that simulates the internal vibration transmission relationship of the transformer is established. The vibration signal of the multiple measuring points can be used to calculate the vibration signal of the target measuring point under specific working conditions. This can provide effective information for fault diagnosis and judgment of the running status of the flexible-DC transformer.
Impulse Exciter of Rotating Blades With an Increased Excitation Force. IEEE Transactions on Instrumentation and Measurement. 68:300–302.
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2019. This paper deals with electromagnetic vibration excitation of rotating machine blades in a purpose of dynamic measurement and testing. A novel method for increasing the excitation force is presented. At the same time, the suggested method allows to reduce blade remanent induction. Examples of measurements are shown, and obtained results are discussed.