Guoli Li

Bio: Guoli Li is an academic researcher from Anhui University. The author has contributed to research in topics: Signal & Series (mathematics). The author has an hindex of 2, co-authored 2 publications receiving 10 citations.

Self-Sensing Vibration Suppression of Piezoelectric Cantilever Beam Based on Improved Mirror Circuit

Abstract: The self-sensing technique allows a single piece of piezoelectric element to function simultaneously as an actuator and a sensor in a closed-loop system. This study proposes an improved vibration suppression system using the piezoelectric self-sensing technique whose usefulness is experimentally verified in a cantilever beam. A single piezoelectric element is bonded to the root of the beam and functions as an actuator and a sensor simultaneously. A mirror circuit constructed with two charge driver circuits is used to pick up the sensing signal from the driving voltage signal. Then, a closed-loop control strategy based on the proportion integration differentiation (PID) algorithm can adjust the sensing signal precisely to suppress the vibration of the cantilever beam quickly. The first mode of vibration is suppressed, and the amplitude of the vibration is actively dampened by a factor exceeding 96.4%. Moreover, the frequency sweep experiments demonstrate that with the PID feedback control circuit connected to the piezoelectric cantilever beam, the Q value of the system is greatly reduced, and the loss factor is increased from 0.053 to 0.288. The improved mirror circuit with PID control has a good suppression effect in the frequency range near the first order mode of the cantilever beam.

A Method for Detecting Dynamic Mutation of Complex Systems Using Improved Information Entropy

Abstract: In this study, a nonlinear analysis method called improved information entropy (IIE) is proposed on the basis of constructing a special probability mass function for the normalized analysis of Shannon entropy for a time series. The definition is directly applied to several typical time series, and the characteristic of IIE is analyzed. This method can distinguish different kinds of signals and reflects the complexity of one-dimensional time series of high sensitivity to the changes in signal. Thus, the method is applied to the fault diagnosis of a rolling bearing. Experimental results show that the method can effectively extract the sensitive characteristics of the bearing running state and has fast operation time and minimal parameter requirements.

Understanding the Evolution of Tree Size Diversity within the Multivariate Nonsymmetrical Diffusion Process and Information Measures

Abstract: This study focuses on the stochastic differential calculus of Ito, as an effective tool for the analysis of noise in forest growth and yield modeling. Idea of modeling state (tree size) variable in terms of univariate stochastic differential equation is exposed to a multivariate stochastic differential equation. The new developed multivariate probability density function and its marginal univariate, bivariate and trivariate distributions, and conditional univariate, bivariate and trivariate probability density functions can be applied for the modeling of tree size variables and various stand attributes such as the mean diameter, height, crown base height, crown width, volume, basal area, slenderness ratio, increments, and much more. This study introduces generalized multivariate interaction information measures based on the differential entropy to capture multivariate dependencies between state variables. The present study experimentally confirms the effectiveness of using multivariate interaction information measures to reconstruct multivariate relationships of state variables using measurements obtained from a real-world data set.

Fault Feature Extraction and Diagnosis of Rolling Bearings Based on Enhanced Complementary Empirical Mode Decomposition with Adaptive Noise and Statistical Time-Domain Features

Abstract: In this paper, a novel method is proposed to enhance the accuracy of fault diagnosis for rolling bearings. First, an enhanced complementary empirical mode decomposition with adaptive noise (ECEEMDAN) method is proposed by determining two critical parameters, namely the amplitude of added white noise (AAWN) and the ensemble trails (ET). By introducing the concept of decomposition level, the optimal AAWN can be determined by judging the mutation of mutual information (MI) between adjacent intrinsic mode functions (IMFs). Furthermore, the ET is fixed at two to reduce the computational cost. This method can avoid disturbance of the spurious mode in the signal decomposition and increase computational speed. Enhanced CEEMDAN demonstrates a more significant improvement than that of the traditional CEEMDAN. Vibration signals can be decomposed into a set of IMFs using enhanced CEEMDAN. Some IMFs, which are named intrinsic information modes (IIMs), effectively reflect the vibration characteristic. The evaluated comprehensive factor (CF), which combines the shape, crest and impulse factors, as well as the kurtosis, skewness, and latitude factor, is developed to identify the IIM. CF can retain the advantage of a single factor and make up corresponding drawbacks. Experiment results, especially for the extraction of bearing fault under variable speed, illustrate the superiority of the proposed method for the fault diagnosis of rolling bearings over other methods.

Electromechanical Equivalent Circuit Model of a Piezoelectric Disk Considering Three Internal Losses

Abstract: Heat generation by internal loss factors of piezoelectrics is one of the critical issues for high power density piezoelectric applications, such as ultrasonic motors, piezoelectric actuators and transducers. There are three types of internal losses in piezoelectric materials, namely dielectric, elastic and piezoelectric losses. In this paper, a decoupled equivalent circuit is proposed to emulate a piezoelectric disk in radial vibration mode considering all three types of internal losses. First, the decoupled equivalent circuit is derived according to the conventional electromechanical equivalent circuit model. Then, a piezoelectric disk configuration in radial vibration mode is explored and simulated. The resonance and antiresonance frequencies and their corresponding mechanical quality factors are achieved by the proposed circuit. In order to verify the accuracy of the simulation results, the piezoelectric disk is fabricated and tested. Simulation results with the new circuit exhibit a good agreement with experimental results. Finally, the equivalent circuit with only dielectric and elastic losses are simulated and compared which further validates the accuracy improvement of the new equivalent circuit considering all three losses.

SPICE Modeling of a High-Power Terfenol-D Transducer Considering Losses and Magnetic Flux Leakage

Abstract: Of great importance is modeling for transducer design and application to predict its performance and simulate key characteristics. The equivalent circuit modeling (ECM), one of the most powerful tools, has been widely used in the transducer industry and academia due to its outstanding merits of low simulation cost and easy usage for multi-field simulation in both time and frequency domains. Nevertheless, most of the existing equivalent circuit models for Terfenol-D transducers normally ignore three material losses, namely elastic loss, piezomagnetic loss, and magnetic loss. Additionally, the magnetic leakage due to the intrinsic poor magnetic permeability of Terfenol-D is rarely considered into the piezomagnetic coupling. Both loss effects will produce substantial errors. Therefore, an improved SPICE model for a high-power Terfenol-D transducer considering the aforementioned three losses and magnetic flux leakage (MFL) is proposed in this article, which is implemented on the platform of LTspice software. To verify the usefulness and effectiveness of the proposed technique, a high-power Terfenol-D tonpilz transducer prototype with a resonance frequency of around 1 kHz and a maximum transmitting current response (TCR) of 187.1 dB/1A/ μ Pa is built and tested. The experimental results, both in the air and water of the transducer, are in excellent agreement with the simulated results, which well validates our proposed modeling methods.