scholarly journals Method for QCM Resonator Device Equivalent Circuit Parameter Extraction and Electrode Quality Assessment

Micromachines ◽  
2021 ◽  
Vol 12 (9) ◽  
pp. 1086
Author(s):  
Dong Liu ◽  
Xiaoting Xiao ◽  
Ziqiao Tang ◽  
Qiao Chen ◽  
Haoran Li ◽  
...  
Keyword(s):  
Measurement Error ◽  
Quality Assessment ◽  
Electrode Material ◽  
Parameter Extraction ◽  
Circuit Parameter ◽  
Lumped Element ◽  
Crystal Resonator ◽  
Wide Range ◽  
Data Points ◽  
Physical Quantities

Quartz crystal microbalance (QCM) resonators are used in a wide range of sensors. Current QCM resonators achieve a simultaneous measurement of multiple physical quantities by analyzing lumped-element equivalent parameters, which are obtained via the introduction of external devices. This introduction of external devices will probably increase measurement error. To realize the measurement of multiple physical quantities while eliminating the measurement error caused by external devices, this paper proposes a measurement method for the lumped-element equivalent parameters of QCM resonators without the need for extra external devices. Accordingly, a numerical method for solving nonlinear equations with fewer data points required and a higher accuracy was adopted. A standard crystal resonator parameter extraction experiment is described. The extracted parameters were consistent with the nominal parameters, which confirms the accuracy of this method. Furthermore, six QCM resonator device samples with different electrode diameters and materials were produced and used in the parameter measurement experiment. The linear relationship between the electrode material conductivity and motional resistance R1 is discussed. The ability of this method to characterize the electrode material and to detect the rust status of the electrode is also demonstrated. These abilities support the potential utility of the proposed method for an electrode quality assessment of piezoelectric devices.

Quantitation of measurement error with Optimal Segments: basis for adaptive time course smoothing

1993 ◽  
Vol 264 (6) ◽  
pp. E902-E911 ◽  
Author(s):  
D. C. Bradley ◽  
G. M. Steil ◽  
R. N. Bergman
Keyword(s):  
Measurement Error ◽  
Measurement Errors ◽  
Time Course ◽  
Smooth Curve ◽  
Random Group ◽  
Smooth Curves ◽  
Original Curve ◽  
Wide Range ◽  
Data Points ◽  
Time Courses

We introduce a novel technique for estimating measurement error in time courses and other continuous curves. This error estimate is used to reconstruct the original (error-free) curve. The measurement error of the data is initially assumed, and the data are smoothed with "Optimal Segments" such that the smooth curve misses the data points by an average amount consistent with the assumed measurement error. Thus the differences between the smooth curve and the data points (the residuals) are tentatively assumed to represent the measurement error. This assumption is checked by testing the residuals for randomness. If the residuals are nonrandom, it is concluded that they do not resemble measurement error, and a new measurement error is assumed. This process continues reiteratively until a satisfactory (i.e., random) group of residuals is obtained. In this case the corresponding smooth curve is taken to represent the original curve. Monte Carlo simulations of selected typical situations demonstrated that this new method ("OOPSEG") estimates measurement error accurately and consistently in 30- and 15-point time courses (r = 0.91 and 0.78, respectively). Moreover, smooth curves calculated by OOPSEG were shown to accurately recreate (predict) original, error-free curves for a wide range of measurement errors (2-20%). We suggest that the ability to calculate measurement error and reconstruct the error-free shape of data curves has wide applicability in data analysis and experimental design.

FIT/PVL circuit-parameter extraction for general electromagnetic devices

2000 ◽  
Vol 36 (4) ◽  
pp. 1421-1425 ◽  
Author(s):  
D. Ioan ◽  
T. Weiland ◽  
T. Wittig ◽  
I. Munteanu
Keyword(s):  
Parameter Extraction ◽  
Circuit Parameter ◽  
Electromagnetic Devices

scholarly journals Modelling with star-shaped distributions

2020 ◽  
Vol 8 (1) ◽  
pp. 45-69
Author(s):  
Eckhard Liebscher ◽  
Wolf-Dieter Richter
Keyword(s):  
Probabilistic Models ◽  
Arbitrary Dimension ◽  
Probability Density Functions ◽  
Density Functions ◽  
Wide Range ◽  
Gaussian Density ◽  
Spherical Distributions ◽  
Data Points ◽  
Non Gaussian ◽  
General Method

AbstractWe prove and describe in great detail a general method for constructing a wide range of multivariate probability density functions. We introduce probabilistic models for a large variety of clouds of multivariate data points. In the present paper, the focus is on star-shaped distributions of an arbitrary dimension, where in case of spherical distributions dependence is modeled by a non-Gaussian density generating function.

scholarly journals An Efficient Filtering Approach for Removing Outdoor Point Cloud Data of Manhattan-World Buildings

2021 ◽  
Vol 13 (19) ◽  
pp. 3796
Author(s):  
Lei Fan ◽  
Yuanzhi Cai
Keyword(s):  
Point Cloud ◽  
Indoor Environment ◽  
Laser Scanning ◽  
Point Cloud Data ◽  
Hole Filling ◽  
Cloud Data ◽  
Indoor Space ◽  
Wide Range ◽  
Data Points ◽  
Filtering Approach

Laser scanning is a popular means of acquiring the indoor scene data of buildings for a wide range of applications concerning indoor environment. During data acquisition, unwanted data points beyond the indoor space of interest can also be recorded due to the presence of openings, such as windows and doors on walls. For better visualization and further modeling, it is beneficial to filter out those data, which is often achieved manually in practice. To automate this process, an efficient image-based filtering approach was explored in this research. In this approach, a binary mask image was created and updated through mathematical morphology operations, hole filling and connectively analysis. The final mask obtained was used to remove the data points located outside the indoor space of interest. The application of the approach to several point cloud datasets considered confirms its ability to effectively keep the data points in the indoor space of interest with an average precision of 99.50%. The application cases also demonstrate the computational efficiency (0.53 s, at most) of the approach proposed.

Design of an FMCW Radar Altimeter for Wide-Range and Low Measurement Error

2015 ◽  
Vol 64 (12) ◽  
pp. 3517-3525 ◽  
Author(s):  
Jae-Hyun Choi ◽  
Jong-Hun Jang ◽  
Jin-Eep Roh
Keyword(s):  
Measurement Error ◽  
Radar Altimeter ◽  
Fmcw Radar ◽  
Wide Range
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