Data Preprocessing of Magnetic Suspension Gyro-Total-Station by Vondrak Filter

2013 ◽  
Vol 671-674 ◽  
pp. 2099-2102
Author(s):  
Hui Ru Li ◽  
Zhi Qiang Yang ◽  
Zhen Shi
Keyword(s):  
Mathematical Model ◽  
Root Mean Square ◽  
High Precision ◽  
Data Preprocessing ◽  
Magnetic Suspension ◽  
Mean Square ◽  
Total Station ◽  
Maximum Extent ◽  
Process Measurements ◽  
Vondrak Filter

For Magnetic Suspension Gyro-total-station has vulnerable to outside interference factors, there are some random drifting containing in measurements which are unable to establish its mathematical model. Vondrak filter which does not require the model is used to pre-process measurements of Magnetic Suspension Gyro-total-station. In this paper a high-precision astronomical baseline is established in Xi'an, and the gyro azimuth is tested eight times in baseline. 40,000 north-seeking torque of the first and second place is filtered by the Vondrak filter for each test. The results show that the burr of data is reduced after filtered, and the filtered values reflect the trends of gyro north-seeking. Compared with the root mean square (RMS) of the measurements, RMS of Vondrak filter is decreased, the data is denser. Vondrak filter can effectively eliminate the random drifting containing in measurements, retain useful information in the maximum extent, and improve the accuracy of true north azimuth.

scholarly journals The new analytical expression for measurement uncertainty in a measuring of RMS value of AC signals as result of non ideal synchronization

2006 ◽  
Vol 3 (1) ◽  
pp. 33-43
Author(s):  
Predrag Petrovic
Keyword(s):  
Computer Simulation ◽  
Measurement Uncertainty ◽  
Root Mean Square ◽  
Fundamental Frequency ◽  
High Precision ◽  
Mathematical Expression ◽  
Mean Square ◽  
Precision Instrument ◽  
Synchronous Sampling ◽  
Measurement Uncertainties

Synchronous sampling allows alternating current (AC) quantities, such as the root mean square (RMS) values of voltage and power, to be determined with very low uncertainties (on the order of a few parts of 10-6 [1]). In this a new mathematical expression for estimating measurement uncertainties in non ideal synchronization with fundamental frequency AC signals is presented. The obtained results were compared with those obtained with a high-precision instrument for measuring basic AC values. Computer simulation demonstrating the effectiveness of these new expression, are also presented.

scholarly journals Debris Recognition Methods in the Lubrication System with Electrostatic Sensors

2018 ◽  
Vol 2018 ◽  
pp. 1-15
Author(s):  
Huijie Mao ◽  
Hongfu Zuo ◽  
Han Wang ◽  
Yibing Yin ◽  
Xin Li
Keyword(s):  
Mathematical Model ◽  
Root Mean Square ◽  
Electrostatic Charge ◽  
Bench Test ◽  
Lubrication System ◽  
Mean Square ◽  
Test Results ◽  
Test Rig ◽  
Traditional Methods ◽  
New Methods

The oil-line electrostatic sensor (OLS) is a developing debris monitoring sensor. Previous work has shown that electrostatic charge signals can indicate the debris by calculating the Root Mean Square (RMS) value or the correlation-based indicator, but the precision of these methods is not high. This paper further developed the more accurate methods to obtain detailed debris information. Firstly, to interpret the monitoring principle of OLS and provide the guidance for developing the debris recognition methods, this paper analyzed the possible charge sources in the lubrication system and obtained the characteristics of the OLS by establishing its mathematical model. Further, a new OLS test rig was designed and verified the correctness of the sensor’s characteristics and its mathematical model. Based on the characteristics of the sensor, two new debris recognition methods were proposed. Finally, the effects of the new debris recognition methods were verified by the practical industrial gearbox bench test. Results showed that, compared to the traditional methods, the new methods could recognize the debris effectively and provide more detailed information of the debris.

scholarly journals Experimental Validation of Numerical Model for Bi-Tilt-Isolator

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Ming-Hsiang Shih ◽  
Wen-Pei Sung ◽  
Chia-Yu Ho
Keyword(s):  
Mathematical Model ◽  
Root Mean Square Error ◽  
Mean Square Error ◽  
Root Mean Square ◽  
Friction Force ◽  
Polynomial Function ◽  
Mean Square ◽  
Test Results ◽  
Cubic Polynomial ◽  
Simulation Results

Bi-Tilt Isolator (BTI) is composed of bi-tilt beveled substrate and slider. The advantages of BTI are that the maximum upload seismic force of structure can be easily controlled and displacement of isolation layer will be reduced. Sliding force, friction force, and impulse force are caused in the slanting process of BTI, nonlinear behavior. A nonlinear mathematical model is derived based on the sliding upwards, sliding downwards, and transition stages. Then, BTI element of nonlinear analysis program, GENDYN, is developed by the fourth-order Runge-Kutta method, the discretized ordinary differential equation for three movement stages of BTI. Then, test set-up of superstructure installed with BTI is tested and recorded the real displacement and acceleration responses under conditions of full lubrication, mild lubrication, and without lubrication between interface of bi-tilt beveled substrate and slider with three various initial displacements. The comparison of simulation results and test results shows the following: (1) root mean square error is below 1.35% for WD40 sprayed, 0.47% for WD40 whipped, and 0.54% for without lubrication, respectively; (2) the maximum root mean square error for simulating with cubic polynomial function of friction is much less than those of constant friction except conditions of full lubrication, which are not affected by kinetic friction force; (3) application of cubic polynomial function for simulating friction of BTI with three different lubricated conditions can perform very fine simulation results, compared with the test results. This proposed mathematical model and BTI element of GENDYN program, using cubic polynomial function of friction, perform fine simulation capability to assess nonlinear isolation effect of structure installed with BTI.

Short-Time Torque Investigations on DMA-Bearings

1977 ◽  
Vol 99 (1) ◽  
pp. 65-74
Author(s):  
M. P. Rivera
Keyword(s):  
Root Mean Square ◽  
High Precision ◽  
Ball Bearing ◽  
Mean Square ◽  
Time Basis ◽  
Short Time ◽  
Minimum Torque

A new bearing torque rig capable of qualifying and analyzing bearing torque signals for large-bore high-precision bearings is described. The servomechanical subsystem responsible for torque definition within ± 5.9 × 10−4 Nm is also described. In addition to a space proven lubricant, two lubricants were tested in this rig: KG-80 oil and Polyfluoralkylalkyl polysiloxane grease. Tests were conducted on short-time basis in open air conditions. All three lubricants were tested in a 100 mm bore high-precision angular ball bearing, with and without ball retainer. The bearing was operated at various loads and speeds. Dependence on torque and Root Mean Square-torque as function of lubricant quantity are established. Data trend reveals the existence of a region of minimum torque for oil-retainer bearing configurations. Data also imply the feasability of using the two aforementioned lubricants and the full ball complement configuration in DMA-type applications.

scholarly journals Advances in Tracking Control for Piezoelectric Actuators Using Fuzzy Logic and Hammerstein-Wiener Compensation

Mathematics ◽  
2020 ◽  
Vol 8 (11) ◽  
pp. 2071
Author(s):  
Cristian Napole ◽  
Oscar Barambones ◽  
Isidro Calvo ◽  
Mohamed Derbeli ◽  
Mohammed Yousri Silaa ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Root Mean Square Error ◽  
Mean Square Error ◽  
Root Mean Square ◽  
High Precision ◽  
Complex Structure ◽  
Piezoelectric Actuators ◽  
Absolute Error ◽  
Hysteresis Effect ◽  
Mean Square

Piezoelectric actuators (PEA) are devices that are used for nano- microdisplacement due to their high precision, but one of the major issues is the non-linearity phenomena caused by the hysteresis effect, which diminishes the positioning performance. This study presents a novel control structure in order to reduce the hysteresis effect and increase the PEA performance by using a fuzzy logic control (FLC) combined with a Hammerstein–Wiener (HW) black-box mapping as a feedforward (FF) compensation. In this research, a proportional-integral-derivative (PID) was contrasted with an FLC. From this comparison, the most accurate was taken and tested with a complex structure with HW-FF to verify the accuracy with the increment of complexity. All of the structures were implemented in a dSpace platform to control a commercial Thorlabs PEA. The tests have shown that an FLC combined with HW was the most accurate, since the FF compensate the hysteresis and the FLC reduced the errors; the integral of the absolute error (IAE), the root-mean-square error (RMSE), and relative root-mean-square-error (RRMSE) for this case were reduced by several magnitude orders when compared to the feedback structures. As a conclusion, a complex structure with a novel combination of FLC and HW-FF provided an increment in the accuracy for a high-precision PEA.

The Relationship of Root Mean Square Value of Electromyography and Isometric Torque of Quadriceps in Normal Subjects

2016 ◽  
Vol 26 (1) ◽  
pp. 58
Author(s):  
Qiurong XIE ◽  
Zheng JIANG ◽  
Qinglu LUO ◽  
Jie LIANG ◽  
Xiaoling WANG ◽  
...  
Keyword(s):  
Root Mean Square ◽  
Normal Subjects ◽  
Mean Square ◽  
Isometric Torque ◽  
Relationship Of ◽  
The Relationship

scholarly journals Estimation of Apple Flowering Frost Loss for Fruit Yield Based on Gridded Meteorological and Remote Sensing Data in Luochuan, Shaanxi Province, China

2021 ◽  
Vol 13 (9) ◽  
pp. 1630
Author(s):  
Yaohui Zhu ◽  
Guijun Yang ◽  
Hao Yang ◽  
Fa Zhao ◽  
Shaoyu Han ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Root Mean Square Error ◽  
Mean Square Error ◽  
Root Mean Square ◽  
Minimum Temperature ◽  
Price Regulation ◽  
Flowering Period ◽  
Mean Square ◽  
Prevention Measures ◽  
Agricultural Insurance

With the increase in the frequency of extreme weather events in recent years, apple growing areas in the Loess Plateau frequently encounter frost during flowering. Accurately assessing the frost loss in orchards during the flowering period is of great significance for optimizing disaster prevention measures, market apple price regulation, agricultural insurance, and government subsidy programs. The previous research on orchard frost disasters is mainly focused on early risk warning. Therefore, to effectively quantify orchard frost loss, this paper proposes a frost loss assessment model constructed using meteorological and remote sensing information and applies this model to the regional-scale assessment of orchard fruit loss after frost. As an example, this article examines a frost event that occurred during the apple flowering period in Luochuan County, Northwestern China, on 17 April 2020. A multivariable linear regression (MLR) model was constructed based on the orchard planting years, the number of flowering days, and the chill accumulation before frost, as well as the minimum temperature and daily temperature difference on the day of frost. Then, the model simulation accuracy was verified using the leave-one-out cross-validation (LOOCV) method, and the coefficient of determination (R2), the root mean square error (RMSE), and the normalized root mean square error (NRMSE) were 0.69, 18.76%, and 18.76%, respectively. Additionally, the extended Fourier amplitude sensitivity test (EFAST) method was used for the sensitivity analysis of the model parameters. The results show that the simulated apple orchard fruit number reduction ratio is highly sensitive to the minimum temperature on the day of frost, and the chill accumulation and planting years before the frost, with sensitivity values of ≥0.74, ≥0.25, and ≥0.15, respectively. This research can not only assist governments in optimizing traditional orchard frost prevention measures and market price regulation but can also provide a reference for agricultural insurance companies to formulate plans for compensation after frost.

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