scholarly journals Effect of phase in fast frequency measurements for sensors embedded in robotic systems

2019 ◽  
Vol 16 (4) ◽  
pp. 172988141986972 ◽  
Author(s):  
Juan de Dios Sanchez-Lopez ◽  
Fabian N Murrieta-Rico ◽  
Vitalii Petranovskii ◽  
Joel Antúnez-García ◽  
Rosario I Yocupicio-Gaxiola ◽  
...  
Keyword(s):  
Frequency Estimation ◽  
Frequency Measurement ◽  
Measurement Methods ◽  
Sampling Time ◽  
Measurement Process ◽  
Robotic Systems ◽  
Rational Approximations ◽  
Input Stimulus ◽  
Input Signals ◽  
Time Accuracy

The use of sensors is a primary need in robotic systems. There are sensors that generate a signal whose frequency depends on input stimulus. The application of such sensors is desirable due to their short response time, accuracy, and resolution. For proper use of these sensors, adequate frequency measurement is required. The principle of rational approximations is a method for frequency estimation that has advantages over other measurement methods. Some of them include not a fixed sampling time, insensitivity to jitter, and accuracy limited by the reference stability. Nevertheless, there are some measurement parameters with a not well-researched effect in measurement process. The objective of this work is to elucidate how the phase of input signals (measurand and reference) affects the frequency measurement process.

scholarly journals A New Approach to Measurement of Frequency Shifts Using the Principle of Rational Approximations

2017 ◽  
Vol 24 (1) ◽  
pp. 45-56 ◽  
Author(s):  
Fabian N. Murrieta-Rico ◽  
Vitalii Petranovskii ◽  
Oleg Y. Sergiyenko ◽  
Daniel Hernandez-Balbuena ◽  
Lars Lindner
Keyword(s):  
Frequency Domain ◽  
Input Parameter ◽  
Research Result ◽  
Frequency Measurement ◽  
Signal Frequency ◽  
Rational Approximations ◽  
Input Stimulus ◽  
Frequency Shifts ◽  
Time Frequency ◽  
Time Required

Abstract When a frequency domain sensor is under the effect of an input stimulus, there is a frequency shift at its output. One of the most important advantages of such sensors is their converting a physical input parameter into time variations. In consequence, changes of an input stimulus can be quantified very precisely, provided that a proper frequency counter/meter is used. Unfortunately, it is well known in the time-frequency metrology that if a higher accuracy in measurements is needed, a longer time for measuring is required. The principle of rational approximations is a method to measure a signal frequency. One of its main properties is that the time required for measuring decreases when the order of an unknown frequency increases. In particular, this work shows a new measurement technique, which is devoted to measuring the frequency shifts that occur in frequency domain sensors. The presented research result is a modification of the principle of rational approximations. In this work a mathematical analysis is presented, and the theory of this new measurement method is analysed in detail. As a result, a new formalism for frequency measurement is proposed, which improves resolution and reduces the measurement time.

scholarly journals Performance of Frequency Anti-Islanding Protection Considering Different Frequency Estimation Methods

2020 ◽  
Author(s):  
Daniel F. Friedemann ◽  
Daniel Motter
Keyword(s):  
High Frequency ◽  
Frequency Estimation ◽  
Frequency Measurement ◽  
Measurement Methods ◽  
Estimation Methods ◽  
Frequency Components

Frequency anti-islanding protections use frequency measures to determine an islanding condition, which are usually filtered to eliminate high frequency components. Digital relays can use different frequency estimation methods, which could lead to different results between different methods and filter lengths. This paper compares three frequency estimation methods found in digital relays against noise, harmonics, DC decays, steps and slopes of frequency, showing their intrinsic differences. Islanding events are simulated to show the importance of investigating frequency measurement methods and filter lengths before performing any protection study.

Application of the Principle of Rational Approximations for Measuring Dynamic Frequency Values Generated by an IMU

2020 ◽  
pp. 26-51
Author(s):  
Fabian N. Murrieta-Rico ◽  
Vitalii Petranovskii ◽  
Juan de Dios Sanchez-Lopez ◽  
Juan Ivan Nieto-Hipolito ◽  
Mabel Vazquez-Briseño ◽  
...  
Keyword(s):  
Frequency Estimation ◽  
Frequency Measurement ◽  
Critical Parameters ◽  
Measurement Unit ◽  
Accurate Information ◽  
Rational Approximations ◽  
Inertial Measurement ◽  
Aerial Vehicles ◽  
Measurement Algorithm ◽  
Dynamic Frequency

In most aerial vehicles, accurate information about critical parameters like position, velocity, and altitude is critical. In these systems, such information is acquired through an inertial measurement unit. Parameters like acceleration, velocity, and position are obtained after processing data from sensors; some of them are the accelerometers. In this case, the signal generated by the accelerometer has a frequency that depends from the acceleration experienced by the sensor. Since the time available for frequency estimation is critical in an aerial device, the frequency measurement algorithm is critical. This chapter proposes the principle of rational approximations for measuring the frequency from accelerometer-generated signals. In addition, the effect of different measurement parameters is shown, discussed, and evaluated.

scholarly journals Learning to See the Vibration: A Neural Network for Vibration Frequency Prediction

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2530 ◽  
Author(s):  
Jiantao Liu ◽  
Xiaoxiang Yang
Keyword(s):  
Neural Network ◽  
Vibration Frequency ◽  
Frequency Estimation ◽  
Vibration Signal ◽  
Frequency Measurement ◽  
Optical Methods ◽  
Vibration Measurement ◽  
Vibration Signals ◽  
Engineering Practices ◽  
To Receive

Vibration measurement serves as the basis for various engineering practices such as natural frequency or resonant frequency estimation. As image acquisition devices become cheaper and faster, vibration measurement and frequency estimation through image sequence analysis continue to receive increasing attention. In the conventional photogrammetry and optical methods of frequency measurement, vibration signals are first extracted before implementing the vibration frequency analysis algorithm. In this work, we demonstrate that frequency prediction can be achieved using a single feed-forward convolutional neural network. The proposed method is verified using a vibration signal generator and excitation system, and the result compared with that of an industrial contact vibrometer in a real application. Our experimental results demonstrate that the proposed method can achieve acceptable prediction accuracy even in unfavorable field conditions.

scholarly journals High-accuracy Photonics-assisted Frequency Measurement With Rough-accurate Compensation Based on Mach-Zehnder Interfering and Power Cancellation

2021 ◽  
Author(s):  
Lanfeng Huang ◽  
Yongjun Li ◽  
Shanghong Zhao ◽  
Tao Lin ◽  
Guodong Wang ◽  
...  
Keyword(s):  
Frequency Estimation ◽  
Frequency Measurement ◽  
High Accuracy ◽  
Optical Field ◽  
Comparison Function ◽  
Multiple Frequency ◽  
Frequency Identification ◽  
Mach Zehnder Modulator ◽  
Rf Signal ◽  
Polarization Division Multiplexing

Abstract A high-accuracy photonics-assisted frequency measurement with rough-accurate compensation based on Mach-Zehnder interfering and power cancellation is proposed. A polarization division multiplexing dual-parallel Mach–Zehnder modulator (PDM-DPMZM) is employed to mix the unknown RF signal and sweep signal to optical field. The rough measurement is firstly performed by the interference of a Mach-Zehnder interferometer (MZI) to realize fast frequency estimation. Then, based on the rough measurement result, the accurate measurement based on power cancellation is implemented in a much narrower range, which greatly improves the efficiency of frequency measurement. The simulation results show that the amplitude comparison function (ACF) established by interference can achieve a measurement error of less than 0.3 GHz over 0.5 ~39 GHz. Moreover, thanks to the rough-accurate compensation, the accuracy can be further improved to 4 MHz. Additionally, the multiple frequency identification with a resolution of 10 MHz can also be achieved based on this system.

scholarly journals Robust Reservoir Generation by Correlation-Based Learning

2009 ◽  
Vol 2009 ◽  
pp. 1-7
Author(s):  
Tadashi Yamazaki ◽  
Shigeru Tanaka
Keyword(s):  
Interstimulus Interval ◽  
Conditioned Response ◽  
Eyeblink Conditioning ◽  
Activity Patterns ◽  
Reservoir Computing ◽  
Input Stimulus ◽  
Connection Weight ◽  
Input Signals ◽  
Trace Eyeblink Conditioning ◽  
New Framework

Reservoir computing (RC) is a new framework for neural computation. A reservoir is usually a recurrent neural network with fixed random connections. In this article, we propose an RC model in which the connections in the reservoir are modifiable. Specifically, we consider correlation-based learning (CBL), which modifies the connection weight between a given pair of neurons according to the correlation in their activities. We demonstrate that CBL enables the reservoir to reproduce almost the same spatiotemporal activity patterns in response to an identical input stimulus in the presence of noise. This result suggests that CBL enhances the robustness in the generation of the spatiotemporal activity pattern against noise in input signals. We apply our RC model to trace eyeblink conditioning. The reservoir bridged the gap of an interstimulus interval between the conditioned and unconditioned stimuli, and a readout neuron was able to learn and express the timed conditioned response.

A context-aware frequency estimation method for wireless passive resonant SAW sensors

Sensor Review ◽  
2017 ◽  
Vol 37 (4) ◽  
pp. 458-467
Author(s):  
Boquan Liu ◽  
Pinghua Tang
Keyword(s):  
Measurement Method ◽  
Design Methodology ◽  
Frequency Estimation ◽  
Estimation Method ◽  
Frequency Measurement ◽  
Wireless Channel ◽  
Physical Parameters ◽  
Medical Applications ◽  
Context Aware ◽  
Content Type

Purpose This paper aims to present an context evaluation and frequency measurement method for surface acoustic wave (SAW) resonant sensor. Design/methodology/approach This method is based on a signal subspace construction, which, along with assembling optional value set, provides the results. Findings The method can assess the application context and improve the resolution and accuracy of the passive wireless SAW resonator sensor system. Originality/value Passive wireless SAW resonators have been used as sensor elements for different physical parameters such as temperature, pressure and force in a number of industrial and medical applications. Various wireless channel environments introduce different application contexts.

A comparison of frequency measurement methods for underfrequency load shedding

1998 ◽  
Vol 45 (3) ◽  
pp. 209-219 ◽  
Author(s):  
Zoran Salcic ◽  
Zhenguo Li ◽  
U.D. Annakkage ◽  
Nalin Pahalawaththa
Keyword(s):  
Frequency Measurement ◽  
Measurement Methods ◽  
Load Shedding

scholarly journals Frequency Measurement Methods by Signal Processing Techniques

2012 ◽  
Vol 38 ◽  
pp. 2590-2594 ◽  
Author(s):  
Shilpa Y. Sondkar ◽  
Santosh Dudhane ◽  
Hemant K. Abhyankar
Keyword(s):  
Signal Processing ◽  
Frequency Measurement ◽  
Measurement Methods ◽  
Processing Techniques ◽  
Signal Processing Techniques

scholarly journals Learning to See the Vibration: a Neural Network for Vibration Frequency Prediction

2018 ◽  
Author(s):  
Jiantao Liu ◽  
Xiaoxiang Yang
Keyword(s):  
Neural Network ◽  
Vibration Frequency ◽  
Frequency Estimation ◽  
Vibration Signal ◽  
Frequency Measurement ◽  
Optical Methods ◽  
Vibration Measurement ◽  
Vibration Signals ◽  
Engineering Practices ◽  
To Receive

Vibration measurement serves as the basis for various engineering practices such as natural frequency or resonant frequency estimation. As image acquisition devices become cheaper and faster, vibration measurement and frequency estimation through image sequence analysis continue to receive increasing attention. In the conventional photogrammetry and optical methods of frequency measurement, vibration signals are first extracted before implementing the vibration frequency analysis algorithm. In this work, we demonstrated that frequency prediction can be achieved using a single feed-forward convolutional neural network. The proposed method is verified using a vibration signal generator and excitation system, and the result obtained was compared with that of an industrial contact vibrometer in a real application. Our experimental results demonstrate that the proposed method can achieve acceptable prediction accuracy even in unfavorable field conditions.

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