Rotary Encoder Research Articles

Optimizing the De-Bruijn Code of Rotary Optical Encoders Preventing From the Photocurrent Blooming

The De-Bruijn sequences could provide appropriate circular arrangements to achieve a single-track absolute rotary optical encoder in the servo motor application. One example used popularly is the maximum length sequences. High-resolution single-track encoders need a sensor array to obtain the position signal simultaneously. Nevertheless, the individual photocurrents would interference by other adjacent photocurrents, like the photocurrent blooming. The circumstances would increase the bias noise for the digital binarization. The concept in this article would try to find the optimal De-Bruijn sequences to reduce the photocurrent blooming interference intrinsically without signal process remodification. Three different types of the 9-bits codes, the adjacent De-Bruijn code, the quarter De-Bruijn codes, and the optimal De-Bruijn codes, are analyzed, manufactured, and experimented in the actual encoders. Based on the open-factor of the eye-diagram, the adjacent De-Bruijn code has 0.328 and would be the worse signal quality in De-Bruijn sequences. The quarter De-Bruijn codes have 0.386 of the open-factor with 17.7% improvement to adjacent De-Bruijn code. Finally, the optimal De-Bruijn codes have 0.436 of the open-factor with 32.9% improvement to the traditional M-code. The fact would mean the possible ability of 3-bits progress from 9-bits of adjacent De-Bruijn code to 12-bits of the optimal De-Bruijn codes under the same signal-to-noise ratio.

OpBox: Open Source Tools for Simultaneous EEG and EMG Acquisition from Multiple Subjects.

In vivo electrophysiology experiments require the collection of data from multiple subjects, often for extended periods. Studying multiple subjects for extended periods can be made more efficient through simultaneous recordings, but scaling up recordings to accommodate larger numbers of subjects simultaneously requires coordination and consideration of costs and flexibility. To facilitate this process, we have developed OpBox, an open source set of tools to acquire electroencephalography (EEG) and electromyography (EMG) flexibly from multiple rodent subjects simultaneously. OpBox combines open source hardware and software with off-the-shelf components to create a system that costs less than commercial solutions ($500 per subject), and can be easily deployed for multiple subjects. Coded in MATLAB, OpBox scripts can simultaneously and flexibly collect and display multiple analog and digital data streams, for instance real-time EEG and EMG, event triggers from a behavioral system, and rotary encoder data. OpBox also calculates and displays real-time spectral representations and event-related potentials (ERPs). To verify the performance of our system, we compare our amplifiers with two other commercial amplifiers, a Grass P55 AC preamplifier and an Intan RHD2000-series amplifier. The OpBox amplifier performs comparably to commercial amplifiers for signal-to-noise ratios (SNRs), noise floors, and common mode rejection. We also demonstrate that our acquisition system can reliably record multichannel data from multiple subjects, and has been successfully tested with 12 subjects running simultaneously on a single standard desktop computer. Together, OpBox increases the flexibility and lowers the cost for simultaneous acquisition of electrophysiology data from multiple subjects.

Stabilized controller of a two wheels robot

The Segway Human Transport (HT) robot, it is dynamical self-balancing robot type. The stability control is an important thing for the Segway robot. It is an indisputable fact that Segway robot is a natural instability framework robot. The case study of the Segway robot focuses on running balance control systems. The roll, pitch, and yaw balance of this robot are obtained by estimating the Kalman Filter with a combination of the pole placement and the Linear Quadratic Regulator (LQR) control method. In our system configuration, the mathematical model of the robot will be proved by Matlab Simulink by modelling of the stabilizing control system of all state variable input. Furthermore, the implementation of this system modelled to the real-time test of the Segway robot. The expected result is by substitute the known parameters from Gyro, Accelero and both rotary encoder to initial stabilize control function, the system will respond to the zero input curve. The coordinate units of displacement response and inclination response pictures are the same. As our expected, the response of the system can reach the zero point position.

Detecting feeble position oscillations from rotary encoder signal in an industrial robot via singular spectrum analysis

Position signal faces several weak oscillations due to mechanical flaw and faults occurred in the systems. These oscillations can be identified by the encoders that determine the performance and health condition of the machine. Nevertheless, also the concerned oscillation, rotary encoder signal also includes some measurement noise and a significant trend. These trends are typically of several orders, greater in activities than the involved amplitude oscillations, making it tough to detect the small oscillations except deformation of the signal. In addition, the oscillations can be problematic, and magnitude adjusted in unstable conditions. Singular spectrum analysis (SSA) is proposed to overcome this issue. A numerical emulation is demonstrated to show the efficiency of the approach. It indicates that SSA outperforms ensemble empirical mode decomposition (EEMD), empirical mode decomposition, and complete EEMD with adaptive noise in ability and accuracy. Moreover, during the movement of the robotic arm, encoder signals from the robot are analysed to determine the sources of oscillations in joints. The suggested technique is proven to be reliable and feasible for an industrial robot.

The Influence of Functional Flywheel Resistance Training on Movement Variability and Movement Velocity in Elite Rugby Players.

The aim of this study was to identify the changes in movement variability and movement velocity during a six-week training period using a resistance horizontal forward–backward task without (NOBALL) or with (BALL) the constraint of catching and throwing a rugby ball in the forward phase. Eleven elite male rugby union players (mean ± SD: age 25.5 ± 2.0 years, height 1.83 ± 0.06 m, body mass 95 ± 18 kg, rugby practice 14 ± 3 years) performed eight repetitions of NOBALL and BALL conditions once a week in a rotational flywheel device. Velocity was recorded by an attached rotary encoder while acceleration data were used to calculate sample entropy (SampEn), multiscale entropy, and the complexity index. SampEn showed no significant decrease for NOBALL (ES = -0.64 ± 1.02) and significant decrease for BALL (ES = -1.71 ± 1.16; p < 0.007) conditions. Additionally, movement velocity showed a significant increase for NOBALL (ES = 1.02 ± 1.05; p < 0.047) and significant increase for BALL (ES = 1.25 ± 1.08; p < 0.025) between weeks 1 and 6. The complexity index showed higher levels of complexity in the BALL condition, specifically in the first three weeks. Movement velocity and complex dynamics were adapted to the constraints of the task after a four-week training period. Entropy measures seem a promising processing signal technique to identify when these exercise tasks should be changed.

A super-high-accuracy angular index table

This study quantitatively derives a principle for super-high-accuracy angular indexing using an index table formulation, and verifies it in a mathematical simulation. An index table is a rotary table installed on a machine tool. Its main function is to fix the angle position of the rotational shaft. The angle position is measured by a rotary encoder built into the rotary table. The rotary encoder is required to measure the angle with high accuracy. In previous studies, the performance of the rotary encoder has been improved by two methods: direct reduction of the angle error factors, and self-calibration. The angle accuracy in these methods varies from 0.1 to 0.4 arcsecs during one rotation. Instead, the National Institute of Advanced Industrial Science and Technology (NMIJ/AIST) in Japan has developed an angular indexing device with super high accuracy, which measures the static angle position to 0.01 arcsecs. Although the principle of super-accurate angular indexing has been qualitatively discussed, a quantitative understanding is lacking. In the present paper, the principle is derived from a Fourier transform analysis, exploiting the circular closure characteristic of the angle error. The principle is then investigated in mathematical simulation of the quantitative formulation. The simulation has obtained positive results to derive the principle quantitatively.

"Ester"-A new ring-shear-apparatus for hydrate-bearing sediments.

We developed a new thermostated ring-shear-apparatus for investigation on hydrate- or ice-bearing sediments. A fluid inlet at the bottom of the static part of the cell and a fluid outlet at the top of the rotating half-cell allow exchanging and pressurizing the pore fluid in the sample cell to a certain value below the pressure providing the normal load that is applied hydraulically via a seal disk using a syringe pump. The volume change in the sample can be derived from the volume received or injected by the pump. The system allows the use of different methods for the formation and controlled decomposition of hydrate before, after, and during a shear test. The ring-shear-cell is designed for a maximum hydraulic pressure of 30 MPa. A commercial hollow shaft servo actuator applies the torque to the rotating half of the sample cell, and a rotary encoder provides information for determining the shear displacement. Stress path investigations in shear rate controlled experiments with large strain are possible with shear rates up to 12.6 mm/s and torques up to 1440 N m. The system design allows for complex experiments studying the behavior of a shear plane in hydrate- and/or ice-bearing sediments, including the decomposition and reformation of hydrate and/or ice under varying pressure and temperature conditions. It is a useful tool to provide experimental data to support research and engineering in solving problems related to permafrost and hydrate-bearing formations. The system performance is demonstrated by examples of tests on hydrate- and ice-bearing sand samples.

Proof of concept of a novel absolute rotary encoder

Rotary encoders are used in many applications that require monitoring or controlling mechanical systems such as robots. Typically, small rotary encoders have poor resolution; this is unfortunate for applications such as robotics in medical surgery procedures. For example, in an articulated robotic endoscope, miniaturization is mandatory and, when automation is desired, high accuracy to track the shape and pose of the device is required; small (few millimeters) and accurate (few hundred arcsec) rotary encoders are thus needed.Previously, we introduced a novel concept of a miniaturizable angular sensor, called ASTRAS (Angular Sensor for TRAcking System). This was presented as a basic element of a tracking system for articulated endoscopes. The principle of measurement of ASTRAS is based on processing a shadow image cast by a shadow mask onto an image sensor. The characterization of the first prototype of ASTRAS was very promising, however, its angular range of about ±30 degrees was too limiting for many practical applications.In this work, we present an extension of the concept mentioned above to a rotary encoder that can measure one full rotation of 360 degrees thus the name is ASTRAS360. Its working principle bases on encoding the shadow image using colored light to distinguish different angular sectors. The identification of the sector corresponds to a coarse angular measurement, which is afterward refined using the same technique as in ASTRAS. We implemented this concept, realizing a prototype and an algorithm to calculate the angle from the shadow image. The experiments demonstrated the validity of this concept and showed encouraging results with a precision of ∼0.6 arcsec and 6σ-resolution of 3.6 arcsec corresponding to 19 bits.

Dual-Laser Goniometer: A Flexible Optical Angular Sensor for Joint Angle Measurement

This article presents a flexible optical goniometer for the measurement of single-axis joint angular displacement. The design philosophy behind the apparatus lies that the agent's angular displacement is converted to the laser's distance measurement thanks to geometric conversion. We propose a dual-laser ranging model for joint angle measurement with the aid of a reference plane. This model converts the agent's rotational angle to the distance of laser range measurements under triangular constraints. Compared with the commonly used rotary encoders, the proposed sensor shows its competence in easy installation and flexible deployment. Furthermore, a model parameter calibration approach is introduced to decrease the angular measurement error. Extensive validation experiments with a prototype sensor on a robot arm prove the aforementioned claims and show that the prototype sensor can reach an angular precision of 0.3° with a measurement range of -30°-30°.

Compensation of Rotary Encoders Using Fourier Expansion-Back Propagation Neural Network Optimized by Genetic Algorithm.

The measurement accuracy of the precision instruments that contain rotation joints is influenced significantly by the rotary encoders that are installed in the rotation joints. Apart from the imperfect manufacturing and installation of the rotary encoder, the variations of ambient temperature could cause the angle measurement error of the rotary encoder. According to the characteristics of the periodicity of the angle measurement at the stationary temperature and the complexity of the effects of ambient temperature changes, the method based on the Fourier expansion-back propagation (BP) neural network optimized by genetic algorithm (FE-GABPNN) is proposed to improve the angle measurement accuracy of the rotary encoder. The proposed method, which innovatively integrates the characteristics of Fourier expansion, the BP neural network and genetic algorithm, has good fitting performance. The rotary encoder that is installed in the rotation joint of the articulated coordinate measuring machine (ACMM) is calibrated by using an autocollimator and a regular optical polygon at ambient temperature ranging from 10 to 40 °C. The contrastive analysis is carried out. The experimental results show that the angle measurement errors decrease remarkably, from 110.2″ to 2.7″ after compensation. The mean root mean square error (RMSE) of the residual errors is 0.85″.

Chaos in the switched reluctance motor drive employing digital speed and current control

Adjustable speed motor drives are among the most representative types of non-linear systems which can exhibit rich varieties of complex dynamic behaviours. This study presents the investigation of chaotic phenomena in the switched reluctance (SR) motor drive employing digital speed regulator and hysteresis current controller. For conducting stability analysis, a small signal discrete-time model of the SR drive has been derived and analysed for a range of control parameters. The simulation results of time-domain and frequency-domain analysis and phase portraits of the SR drive system are also demonstrated and discussed. Two influencing factors for chaotic behaviour in the SR drive system are identified and examined in detail: the feedback delay of the speed regulator and measurement imperfection from a rotary incremental encoder. For verification, an 8/6 pole 2.3 kW SR drive is employed in experimental tests. The bifurcation diagrams of the reference signal, waveforms of phase current, and the corresponding frequency spectra are recorded and illustrated for both normal and chaotic operations, which reveal the pattern of chaos exhibited from this type of electric drive system.

Development of Liquefied Petroleum Gas (LPG) leakage detection wheeled robot on horizontal pipes based on Arduino Uno

LPG utilization need more attention to safety aspects of human, environmental and equipment. This research aims to develop a wheeled robot which is capable of detecting LPG leaks in horizontal pipes by data acquisition via wireless internet, so that it is useful to facilitate human work in determining LPG leak points on horizontal pipes. The controller of this robot is Arduino UNO and equipped with sensors. The sensor measurement data is acquisitioned using the Node MCU module to the Blynk application as an interface application. This robot has an emergency stop feature on the Blynk application. The final results of this research are LPG leak detection robots on horizontal pipes which can provide information on leak points based on gas sensor measurement data and rotary encoder installed on robots with acquisition via wireless internet and data storage on MicroSD. The robot is equipped with buzzer indicator that will sound when a leak is indicated with a gas concentration of more than 30% on one of the gas sensors. Based on the results of final test of the robot, the average value of the leakage point distance obtained is +8.7 cm.

Control Position of Mobile Robot Based on Odometry Method and PID Controller

A mobile robot had been made based on kinematics drive differential concept. This robot used odometry method in order to reach a position and determine its current position. Proportional Integral Derivative (PID) control has been applied for improving response of robot while it reach a detremined position. Two rotary encoder sensors were attached at right and left side of robot motors for measuring distance. While motor rotating, rotary encoder sensors counted a number of pulses conversed into left and right wheel mileage. Both of them were used to get robot position at certain time (x, y, and heading angle). Robot passed some tracks and reached two positions in each track as destination positions. These positions are the position which had final heading 30° and 90°on first track, 45° and 90° on second track, 60° and 90° on third track. PID control was examined by put mobile robot in first position 0,0,0°. Some PID parameters have been applied to examine the performance and response of robot. The increment of derivative parameter reduced the steady state error and increased the stability of system.

CONCEPTUAL DESIGN OF AUTONOMOUS CART FOLLOWER FOR WHEELCHAIR USER

This paper focuses on kinematics of the cart follower and the system identification of propulsion system by using brushed DC motor. The cart follower uses Ackermann configuration as the steering system. The modeling of kinematics equation takes into account the instantaneous center of rotation (ICR), velocity of each tire, heading angle, and simple movement of the cart. The cart is propelled by transaxle brushed DC motor. It is important to approximate an accurate transfer function to represent the motor as the plant module is unavailable. The motor is simulated by using Arduino hardware package in MATLAB®. Rotary encoder is used to record the angular velocity of the shaft. MATLAB® code is created in order to calculate the linear velocity and tabulate the datasets. System Identification Toolbox determines the transfer function of the motor and its performance. The variables measured in experiment to identify the transfer function of the DC motor system are output angular velocity and input voltage. The parameters taken from the DC motor’s mathematical model are derived based on existing literatures. The graph of output velocity against time is plotted and the transfer function is estimated by using System Identification Toolbox in MATLAB®. From the results, it is demonstrated that the motor exhibits second order system.&#x0D; Keywords: Cart follower, wheel mobile robot, kinematics, system identification

Some approaches on instantaneous angular speed measurement using a two-phase n poles AC generator as sensor

The paper proposes an instantaneous angular speed (IAS) measurement method, based on computer-aided processing of two instantaneous induced electromotive force (EMF) signals (in phase quadrature) delivered by a two-phase n poles AC rotary generator used as sensor, which works also as a n poles sine and cosine waves rotary encoder. In this approach, firstly, an optional number of m virtual EMF signals are generated by computing the two real EMF signals. Afterwards, a high sampling rate and high accuracy IAS measurement method is proposed using the elapsed time between zero-crossing moments of each two consecutive virtual EMF signals. On the same generator, a known IAS measurement method (slightly adapted) is used also for comparison purposes. In this method, the two real EMF signals define by calculus a rotation angle whose numerical differentiation produces the IAS value. Both IAS measurement methods validate well each other through frequency domain signal processing and analysis, from 0 to 7000 Hz. Some experiments, achieved on a lathe headstock output spindle, confirm the availability of the proposed IAS measurement method for monitoring and diagnosis.

Projeto de uma biruta eletrônica híbrida

The windsock is a meteorological instrument that indicates wind direction. This instrument is critical in sea travel and aviation and this sensor can prevent accidents in emergency situations such as storms caused by a particular wind direction.hus, in this work it is proposed to develop an electronic windsock using a rotary encoder module and infrared LEDS. For the development of the Wind Direction Sensor project an Arduino microcontroller and c ++ language were used. The engineered hybrid system converts the rotations into an electrical signal. These signals were associated with east, west, north and south orientations. The projected sensor presented a lower probability of error in the wind direction information when compared to the windsock that employs 5mm Infrared LED.

Missing value recovery for encoder signals using improved low-rank approximation

Rotary encoders have been increasingly equipped in high precision machinery, and their data missing may pose great challenges for both numeric control and health monitoring. In view of this limitation, a new methodology, termed improved low-rank approximation (ILRA), is proposed for encoder signal recovery. In this approach, phase space representation (PSR) is first introduced to transform the one-dimensional encoder signal into a matrix for low-rank exploration. Bidirectional centralization with cumulative energy ratio is then proposed to identify and extract the principal components embedded in phase space. Finally, an improved low-rank approximation scheme is employed to recover the missing values in an iterative manner. The performance of the proposed ILRA is evaluated by both simulation and experimental analysis. The results show that the proposed method can recover the missing values efficiently. Furthermore, the method yields satisfactory results for subsequent instantaneous angular speed estimation. Therefore, it may offer a promising tool for numerical data recovery in industrial applications.

Nonlinear Error Compensation of Capacitive Angular Encoders Based on Improved Particle Swarm Optimization Support Vector Machines

Rotary encoders are widely applied in a variety of industrial fields. However, as the exist of the installation, processing and demodulation circuits errors, the test result of the encoder is superimposed with periodic nonlinear errors and the encoder needs compensation to achieve high measurement accuracy. Traditional methods including the least square method (LSM) and back propagation artificial neural network (BP-ANN), are not capable of addressing nonlinear errors. Thus, a novel method based on improved particle swarm optimization (IPSO) and support vector machines (SVM) is proposed to provide better compensation. The proposed method incorporates the SVM method into the design of the compensation model, and the IPSO algorithm is applied to tune the SVM parameters. To validate the algorithm, four sets of data were obtained from encoders with different numbers of segments. The experimental results show that the IPSO-SVM algorithm has a better prediction precision and the nonlinear standard deviation of 180 petal-shaped numbers has dropped from 0.08° to 0.0005° after compensation over 0° to 360° measurement range. Based on the results, the proposed IPSO-SVM model provided more accurate compensation on the nonlinear errors to the capacitive angular encoders than other method.

Development of a General- Purpose Test Platform for Agricultural Navigation

Field tests are necessary in establishing navigation models and algorithms for agricultural vehicle robots. And it costs much to use tractors or combine harvesters as the platform in terms of system modification, routine maintenance and fuel consumption. The objective of this research was to develop a general-purpose test platform for conducting experiments in agricultural autonomous navigation at a low cost based on a commercially available electric vehicle. A brushless motor was utilized as the power source for automatic steering. An analog PID controller was designed to compare steering commands and actual steering angle and calculate an appropriate voltage signal as the input of the motor driver. A rotary encoder was attached to the driving wheel and a digital PID controller was implemented to determine the throttle value in real-time in maintaining the test platform at a desired speed. A CAN-bus network was established to integrate the automatic steering system and the speed control system as two nodes for information communication. And a CAN node interface was reserved for receiving commands from autonomous navigation systems to be evaluated. Field tests showed that RMS errors were 2.6 cm and 0.054 m·s-1 for lateral offset and speed control, respectively, in tracking straight paths, which indicated that the newly developed test platform met requirements for agricultural navigation experiments.

A Sensor Based Monitoring System for Real-Time Quality Control: Semi-Automatic Arc Welding Case Study

Welding is one of the mostly used joining techniques for metal parts in the manufacturing industry. The quality of a weld is critical since it influences the lifetime of the product or people’s safety. Therefore, manufacturers are looking for reliable and cost-effective methods to monitor and control welding quality in real-time. In this paper, an attempt has been made to investigate data acquisition, integration, and visualization using heterogeneous sensor data. A semi-automatic welding system is then developed using a linear track and a Gas Metal Arc Welding (GMAW) power source. The system includes voltage, current and temperature sensors, a rotary encoder, CCD camera, and signal processing hardware and software. Welding signatures were captured using a data acquisition (DAQ) module and software was developed to store and visualize the captured data. The developed system can be used as a testbed for experimental applications or as a quality control system for the arc welding process in manufacturing shop floors.