Built-in Encoder Research Articles

Gear Tooth Fault Detection in Servo Motor Transmission Chain Using the Built-In Encoder of Servo Motors

Gear Tooth Fault Detection in Servo Motor Transmission Chain Using the Built-In Encoder of Servo Motors

Intelligent Obstacle Avoidance Controller for QBot2

This paper describes the design process and the steps involved in the implementation of a fuzzy logic-based controller for autonomous navigation of an educational robot called Qbot2. The differential-driven robot is equipped with three ultrasonic sensors (SRF-04) mounted on the front bumper and DC motors with built-in encoders and current sensors. The controller takes the inputs from three ultrasonic sensors and generates the speed commands to avoid any obstacle in its path. PCB is designed to process all the data from the sensors and direct the signal to the motors via motor driver circuits. The low-level implementation of the hurdle avoidance controller is implemented using an inexpensive Arduino UNO in real-time. The controller performance is validated through an experimental run. The designed platform can be used to implement various fuzzy inference systems in real-time and hence can be utilized as laboratory work for testing soft computing algorithms on mobile robotics.

A low-cost camera-based tracking theodolite for large-scale metrology applications

ABSTRACT A wide spectrum of Large-Scale Metrology instruments for measuring 3D positions of mobile targets with different levels of accuracy, operational ranges and corresponding cost exist. However, future assembly paradigms and further industrial applications would benefit from a system with ultra low-cost targets and an accuracy in the order of magnitude of 1 mm, which is currently not available. Therefor the authors propose a camera-based tracking theodolite as a novel instrument for measuring 3D positions of printed visual markers. The approach is implemented as a prototype composed of two rotation stages with built-in encoders, a state-of-the-art industrial CMOS-camera and lens with fixed focal length in conjunction with printed chessboard targets. According mathematical models for the calculation of the targets’ position, kinematic error compensation and measurement uncertainty estimation are elaborated. Competitive experiments against a laser tracker show that the position of the marker can be measured with an absolute error below 1 mm and a statistical uncertainty close to 1 mm in a radius of 5 m, confirming the applicability of the developed concept for a novel Large-Scale Metrology instrument.

Application of improved reweighted singular value decomposition for gearbox fault diagnosis based on built-in encoder information

Due to the harsh operating condition and persistent heavy load, planetary gearboxes as the key transmission parts are prone to damage. With lower cost and better accessibility, the built-in encoder signal has been considered an alternative tool for health state monitoring of gearboxes in recent researches. However, how to extract the feature signature without phase shift or waveform distortion has become a major challenge for current methods. Motivated by this, an improved reweighted singular value decomposition (IRSVD) method is designed to deal with the aforementioned problem in this paper. Firstly, through mathematical derivation combined with numerical analysis, the characteristics of the encoder signal from faulty gear are studied. To accurately evaluate this kind of fault feature, a new index, namely the normalized proportion of harmonics (NPH), is introduced. Without any prior information, it can be used for the optimal selection of the signal component (SC) when applying the proposed IRSVD method. Benefiting from the merit of NPH, IRSVD can choose the optimal SC as the denoised signal, which greatly simplifies the application of traditional singular value decomposition (SVD). Finally, the effectiveness of IRSVD is verified by case studies with both simulated data and real experimental data from a faulty planetary gearbox, containing the challenging corrosion fault and two-worn-teeth fault.

Servo axis incipient degradation assessment of CNC machine tools using the built-in encoder

Servo axis system has been widely applied in the high-precision CNC machine tools. Its performance degradation may lead to the degradation of whole machine and ultimately result to the accuracy degradation of parts manufacturing. Thus, health assessment of the servo axis is very essential, especially for those in-service CNC machine tools. However, restricted by the complexity of servo axis structure, weak signal of incipient degradation, and limited sensors’ installation space, traditional degradation evaluation methods, such as the vibration based scheme, are very difficult to be applied in real service environment directly. In this paper, a new methodology is established for servo axis incipient degradation assessment by reusing the position fluctuation information captured by built-in encoder. Firstly, to highlight the torsional behavior of the servo axis components, the instantaneous angular acceleration (IAA) is estimated by using the position fluctuation information with frequency domain weighting (FDW) method. After that, the wavelet packet transform (WPT) is employed for decomposition of these nonstationary IAA signals. Finally, a Gini index (GI)–guided denoising scheme is established for incipient degradation feature reconstruction. The effectiveness of the proposed method is investigated by simulations; thereafter, it is applied for the X-axis assessment of an in-service high-precision vertical machining center. All the results illustrate that the proposed method is sensitive to incipient degradation of the rotating components and offers an alternative solution for health assessment of servo axis.

An encoder information-based anomaly detection method for planetary gearbox diagnosis

To keep the reliability of the planetary gearbox, anomaly detection has been widely investigated for its health monitoring. To this end, a novel approach is presented in this paper to extract fault features based on the merits of built-in encoder signals. Considering that collected encoder data is accumulated in angular positions, instantaneous angular acceleration (IAA) is firstly calculated to highlight the characteristic components. And then time synchronization average (TSA) is applied on an estimated multi-period for denoising, which improves the robustness of the TSA to the feature attenuation effect caused by the round-off error of the basic period. In this paper, we explore the distinguishing properties of regular components and the fault anomaly to impose different restraints on them, which is embodied as a periodicity-enhanced model of robust principle analysis. And objective features are further separated by solving this optimization model. The validation analysis of the proposed framework is applied on both the simulation and experimental cases. The results show that the proposed method is of good performance to deal with encoder signals from the planetary gearbox for fault diagnosis.

Application of sparsity-oriented VMD for gearbox fault diagnosis based on built-in encoder information

Encoder signal as the built-in information is always used for the speed and motion control. Meanwhile, it has remarkable superiority in the fault diagnosis of gearbox compared with the popular vibration signal. Traditional decomposition method, such as EMD, gradually loses competitiveness with the increase of the complexity of the encoder signal. To solve the problem, with aid of the unique characteristic of encoder signal and the decomposition performance of variational mode decomposition (VMD), a new sparsity-oriented VMD (SOVMD), is originally designed and initially introduced for encoder signal analysis in this paper. Firstly, SOVMD is free from the selection of mode number and initial center frequency (ICF), which troubles seriously the application of VMD. Since a prior ICF which coarsely indicates the location of the fault band can enhance the decomposing efficiency of VMD, ICF = 0 is more appropriate and easier for the extraction of fault information concentrated in the low frequency region. Benefiting from the characteristics of distribution, the optimization of the mode number is unnecessary since the fault mode will generate in the first mode. Secondly, with the proposed selection criterion of the balance parameter, SOVMD can decompose the mode with most fault information more effectively and accurately. Furthermore, a sparsity operation which is originally designed for the encoder signal analysis can further suppress noise and enhance the fault impulses. Through the simulation and experimental cases from the planet gearbox bench, the feasibility and effectiveness of SOVMD can be verified. Therefore, it is reasonable to conclude that the proposed SOVMD is an alternative scheme for gearbox fault diagnosis based on built-in encoder information.

An approach to investigate moiré patterns of a reflective linear encoder with application to accuracy improvement of a machine tool

The accuracy of a machine tool is based on the direct position feedback from its built-in encoders which accurately measure displacements of motion axes by moiré patterns. However, the posture of an encoder is altered by errors from the machine tool, resulting in six geometric deviations. A comprehensive analysis and scientific understanding on the influences of these deviations on moiré patterns are necessary. To investigate the influences, a simulation model of a reflective encoder is constructed to obtain moiré patterns, and four new methods are developed to identify characteristic parameters of the patterns. Variations in characteristic parameters caused by four geometric deviations are simulated and experiments are designed and performed. The results prove that the approach is able to assess the influences of geometric deviations. The approach can be used as a powerful aid for estimating impacts of geometric deviations and external errors on encoders to improve the accuracy of a machine tool.

Manufacturing-error-based maintenance for high-precision machine tools

Nowadays, the condition-based maintenance (CBM), in which repairs are triggered by the heuristic symptoms of the component faults, is finding increasing applications in the industrial fields. However, for the high-precision machine tools, the conventional CBM might not be the optimal option, which is uneconomic and incapable of ensuring their machining accuracy. In order to overcome these shortcomings, this paper propose the manufacturing-error-based maintenance (MEBM), where the repairs are initiated based on the manufacturing errors instead of the heuristic symptoms. In MEBM, repairs are taken properly at the occurrence of the excessive machining errors, and therefore, the premature and redundant maintenance can be avoided and the maintenance cost can be minimized; what is more, the machining errors are controlled in the closed loops, and therefore, the machining accuracy can be guaranteed. Based on the principles of the MEBM, a prototype maintenance system—the transient backlash error (TBE)-based maintenance system—is established. To achieve this aim, first, the width of the backlash in the mechanical chain is measured by utilizing the built-in encoders and the analytical mapping relationship between the backlash width and the TBE is derived. Relying on these foundations, the TBE can be indirectly estimated. Then, the warning threshold of the TBE is customized according to the permissible roundness error of the workpiece. Thus, the maintenance actions can be precisely implemented: when the monitored TBE exceeds its warning threshold, maintenance workers will be notified to lessen the backlash width, and meanwhile, the permissible maximal size for the backlash will also be informed.

Performance Improvement of Machine Tool by High Accuracy Calibration of Built-in Rotary Encoders

Performance Improvement of Machine Tool by High Accuracy Calibration of Built-in Rotary Encoders

High Resolution SelfA Rotary Table by the Interpolation Signal Calibration

Self-A (Self-calibratable Angle device) rotary encoder can detect some kinds of angle error, not only its encoder scale error, but also the encoder attachment error (e.g. eccentricity error). When rotary table with built-in Self-A encoder rotates only one revolution, inner Self-A rotary encoder can calibrate the own angle error with a high accuracy. However, in the case of the Self-A using the encoder of 36,000 graduation scales, since the angular interval of the calibrated main scales corresponds to 36", it is insufficient for high resolution angular indexing control with high accuracy. Generally, the angle error of electric interpolation signal is estimated to be 1 % of main scale resolution that corresponds to about 0.36" for 36,000 scales encoder. Accordingly, even if Self-A had the ability which can calibrate in the accuracy 0.1", when it was controlling the rotary table using an electric interpolation signal, its total accuracy worsened to about 0.36". For improvement in precise angular-position control, we developed Self-A rotary table which can calibrate the angle signal at high resolution including electric interpolation signals. In this paper, we introduce the performance of the new high resolution Self-A encoder table. It keeps high accuracy and good repeatability in the 360° whole range as well as in the short range of ±1,000".

Self-feedback motion control for cable-driven parallel manipulators

This article proposes a closed-loop control scheme based on joint-angle feedback for cable-driven parallel manipulators (CDPMs), which is able to overcome various difficulties resulting from the flexible nature of the driven cables to achieve higher control accuracy. By introducing a unique structure design that accommodates built-in encoders in passive joints, the seven degrees of freedom (7-DOF) CDPM can obtain joint angle values without external sensing devices, and it is used for feedback control together with a proper closed-loop control algorithm. The control algorithm has been derived from the time differential of the kinematic formulation, which relates the joint angular velocities to the time derivative of cable lengths. In addition, the Lyapunov stability theory and Monte Carlo method have been used to mathematically verify the self-feedback control law that has tolerance for parameter errors. With the aid of co-simulation technique, the self-feedback closed-loop control is applied on a 7-DOF CDPM and it shows higher motion accuracy than the one with an open-loop control. The trajectory tracking experiment on the motion control of the 7-DOF CDPM demonstrated a good performance of the self-feedback control method.

Predictive Closed-Loop Power Control for Delay-Prone Burst Transmission Systems in Rayleigh Fading

We present a predictive closed-loop power control scheme for delay-prone burst transmission systems. The scheme has a sample-by-sample predictor compensating burst delay and a built-in channel encoder reducing power control command bit error.

The optical mouse as an inexpensive region-of-interest position recorder in optical microscopy.

In optical microscopy, the microscopic features of interest typically have to be derived from regions that are spatially distributed over the sample. While the features to be analyzed may be minute, the regions from where they must be obtained from may be located quite far apart from one another. If the features are not distinct enough to allow easy visual discrimination, it would be tedious and time-consuming to attempt to recall and revisit these regions of interest. One method to overcome this difficulty would be to note and record the graduated markings on the microscope, or to use built-in position encoders. The former is tedious while the latter is generally expensive. Here, a region-of-interest position-recording implement based on the use of an optical mouse is presented. It is inexpensive and easily adaptable to the manual stage of any optical microscope.