Modelling and control of a high redundancy actuator

The high redundancy actuation concept is a completely new approach to fault tolerance, and it is important to appreciate that it provides a transformation of the characteristics of actuators so that the actuation performance (capability) degrades slowly rather than suddenly failing, even though individual elements themselves fail. This paper aims to demonstrate the viability of the concept by showing that a highly redundant actuator, comprising a relatively large number of actuation elements, can be controlled in such a way that faults in individual elements are inherently accommodated, although some degradation in overall performance will inevitably be found. The paper introduces the notion of fault-tolerant systems and the highly redundant actuator concept. Then a model for a two by two configuration with electro-mechanical actuation elements is derived. Two classical control approaches are then considered based on frequency domain techniques. Finally simulation results under a number of faults show the viability of the approach for fault accommodation without re-configuratio

Multiple-fault detection methodology based on vibration and current analysis applied to bearings in induction motors and gearboxes on the kinematic chain

© 2016 Juan Jose Saucedo-Dorantes et al. Gearboxes and induction motors are important components in industrial applications and their monitoring condition is critical in the industrial sector so as to reduce costs and maintenance downtimes. There are several techniques associated with the fault diagnosis in rotating machinery; however, vibration and stator currents analysis are commonly used due to their proven reliability. Indeed, vibration and current analysis provide fault condition information by means of the fault-related spectral component identification. This work presents a methodology based on vibration and current analysis for the diagnosis of wear in a gearbox and the detection of bearing defect in an induction motor both linked to the same kinematic chain; besides, the location of the fault-related components for analysis is supported by the corresponding theoretical models. The theoretical models are based on calculation of characteristic gearbox and bearings fault frequencies, in order to locate the spectral components of the faults. In this work, the influence of vibrations over the system is observed by performing motor current signal analysis to detect the presence of faults. The obtained results show the feasibility of detecting multiple faults in a kinematic chain, making the proposed methodology suitable to be used in the application of industrial machinery diagnosis.Postprint (published version

Alpha-canonical form representation of the open loop dynamics of the Space Shuttle main engine

A parameter and structure estimation technique for multivariable systems is used to obtain a state space representation of open loop dynamics of the space shuttle main engine in alpha-canonical form. The parameterization being used is both minimal and unique. The simplified linear model may be used for fault detection studies and control system design and development

Wireless Fault Detection System for an Industrial Robot Based on Statistical Control Chart

Industrial robots are now commonly used in production systems to improve productivity, quality and safety in manufacturing processes. Recent developments involve using robots cooperatively with production line operatives. Regardless of application, there are significant implications for operator safety in the event of a robot malfunction or failure, and the consequent downtime has a significant impact on productivity in manufacturing. Machine healthy monitoring is a type of maintenance inspection technique by which an operational asset is monitored and the data obtained is analysed to detect signs of degradation and thus reducing the maintenance costs. Developments in electronics and computing have opened new horizons in the area of condition monitoring. The aim of using wireless electronic systems is to allow data analysis to be carried out locally at field level and transmitting the results wirelessly to the base station, which as a result will help to overcome the need for wiring and provides an easy and cost-effective sensing technique to detect faults in machines. So, the main focuses of this research is to develop an online and wireless fault detection system for an industrial robot based on statistical control chart approach. An experimental investigation was accomplished using the PUMA 560 robot and vibration signal capturing was adopted, as it responds immediately to manifest itself if any change is appeared in the monitored machine, to extract features related to the robot health conditions. The results indicate the successful detection of faults at the early stages using the key extracted parameters

Data-based detection and diagnosis of faults in linear actuators

Modern industrial facilities, as well as vehicles and many other assets, are becoming highly automated and instrumented. As a consequence, actuators are required to perform a wide variety of tasks, often for linear motion. However, the use of tools to monitor the condition of linear actuators is not widely extended in industrial applications. This paper presents a data-based method to monitor linear electro-mechanical actuators. The proposed algorithm makes use of features extracted from electric current and position measurements, typically available from the controller, to detect and diagnose mechanical faults. The features are selected to characterize the system dynamics during transient and steady-state operation and are then combined to produce a condition indicator. The main advantage of this approach is the independence from a need for a physical model or additional sensors. The capabilities of the method are assessed using a novel experimental linear actuator test rig specially designed to recreate fault scenarios under different operating conditions

LQG control of a high redundancy actuator

A high redundancy actuator, comprising a relatively large number of actuation elements, is being developed for safety critical applications. Some classical control results have previously been reported and this paper will focus on evaluation of the LQG control design. Three different design approaches will be presented and compared under different types of typical faults in the sub-actuation elements. Overall a LQG design using a physically motivated reduced order model appears to be the best approach

Modelling and control of a high redundancy actuator

The high redundancy actuation concept is a completely new approach to fault tolerance, and it is important to appreciate that it provides a transformation of the characteristics of actuators so that the actuation performance (capability) degrades slowly rather than suddenly failing, even though individual elements themselves fail. This paper aims to demonstrate the viability of the concept by showing that a highly redundant actuator, comprising a relatively large number of actuation elements, can be controlled in such a way that faults in individual elements are inherently accommodated, although some degradation in overall performance will inevitably be found. The paper introduces the notion of fault tolerant systems and the highly redundant actuator concept. Then a model for a two by two configuration with electromechanical actuation elements is derived. Two classical control approaches are then considered based on frequency domain techniques. Finally simulation results under a number of faults show the viability of the approach for fault accommodation without reconfiguration

"The Important Role of Gears in Mechanical Engineering"

Nowadays, the basic requirements of gear transmissions are not limited to resistance and reliability, but often include good efficiency and low vibration and noise emissions. This article investigates the role of tooth flank micro-geometry in fulfilling these needs. A non-linear finite element approach has been conceived and exploited to investigate in detail the influence of the shape of profile modifications (PMs) on transmission error, root stress, and contact pressure. In this approach, harmonic drive gears are widely used in space applications, robotics, and precision positioning systems because of their attractive attributes including near-zero backlash, high speed reduction ratio, compact size, and small weight. On the other hand, they possess an inherent periodic positioning error known as kinematic error responsible for transmission performance degradation. No definite understanding of the mechanism of kinematic error as well as its characterization is available in the literature. The numerical results are first assessed by comparison with experimental measurements and then a comparison of contact and bending stresses of the same gear with long linear and long circular PMs is presented and discussed. The results of these comparisons show that the optimal amount of PMs is not independent of PM shape; hence, the procedures used to design linear PMs cannot be directly applied to the design of non-linear PMs

Predictive Modeling of a Two-stage Gearbox towards Fault Detection

This research presents a systematic approach to health monitoring using dynamic gearbox models (DGM) and the harmonic wavelet transforms (HWT) for vibration response analysis. A comprehensive DGM is developed, the model parameters are identified through correlated numerical and experimental investigations, and HWT analysis is performed to illustrate the fault detection and diagnosis procedure and capability of this approach. The model fidelity is validated first by spectrum analysis, using constant speed experimental data, and secondly by HWT analysis, using non-stationary experimental data. The comparison confirms that both the frequency content and the predicted, relative response magnitudes match with physical measurements. Model prediction and experimental data are compared for healthy gear operation and seeded gear faults including a pinion with a missing tooth, tooth root crack, tooth spall and varying tooth chip severities, demonstrating that fault type and severity are distinguishable. The research shows fault modeling in combination with HWT data analysis is able to identify fault types, evaluate fault relative severity, and greatly reduce pattern recognition library development. This approach can facilitate successful fault detection, diagnosis and prognosis for gearbox systems, providing a physically meaningful connection of fault indicators to the actual fault patterns thus paving the way to real-time condition monitoring