On Increasing the Automation Level of Heavy-Duty Hydraulic Manipulators with Condition Monitoring of the Hydraulic System and Energy-Optimised Redundancy Resolution

Hydraulic manipulators on mobile machines are predominantly used for excavation and lifting applications at construction sites and for heavy-duty material handling in the forest industry due to their superior power-density and rugged nature. These manipulators are conventionally open-loop controlled by human operators who are sufficiently skilled to operate the machines. However, in the footsteps of pioneering original equipment manufacturers (OEMs) and to keep up with the intensifying demand for innovation, more and more mobile machine OEMs have a major interest in significantly increasing the automation level of their hydraulic manipulators and improving the operation of manipulators. In this thesis, robotic software-based functionalities in the form of modelbased condition monitoring and energy-optimal redundancy resolution which facilitate increased automation level of hydraulic manipulators are proposed.A condition monitoring system generally consists of software modules and sensors which co-operate harmonically and monitor the hydraulic system’s health in real-time based on an indirect measure of this system’s health. The premise is that when this condition monitoring system recognises that the system’s health has deteriorated past a given threshold (in other words, when a minor fault is detected, such as a slowly increasing internal leakage of the hydraulic cylinder), the condition monitoring module issues an alarm to warn the system operator of the malfunction, and the module could ideally diagnose the fault cause. In addition, when faced with severe faults, such as an external leakage or an abruptly increasing internal leakage in the hydraulic system, an alarm from the condition monitoring system ensures that the machine is quickly halted to prevent any further damage to the machine or its surroundings.The basic requirement in the design of such a condition monitoring system is to make sure that this system is robust and fault-sensitive. These properties are difficult to achieve in complex mobile hydraulic systems on hydraulic manipulators due to the modelling uncertainties affecting these systems. The modelling uncertainties affecting mobile hydraulic systems are specific compared with many other types of systems and are large because of the hydraulic system complexities, nonlinearities, discontinuities and inherently time-varying parameters. A feasible solution to this modelling uncertainty problem would be to either attenuate the effect of modelling errors on the performance of model-based condition monitoring or to develop improved non-model-based methods with increased fault-sensitivity. In this research work, the former model-based approach is taken. Adaptation of the model residual thresholds based on system operating points and reliable, load-independent system models are proposed as integral parts of the condition monitoring solution to the modelling uncertainty problem. These proposed solutions make the realisation of condition monitoring solutions more difficult on heavy-duty hydraulic manipulators compared with fixed-load manipulators, for example. These solutions are covered in detail in a subset of the research publications appended to this thesis.There is wide-spread interest from hydraulic manipulator OEMs in increasing the automation level of their hydraulic manipulators. Most often, this interest is related to semi-automation of repetitive work cycles to improve work productivity and operator workload circumstances. This robotic semi-automated approach involves resolving the kinematic redundancy of hydraulic manipulators to obtain motion references for the joint controller to enable desirable closed-loop controlled motions. Because conventional redundancy resolutions are usually sub-optimal at the hydraulic system level, a hydraulic energy-optimised, global redundancy resolution is proposed in this thesis for the first time. Kinematic redundancy is resolved energy optimally from the standpoint of the hydraulic system along a prescribed path for a typical 3-degrees-of-freedom (3-DOF) and 4-DOF hydraulic manipulator. Joint motions are also constrained based on the actuators’ position, velocity and acceleration bounds in hydraulic manipulators in the proposed solution. This kinematic redundancy resolution topic is discussed in the last two research papers. Overall, both designed manipulator features, condition monitoring and energy-optimised redundancy resolution, are believed to be essential for increasing the automation of hydraulic manipulators

Performance evaluation of wireless MEMS accelerometer for reciprocating compressor condition monitoring

With recent development in wireless communication and Micro Electro Mechanical Systems (MEMS) technology, it becomes easier to monitor rotating machinery conditions by mounting compact wireless MEMS accelerometers directly on the rotor. This has the potential to provide more accurate dynamic characteristics of the rotating machine and hence achieving high monitoring performance. In this paper, a tiny MEMS accelerometer together with a battery powered microcontroller is mounted on the flywheel to acquire the on-rotor accelerations of a two-stage reciprocating compressor. The measured acceleration data is streamed to a host computer wirelessly via Bluetooth Low Energy (BLE) module. The true tangential acceleration is reconstructed by combining two orthogonal outputs of the sensor, which contain gravitational accelerations. To evaluate the performance of the wireless sensor, three different fault conditions including intercooler leakage, second stage discharge valve leakage and asymmetric stator winding of the motor driver are simulated individually on the compressor test rig. To confirm the wireless sensor performance, an incremental optical encoder was installed on the compressor flywheel to acquire the Instantaneous Angular Speed (IAS) signal for comparison with signals from the wireless sensor. The experimental results show that the running status of the compressor can be remotely monitored, allowing different leakages and motor faults to be diagnosed based on the tangential acceleration reconstructed from a wireless on-rotor MEMS accelerometer

Predictive model for the degradation state of a hydraulic system with dimensionality reduction

In recent years, the optimization in the use of resources has a key role in achieving a bigger marginality, reducing the operative costs. Due to the advances in the data science field, even the maintenance context is living important changes. The predictive maintenance and the condition-based maintenance can overcome the classic traditional maintenance methods, like the time-based maintenance or the corrective maintenance, with respect to the first intervention, reducing the costs for unscheduled maintenance, manpower, or loss of production and extending the useful life of the components. Based on these presuppositions, the paper proposes the development of a predictive model for the degradation state of the components of a complex hydraulic system, with some tests and some suggestions about the dimensionality reduction. The system has four known types of breakdown, with different degrees of severity; moreover, a fifth parameter represents whether the cycle has reached stable conditions or not

Optimized state feedback regulation of 3DOF helicopter system via extremum seeking

In this paper, an optimized state feedback regulation of a 3 degree of freedom (DOF) helicopter is designed via extremum seeking (ES) technique. Multi-parameter ES is applied to optimize the tracking performance via tuning State Vector Feedback with Integration of the Control Error (SVFBICE). Discrete multivariable version of ES is developed to minimize a cost function that measures the performance of the controller. The cost function is a function of the error between the actual and desired axis positions. The controller parameters are updated online as the optimization takes place. This method significantly decreases the time in obtaining optimal controller parameters. Simulations were conducted for the online optimization under both fixed and varying operating conditions. The results demonstrate the usefulness of using ES for preserving the maximum attainable performance

Combining Sensors and Multibody Models for Applications in Vehicles, Machines, Robots and Humans

The combination of physical sensors and computational models to provide additional information about system states, inputs and/or parameters, in what is known as virtual sensing, is becoming increasingly popular in many sectors, such as the automotive, aeronautics, aerospatial, railway, machinery, robotics and human biomechanics sectors. While, in many cases, control-oriented models, which are generally simple, are the best choice, multibody models, which can be much more detailed, may be better suited to some applications, such as during the design stage of a new product

FLEXIBLE LOW-COST HW/SW ARCHITECTURES FOR TEST, CALIBRATION AND CONDITIONING OF MEMS SENSOR SYSTEMS

During the last years smart sensors based on Micro-Electro-Mechanical systems (MEMS) are widely spreading over various fields as automotive, biomedical, optical and consumer, and nowadays they represent the outstanding state of the art. The reasons of their diffusion is related to the capability to measure physical and chemical information using miniaturized components. The developing of this kind of architectures, due to the heterogeneities of their components, requires a very complex design flow, due to the utilization of both mechanical parts typical of the MEMS sensor and electronic components for the interfacing and the conditioning. In these kind of systems testing activities gain a considerable importance, and they concern various phases of the life-cycle of a MEMS based system. Indeed, since the design phase of the sensor, the validation of the design by the extraction of characteristic parameters is important, because they are necessary to design the sensor interface circuit. Moreover, this kind of architecture requires techniques for the calibration and the evaluation of the whole system in addition to the traditional methods for the testing of the control circuitry. The first part of this research work addresses the testing optimization by the developing of different hardware/software architecture for the different testing stages of the developing flow of a MEMS based system. A flexible and low-cost platform for the characterization and the prototyping of MEMS sensors has been developed in order to provide an environment that allows also to support the design of the sensor interface. To reduce the reengineering time requested during the verification testing a universal client-server architecture has been designed to provide a unique framework to test different kind of devices, using different development environment and programming languages. Because the use of ATE during the engineering phase of the calibration algorithm is expensive in terms of ATE’s occupation time, since it requires the interruption of the production process, a flexible and easily adaptable low-cost hardware/software architecture for the calibration and the evaluation of the performance has been developed in order to allow the developing of the calibration algorithm in a user-friendly environment that permits also to realize a small and medium volume production. The second part of the research work deals with a topic that is becoming ever more important in the field of applications for MEMS sensors, and concerns the capability to combine information extracted from different typologies of sensors (typically accelerometers, gyroscopes and magnetometers) to obtain more complex information. In this context two different algorithm for the sensor fusion has been analyzed and developed: the first one is a fully software algorithm that has been used as a means to estimate how much the errors in MEMS sensor data affect the estimation of the parameter computed using a sensor fusion algorithm; the second one, instead, is a sensor fusion algorithm based on a simplified Kalman filter. Starting from this algorithm, a bit-true model in Mathworks Simulink(TM) has been created as a system study for the implementation of the algorithm on chip

Advanced Strategies for Robot Manipulators

Amongst the robotic systems, robot manipulators have proven themselves to be of increasing importance and are widely adopted to substitute for human in repetitive and/or hazardous tasks. Modern manipulators are designed complicatedly and need to do more precise, crucial and critical tasks. So, the simple traditional control methods cannot be efficient, and advanced control strategies with considering special constraints are needed to establish. In spite of the fact that groundbreaking researches have been carried out in this realm until now, there are still many novel aspects which have to be explored

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Effective use of machinery and maintenance planning requires improving of situational awareness and knowing the condition of the machinery. In mineral and aggregate industry, the maintenance is traditionally performed according to fixed time intervals or when the machines break down. One implemented solution for improving situational awareness is different kind of remote monitoring solutions. Knowing the condition of the machines improves the up-time and helps to prevent unexpected failures of the machines that work in difficult conditions. There are various condition monitoring products and services on the market, but they may not fulfil directly all of the requirements of this industry. It may therefore be a risk that the condition monitoring may not be comprehensive enough, if they are implemented with those commercial services. The goal of this work is divided in three research questions. The focus of the work is on the first one. The question number one is associated with searching of condition monitoring applications, which are application specific for mineral and aggregate industry. In this context, this work reviews different condition monitoring methods, but the actual measurements are implemented by using vibration sensors. The found application specific condition monitoring methods are tested by designing and implementing measurement setup. The measurement setup is installed on a mobile crushing unit – Metso Lokotrack LT106. The measurement setup includes measuring of machine orientation, monitoring of a frame bearing of the crusher and monitoring vibration of machine’s main conveyor. The used data-analysis methods are calculating the machine frame orientation by using the measured direction of gravity, monitoring of vibration root-mean-square velocity, envelope analysis of bearing high-frequency vibration and analysis of vibration frequency spectrum. The second research question estimates the minimum hardware requirements for the measurements, so that the desired phenomena can be reliably detected. The third question is to assess the economic feasibility of the selected measurements. Based on the results of this work, the current single point measurement of unit orientation is insufficient solution. Elastic frame may twist too much during use of the machine, and the operator may not notice it. On the other hand, inclination of the machine may change excessively during the use, if the ground under the machine sinks. In case of the crusher frame bearing, the result of envelope analysis indicates developing faults in a rolling element and inner race of the bearing. In turn, monitoring of the vibration root-mean-square velocity of the main conveyor does detect excessive vibration during the monitoring period, which is quite expected result, because the conveyor is accurately designed by using Finite element method. Based on the results, the orientation of the machine would be worthwhile to implement as commercial product, as well as the crusher bearing condition monitoring