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Automation of the drilling process is a widely spread goal in the rock excavator industry. An intermediate step can be to assist a manual drilling process by informing the operator of the quality of the drilling. To reach the goals, it is thus imperative to have a high performance monitoring system based on physics involved in the drilling process. A necessity to develop such an information system, is insight into the physics involved in the drilling process. This can be gained by using combinations of simulations, lab tests and in-situ tests. Here, a 1D model representing Down The Hole (DTH) drilling is used. Such a model can be further developed to simulate good and bad performance of drilling. The resulting vibration responses, hydraulic pressure responses, etc. of the system can be analyzed with the purpose to identify possible sources of informative data which can be measured and recorded during a real world rock drilling operation. Here, a simplified 3D model of the DTH drilling system involving the bit, hammer and the drill string is also made and used together with boundary conditions constituting a simplified model of the rock. The aim here is to find a computationally efficient 3D modeling methodology to simulate the drilling for various conditions, due to various drilling parameter settings. The aim is to develop a 3D model that can be refined further and can be used extensively to understand the DTH drilling process in order to facilitate performance monitoring and in the end automized DTH drilling.

In order to reduce costly downtime, adequate condition monitoring of the automatic transmission components in heavy duty construction equipment is necessary. The transmission in such equipment enables to change the gear ratio automatically. Further, the bearings in an automatic transmission provide low friction support to its rotating parts and act as an interface separating stationary from rotating components. Wear or other bearing faults may lead to an increase in energy consumption as well as failure of other related components in the automatic transmission, and thus costly downtime. In this study, different sensor data (particularly vibration) was collected on the automatic transmission during controlled test cycles in an automatic transmission test rig to enable adequate condition monitoring. An analysis of the measured vibration data was carried out using signal processing methods. The results indicate that predictive maintenance information related to the automatic transmission bearings may be extracted from vibrations measured on an automatic transmission. This information may be used for early fault detection, thus improving uptime and availability of heavy duty construction equipment.

Improving uptime is paramount in the heavy duty construction equipment business. Failure ofcritical components in the heavy duty machine may lead to unnecessary stops and expensive downtime. The torque converter, a complex omponent of the driveline, transmits and multiplies torque from the engine to the gearbox, and its failure may not only lead to the machine standing still but may also lead to damage of other parts of the automatic transmission. For adequate condition monitoring of the torque converter, different sensor data are measured on a construction equipment machine during controlled driving sessions. Vibration has been measured on the torque converter. An initial investigation of the vibration measured on the torque converter has been carried out to identify its vibration properties in order to enable its health monitoring to prevent failure. Initial signal analysis of the data have been carried out using Order Power Spectrum and Order Modulation Spectrum methods. The results indicate that the torque converter vibration properties contain information relevant for early fault detection. Fastelaboratoriet - VINNEXC

With increasing complexities in the heavy duty construction equipment, early fault detection of certain components in the machine becomes more and more challenging due to too many fault code generated when a failure occurs. The axle is one of such component. The axle transfers driving torque from the transmission to the wheels and axle failure may result in costly downtime of construction equipment. To reduce service cost and to improve uptime, adequate condition monitoring based on sensor data from the axle is considered. Vibration is measured on the axle. Analysis of the data has been carried out using adequate signal processing methods. The results indicate that the vibration properties of the axle are relevant for early fault detection of the axle. In this way; the health of the axle may be continuously monitored on-board using the vibration information and if the axle health starts to degrade a service and/or repair may be scheduled well in advance of a potential axle failure and in that way the downtime of a machine may be reduced. Fastelaboratoriet - VINNEXC

Godkänd; 2015; 20150303 (jlm) Fastelaboratoriet - VINNEXC

Godkänd; 2014; 20140819 (jlm)