A mechanism (30) and a method for inserting an elongate member (35) through an aperture of a body, along a longitudinal axis (35), the mechanism comprising a feed portion (42) comprising a feed actuator (43) configured to engage with and drive the elongate member along the longitudinal axis; and, a twist portion (44) comprising a twist actuator (82) configured to engage with the feed portion and rotate the elongate member about the longitudinal axis.

A method for stability analysis of a combustion chamber of a gas turbine engine based on image sequence analysis belongs to the field of fault prediction and health management of aeroengine. Firstly, flow field data inside a combustion chamber of a gas turbine engine is acquired. Secondly, flow field images of the combustion chamber are preprocessed to respectively obtain a discrimination model data set and a prediction model data set. Then, a 3DWaveNet model is constructed as a generation network of a prediction model. A discrimination network of the module is constructed. The generation network and the discrimination network are combined to form the prediction model. Finally, a discrimination model is constructed according to the discrimination model data set; the training set in the discrimination model data set is used for training, and the test set is used for assessment.

Embodiments in accordance with the present disclosure include a meta-stable detergent based foam generating device of a turbine cleaning system includes a manifold configured to receive a liquid detergent and an expansion gas, a gas supply source configured to store the expansion gas, and one or more aerators fluidly coupled with, and between, the gas supply source and the manifold. Each aerator of the one or more aerators comprises an orifice through which the expansion gas enters the manifold, and wherein the orifice of each aerator is sized to enable generation of a meta-stable detergent based foam having bubbles with bubble diameters within a range of 10 microns (3.9×10.sup.−4 inches inches) and 5 millimeters (0.2 inches), having a half-life within a range of 5 minutes and 180 minutes, or a combination thereof.

A turbine blade or vane inspection apparatus comprising a controller, mounting for holding a turbine blade or vane, a source of illumination, and a camera. At least two of the source of illumination, the camera, and the mounting are moveable components. The controller is configured to control the moveable components to (a) position the turbine blade or vane mounted thereon relative to the illumination source so as to provide a contrast of illumination between a feature of the turbine blade or vane and an adjacent surface of the turbine blade or vane and (b), position the camera so that the optical axis of the camera is directed towards the feature. The controller is further configured to determine a dimension and/or shape of the feature based on an image obtained by the camera.

A method for generating material test samples for conducting material tests of a legacy steam turbine rotor having an inter-blade region rotor surface, and an inlet region rotor surface adjoining the inter-blade region rotor surface. The method includes forming an annular ring of rotor material in the sample area and forming a material test sample from a portion of the annular ring. Also described is a legacy steam turbine rotor including an inter-blade region rotor surface, and an inlet region rotor surface adjoining the inter-blade region rotor surface. The steam turbine rotor having a groove formed therein, and wherein the groove is machined to enable removal of material from the steam turbine rotor to form samples configured to enable at least one of conducting material property tests and operating the improved legacy steam turbine rotor at an expanded thermal stress compared to the legacy steam turbine rotor.

A phonic wheel having a body and a tooth is disclosed. An embodiment of the phonic wheel includes a body that is configured to rotate about a rotation axis. The tooth is attached to the body. The tooth has a first axial end relative to the rotation axis, a second axial end opposite the first axial end, and a mid portion extending between the first and second axial ends. The mid portion has a substantially axially uniform height from the body. The first axial end has a greater height from the body than the height of the mid portion.

A method and system for aligning a component within a turbine casing, and a related turbine casing. In a top-on position, a location of an optical target and another, vertically spaced optical target on the joint flange are measured. After removing at least the upper casing, the optical targets' locations are measured again, and the locations of a pair of reference points on an upper surface of the horizontal joint flange are measured. A prediction offset value is calculated for the component support position in the top-on position based on the locations. The prediction offset value may include a vertical adjustment based, in part, on a translation of a triangular spatial relationship of a number of the reference points and/or a tilt angle, a horizontal adjustment, and a horizontal joint flange surface distortion adjustment. Support position is adjusted by the prediction offset value to improve alignment.

The invention relates to a method for training machine learning models, having the steps of: detecting data in the form of time series data using one or more computers, said data being obtained by means of one or more measuring devices (60-62), in each case in the form of a sensor for measuring a physical variable; receiving multiple classification data units relating to the data using the one or more computers; receiving a selected part of the data using the one or more computers for each of the classification data units; and training multiple machine learning models using the one or more computers, in each case on the basis of at least one of the classification data units and the at least one corresponding selected part of the data, wherein the multiple machine learning models represent multiple instances of the same machine learning model.

Systems, program products, and methods for detecting thermal stability within gas turbine systems are disclosed. The systems may include a computing device(s) in communication with a gas turbine system, and a plurality of sensors positioned within or adjacent the gas turbine system. The sensor(s) may measure operational characteristics of the gas turbine system. The computing device(s) may be configured to detect thermal stability within the gas turbine system by performing processes including calculating a lag output for each of the plurality of measured operational characteristics. The calculated lag output may be based on a difference between a calculated lag for the measured operational characteristics and the measured operational characteristic itself. The calculated lag output may be also be based on a time constant for the measured operational characteristics. The computing device(s) may also determine when each of the calculated lag outputs are below a predetermined threshold.

A method of identifying a fuel contained in a fuel tank of an aircraft and arranged to power a gas turbine engine of the aircraft is performed by processing circuitry of the aircraft and includes: obtaining at least one fuel characteristic of any fuel already present in the fuel tank prior to refuelling; determining at least one fuel characteristic of a fuel added to the fuel tank on refuelling; and calculating at least one fuel characteristic of the resultant fuel in the fuel tank after refuelling. The method may further controlling the propulsion system of the aircraft based on the calculated at least one fuel characteristic of the resultant fuel in the fuel tank after refuelling.