An investigation on the impact fatigue characteristics of valve leaves for small hermetic reciprocating compressors in a new automated test system

This paper presents an investigation on the impact fatigue characteristics of valve leaves that are prevalently used in hermetic reciprocating compressors especially for the household type refrigerators. A unique automated impact fatigue test system has been designed and produced, which enables to carry out impact fatigue tests of the compressor valve leaves under the desired impact velocities. The test system serves investigations on the impact fatigue characteristics with the ability of crack detection and as the subsequent step of automatically terminating the test. The crack detection technique incorporates a non-contact actuation, a data acquisition system and a microphone. The investigation relates the impact fatigue lifetime of the valve leaves with the impact velocity, asymmetrical impact, operation temperature, material type (carbon strip steel, stainless strip steel and new stainless strip steel grade) and tumbling operation duration. Microscopic and metallographic observations were performed on the specimens. It was observed that the crack initiated at the edge of the valve leaves on the contact surface of valve leaf and vale plate and a particle is torn away from the edge before propagation. As the crack propagates, branching along the crack path is caused by the geometrical shape and stress waves on the valve leaves. The investigation and introduced test system guide the design optimization of valve leaves in terms of compressor performance due to energy consumption and lifetime of the valve leaf

Tool flank wear prediction using high-frequency machine data from industrial edge device

Tool flank wear monitoring can minimize machining downtime costs while increasing productivity and product quality. In some industrial applications, only a limited level of tool wear is allowed to attain necessary tolerances. It may become challenging to monitor a limited level of tool wear in the data collected from the machine due to the other components, such as the flexible vibrations of the machine, dominating the measurement signals. In this study, a tool wear monitoring technique to predict limited levels of tool wear from the spindle motor current and dynamometer measurements is presented. High-frequency spindle motor current data is collected with an industrial edge device while the cutting forces and torque are measured with a rotary dynamometer in drilling tests for a selected number of holes. Feature engineering is conducted to identify the statistical features of the measurement signals that are most sensitive to small changes in tool wear. A neural network based on the long short-term memory (LSTM) architecture is developed to predict tool flank wear from the measured spindle motor current and dynamometer signals. It is demonstrated that the proposed technique predicts tool flank wear with good accuracy and high computational efficiency. The proposed technique can easily be implemented in an industrial edge device as a real-time predictive maintenance application to minimize the costs due to manufacturing downtime and tool underuse or overuse.Comment: The first four authors have equal contributio

Tool path pattern and feed direction selection in robotic milling for increased chatter-free material removal rate

Robotic milling becomes increasingly relevant to large-scale part manufacturing industries thanks to its cost-effective and portable manufacturing concept compared to large-scale CNC machine tools. Integration of milling processes with industrial robots is proposed to be well aligned with the aims and objective of the recent fourth industrial revolution. However, the industrial robots introduce position-dependent and asymmetrical dynamic flexibility, which may reflect to the tool tip dynamics under several conditions. Under such circumstances, the stability limits become dependent on the machining location and the feed direction. In this respect, selection of machining tool path patterns is crucial for increased chatter-free material removal rates (MRR). This paper proposes an approach to evaluate and select tool path patterns, offered by the existing CAM packages, for increased chatter-free MRR. The machining area is divided into number of machining locations. The optimal feed direction is decided based on the absolute stability at each region considering the asymmetrical and position-dependent tool tip dynamics. Then, the alternative tool path patterns are evaluated and the corresponding optimum feed direction is decided for increased chatter-free material removal. The application of the proposed approach is demonstrated through simulations and representative experiments

A Novel Mosaic Quality Measurement Method for UAV Surveillance and Remote Sensing

A novel hardware independent real-time aerial image stabilization and mosaicing system is developed for mini UAV surveillance and remote sensing operations. In order to measure the quality of the constructed mosaics, several in-door and flight tests were performed. A novel mosaic quality measurement method utilizing 5 axis CNC for 3D positioning of the camera and printed high resolution aerial images for ground truth information is described. Results of the path following tests employing several state of art registration algorithms are provided. Mosaics constructed in real-time during flight tests are presented

An enhanced analytical model for residual stress prediction in machining

The predictions of residual stresses are most critical on the machined aerospace components for the safety of the aircraft. In this paper, an enhanced analytic elasto-plastic model is presented using the superposition of thermal and mechanical stresses on the workpiece, followed by a relaxation procedure. Theoretical residual stress predictions are verified experimentally with X-ray diffraction measurements on the high strength engineering material of Waspaloy that is used critical parts such as in aircraft jet engines. With the enhanced analytical model, accurate residual stress results are achieved, while the computational time compared to equivalent FEM models is decreased from days to secends. (c) 2008 CIRP