Impact Fatigue Characteristics of Valve Leaves for Small Hermetic Reciprocating Compressors

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. The investigation relates the impact fatigue lifetime of the valve leaves that is the heart of the compressor, with the working temperature, material type (carbon steel, stainless steel and improved stainless steel grade) and tumbling duration after the manufacturing process. The investigation provides a better understanding of the impact fatigue characteristics of valve leaves while designing a high performance compressor to decrease the energy consumption. \ud A unique automated impact fatigue test system was designed and produced, which enables to carry out impact fatigue tests of the compressor valve leaves under the desired impact velocities. In the test system, original valve plate and valve leaf couple was utilized through the experimentation in order to simulate the real behavior in the compressor. A fixture was designed to mount the valve plate. The main principle of the system is to create pulsating airflow through a high frequency solenoid valve. The impact fatigue life was determined for various impact velocities and at different operating temperatures

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

Temperature Effects on Grinding Residual Stress

AbstractResidual stress is a key factor that influences the reliability, precision, and life of final products. Earlier studies have alluded to the fact that the grinding process is usually the source of a tensile residual stress on the part surface, while there exists a temperature level commonly referred to as the onset tensile temperature beyond which the tensile profile of residual stresses starts to be generated. In this paper, a physics-based model is proposed to predict the onset temperature as a function of residual stress on an analytical and quantitative basis. The predictive model is based on the temperature distribution function using a moving heat source approach. Then, the thermal stresses are calculated analytically using Timoshenko thermal stress theory [1] followed by an elastic-plastic relaxation condition imposed on these stresses, thus leading to the resulting residual stresses. The model-predicted results have been experimentally validated using data of the grinding of AISI52100 hardened steel with subsequent X-ray and Neutron diffraction measurements. The model was shown to predict the residual stress profile under given process conditions and material properties, therefore providing an analytical tool for grinding process planning and optimization based on the understanding of onset tensile temperature for control of tensile residual stresses

An optimization methodology for material databases to improve cutting force predictions when milling martensitic stainless steel JETHETE-M152

A material database for JETHETE-M152 was developed applying a novel methodology for improving the precision of cutting forces. This approach defines a variable specific edge force depending on the feed rate and cutting edge geometry. Applying this methodology, accurate predictions could be obtained when using complex shape inserts with different micro-geometries or with feed rates lower than the cutting edge radius. These predictions showed an improvement compared to those of the strategy of keeping constant the specific edge coefficient. Furthermore, an orthogonal to oblique transformation technique was applied to predict the cutting forces in face and side milling. The results showed good agreement with experimental results

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

Thermal analysis in Ti-6Al-4V drilling

Ti-6Al-4V is commonly used especially in aerospace and biomedical industries. This alloy is known as a difficult-to-cut material. Due to its poor thermal properties, the heat generated during machining processes traps near material deformation zones. This causes detrimental high temperatures for the cutting tools. This article combines the analytical and FEM modeling techniques to estimate the temperature evolution of carbide tools in Ti-6Al-4V drilling. In this article, a novel thermocouple based temperature measurement setup is also introduced. Moreover, the simulated and measured temperatures under various cutting conditions for the drilling of Ti-6Al-4V are presented for the validation

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

Modeling and compensation of geometric errors in simultaneous cutting using a multi-spindle machine tool

A volumetric error compensation method for a machining center that has multiple cutting tools operating simultaneously has been developed. Due to axis sharing, the geometric errors of multi-spindle, concurrent cutting processes are characterized by a significant coupling of error components in each cutting tool. As a result, it is not possible to achieve exact volumetric error compensation for all axes. To minimize the overall volumetric error in simultaneous cutting, a method to determine compensation amount using weighted least squares has been proposed. This method also allows tolerance distribution of machining accuracy for different surfaces of a workpiece. A geometric error model has been developed using an arch-type, multi-spindle machine tool, and the error compensation simulation results based on this model are presented. The simulation results demonstrated effectiveness of the proposed error compensation algorithm for use with multi-spindle simultaneous cutting applications.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45848/1/170_2005_Article_2615.pd