Evaluation of touch trigger probe measurement uncertainty using FEA

Evaluation of measurement uncertainty is an essential subject in dimensional measurement. It has also become a dominant issue in coordinate measuring machine (CMM) even though its machine performance has been well accepted by many users. CMM probes, especially touch trigger probes which are commonly used, have been acknowledged as a key error source, largely due to pre-travel variations. The probe errors result in large measurement uncertainty in CMM measurement. Various methods have been introduced to estimate measurement uncertainty, but they tend to be time consuming and necessarily require a large amount of experimental data for analyzing the uncertainty. This paper presents the method of evaluation of CMM probe uncertainty using FEA modeling. It is started with the investigation of the behavior of probe by recording stylus displacement with vary triggering force. Then, those displacement results will be analyzed with sensitivity analysis technique to estimate the uncertainty of recorded results

Acoustic emission and vibration for tool wear monitoring in single-point

This paper proposes an implementation of calibrated acoustic emission (AE) and vibration techniques to monitor progressive stages of flank wear on carbide tool tips. Three cutting conditions were used on workpiece material, type EN24T, in turning operation. The root-mean-square value of AE (AErms) and the coherence function between the acceleration signals at the tool tip in the tangential and feed directions was studied. Three features were identified to be sensitive to tool wear: AErms, coherence function in the frequency ranges 2.5-5.5 kHz and 18-25 kHz. Belief network based on Bayes’ rule was used to integrate information in order to recognise the occurrence of worn tool. The three features obtained from the three cutting conditions and machine time were used to train the network. The set of feature vectors for worn tools was divided into two equal sub-sets: one to train the network and the other to test it. The AErms in term of AE pressure equivalent was used to train and test the net work to validate the calibrated acoustic. The overall success rate of the network in detecting a worn tool was high with low error rate

Experimental validation of FEA modelling of touch trigger probes

The authors have previously proposed the use of finite element method (FEM) for the modeling of coordinate measuring machine probes. Whilst the modeling results have been published previously, this paper presents the detailed experimental validation to compare the FEM and experimental results. The comparison shows that the agreement is generally good with probing contacts at lower latitudes near the equator of the reference sphere. The differences between the modeling and experimental results become large at higher latitudes. This is believed to be mainly caused by the sliding effects which occur during probing contact in the experiments

Symbolic computation for evaluation of measurement uncertainty

In recent years, with the rapid development of symbolic computation, the integration of symbolic and numeric methods is increasingly applied in various applications. This paper proposed the use of symbolic computation for the evaluation of measurement uncertainty. The general method and procedure are discussed, and its great potential and powerful features for measurement uncertainty evaluation has been demonstrated through examples

Characteristics of a 9mm triple-beam tuning fork resonant sensor

This paper describes the design and testing of the first miniaturised metallic triple-beam tuning fork resonant sensors for use in force, pressure and torque measurement applications. The new devices with 9mm length vibrating tines have resulted in over a 40% reduction in size when compared to previously tested resonators. The four fold increase in operating frequency to 26 kHz, with Q factors in air up to 4000, provides additional benefits for resolution, accuracy, range and overload capability. Measurement repeatability of at least 0.02% of span levels for torque transducers employing the sensors are quoted. Results of characterisation over the temperature range -30oC to +90oC are given

Finite elements modeling and simulation of probe system

Coordinate measuring machines (CMMs) have been widely used for enhancing product quality, productivity and reliability. This powerful instrument assists the user by providing them with highly accurate and reliable measurement results. Many studies involving the application of various different methods have been carried out to enhance the performance of CMM. This paper discusses the application of finite element analysis (FEA) to study the probe system of CMM. Finite element modeling is utilized to investigate the displacement of the probe stylus, pre-travel variation (lobing effects) and the associated measurement uncertainty. Different characteristics of styli have been considered and the corresponding effects on the probe operation are reported

Effects of the size of the measured surface on the performance of an air cone-jet sensor for in-process inspection

This paper investigates the effects of the size of the measured surface on the performance of an air-jet sensor using 2-D finite element method. The modeling and experimental results have shown that in the measuring range of 1.5 mm to 4.5 mm with a nozzle of diameter of 6 mm, the output of the cone-jet is not significantly affected by the size change from 10 mm to 14 mm. It also proved that this particular sensor is not suitable for measuring an object with a size less than 9 mm

Continuous wavelet transform and neural network for condition monitoring of rotodynamic machinery

This paper describes a novel method of rotodynamic machine condition monitoring using a wavelet transform and a neural network. A continuous wavelet transform is applied to the signals collected from accelerometer. The transformed images are then extracted as unique characteristic features relating to the various types of machine conditions. In the experiment, four types of machine operating conditions have been investigated: a balanced shaft; an unbalanced shaft, a misaligned shaft and a defective bearing. The back propagation neural network (BPNN) is used as a tool to evaluate the performance of the proposed method. The experimental results result in a recognition rate of 90 percent

Output-based Aid for Sustainable Sanitation

A review of the experience to date in applying output-based and other results-oriented financing aid formats to the delivery of sanitation services and goods in developing countries. The paper looks at the theoretical underpinnings which justify output-based subsidies in sanitation, reviews a selection of output-based aid projects and then proposes some new approaches which could help to make financing in sanitation more effective and accountable