Papers by Keyword: Audible Sound

Abstract: This paper presents a method for inspecting micro-holes with diameters of less than 100 μm using audible sound. The inspection system measures the micro-hole diameter by comparing two sound signals. Fluid flow through micro-holes affects the performance of products such as CO gas sensor parts, microphone filters and fuel injection plates. Therefore, if the flow rate of fluid passing through micro-holes is accurately assessed by an inspection system, the performance of a product can be guaranteed.

Abstract: In this paper, we demonstrate ways of identifying audible sound of working engine to distinguish whether it is in normal condition or faulty condition. A set of experiments were carried out on an engine from a heavy trunk, in order to verify the method, allowing the three sensors located on engine surface to accurately adapt the normal signal and the faulty signal. A technique for faulty mode identification on the engine has been developed based on audible sound. In a practical application of the technique to running engines we capture data of audible sound and a series of analysis were acted on the data, then we could acquire the result to distinguish the state of engine.

Abstract: Development of modern society is converging to a status where many human actions can be performed by machines. To achieve production without human intervention, machines require artificial receptors. Data gathering for processing and analysis of signals, together with determination of feedback reactions can be achieved by a suitable decision maker unit. A sensed value suited to this so-called intelligent sensing process would be the acoustic emission signal. In the case of intelligent cutting tools this would require miniature highly sensitive sensors integrated into the cutting tool body. Part I of this paper deals with the possibility of practical usage of the piezoelectric properties of copolymer foils for the acoustic emission sensor as a transducer of a mechanical surface wave into electrical signal. Part II of the paper deals with the most fundamental requirement for monitoring of cutting conditions during machining, i.e. excellent processing of measured data. Data obtained from machining process obtained by means of acoustic emission sensors, as discussed in the first part of this article, have high-frequency and continuous character of a white noise. These data are very difficult to process. New apparatus for transformation of acoustic emission into audible sound in the workplace is presented. The first stage of processing is by listening to transformed data it is subjectively possible to recognize differences in audible spectrum, corresponding to different states of the cutting tool. The second step is visualization of the differences via the fast Fourier transform (FFT) in the spectrum graphic chart.