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2007 | Buch

Digital Noise Monitoring of Defect Origin

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Digital Noise Monitoring of Defect Origin is for both academics and professionals in the fields of engineering, biological sciences, physical science, and automation with particular emphasis on power engineering, oil-and-gas extraction, and aviation among others. The focus of the book is on determining defect origins. The author divides the process into the stages of monitoring the defect origin, identification of the defect and its stages, and control of the defect. The significance of this work is also connected to the possibility of using the noise as a data carrier for creating technologies that detect the initial stage of changes in objects.

Inhaltsverzeichnis

Frontmatter
1. Difficulties of Monitoring a Defect at Its Origin and Its Dataware Features
Reasons for the rise of defects on various objects such as living organisms and equipment are the subject of much research of corresponding science directions. However, considering these problems in view of obtaining information and methods of analysis, monitoring, and diagnostics, one can notice that the problems have much in common. In many cases, the signals describing the current state are obtained from the sensors installed on the corresponding objects. Similar or nearly the same information technologies are used in different areas for analyzing these signals as the information carriers. These technologies are realized on the same modern computers. Taking this into account, the IT specialist does not consider the differences in solving the problem of monitoring the state of these objects despite the wide areas of specific features of each object.
2. Position-Binary Technology of Monitoring Defect at its Origin
It’s known that in most cases the spectral methods are used for the experimental analysis of the cyclical (periodic) processes [12, 41]. For example, the objects of the back-and-forth motion equipment, the objects of the rotating equipment, those of the biological processes, etc. are cyclical. As a rule, the signals obtained from many cyclical objects have the complicated spasmodic leaping form and are accompanied by significant noise. At present, spectral methods and algorithms are commonly used in the experimental research of such signals [12, 37, 61]. But they are not effective enough for these objects in some cases [37]. Thus, in many cases it is necessary to use the large number of harmonic components of the corresponding amplitudes and frequencies for the appropriate description of spasmodic and leaping signals. That essentially complicates the analysis and use of the obtained results for solving the corresponding problems [37, 41]. That is why, in solving the problem of monitoring the defect origin, there is a need for methods and algorithms allowing one to (1) increase the reliability of the obtained results in comparison with the spectral method and (2) decrease the quantity of the spectrum components of the considered class of the objects [37, 41].
3. Technology of Digital Analysis of Noise as a Carrier of Information about the Beginning of a Defect's Origin
As was shown in Chapter 1, in most cases the beginning of a defect’s origin reflects in signals \(g\left( {i\Delta t} \right)\) collected from sensors as a high-frequency noise. Therefore, for monitoring the defect at the beginning of its origin, it is necessary to extract the information in the noise. In this chapter, one of the possible variants for this problem is considered.
It is known that in traditional technologies for eliminating noise (noise) influence on the results of problems, methods of filtration are often used. They give good results when the spectrum of the filter coincides with the spectrum of the noise. At the same time, for many real processes the spectrum and variance of the noise change in time in a wide range and classical conditions are not fulfilled. For these reasons for eliminating noise influence on the result of signal processing, one has to enlarge the range of a “filter” spectrum. In its turn, it distorts the legitimate signal much more.
4. Robust Correlation Monitoring of a Defect at its Origin
When using traditional technologies of signal analysis in solving a monitoring task, getting more or less acceptable results is possible only if the error has a salient character, the analyzed signals are stationary and are subjected to the normal distribution law, the correlation between the noise and the useful signal is equal to zero, and the noise represents white noise. However, even in this case, the errors from the obtained estimates depend on the change of the noise variance, the change of the correlation between the noise and the legitimate signal, or the change of their distribution law. Due to this, the adequacy of the description of many analyzed processes by means of probabilistic-statistical methods is not satisfied and we end up with wrong results in determining the origin of a defect. For these reasons, in the framework of classical theories, many problems of great importance are practically not solved nowadays. Thus, great possibilities are not realized, but if they were, we would solve a great number of problems having tremendous economical and social importance.
For example, eliminating the disadvantages of traditional technologies would allow us to increase the reliability of forecasting earthquakes and other natural disasters, improve disease diagnostics, increase the efficiency of prospecting mineral resources, increase the reliability of forecasting failures at heat and nuclear power stations, forecast failures in drilling, diagnose a technical plane state, allow us to realize adequate mathematical models, and so on. In this connection, among real applications of great potential of considered theories lies the necessity to revise traditional algorithms and create new technologies that provide the robustness of the obtained estimates in fulfilling classical conditions and in case there is a lack of obedience to classical conditions.
In this chapter, on the basis of the technology of noise analysis is a robust technology of correlation analysis. Due to this, the opportunity appears to eliminate serious obstacles by using the enormous potential of this technology for solving the most important tasks of monitoring an error at its origin.
5. Spectral Monitoring of a Defect's Origin
The spectral analysis of random processes or the measurement of the value of spectral functions that are the frequency distribution of the energy characteristics of the process is the most important part of the statistical measurements. At first, spectral analysis was used for solving the problem of investigating the characteristics of deterministic processes in contrast to the analysis of the distribution functions and correlation analysis, which were formed directly as a type of statistical measurement. Spectral analysis became an independent branch only after the role of measurement theory of the probability characteristics of random processes as well as the need for apparatus analysis of random processes had increased.
6. The Digital Technology of Forecasting Failures by Considering Noise as a Data Carrier
In the past, the errors in forecasting such objects as oil-chemical complexes, deep-water stationary sea platforms and communications, hydraulic works, etc. were assumed to be connected with meteorological and assurance characteristics of the element base of information measurement systems. Now they have been improved, but the probability of a failure has remained the same. Analysis shows that the main reason for an inadequate decision from a diagnostic system is connected with the impossibility of detecting the initial state of arising defects with the known methods of analyzing noisy signals [14, 15, 17, 56].
In the literature, a “fault” is defined as the inability of a system to realize required functions [55–57]. The fault is the initial state of the failure, which means the inability of work on a substantial scale. In this case, the fault of certain elements of a system leads to faults of general parts of an object and finally to complete destruction. In this case, the future use of an object is impossible or requires major repairs [55–57].
7. The Technology of Monitoring a Defect's Origin by Considering Noise as a Data Carrier
It is known that monitoring and diagnostics by vibration are commonly used for controlling the technical state of the most important equipment for airplanes, helicopters, tankers, compressor stations, electric power stations, main oil-and-gas pipelines, deep-sea platforms, and so on, and especially for objects with rotating equipment, for example compressor stations (http://​www.​rotatingequip.​com). However, all technological parameters obtained from the output of sensors as the signals \(g_1 \left( {i\Delta t} \right),g_2 \left( {i\Delta t} \right), \ldots g_m \left( {i\Delta t} \right)\) are analyzed in modern information systems provide reliable results during monitoring. At the same time, the used measuring tools and the information systems detect changes to the technical state of the equipment only after a series of significant defects has appeared [12, 14, 56, 57]. Unfortunately, in some cases, this detection occurs not long before an accident [15, 56]. Methods and technologies of detecting the defects at their origin have been worked out recently [16, 19–23]. Simultaneously, for example, for the above-mentioned objects, it is considered that weak vibrations appear in the initial moment in the spot of the defect’s origin. However, they quickly damp during the spread. They are represented as noise with a highfrequency spectrum in the signals obtained from the vibration sensors. For example, a change to the properties of the frictional forces and caused by vibrations are the basic indications of the defects in the bearings used in many vulnerable places of technical objects. Their extraction and sub- sequent analysis can give the opportunity to detect this defect at its origin—in some cases, sufficiently before an accident [15, 21, 22, 56].
Backmatter
Metadaten
Titel
Digital Noise Monitoring of Defect Origin
verfasst von
Telman Aliev
Copyright-Jahr
2007
Verlag
Springer US
Electronic ISBN
978-0-387-71754-8
Print ISBN
978-0-387-71753-1
DOI
https://doi.org/10.1007/978-0-387-71754-8

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