Integration of multidimensional fault diagnostic indicators on the example of rolling element bearings

Diagnostics of rotating machinery relies on examining of many dozens of fault indicators that enable recognition of malfunction symptoms at the earliest stage possible. Unfortunately, in many industrial applications and especially in large machinery parks, the number of diagnostic features to monitor goes beyond the perception capabilities of responsible maintenance personnel. Therefore, there is need for a data reduction techniques that simplify and provide the most important information within the condition monitoring system, starting from a single kinematic element. In this paper it is proposed to employ a simple Euclidean distance that relates the object’s condition to the difference between the vibration-based indicators and the initial state. As an example, the authors examine the integration of diagnostic features used to identify localized and extended fault of rolling element bearings for simulated data and real industrial event that occurred at wind turbine’s generator bearing

The use of a fuzzy logic approach for integration of vibration-based diagnostic features of rolling element bearings

Modern condition monitoring systems (CMS) collect and process enormous amount of data in order to provide the earliest and most dependable information of fault development within any of the machine components and their operation combined. According to numerous studies one of the most fault susceptible mechanical elements in rotating machinery are rolling element bearings. Although reliable techniques for their diagnostics are already proposed, the new investigation is needed. According to authors experience in many industrial applications the operators are obligated to simultaneously track hundreds of diagnostic estimates, such as signals energy, its peakedness or narrowband characteristics for localized faults. As mentioned, for a vibration-based CMS of single wind turbine there are nearly 150 of them. Therefore, the authors employ a fuzzy logic approach for integration of bearing diagnostic features. A new estimate that carry most relevant information about bearing condition is discussed. The reasoning is presented on simulated data that mimics real rotating machine

Informative frequency band identification for automatic extraction of impulsive components in vibration data from rotating machinery

In this paper authors address the issue of local damage detection in rolling element bearings in the presence of non-Gaussian noise. Typically damage detection problems concern the techniques of filtration, decomposition, separation, extraction etc. In such real-life cases, main difficulty lies in non-Gausianity of the noise present in the operational environment, hence popular denoising techniques cannot be used. In presented article, a real-life industrial scenario will be discussed and a new approach to cyclic component extraction will be presented. Classical detection methods are often not sufficient for the task because of high energy of impulsive noise in comparison to spectral structure of the damage. Proposed method utilizes Cyclic Spectral Coherence map as two-dimensional data representation, and Nonnegative Matrix Factorization as analytical tool to extract individual components

Automatic and Full-band Demodulation for Fault Detection. Validation on a Wind Turbine Test Bench

International audienceIn order to improve vibration analysis of a signal measured on multi-component systems and especially on systems operating under non-stationary conditions, advanced signal processing methods are required. To contribute to this need a new diagnostic approach is presented in this work. This paper focuses on some parts of an autonomous full-band spectrum analyzer, referred to as AStrion. AStrion consists different function blocks, referred to as "modules". In the first module, among other processing tasks, the signal is pre-processed with a new order tracking algorithm described in this paper. The subsequent modules, referred to as AStrion-I and AStrion-H, automatically identify all the harmonic series and modulation side-bands in all the frequency band of the signal [1]. The first module described in this paper is called AStrion-K, where K stands for Kinematic. This module associates the detected spectral structure, harmonic series and modulation side-bands, with the characteristic fault frequencies of the monitored system. This approach has the advantage of analyzing all the frequency band of the signal and of being able to monitor a system even if the kinematic of the system is unknown. The second part of this paper describes the demodulation task, done by AStrion-M module. The demodulation is conducted over each carrier frequency along with its side-bands detected by AStrion-H. A multi-rate filtering process is applied over each band to isolate the component. Such filtering method downsamples the signal in such a way that the digital filter can achieve a satisfactory precision and stability over the targeted demodulation band, even if it is extremely narrow. In order to extract the corresponding deterministic component and to increase the signal to noise ratio, a time synchronous averaging is carried out over the filtered signal sampled according to the corresponding triggering frequency. Therefore, after computing the analytical signal of the averaged signal, a demodulation process estimates the amplitude and frequency functions, which are employed to derive fault indicators both in time and in frequency domains. Finally, results are presented on real data gathered on a test bench designed in KAStrion project for simulating a wind turbine operation. This test bench was prepared to simulate all components of a wind turbine drive train and is composed of mechanisms for accelerated deterioration of bearings and gearbox, which allows the investigation of the wear of selected elements separately. This paper is focused on the fault of the main bearing. A comparison with commonly used fault indicators is carried out

Nonlinear cointegration approach for condition monitoring of wind turbines

Monitoring of trends and removal of undesired trends from operational/process parameters in wind turbines is important for their condition monitoring. This paper presents the homoscedastic nonlinear cointegration for the solution to this problem. The cointegration approach used leads to stable variances in cointegration residuals. The adapted Breusch-Pagan test procedure is developed to test for the presence of heteroscedasticity in cointegration residuals obtained from the nonlinear cointegration analysis. Examples using three different time series data sets-that is, one with a nonlinear quadratic deterministic trend, another with a nonlinear exponential deterministic trend, and experimental data from a wind turbine drivetrain-are used to illustrate the method and demonstrate possible practical applications. The results show that the proposed approach can be used for effective removal of nonlinear trends form various types of data, allowing for possible condition monitoring applications

Automatic Characteristic Frequency Association and All-Sideband Demodulation for Detection of a Bearing Fault of a Test Rig

International audienceThis paper proposes advanced signal-processing techniques to improve condition monitoring of operating machines. The proposed methods use the results of a blind spectrum interpretation that includes harmonic and sideband series detection. The rst contribution of this study is an algorithm for automatic association of harmonic and sideband series to characteristic fault frequencies according to a kinematic conguration. The approach proposed has the advantage of taking into account a possible slip of the rolling-element bearings. In the second part, we propose a full-band demodulation process from all sidebands that are relevant to the spectral estimation. To do so, a multi-rate ltering process in an iterative schema provides satisfying precision and stability over the targeted demodulation band, even for unsymmetrical and extremely narrow bands. After synchronous averaging, the ltered signal is demodulated for calculation of the amplitude and frequency modulation functions, and then any features that indicate faults. Finally, the proposed algorithms are validated on vibration signals measured on a test rig that was designed as part of the Eu-ropean Innovation Project KAStrion'. This rig simulates a wind turbine drive * Corresponding author Email address: [email protected] (Marcin Firla) Preprint submitted to Mechanical Systems and Signal Processing March 11, 2016 train at a smaller scale. The data show the robustness of the method for localizing and extracting a fault on the main bearing. The evolution of the proposed features is a good indicator of the fault severity

PROGRAMMABLE LOGIC DEVICES AS A TOOL IN STRUCTURE'S DAMAGE DETECTION APPLICATIONS

Programmable logic devices is one of the most dynamically developing fields of technology today. It is widely used in many kinds of signal acquisition as well as data processing systems mainly because of it's large flexibility and contin­uously growing abilities. It gives a designer a powerful tool, which allows for the creation of almost any kind of logic topology and any kind of data processing system, which additionally may be freely reprogrammable without any phys­ical changes in the platform device. This paper briefly describes programmable devices technology contribution in the development of various SHM (System Health Monitoring) systems. The SHM systems mentioned in this paper have already been designed, built and successfully tested on real structures

Analiza statystyczna zabiegów wewnątrzczaszkowych przeprowadzonych w Polsce w latach 2008–2009

Background and purpose Quantitative and qualitative analysis of neurosurgical procedures provides important data for assessment of the development and trends in the field of neurosurgery. The authors present statistical data on intracranial procedures (IPs) performed in Poland in 2008–2009. Material and methods Data on IPs come from reports of the National Health Fund, grouped according to the system of Diagnosis-Related Groups, group A – nervous system diseases. Data concerning the year 2009 include all IPs performed in Poland. Data from the second half of 2008 to 2009 (18 months) come from 35 neurosurgical centers in Poland, divided by provinces. We analyzed the number of IPs, the cost of procedures, duration of hospitalization and deaths. Results 20 849 IPs were performed in Poland in 2009. The most common procedure was A12 (6807; 32.65%), and the rarest was A04 (96; 0.46%). The annual cost of all IPs was 228 599 956 PLN. Average cost of the procedure ranged from 1578 PLN (A14) to 47 940 PLN (A03). Duration of the hospitalization ranged between 3 days (A14) and 12 days (A12). The highest percentage of deaths was reported for A01 (n = 1050, 19.06%). Reports from 35 neurosurgical centers in the second half of 2008 and 2009 showed the highest number of IPs per 100 000 population in Kujawsko-Pomorskie (93) and the lowest in Wielkopolskie (27) and Podkarpackie (27). The highest number of IPs (1669) was performed in neurosurgical center Ml (Małopolskie), and the lowest (99) in W1 (Wielkopolskie). Conclusions A significant disparity in the number of IPs performed in different centers in Poland was observed. There are no data in the literature on the number of neurosurgical procedures performed in Poland in other periods.Wstęp i cel pracy Analiza ilościowa i jakościowa procedur neurochirurgicznych dostarcza istotnych danych dotyczących rozwoju oraz trendów w dziedzinie neurochirurgii. Autorzy pracy przedstawiają dane statystyczne dotyczące procedur wewnątrzczaszkowych (PW) wykonywanych w Polsce w latach 2008–2009. Materiał i metody Dane dotyczące PW pochodzą z raportów Narodowego Funduszu Zdrowia i były grupowane wg systemu Jednorodnych Grup Pacjentów dla grupy A – choroby układu nerwowego. Dane z 2009 r. uwzględniają wszystkie PW wykonane w Polsce, dane z drugiej połowy 2008 i 2009 r. (18 miesięcy) pochodzą z 35 ośrodków neurochirurgicznych w Polsce podzielonych według województw. Analizowano liczbę PW, koszty procedur, czas hospitalizacji i liczbę zgonów. Wyniki W 2009 r. w Polsce wykonano 20 849 PW. Najczęstszą procedurą była A12 (6807; 32,65%), a najrzadszą A04 (96; 0,46%). Roczny koszt wszystkich PW wyniósł 228 599 956 PLN. Średni koszt procedury wahał się od 1 578 PLN (A14) do 47 940 PLN (A03). Czas hospitalizacji wahał się od 3 dni (A14) do 12 dni (A12). Największy odsetek zgonów odnotowano dla procedury A01 (19,06%; n = 1050). Analizowano raporty 35 ośrodków neurochirurgicznych w Polsce. W ciągu 18 miesięcy (druga połowa 2008 i 2009) najwięcej PW na 100 tys. mieszkańców wykonano w kujawsko-pomorskim (93), natomiast najmniej w wielkopolskim (27) i podkarpackim (27). Najwięcej PW (1669) wykonano w ośrodku M1 (małopolskie), najmniej (99) w W1 (wielkopolskie). Najczęściej raportowana była procedura A12. Wnioski Obserwowano znaczną dysproporcję w liczbie PW wykonywanych w różnych ośrodkach w Polsce. Brakuje danych w piśmiennictwie dotyczących liczby procedur neurochirurgicznych wykonywanych w Polsce we wcześniejszych okresach

Stymulacja kory ruchowej w leczeniu bólów neuropatycznych

Background and purpose Despite the rapid development of neuropharmacotherapy, medical treatment of neuropathic pain (NP) still constitutes a significant socioeconomic problem. The authors herein present a group of patients treated with motor cortex stimulation (MCS) for NP of various types and aetiologies. Material and methods Our cohort included 12 female and 11 male NP patients aged 53 ± 16 treated with MCS. Eleven patients were diagnosed with neuropathic facial pain (NFP), 8 with hemi-body neuropathic pain (HNP), and 4 with deafferentation pain (DP). Prior to surgery, 16 out of 23 patients were treated with repetitive transcranial magnetic stimulation (rTMS), with a positive response in 10 cases. Pain intensity in our group was evaluated with the visual analogue scale (VAS) one month before and three months after MCS implantation. Results Improvement on the VAS was reported in the whole group of patients (p < 0.001). The best results were reported in the NFP group (p < 0.001) while the worst ones were noted in the DP group (p = 0.04). Anamnesis duration positively correlated with outcome. Infection forced the authors to permanently remove the system in one case. There were no other complications in the group. Conclusions Minimally invasive, safe neuromodulative treatment with MCS permits neuropathic pain control with good efficacy. The type of neuropathic pain might be a prognostic factor.Wstęp i cel pracy Pomimo dynamicznego rozwoju neurofarmakoterapii, leczenie bólów neuropatycznych stanowi istotny problem socjoekonomiczny. Autorzy przedstawiają grupę chorych leczonych metodą stymulacji kory ruchowej (motor cortex stimulation – MCS) z powodu bólów neuropatycznych o różnym obrazie klinicznym i etiologii. Materiał i metody W grupie 12 kobiet oraz 11 mężczyzn w wieku 53 ± 16 lat zastosowano MCS z powodu bólu neuropatycznego. U 11 chorych rozpoznano neuropatyczne bóle twarzy, u 8 chorych połowiczy ból neuropatyczny, a u 4 chorych – ból deaferentacyjny. U 16 chorych przeprowadzono próbną przezczaszkową stymulację magnetyczną, uzyskując przejściową poprawę u 10 z nich. Nasilenie dolegliwości bólowych oceniano z wykorzystaniem wzrokowej skali analogowej (visual analogue scale – VAS) miesiąc przed implantacją oraz w trzecim miesiącu po implantacji MCS. Wyniki U wszystkich chorych w grupie stwierdzono poprawę mierzoną VAS (p < 0,001). Najlepsze efekty leczenia bólu neuropatycznego zaobserwowano w grupie chorych z neuropatycznym bólem twarzy (p < 0,001), a najsłabsze u chorych z rozpoznanym bólem deaferentacyjnym (p = 0,04). Długość wywiadów korelowała dodatnio z wynikami leczenia. U jednego chorego ze względu na zakażenie usunięto system i nie podejmowano próby ponownego wszczepienia. Innych powikłań w grupie nie stwierdzano. Wnioski Wykorzystanie minimalnie inwazyjnych technik neuromodulacyjnych, w tym MCS, pozwala na skuteczne i bezpieczne zmniejszenie nasilenia bólów neuropatycznych. Rodzaj bólu neuropatycznego może mieć znaczenie rokownicze