scholarly journals Misfire detection in a diesel engine using clustering in a short-time analysis of vibroacoustic signals

2005 ◽  
Vol 123 (4) ◽  
pp. 31-40
Author(s):  
Piotr BOGUŚ
Keyword(s):  
Parameter Space ◽  
Time Window ◽  
Diagnostic Methods ◽  
General Idea ◽  
Detection Methods ◽  
Time Signal ◽  
Engine Operation ◽  
Short Time ◽  
Misfire Detection ◽  
Vibroacoustic Signals

The paper presents some results of the research on new diagnostic methods in combustion engines. It describes the application of short-time signal analysis together with pattern recognition techniques in the diagnosis of misfire in Diesel engines through vibroacoustic signals. One considered Diesel locomotive in particular. In the area of the nonroad sources of combustion gases the locomotives rate relatively high as air polluters. There are some regulations in the area of locomotives (e.g. Cart UIC 623 1-2-3 in Europe) but we still observe a lack of obligatory requirements for systems monitoring emission critical damage. Such obligatory on-board diagnostic systems were introduced for passenger cars (OBD II, EOBD). The OBD system performs a continuous monitoring of basic system parameters and one of its most important tasks is misfire detection. All these facts inclined the author to research the new relevant detection methods. The main aim of the research is to distinguish between two states: normal engine operation and the state of misfire. The general idea of the method was taken from the short-time Fourier analysis. The method is based on calculation of the values of some selected parameters in the time window sliding along the signal. For each window position one has a set of parameter values which gives the point in a corresponding multidimensional parameter space. Hence, the time evolution of the signal can be observed as the evolution plot in the parameter space. We suspect that the different system states (misfire) can be distinguished by the different position of points in the parameter space. In order to detect them, the clustering in the parameter space was performed. The first results show the possibility of distinguishing some different clusters within the parameter space which may correspond to different engine states.

scholarly journals Analysis of vibration signals using short-time analysis and clustering in parameter space for detection of combustion engine state

2019 ◽  
Vol 177 (2) ◽  
pp. 83-87
Author(s):  
Piotr BOGUŚ ◽  
Jerzy MERKISZ
Keyword(s):  
Parameter Space ◽  
Time Window ◽  
Combustion Engine ◽  
Vibration Signal ◽  
Time Analysis ◽  
Statistical Parameters ◽  
Vibration Signals ◽  
Before And After ◽  
Vibration Signal Analysis ◽  
Short Time

The paper presents a short-time analysis of the vibration signals for the diagnosis of Diesel engine of combustion locomotive by recognition of different engine states using the clustering technique. The main aim of the researches was to distinguish between different engine states represent different wear extends. The proposed method of vibration signal analysis consists on sliding a time window along signal in time and observing the changes of some given statistical parameters. The set of this parameter values creates a multidimen-sional parameter space where the time evolution can be observed. For recognition and detection of different engine system states some clustering techniques in the parameter space were performed. The results show the possibility of distinguishing different cluster centers within the parameter space which can be assigning to different engine states represented the states before and after a general repair.

scholarly journals Fault Detection in DC Microgrids Using Short-Time Fourier Transform

Energies ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 277
Author(s):  
Ivan Grcić ◽  
Hrvoje Pandžić ◽  
Damir Novosel
Keyword(s):  
Fourier Transform ◽  
Fault Detection ◽  
Operating Conditions ◽  
Time Signal ◽  
Short Time Fourier Transform ◽  
Dc Microgrid ◽  
Protection Scheme ◽  
Simulink Model ◽  
Battery Energy ◽  
Short Time

Fault detection in microgrids presents a strong technical challenge due to the dynamic operating conditions. Changing the power generation and load impacts the current magnitude and direction, which has an adverse effect on the microgrid protection scheme. To address this problem, this paper addresses a field-transform-based fault detection method immune to the microgrid conditions. The faults are simulated via a Matlab/Simulink model of the grid-connected photovoltaics-based DC microgrid with battery energy storage. Short-time Fourier transform is applied to the fault time signal to obtain a frequency spectrum. Selected spectrum features are then provided to a number of intelligent classifiers. The classifiers’ scores were evaluated using the F1-score metric. Most classifiers proved to be reliable as their performance score was above 90%.

Nonlinear Analysis of Combustion Engine Vibroacoustic Signals for Misfire Detection

2003 ◽  
Author(s):  
Piotr Boguś ◽  
Jerzy Merkisz ◽  
Rafał Grzeszczyk ◽  
Stanisław Mazurek
Keyword(s):  
Nonlinear Analysis ◽  
Combustion Engine ◽  
Misfire Detection ◽  
Vibroacoustic Signals

scholarly journals 231 A SHORT TIME WINDOW TO PROFIT FROM IL-4 PLUS IL-10 ADDITION TO PROTECT CARTILAGE FROM BLOOD-INDUCED DAMAGE IN VITRO

2011 ◽  
Vol 19 ◽  
pp. S113
Author(s):  
M.E. van Meegeren ◽  
N.W. Jansen ◽  
G. Roosendaal ◽  
S.C. Mastbergen ◽  
F.P. Lafeber
Keyword(s):  
Time Window ◽  
Short Time Window ◽  
Short Time

scholarly journals Thromboembolic complications following tissue plasminogen activator therapy in patients of acute ischemic stroke - Case report and possibility for detection of cardiac thrombi

Open Medicine ◽  
2018 ◽  
Vol 13 (1) ◽  
pp. 551-555 ◽  
Author(s):  
Junko Yamaguchi ◽  
Kosaku Kinoshita ◽  
Marina Hirabayashi ◽  
Satoshi Hori ◽  
Makoto Furukawa ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Case Report ◽  
Transesophageal Echocardiography ◽  
Plasminogen Activator ◽  
Tissue Plasminogen Activator ◽  
Time Window ◽  
Ulnar Artery ◽  
Diagnostic Methods ◽  
Thromboembolic Complications ◽  
Tissue Plasminogen

AbstractMany reports focus on the probability of intracranial hemorrhage as a complication after recombinant tissue plasminogen activator (rt-PA) therapy. However, thromboembolic complications are not well discussed. We experienced a case in which severe thromboembolic complications occurred in the right radial and right ulnar artery. Arterial fibrillation was observed in this case. If multiple thrombi exist in the atrium or ventricle, multiple small embolic particles may appear following thrombolytic therapy, and that may be a potential risk of secondary thromboembolic complications due to incomplete dissolution of thrombi. Transesophageal echocardiography is a standard method to detect intracardiac sources of emboli in the case of arterial fibrillation. Transesophageal echocardiography is, however, an invasive method for patients with ischemic stroke during rt-PA therapy. High resolution enhanced CT could be a useful tool and may be a reliable alternative to transthoracic echocardiography. Careful assessment of thromboembolic complications following rt-PA therapy in patients with arterial fibrillation is needed. In this case report and mini review, we would like to discuss about the accurate diagnostic methods to detect cardiac or undetermined embolic sources and provide expedited stroke care. These embolic sources may be more readily discovered during rt-PA therapy within the limited therapeutic time window.

scholarly journals Biosensors for the Determination of SARS-CoV-2 Virus and Diagnosis of COVID-19 Infection

2022 ◽  
Vol 23 (2) ◽  
pp. 666
Author(s):  
Maryia Drobysh ◽  
Almira Ramanaviciene ◽  
Roman Viter ◽  
Chien-Fu Chen ◽  
Urte Samukaite-Bubniene ◽  
...  
Keyword(s):  
Current Trend ◽  
Analytical Signal ◽  
Diagnostic Methods ◽  
Detection Methods ◽  
Label Free ◽  
Free Mode ◽  
Rna Hybridisation ◽  
Antigen Antibody ◽  
Affinity Interaction

Monitoring and tracking infection is required in order to reduce the spread of the coronavirus disease 2019 (COVID-19), induced by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). To achieve this goal, the development and deployment of quick, accurate, and sensitive diagnostic methods are necessary. The determination of the SARS-CoV-2 virus is performed by biosensing devices, which vary according to detection methods and the biomarkers which are inducing/providing an analytical signal. RNA hybridisation, antigen-antibody affinity interaction, and a variety of other biological reactions are commonly used to generate analytical signals that can be precisely detected using electrochemical, electrochemiluminescence, optical, and other methodologies and transducers. Electrochemical biosensors, in particular, correspond to the current trend of bioanalytical process acceleration and simplification. Immunosensors are based on the determination of antigen-antibody interaction, which on some occasions can be determined in a label-free mode with sufficient sensitivity.

scholarly journals Real-Time Back Surface Landmark Determination Using a Time-of-Flight Camera

Sensors ◽  
2021 ◽  
Vol 21 (19) ◽  
pp. 6425
Author(s):  
Daniel Ledwoń ◽  
Marta Danch-Wierzchowska ◽  
Marcin Bugdol ◽  
Karol Bibrowicz ◽  
Tomasz Szurmik ◽  
...  
Keyword(s):  
Real Time ◽  
Average Distance ◽  
Time Of Flight ◽  
Point Clouds ◽  
Diagnostic Methods ◽  
Detection Methods ◽  
Back Surface ◽  
Anatomical Landmarks ◽  
Real Time Analysis ◽  
Similar Accuracy

Postural disorders, their prevention, and therapies are still growing modern problems. The currently used diagnostic methods are questionable due to the exposure to side effects (radiological methods) as well as being time-consuming and subjective (manual methods). Although the computer-aided diagnosis of posture disorders is well developed, there is still the need to improve existing solutions, search for new measurement methods, and create new algorithms for data processing. Based on point clouds from a Time-of-Flight camera, the presented method allows a non-contact, real-time detection of anatomical landmarks on the subject’s back and, thus, an objective determination of trunk surface metrics. Based on a comparison of the obtained results with the evaluation of three independent experts, the accuracy of the obtained results was confirmed. The average distance between the expert indications and method results for all landmarks was 27.73 mm. A direct comparison showed that the compared differences were statically significantly different; however, the effect was negligible. Compared with other automatic anatomical landmark detection methods, ours has a similar accuracy with the possibility of real-time analysis. The advantages of the presented method are non-invasiveness, non-contact, and the possibility of continuous observation, also during exercise. The proposed solution is another step in the general trend of objectivization in physiotherapeutic diagnostics.

scholarly journals 383. Feasibility of Specimen Self-collection in Young Children Undergoing SARS-CoV-2 Surveillance for In-person Learning

2021 ◽  
Vol 8 (Supplement_1) ◽  
pp. S293-S293
Author(s):  
Jonathan Altamirano ◽  
Grace Tam ◽  
Marcela Lopez ◽  
India Robinson ◽  
Leanne Chun ◽  
...  
Keyword(s):  
Young Children ◽  
Time Window ◽  
School Administrators ◽  
Error Rates ◽  
Independent Observer ◽  
Specimen Collection ◽  
Timing Data ◽  
Short Time Window ◽  
Short Time ◽  
Over Time

Abstract Background While pediatric cases of COVID-19 are at low risk for adverse events, schoolchildren should be considered for surveillance as they can become infected at school and serve as sources of household or community transmission. Our team assessed the feasibility of young children self-collecting SARS-CoV-2 samples for surveillance testing in an educational setting. Methods Students at a K-8 school were tested weekly for SARS-CoV-2 from September 2020 - June 2021. Error rates were collected from September 2020 - January 2021. Clinical staff provided all students with instructions for anterior nares specimen self-collection and then observed them to ensure proper technique. Instructions included holding the sterile swab while making sure not to touch the tip, inserting the swab into their nostril until they start to feel resistance, and rubbing the swab in four circles before repeating the process in their other nostril. An independent observer timed random sample self-collections from April - June 2021. Results 2,590 samples were collected from 209 students during the study period when data on error rates were collected. Errors occurred in 3.3% of all student encounters (n=87). Error rates over time are shown in Figure 1, with the highest rate occurring on the first day of testing (n=20/197, 10.2%) and the lowest in January 2021 (n=1/202, 0.5%). 2,574 visits for sample self-collection occurred during the study period when independent timing data was collected (April - June 2021). Of those visits, 7.5% (n=193) were timed. The average duration of each visit was 70 seconds. Figure 1. Swab Error Rates Over Time Conclusion Pediatric self-collected lower nasal swabs are a viable and easily tolerated specimen collection method for SARS-CoV-2 surveillance in school settings, as evidenced by the low error rate and short time window of sample self-collection during testing. School administrators should expect errors to drop quickly after implementing testing. Disclosures All Authors: No reported disclosures

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