scholarly journals Fault Identification in Pipeline System Using Normalized Hilbert Huang Transform and Automatic Selection of Intrinsic Mode Function

2018 ◽  
Vol 221 ◽  
pp. 02002 ◽  
Author(s):  
Hanafi M. Yusop ◽  
M.F. Ghazali ◽  
M.F.M. Yusof ◽  
M.A.Pi Remli ◽  
M. Samykano
Keyword(s):  
Distribution Systems ◽  
Water Pressure ◽  
Intrinsic Mode Function ◽  
Transient Signal ◽  
Pipeline System ◽  
Pressure Transient ◽  
Hilbert Huang Transform ◽  
Mode Function ◽  
Automatic Selection ◽  
Selection Of

Pressure transient analysis has been widely used to monitor the condition of pipelines and its assessment in water distribution systems. This is a low-cost nonintrusive technique with the ability to locate uncertainties (leak, pipe fitting, blockage) at a greater distance from the measurement point. In this research, Normalised Hilbert Huang Transform (NHHT) is used as the method to analyse the pressure transient signal. However, this method has difficulty in selecting the suitable intrinsic mode function (IMF) for the advance data analysing. As an alternative, Integrated Kurtosis-based Algorithm for z-filter Technique (Ikaz), which allows automatic selection of intrinsic mode function (IMF) been used to substitute the NHHT limitation in this study. The analysis is conducted on a 67.9-meter Medium High-Density PolyEthylene (MDPE) pipe installed with single artificial leak simulator at a water pressure in the range of 1-4 bar.

scholarly journals Pipeline Condition Assessment by Instantaneous Frequency Response over Hydroinformatics Based Technique—An Experimental and Field Analysis

Fluids ◽  
2021 ◽  
Vol 6 (11) ◽  
pp. 373
Author(s):  
Muhammad Hanafi Yusop ◽  
Mohd Fairusham Ghazali ◽  
Mohd Fadhlan Mohd Yusof ◽  
Muhammad Aminuddin Pi Remli
Keyword(s):  
Transient Analysis ◽  
Water Pressure ◽  
Experimental Tests ◽  
Intrinsic Mode Function ◽  
Field Analysis ◽  
Detection Methods ◽  
Pipeline System ◽  
Pressure Transient Analysis ◽  
Pressure Transient ◽  
Mode Function

A common issue in water infrastructure is that it suffers from leakage. The hydroinformatics technique for recognizing the presence of leaks in the pipeline system by means of pressure transient analysis was briefly explored in this study. Various studies have been done of improvised leak detection methods, and Hilbert Huang Transform has the potential to overcome the concern. The HHT processing algorithm has been successfully proven through simulation and experimentally tested to evaluate the ability of pressure transient analysis to predict and locate the leakage in the pipeline system. However, HHT relies on the selection of the suitable IMF in the pre-processing phase which will determine the precision of the estimated leak location. This paper introduces a NIKAZ filter technique for automatic selector of Intrinsic Mode Function (IMF). A laboratory-scale experimental test platform was constructed with a 68-metre long Medium Polyethylene (MDPE) pipe with 63 mm in diameter used for this study and equipped with a circular orifice as an artificial leak in varying sizes with a system of 2 bar to 4 bar water pressure. The results showed that, although with a low ratio of signal-to-noise, the proposed method could be used as an automatic selector for Intrinsic Mode Function (IMF). Experimental tests showed the efficiency, and the work method was successful as an automatic selector of IMF. The proposed mathematical algorithm was then finally evaluated on field measurement tested on-site of a real pipeline system. The results recommended NIKAZ as an automatic selector of IMF to increase the degree of automation of HHT technique, subsequently enhancing the detection and identification of water pipeline leakage.

A New Method in Gears Fault Diagnosis

2013 ◽  
Vol 333-335 ◽  
pp. 1621-1624
Author(s):  
Feng Lei Ma ◽  
Xiao Long Zhou ◽  
Yong Tao Zheng
Keyword(s):  
Fault Diagnosis ◽  
Signal Analysis ◽  
Intrinsic Mode Function ◽  
New Method ◽  
Signal Frequency ◽  
Hilbert Spectrum ◽  
Hilbert Huang Transform ◽  
Mode Function ◽  
Meshing Gears

In this paper, the gears fault signal in the engine was studied. Hilbert-Huang transform was applied for the gears fault signal analysis. From the experiment, the normal engine frequency of 240 Hz was got and the gears fault signal frequency concentrated in 2800 Hz. Through the study of intrinsic mode function and the Hilbert spectrum, improper meshing gears were the cause of this problem. The results showed that this method can effectively extract the fault feature and found out the cause of the problem. A new effective method is provided for the gears fault diagnosis.

Application of Hilbert-Huang Transform to Vibration Signal Analysis of Coal and Gangue

2010 ◽  
Vol 40-41 ◽  
pp. 995-999 ◽  
Author(s):  
Wei Liu
Keyword(s):  
Signal Analysis ◽  
Vibration Signal ◽  
Intrinsic Mode Function ◽  
Frequency Interval ◽  
Hilbert Huang Transform ◽  
Mode Function ◽  
Mode Decomposition ◽  
Marginal Spectrum ◽  
The Difference ◽  
Vibration Signal Analysis

In this paper, a new method of vibration signal analysis of coal and gangue based on Hilbert-Huang transform is presented. Empirical mode decomposition algorithm was used to decompose the original vibration signal of coal and gangue into the intrinsic modes for further extract useful information contained in response signals under complicated environment. By analyzing local Hilbert marginal spectrum and local energy spectrum of the first four intrinsic mode function components, we found the difference of coal and rock in specific frequency interval that the amplitude and energy mainly distributed at frequency interval between 100Hz and 600Hz when coal was drawn, while the amplitude and energy were more concentrated at 1000Hz or so when gangue was drawn. Furthermore, the further analysis result from marginal spectrum of each intrinsic mode function component agreed well with the conclusion above. So the extracted features with the propose approach can be served as coal and gangue interface recognition.

QUANTIFICATION OF RESPIRATORY SINUS ARRHYTHMIA USING HILBERT–HUANG TRANSFORM

2009 ◽  
Vol 01 (02) ◽  
pp. 295-307 ◽  
Author(s):  
TERRY B. J. KUO ◽  
CHERYL C. H. YANG ◽  
NORDEN E. HUANG
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Respiratory Sinus Arrhythmia ◽  
Amplitude Ratio ◽  
Linear Regression Analysis ◽  
Intrinsic Mode Function ◽  
Chest Circumference ◽  
Sinus Arrhythmia ◽  
Hilbert Huang Transform ◽  
Mode Function

To investigate whether the first intrinsic mode function, obtained from Hilbert–Huang transform (HHT), of heart rate variability is respiratory related. Electrocardiogram and chest circumference signals were recorded from 10 healthy subjects at supine rest. The HHT was applied to both R-R interval and chest circumference signals to figure out their first intrinsic mode functions (C1RR and C1RESP, respectively) from which the instantaneous amplitude, phase, and frequency were calculated. Although the instantaneous amplitudes and frequencies of C1RR and C1RESP were variable, linear regression analysis indicated a phase lock between C1RR and C1RESP. Intake of 500 ml water significantly elevated the amplitude ratio of C1RR to C1RESP; however, the phase difference of C1RR to C1RESP was still unchanged. The data indicate that the first intrinsic mode function of heart rate variability is respiratory related and may be equivalent to respiratory sinus arrhythmia. As compared to fast Fourier transform, HHT of respiratory sinus arrhythmia provides a comparative spatial measurement with a much higher temporal resolution.

Obstructive Sleep Apnea Identification by Heart Rate Features Derived from Intrinsic Mode Function

2013 ◽  
Vol 284-287 ◽  
pp. 1691-1697
Author(s):  
Kang Ming Chang ◽  
Sih Huei Chen
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Gold Standard ◽  
Intrinsic Mode Function ◽  
Ecg Signal ◽  
Original Signal ◽  
Portable Equipment ◽  
Hilbert Huang Transform ◽  
Mode Function ◽  
Obstructive Sleep

Obstructive sleep apnea (OSA) is one of the most important sleep disorders. The gold standard diagnosis of OSA is overnight PSG examination that is time-consuming and labor intensive. Overnight ECG signal was developed to examine OSA, with easy implementation and portable equipment. There were various ECG derived features used for OSA identification, in this study, intrinsic mode function (IMF) was developed. IMF is a byproduct of Hilbert-Huang transform. IMF decompose original signal into various sub components, due to its complexity. In this study, some novel IMF derived features were used to examine the OSA duration measured from ECG signal, compared with traditional HRV features.

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