scholarly journals Bandwidth Enhancement and Frequency Scanning Array Antenna Using Novel UWB Filter Integration Technique for OFDM UWB Radar Applications in Wireless Vital Signs Monitoring

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 3155 ◽  
Author(s):  
MuhibUr Rahman ◽  
Mahdi NaghshvarianJahromi ◽  
Seyed Mirjavadi ◽  
Abdel Hamouda
Keyword(s):  
Frequency Band ◽  
Vital Signs ◽  
Array Antenna ◽  
Band Pass Filter ◽  
Pass Filter ◽  
Bandwidth Enhancement ◽  
Beam Array ◽  
Vital Signs Monitoring ◽  
Frequency Scanning ◽  
Band Pass

This paper presents the bandwidth enhancement and frequency scanning for fan beam array antenna utilizing novel technique of band-pass filter integration for wireless vital signs monitoring and vehicle navigation sensors. First, a fan beam array antenna comprising of a grounded coplanar waveguide (GCPW) radiating element, CPW fed line, and the grounded reflector is introduced which operate at a frequency band of 3.30 GHz and 3.50 GHz for WiMAX (World-wide Interoperability for Microwave Access) applications. An advantageous beam pattern is generated by the combination of a CPW feed network, non-parasitic grounded reflector, and non-planar GCPW array monopole antenna. Secondly, a miniaturized wide-band bandpass filter is developed using SCSRR (Semi-Complementary Split Ring Resonator) and DGS (Defective Ground Structures) operating at 3–8 GHz frequency band. Finally, the designed filter is integrated within the frequency scanning beam array antenna in a novel way to increase the impedance bandwidth as well as frequency scanning. The new frequency beam array antenna with integrated band-pass filter operate at 2.8 GHz to 6 GHz with a wide frequency scanning from the 50 to 125-degree range.

Envelope Analysis Based on the Combination of Morlet Wavelet and Kurtogram

2012 ◽  
Vol 490-495 ◽  
pp. 305-308
Author(s):  
Yu Liang ◽  
Yu Guo ◽  
Chuan Hui Wu ◽  
Yan Gao
Keyword(s):  
Frequency Band ◽  
Filter Banks ◽  
Morlet Wavelet ◽  
Center Frequency ◽  
Band Pass Filter ◽  
Pass Filter ◽  
Filter Bandwidth ◽  
Envelope Analysis ◽  
Band Pass ◽  
Complex Morlet Wavelet

Envelope analysis based on the combination of complex Morlet wavelet and Kurtogram have advantages of automatic calculation of the center frequency and bandwidth of required band-pass filter. However, there are some drawbacks in the traditional algorithm, which include that the filter bandwidth is not -3dB bandwidth and the analysis frequency band covered by the filter-banks are inconsistent at different levels. A new algorithm is introduced in this paper. Through it, both optimal center frequency and bandwidth of band-pass filter in the envelop analysis can be obtained adaptively. Meanwhile, it ensures that the filters in the filter-banks are overlapped at the point of -3dB bandwidth and the consistency of frequency band that the filter-banks covered.

Feature extraction of latent fault components of rolling bearing based on self-learned sparse atomics and frequency band entropy

2020 ◽  
pp. 107754632092566 ◽  
Author(s):  
HongChao Wang ◽  
WenLiao Du
Keyword(s):  
Feature Extraction ◽  
Frequency Band ◽  
Vibration Signal ◽  
Rolling Bearing ◽  
Band Pass Filter ◽  
Pass Filter ◽  
Sparse Decomposition ◽  
Vibration Data ◽  
Fault Features ◽  
Band Pass

As the key rotating parts in machinery, it is crucial to extract the latent fault features of rolling bearing in machinery condition monitoring to avoid the occurrence of sudden accidents. Unfortunately, the latent fault features are hard to extract by using the traditional signal processing method such as envelope demodulation because the effect of envelope demodulation is influenced strongly by the degree of background noise. Sparse decomposition, as a new promising method being able of capturing the latent fault feature components buried in the vibration signal, has attracted a lot of attentions, especially the predefined dictionary-based sparse decomposition methods. However, the feature extraction effect of the predefined dictionary-based sparse decomposition depends on whether the prior knowledge of the analyzed signal is sufficient or not. To overcome the above problems, a feature extraction method of latent fault components of rolling bearing based on self-learned sparse atomics and frequency band entropy is proposed in the article. First, a self-learned sparse atomics method is applied on the early weak vibration signal of rolling bearing and several self-learned atomics are obtained. Then, the self-learned atomics owing bigger kurtosis values are selected and used to reconstruct the vibration signal to remove the other interference signals. Subsequently, the frequency band entropy method is used to analyze the reconstructed vibration signal, and the optimal parameter of band-pass filter could be calculated. At last, the reconstructed vibration signal is filtered using the optimal band-pass filter, envelope demodulation on the filtered signal is applied, and better fault feature is extracted. The feasibility and effectiveness of the proposed method are verified through the vibration data of the accelerated fatigue life test of rolling bearing. Besides, the analysis results of the same vibration data using Autogram and spectral kurtosis methods are also presented to highlight the superiority of the proposed method.

scholarly journals Enhanced Bandwidth of Band Pass Filter Using a Defected Microstrip Structure for Wideband Applications

2018 ◽  
Vol 8 (6) ◽  
pp. 5260 ◽  
Author(s):  
Sanae Azizi ◽  
Mustapha El Halaoui ◽  
Abdelmoumen Kaabal ◽  
Saida Ahyoud ◽  
Adel Asselman
Keyword(s):  
Bandpass Filter ◽  
Dielectric Substrate ◽  
Center Frequency ◽  
Band Pass Filter ◽  
Pass Filter ◽  
Bandwidth Enhancement ◽  
Wireless Applications ◽  
Coupled Lines ◽  
Band Pass ◽  
Microstrip Structure

<p>In this paper, the bandwidth enhancement of bandpass filter (BPF) is proposed by utilizing defected microstrip structure (DMS). The initial micro strip BPF which is designed to have the bandwidth 1GHz with the center frequency of 3.5GHz is deployed on FR4 Epoxy dielectric substrate with overall size and thickness of 14mm x 24mm and 1.6mm, respectively. The proposed filter consists of two parallel coupled lines centred by ring-shaped, to enhance the bandwidth response, an attempt is carried out by applying DMS on the ligne center with a ring-shaped of initial filter. Here, the proposed DMS is constructed of the arrowhead dumbbell. Some parametrical studies to the DMS such as changing to obtain the optimum geometry of DMS with the desired bandwidth response. From the characterization result, it shows that the utilization of DMS on to the microstrip ligne of filter has widened 3dB bandwidth response up to 1.8GHz ranges from 2.55GHz to 4.35GHz yielding an enhanced wideband response for various wideband wireless applications.</p>

SOFM for Image Compression Based on Spatial Frequency Band-Pass Filter and Vector Quantization

2020 ◽  
pp. 388-403
Author(s):  
Shadi M. S. Hilles ◽  
Volodymyr P. Maidaniuk
Keyword(s):  
Image Compression ◽  
Spatial Frequency ◽  
Vector Quantization ◽  
Frequency Band ◽  
Compression Ratio ◽  
Band Pass Filter ◽  
Small Signal ◽  
Pass Filter ◽  
Band Pass ◽  
Three Stages

This chapter presents image compression based on SOFM and vector quantization (VQ). The purpose of this chapter is to show the significance of SOFM with bandpass filter in process of image compression to increase compression ratio and to enhance image compression effectiveness. Image compression by SOFM model is presented and consists of three stages: The first is band-pass filter. The result experiments used Lena.bmp, girl256.bmp, and show compression in block image 16x16 given best compression ratio with a small signal-noise ratio (SNR).

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