Detection of Bearing Faults Using a Novel Adaptive Morphological Update Lifting Wavelet

The current morphological wavelet technologies utilize a fixed filter or a linear decomposition algorithm, which cannot cope with the sudden changes, such as impulses or edges in a signal effectively. This paper pre- sents a novel signal processing scheme, adaptive morpho- logical update lifting wavelet （AMULW）, for rolling element bearing fault detection. In contrast with the widely used morphological wavelet, the filters in AMULW are no longer fixed. Instead, the AMULW adaptively uses a morphological dilation-erosion filter or an average filter as the update lifting filter to modify the approximation signal. Moreover, the nonlinear morphological filter is utilized to substitute the traditional linear filter in AMULW. The effectiveness of the proposed AMULW is evaluated using a simulated vibration signal and experimental vibration sig- nals collected from a bearing test rig. Results show that the proposed method has a superior performance in extracting fault features of defective roiling element bearings.

The Lifting Scheme Based on the Second Generation Wavelets

The lifting scheme is a custom design construclion of Biorthogonal wavelets, a fast and efficient method to realize wavelet transform,which provides a wider range of application and efficiently reduces the computing time with its particular frame. This paper aims at introducing the second generation wavelets, begins with traditional Mallat algorithms, illustrates the lifting scheme and brings out the detail steps in the construction of Biorthogonal wavelets. Because of isolating the degrees of freedom remaining the biorthogonality relations, we can fully control over the lifting operators to design the wavelet for a particular application, such as increasing the number of the vanishing moments.

Second-generation wavelet finite element based on the lifting scheme for GPR simulation

Ground-penetrating radar(GPR)is a highly efficient,fast and non-destructive exploration method for shallow surfaces.High-precision numerical simulation method is employed to improve the interpretation precision of detection.Second-generation wavelet finite element is introduced into the forward modeling of the GPR.As the finite element basis function,the second-generation wavelet scaling function constructed by the scheme is characterized as having multiple scales and resolutions.The function can change the analytical scale arbitrarily according to actual needs.We can adopt a small analysis scale at a large gradient to improve the precision of analysis while adopting a large analytical scale at a small gradient to improve the efficiency of analysis.This approach is beneficial to capture the local mutation characteristics of the solution and improve the resolution without changing mesh subdivision to realize the efficient solution of the forward GPR problem.The algorithm is applied to the numerical simulation of line current radiation source and tunnel non-dense lining model with analytical solutions.Result show that the solution results of the secondgeneration wavelet finite element are in agreement with the analytical solutions and the conventional finite element solutions,thereby verifying the accuracy of the second-generation wavelet finite element algorithm.Furthermore,the second-generation wavelet finite element algorithm can change the analysis scale arbitrarily according to the actual problem without subdividing grids again.The adaptive algorithm is superior to traditional scheme in grid refinement and basis function order increase,which makes this algorithm suitable for solving complex GPR forward-modeling problems with large gradient and singularity.

Vegetation field spectrum denoising via lifting wavelet transform

Field spectrum pretreatment experiments were carried out, and denoising numerical experiment via lifting wavelet transform （LWT） was designed, and several famous test signals including blocks, bumps, heavy sine and doppler were processed via Lw＇r in these experiment. And the field spectrum was processed via Lw＇r. Experiments proved that SNRG-tO-SNRN curves have similar feature and they all have a peak. And SNRG of almost all employed wavelets have higher value with SNRN between 0 and 20 dB. When signal is at high SNR, the SNRG is very little, and the MSED of denoised signal became little by little. LWT is more suite to denoise the low SNR or heavy noise contaminated signals. Bior4.4 have wider SNRN interval for denoising comparing with other five wavelets, includ- ing haar, db6, sym6, bior2.2 and bior3.3. Original field spectrum is processed by 3 stage liftings based on bior4.4 to denoise the trivial noise-contaminated regions. On processing the water band signal, logarithm transform is firstly taken. And then the spectrum is denoised via LWT based on bior4.4. The results show that an excellent denoised spectrum can be get, especially between 350 nm and 1 800 nm, and between 1 960 nm to 2 500 nm. While there is still a bump around 1 900 nm, this maybe due to the spectrum machine＇s limited precision.

A COMPRESSION ALGORITHM FOR ECG BASED ON INTEGER LIFTING SCHEME WAVELET TRANSFORM

In view of the shortcomes of conventional ElectroCardioGram (ECG) compression algo- rithms,such as high complexity of operation and distortion of reconstructed signal,a new ECG compression encoding algorithm based on Set Partitioning In Hierarchical Trees (SPIHT) is brought out after studying the integer lifting scheme wavelet transform in detail.The proposed algorithm modifies zero-tree structure of SPIHT,establishes single dimensional wavelet coefficient tree of ECG signals and enhances the efficiency of SPIHT-encoding by distributing bits rationally,improving zero-tree set and ameliorating classifying method.For this improved algorithm,floating-point com- putation and storage are left out of consideration and it is easy to be implemented by hardware and software.Experimental results prove that the new algorithm has admirable features of low complexity, high speed and good performance in signal reconstruction.High compression ratio is obtained with high signal fidelity as well.

一种生成双正交紧支复小波的Lifting方法

提出了一种构造双正交紧支复小波的方法 :以现有任何一种正交或双正交实小波为基础 ,可构造出消失矩阶数可任意选定的无穷多个相频特性 (包括线性相位特性 )不同的双正交紧支复小波。其特点为 :由于是双正交紧支型 ,可采用Mallat算法等快速算法 ,因此使用时实时性好 ;因为是复小波 ,所以能提取电力系统至关重要的相位信息 ;具有多种相频特性 ,便于与相频特性多变的电力系统信号匹配等 ,因此这类小波在电力系统有广泛的应用前景。

用lifting方法构造具有线性相位的双正交小波

Lifting作为第2代小波的构造方法,同样能够构造出第1代小波。与传统的Daubechies方法相比,该方法简单易懂,并且容易用格状结构(Lattice structrue)构造出满足特定要求的小波。该文首先根据Lawton矩阵的性质证明了几乎所有由此方法构造出的小波满足双正交条件,然后考虑如何构造具有线性相位性质的双正交小波,最后列举几个例子说明lifting方法。

Lifting Scheme及其在小波图象编码中的应用

L ifting Schem e是构造第二代小波的关键技术 .相对于第一代小波而言 ,L ifting Scheme是一种比 Mallat算法更快、更简单和更容易操作的算法 ,也是 JPEG2 0 0 0推荐的算法 .为了将其应用到小波图象编码中 ,提出了一种对 L ifting Scheme作适当改进以用于小波图象编码的方法 .该方法就是先用 L ifting Scheme来实现 D9/ 7双正交小波变换 ,然后再用这种技术实现的 D9/ 7双正交小波变换来进行图象压缩编码 .在将 L ifting Schem e算法用于小波图象编码的过程中 ,对该算法做了必要的简化 ,以便保证每个提升 (lifting)环节都是 FIR滤波 .同时 ,根据能量守恒的原则 ,重新调整了尺度因子 .实验结果表明 ,这种经过改进的 L ifting Schem e取得了比

Lifting Scheme的Haar小波在医学图像压缩中的应用研究

针对医学图像进行实时传输和大量存储时需要进行压缩处理的需求,论述了Lifting Scheme的Haar小波在医学图像压缩中的应用方法。首先,分析了Haar小波的变换原理,然后阐述了基于提升Haar小波的医学图像压缩算法。实验表明,在压缩比和峰值信噪比等评价参数方面,基于Lifting Scheme的Haar小波算法在医学图像压缩中取得了较好效果。

Multiple description scalable video coding based on 3D lifted wavelet transform

In this work, a new method to deal with the unconnected pixels in motion compensated temporal filtering (MCTF) is presented, which is designed to improve the performance of 3D lifted wavelet coding. Furthermore, multiple description scalable coding (MDSC) is investigated, and novel MDSC schemes based on 3D wavelet coding are proposed, using the lifting imple- mentation of temporal filtering. The proposed MDSC schemes can avoid the mismatch problem in multiple description video coding, and have high scalability and robustness of video transmission. Experimental results showed that the proposed schemes are feasible and adequately effective.

Lifting transform via Savitsky-Golay filter predictor and application of denoising

The Savitsky-Golay filter isa smoothing filter based on polynomial regression.Itemploys the regression fitting capacity to improve the smoothing results.But Savit-sky-Golay filter uses a fix sized window.It has the same shortage of Window FourierTransform.Wavelet mutiresolution analysis may deal with this problem.In this paper,tak-ing advantage of Savitsky-Golay filter's fitting ability and the wavelet transform's multiscaleanalysis ability,we developed a new lifting transform via Savitsky-Golay smoothing filteras the lifting predictor,and then processed the signals comparing with the ordinary Savit-sky-Golay Smoothing method.We useed the new lifting in noisy heavy sine denoising.Thenew transform obviously has better denoise ability than ordinary Savitsky-Golay smooth-ing method.At the same time singular points are perfectly retained in the denoised signal.Singularity analysis,multiscale interpolation,estimation,chemical data smoothing andother potential signal processing utility of this new lifting transform are in prospect.

基于Lifting Scheme的自适应小波滤波器组的研究

具有高阶消失矩的滤波器在分析平稳信号时,要比使用低阶消失矩的滤波器效果好;而在信 号的边缘区和突变区,用低阶消失矩的滤波器会达到更好的效果,所以在这一理论基础的指导下,提 出了一种有效的双正交两通道小波滤波器组的构造方法,它是基于Lifting Scheme的一种自适应结构． 它的突出优点是可以保证信号的完全重建．实验证明,这种自适应的小波滤波器组在很多应用中显然 要优于有固定消失矩的小波滤波器组．

An Improved Algorithm for Image Edge Detection Based on Lifting Scheme

Wavelet transform is an ideal way for edge detection because of its multi-scale property, localization both in time and frequency domain, sensitivity to the abrupt change of signals, and so on. An improved algorithm for image edge detection based on Lifting Scheme is proposed in this paper. The simulation results show that our improved method can better reflect edge information of images.

Lifting Scheme Based SPIHT Still Image Coding

In order to eliminate float-point operations for fast wavelet transform, an integer D9/7 biorthogonal reversible wavelet transform was accomplished by lifting scheme. The lifting scheme based wavelet transform can be finished by addition and shift simply. It improved the quality of reconstructive image and greatly reduced the computational complexity due to integer operation. It is suitable for real-time image coding on hardware such as DSP. The simulation results show that the lifting scheme based SPIHT is prior to traditional wavelet based SPHIT in quality and complexity.

New Edge-Directed Interpolation Based-Lifting DWT and MSPIHT Algorithm for Image Compression

The amount of image data generated in multimedia applications is ever increasing. The image compression plays vital role in multimedia applications. The ultimate aim of image compression is to reduce storage space without degrading image quality. Compression is required whenever the data handled is huge they may be required to sent or transmitted and also stored. The New Edge Directed Interpolation (NEDI)-based lifting Discrete Wavelet Transfrom (DWT) scheme with modified Set Partitioning In Hierarchical Trees (MSPIHT) algorithm is proposed in this paper. The NEDI algorithm gives good visual quality image particularly at edges. The main objective of this paper is to be preserving the edges while performing image compression which is a challenging task. The NEDI with lifting DWT has achieved 99.18% energy level in the low frequency ranges which has 1.07% higher than 5/3 Wavelet decomposition and 0.94% higher than traditional DWT. To implement this NEDI with Lifting DWT along with MSPIHT algorithm which gives higher Peak Signal to Noise Ratio (PSNR) value and minimum Mean Square Error (MSE) and hence better image quality. The experimental results proved that the proposed method gives better PSNR value (39.40 dB for rate 0.9 bpp without arithmetic coding) and minimum MSE value is 7.4.

Lifting Scheme and Its Application to Edge Detection

Lifting scheme is a useful and very general technique for constructing wavelet decomposition. The paper adapts the lifting into redundant lifting to obtain shift invariant wavelet transform. In prediction and update stages of the lifting morphological operator is adopted for preserving local maxima of a signal over several scales, which is particularly useful in wavelet\|based signal detec tion. The new transform presented in the paper is applied in multiresoluti on edge detection of medical image and experim ent results are given to show better performance and applicable potentiali ty.

Lift fin stabilizers based on data fusion with wavelet denoising technology

Fin stabilizers with fin-lift feedback control can shield the mapping error of calculation between the fin angle and fin lift force,which is in the fin stabilizer with fin-angle feedback control.In practice,there are some technical difficulties in lift fin stabilizers,such as lift force detection and lift force sensor installation,so it cannot achieve the good antirolling performance.Therefore,a fin stabilizer system with fin-lift/fin-angle integrated control is brought forward.Data fusion based on wavelet denoising technology is employed in the system,which combines lift with fin angle local information from two sensors with different frequency ranges in order to eliminate redundant and contradictory information,and using complementary information to obtain the relative integrity of the lift force signal.The system model is established in this paper,and the fusion signal and the antirolling performance of this model are simulated respectively.The result shows that the control system can meet the antirolling need in different sea situations.

An Image Fusion Algorithm Based on Lifting Scheme

Taking the advantage of the lifting scheme＇s characters that can build wavelet translorms tor transforming from integer to integer and the quality of the reconstructing image＇is independent of the topology way adopted by the boundary, an image fusion algorithm based on lifting scheme is proposed. This paper discusses the fundamental theory of lifting scheme firstly and then after taking transform analysis according to a kind of images that need to be confused.

A Parallel-based Lifting Algorithm and VLSI Architecture for DWT

A novel Parallel-Based Lifting Algorithm （PBLA） for Discrete Wavelet Transform （DWT）, exploiting the parallelism of arithmetic operations in all lifting steps, is proposed in this paper. It leads to reduce the critical path latency of computation, and to reduce the complexity of hardware implementation as well. The detailed derivation on the proposed algorithm, as well as the resulting Very Large Scale Integration （VLSI） architecture, is introduced, taking the 9/7 DWT as an example but without loss of generality. In comparison with the Conventional Lifting Algorithm Based Implementation （CLABI）, the critical path latency of the proposed architecture is reduced by more than half from （4Tm ＋ 8Ta）to Tm ＋ 4Ta, and is competitive to that of Convolution-Based Implementation （CBI）, but the new implementation will save significantly in hardware. The experimental results demonstrate that the proposed architecture has good performance in both increasing working frequency and reducing area.