Design and application of discrete wavelet packet transform based multiresolution controller for liquid level system

A new controller based on discrete wavelet packet transform (DWPT) for liquid level system (LLS) has been presented here. This controller generates control signal using node coefficients of the error signal which interprets many implicit phenomena such as process dynamics, measurement noise and effect of external disturbances. Through simulation results on LLS problem, this controller is shown to perform faster than both the discrete wavelet transform based controller and conventional proportional integral controller. Also, it is more efficient in terms of its ability to provide better noise rejection. To overcome the wind up phenomenon by considering the saturation due to presence of actuator, anti-wind up technique is applied to the conventional PI controller and compared to the wavelet packet transform based controller. In this case also, packet controller is found better than the other ones. This similar work has been extended for analogous first order RC plant as well as second order plant also.     

Time–frequency interpretation of multi-frequency signal from rotating machinery using an improved Hilbert–Huang transform

The Hilbert–Huang transform (HHT) has proven to be a promising tool for the analysis of non-stationary signals commonly occurred in industrial machines. However, in practice, multi-frequency intrinsic mode functions (IMFs) and pseudo IMFs are likely generated and lead to grossly erroneous or even completely meaningless instantaneous frequencies, which raise difficulties in interpreting signal features by the HHT spectrum. To enhance the time–frequency resolution of the traditional HHT, an improved HHT is proposed in this study. By constructing a bank of partially overlapping bandpass filters, a series of filtered signals are obtained at first. Then a subset of filtered signals, each associated with certain energy-dominated components, are selected based on the maximal-spectral kurtosis–minimal-redundancy criterion and the information-related coefficient, and further decomposed by empirical mode decomposition to extract sets of IMFs. Furthermore, IMF selection scheme is applied to select the relevant IMFs on which the HHT spectrum is constructed. The novelty of this method is that the HHT spectrum is just constructed with the relevant, almost monochromatic IMFs rather than with the IMFs possibly with multiple frequency components or with pseudo components. The results on the simulated data, test rig data, and industrial gearbox data show that the proposed method is superior to the traditional HHT in feature extraction and can produce a more accurate time–frequency distribution for the inspected signal.     

Growth mechanism and gas-sensing characteristics of organic-additive-free zinc oxide of various shapes

Zinc oxide is widely used in gas sensors, solar cells, and photocatalysts because of its wide bandgap and exciton binding energy of 60 meV in various metal oxides. To use ZnO as a gas sensor, it is necessary to synthesize it with surface defects and a large specific surface area. In this study, hydrothermal synthesis without surfactants was employed to obtain organic-additive-free ZnO. For morphology control, we varied the ratio of the hydroxide ion concentration to the zinc ion concentration. To confirm the growth mechanism of ZnO, we performed X-ray diffraction, scanning electron microscopy, and transmission electron microscopy analyses. Raman spectroscopy and photoluminescence measurements were performed to analyze the surface properties. The Brunauer–Emmett–Teller method and probe stations were used to measure the specific surface area and sensitivity of the gas sensor, respectively. The results confirmed that flower-shaped ZnO is the most suitable gas-sensing material.     

Highly efficient VLSI architecture for DWT with low-storage implementation

With the gradual increase in image resolution of the spacecraft camera, it is highly required to figure out the problem how to process a huge amount of image data on board at a high speed. As a solution, the CCSDS proposes a space-oriented image-coding standard. For the sake of high image-coding performance, it adopts wavelet transformation as a method of image data transformation. However, wavelet transformation contains multi-level data processing, which causes more computational time consumption and more memory utilization. In order to solve this problem, we propose a highly efficient VLSI architecture for DWT with low-storage. By revising the traditional lifting structure and employing time-multiplex data processing strategy to perform the second and third level of wavelet transformation by the same logic module, the usage of logic resource is reduced with no sacrifice on speed.Using a small amount of on-chip memory instead of off-chip memory to save certain parts of DWT coefficients and sending the coefficients in a specific sequence to entropy coder timely, the off-chip memory for storage of DWT coefficients is no longer required. The proposed VLSI architecture of DWT is already implemented on the Xilinx FPGA XC4VSX55, which can achieve a high performance, in terms of data throughput, reaching 95.91MPixels/s.     

Windowed linear canonical transform and its applications

In this paper, we generalize the windowed Fourier transform to the windowed linear canonical transform by substituting the Fourier transform kernel with the linear canonical transform kernel in the windowed Fourier transform definition. It offers local contents, enjoys high resolution, and eliminates cross terms. Some useful properties of the windowed linear canonical transform are derived. Those include covariance property, orthogonality property and inversion formulas. As applications analogues of the Poisson summation formula, sampling formulas and series expansions are given.     

A Modified Method Based on the Discrete Sliding Norm Transform to Reduce the PAPR in OFDM Systems

Orthogonal frequency division multiplexing (OFDM) is a modulation technique that allows the transmission of high data rates over wideband radio channels subject to frequency selective fading by dividing the data into several narrowband and flat fading channels. OFDM has high spectral efficiency and channel robustness. However, a major drawback of OFDM is that the peak‐to‐average power ratio (PAPR) of the transmitted signals is high, which causes nonlinear distortion in the received data and reduces the efficiency of the high power amplifier in the transmitter. The most straightforward method to solve this problem is to use a nonlinear mapping algorithm to transform the signal into a new signal that has a smaller PAPR. One of the latest nonlinear methods proposed to reduce the PAPR is the L₂‐by‐3 algorithm, which is based on the discrete sliding norm transform. In this paper, a new algorithm based on the L₂‐by‐3 method is proposed. The proposed method is very simple and has a low complexity analysis. Simulation results show that the proposed method performs better, has better power spectral density, and is less sensitive to the modulation type and number of subcarriers than L₂‐by‐3.     

Wavelet transform-based stress-time history editing of horizontal axis wind turbine blades

Full scale blade fatigue testing is required to verify that the horizontal axis wind turbine (HAWT) blades posses the strength and service life specified in the design. Unfortunately, fatigue tests must be run for a long time period, which has led blade testing laboratories to seek ways of accelerating fatigue testing time and reducing the costs of tests. The objective of this article is to develop a novel method called a WT-based fatigue damage part extracting method. Based on wavelet transform (WT), this method extracts fatigue damage parts from the stress-time history and generates the edited stress-time history with shorter time length. Also, this article proposes a concept of applying accumulative power spectral density (AccPSD) to identify fatigue damage events contained in the stress-time history of HAWT blades. Wavelet functions used in this study are Morl, Meyr, Dmey, Mexh and DB30. It has been found that Mexh wavelet with an AccPSD level of 9000 Energy/Hz provides the edited stress-time history having a maximum reduction of 20.77% in length with respect to the original length, whilst fatigue damage per repetition can be retained almost the same as the original one. In addition, an existing method, time correlated fatigue damage (TCFD), is used to validate the effectiveness of a WT-based fatigue damage part extracting method. The results suggest that not only does the WT improve the accuracy of fatigue damage retained, but also it provides a shorter length of the edited stress-time history. To conclude, WT is suggested as an alternative technique in fatigue durability study, especially for the field of wind turbine engineering.     

Transient response of a hygrothermoelastic cylinder based on fractional diffusion wave theory

A coupled fractional hygrothermoelasticity theory is formulated within the framework of fractional calculus. Both the classical Fourier’s and Fick’s laws are generalized to anomalous diffusion which is characterized by the time- fractional diffusion-wave equation. Based on the fractional hygrothermoelasticity theory, the transient response of an infinitely long cylinder subjected to hygrothermal loadings at the surface is analyzed. The finite Hankel integral transform method and decoupled technique are used to derive closed-form expressions for temperature, moisture, displacement, and hygrothermal stresses in the solid. The coupling effect of temperature and moisture on elastic fields is discussed. Numerical results of transient response of hygrothermoelastic fields are presented graphically for the cases of subdiffusion, normal diffusion, and superdiffusion, respectively.