16 research outputs found
A Low Cost Image Steganalysis by Using Domain Adaptation
Information hiding and data encryption are used widely to protect data and information from anonymous access. In digital world, hiding and encrypting of the desired data into an image is a smart way to protect information with a low cost. In the digital images, steganalysis is a known method to distinguish between clean and stego images. Most of recent researches in this scope exploit feature reduction algorithms to improve the performance of correct detections. However, dimension reduction alone could not tackle the problem of steganalysis because the properties of stego images change during the steganalysis process. In this work, it is intended to propose an Image Steganalysis using visual Domain Adaptation (ISDA), which this steganalysis target images to distinguish across stego and clean images. ISDA is a dimensionality reduction approach that considers the image drifts during the steganography process in the steganalysis of target images. Moreover, ISDA employs domain invariant clustering in an embedded representation to cluster clean and stego images in the reduced subspace. The results on benchmark datasets demonstrate that ISDA thoroughly outperforms all of the state of the art methods on validation parameters, accuracy of detection and time complexit
Markov bidirectional transfer matrix for detecting LSB speech steganography with low embedding rates
Steganalysis with low embedding rates is still a challenge in the field of information hiding. Speech signals are typically processed by wavelet packet decomposition, which is capable of depicting the details of signals with high accuracy. A steganography detection algorithm based on the Markov bidirectional transition matrix (MBTM) of the wavelet packet coefficient (WPC) of the second-order derivative-based speech signal is proposed. On basis of the MBTM feature, which can better express the correlation of WPC, a Support Vector Machine (SVM) classifier is trained by a large number of Least Significant Bit (LSB) hidden data with embedding rates of 1%, 3%, 5%, 8%,10%, 30%, 50%, and 80%. LSB matching steganalysis of speech signals with low embedding rates is achieved. The experimental results show that the proposed method has obvious superiorities in steganalysis with low embedding rates compared with the classic method using histogram moment features in the frequency domain (HMIFD) of the second-order derivative-based WPC and the second-order derivative-based Mel-frequency cepstral coefficients (MFCC). Especially when the embedding rate is only 3%, the accuracy rate improves by 17.8%, reaching 68.5%, in comparison with the method using HMIFD features of the second derivative WPC. The detection accuracy improves as the embedding rate increases
Cylindrical piezorobot’s trajectory planning and control
This paper analyses the movement of piezoelectric actuator. The goal of this work was to create an algorithm for trajectory planning of piezorobot, create a system for trajectory control, develop software and verify the functioning of the algorithm in practice. Movements of piezorobot are very small and very frequent therefore it is difficult to measure trajectories using standard equipment. Design of a novel measurement system and trajectory adjustment was created in this paper. An experimental system for control and trajectory movement tracking of piezorobot was developed. It consists of cylindrical piezorobot, control signal forming and image processing system for trajectory tracking. The cylindrical piezorobot moves in specific trajectories on the plane and is controlled with sinusoidal signals. They are generated by trajectory forming and control software using MATLAB and LabVIEW. The control signals are monitored using a system with oscilloscope. The trajectory of piezorobot was monitored and measured using video camera and video processing software developed by LabVIEW. The software contains image processing and object path tracking, and is implemented using LabVEW and MATLAB. Experimental results showed that trajectories forming algorithm and developed control software is suitable for controlling robots moving on plane
Cylindrical piezorobot’s trajectory planning and control
This paper analyses the movement of piezoelectric actuator. The goal of this work was
to create an algorithm for trajectory planning of piezorobot, create a system for trajectory control,
develop software and verify the functioning of the algorithm in practice. Movements of piezorobot
are very small and very frequent therefore it is difficult to measure trajectories using standard
equipment. Design of a novel measurement system and trajectory adjustment was created in this
paper. An experimental system for control and trajectory movement tracking of piezorobot was
developed. It consists of cylindrical piezorobot, control signal forming and image processing
system for trajectory tracking. The cylindrical piezorobot moves in specific trajectories on the
plane and is controlled with sinusoidal signals. They are generated by trajectory forming and
control software using MATLAB and LabVIEW. The control signals are monitored using a
system with oscilloscope. The trajectory of piezorobot was monitored and measured using video
camera and video processing software developed by LabVIEW. The software contains image
processing and object path tracking, and is implemented using LabVEW and MATLAB.
Experimental results showed that trajectories forming algorithm and developed control software
is suitable for controlling robots moving on plane
Rolling element bearings localized fault diagnosis using signal differencing and median filtration
With the increase complexity of bearings’ processing algorithms and the growing trend of using computationally demanding algorithms, it is advantageous to provide analysts with a simple to use and implement algorithm. In this spirit, this paper combines simple functions to provide machine condition analysts with the capacity to diagnose bearing faults without all the complexity and jargon that comes with existing methods. The paper proposes a simplified surveillance and diagnostic algorithm for diagnosing localized faults in rolling element bearings using measured raw vibration signals. The proposed algorithm is based on analyzing the frequency content obtained from applying a median filter on the squared derivative signal (first or higher derivatives) of the vibration signal. The combination of signal differencing and median filters provides a squared envelope signal, which can be used directly to diagnose faults. Signal differencing gives a measure of jerk forces and lifts the high frequency content of the signal. To select the optimum order of differentiation, Kurtosis and maximum correlated kurtosis (MCK) are proposed. Median filter usage represents a better alternative of normal low pass filtration. This completely suppresses impulses with large magnitudes, which may interfere with the diagnosis. The length of the median filter (odd number 3, 5, 7 etc.) is selected as such to include the first 10 harmonics of the defect frequency. Simulated signals are used to demonstrate the efficiency of the proposed algorithm and give insights into the choices of the differentiation and smoothening orders. The proposed processing algorithm gives a first measure (surveillance) for detecting localized faults in rolling element bearings in a very simple way and can be employed in online learning and diagnosis systems. Results obtained from applying the algorithm on complex vibration signals from two types of gearboxes are compared with a well-established semi-automated technique with good correspondence
Knock detection in spark ignition engines based on complementary ensemble improved intrinsic time-scale decomposition (CEIITD) and Bi-spectrum
Engine knock limits the thermal efficiency improvement of spark-ignition (SI) engines. Thus, the extract research of the knock characteristics has a great significance for the development of gasoline engines. The research proposes a novel knock detection and diagnosis method in SI engines using the CEIITD (Complementary Ensemble Improved Intrinsic time-scale decomposition) and Bi-spectrum algorithm. The CEIITD algorithm is used to extract the knock characteristics. The results show that the CEIITD algorithm can effectively and clearly extract the knock shock characteristics (including light knock) through the vibration signals. A Bi-spectrum analysis can further distinguish between the light knock signal and normal combustion signal. The Bi-spectrum results also show that knock characteristic has a strong non-Gaussian property. At last, the Band pass filter and Improved ITD method were employed to identify the knock characteristics from these cylinder block vibration signals. The comparison result shows that the CEIITD method proposed in this paper is more suitable to detect the knock characteristic
Modeling and active disturbance rejection control for sequential airdrop operations
With the assumption t at the motion acceleration of the cargo is unknown, the dynamic model that accords with the engineering practice of sequential cargo airdrop operations is derived by using the separation body method, which can describe the impact of the sequential moving cargos on the flight safety and airdrop-mission capacity. On this basis, a novel flight control method is designed based on the active disturbance rejection control (ADRC) theory. the system is decoupled and linearized through the nonlinear state error feedback; the total unknown disturbances, including unmolded dynamics and uncertainty, are estimated and compensated real-timely by the extended state observer. Moreover, with the consideration of the time-delay system, the ADRC is improved to enhance the accuracy and rapidity of the control system. Simulations are carried out under the condition that one transport aircraft performs sequential airdrop operations. The results verify that the desirable performance and robustness have been achieved and the proposed control method is quite competent for the sequential airdrop operations
Effect of misaligned bearing support performance on natural frequencies of marine propulsion shafting
The influences of bearing support performance which would be affected by the quality of shafting alignment apparently on the lateral vibration natural frequencies of marine propulsion shafting are analyzed in this paper. A three dimensional finite element model representing the entire propulsion shafting, including the bearings, shaft and propeller, has been developed using finite element software for lateral vibration analyses. The effects of the number of bearings, the stiffness and effective contact length of the bearings on the natural frequencies of the shaft are studied respectively. The simulation analysis show that the bearing of a certain position often only has a significant impact on the frequencies of a certain order or a few orders, and the natural frequencies of the shaft can be transferred to avoid the resonance speeds through the reasonable arrangement and performance design of the shaft bearings. In addition, the curve alignment technology is also presented to improve the current shafting alignment quality and misalignment angle error, so as to ensure the design performance of radial bearings. Experimental results show that the curve alignment technology is an effective method to reduce the uneven load and eccentric wear of the bearings, which are beneficial to avoid the resonance vibration and improve the life and stability of shaft system
Effect of stabilizer on flutter stability of truss girder suspension bridges
An aerodynamic optimization measure of the flutter stability of long-span suspension bridges with truss girder is presented in this paper. At first, the improvement of several kinds of central stabilizers and horizontal stabilizers on flutter stability is examined through series of section model and full aeroelastic model wind tunnel tests. Subsequently, the flutter derivatives of the truss girder with and without stabilizer are identified based on two degrees of freedom coupling free vibration method. Furthermore, based on the identified flutter derivatives, the critical flutter velocities of the truss girder section with and without stabilizer are analyzed through two dimensional flutter analysis method and the critical flutter velocities of the full bridge with and without stabilizer are analyzed through three dimensional method. Afterwards, the influence of each flutter derivative on the flutter stability of the truss girder is investigated. The results indicate that central upper stabilizer can effectively increase the critical flutter velocity of the truss girder. In contrast, the central lower stabilizer and horizontal stabilizer have less influence. Setting up central upper stabilizer leads to an obvious decrease in the value of the flutter derivatives A2* and H2*, while the flutter derivatives H1*, H4*, A1* and A3* are little influenced. The two dimensional and three dimensional flutter analysis results agree well with the sectional model and full model wind tunnel test results respectively