Research on transverse parametric vibration and fault diagnosis of multi-rope hoisting catenaries

According to application characteristics of the multi-rope friction hoisting catenaries, a linear transverse parametric vibration model of axially moving string was setup with fixed length and inhomogeneous boundary conditions. The Galerkin method was applied to discretize the dynamic governing equations. Using the Newmark method, the coupling coefficient second-order ODEs were solved. The parametric resonance vibrations of catenaries generated by tension variation along with forced boundary excitations were diagnosed with analytical and experimental validations. The transverse vibration amplitudes and frequencies of catenaries measured and analyzed by non-contact video gauge method were consistent with simulation outputs. The simulation outputs were based on practically measured parameters such as boundary displacement excitations and tension variations. The research results indicated that tension imbalance distributions of the catenaries could change their natural frequencies and result in transverse resonance under boundary harmonic displacement excitations. Therefore specific measures should be provided to maintain tension balance in multi-rope hoisting applications

A contrast-sensitive reversible visible image watermarking technique

A reversible (also called lossless, distortion-free, or invertible) visible watermarking scheme is proposed to satisfy the applications, in which the visible watermark is expected to combat copyright piracy but can be removed to losslessly recover the original image. We transparently reveal the watermark image by overlapping it on a user-specified region of the host image through adaptively adjusting the pixel values beneath the watermark, depending on the human visual system-based scaling factors. In order to achieve reversibility, a reconstruction/ recovery packet, which is utilized to restore the watermarked area, is reversibly inserted into non-visibly-watermarked region. The packet is established according to the difference image between the original image and its approximate version instead of its visibly watermarked version so as to alleviate its overhead. For the generation of the approximation, we develop a simple prediction technique that makes use of the unaltered neighboring pixels as auxiliary information. The recovery packet is uniquely encoded before hiding so that the original watermark pattern can be reconstructed based on the encoded packet. In this way, the image recovery process is carried out without needing the availability of the watermark. In addition, our method adopts data compression for further reduction in the recovery packet size and improvement in embedding capacity. The experimental results demonstrate the superiority of the proposed scheme compared to the existing methods

Pattern recognition of rigid hoisting guides based on vibration characteristics

A test rig is built to simulate the typical fault patterns of rigid hoisting guides and to collect vibration and inclination signals. In this work, we use these signals to perform data mining for fault-pattern recognition. Parameters are initially defined by analyzing collected signals. Then, the importance of each parameter is calculated using the boosting-tree method. Some valuable parameters are retained. To establish a data-mining algorithm that works remarkably for the fault recognition of rigid hoisting guides, six different algorithms including the boosting tree, K-nearest neighbor, MARSpline, neural network, random forest, and support vector machine are compared. Results show that the best performance is that of the boosting-tree algorithm, whose mechanism is then presented in detail

Semi-active control system for magneto-rheological damper based on the identification model with fuzzy neural network

Semi-active suspensions that dissipate energy through controllable dampers have been used in trains, tractors and off-road vehicles in the last decades. Magneto-rheological (MR) fluids have been widely applied as a new material in the field of vibration control. Magneto-rheological (MR) damper is an extremely ideal semi-active control device compared with traditional semi-active damping control device for its superiorities of rapid response (in millisecond), far less response time than sampling time, and almost no time lag caused by the control devices. However, its complicated dynamic hysteresis characteristics vary with the currents imposed on it, resulting in the difficulty in establishing the mathematical model which can truly describe its dynamic behavior. Besides, an effective and precision mathematical model can be of help for constructing the semi-active control law. In this paper, the system identification method based on the theory of fuzzy neural network (FNN) is employed to identify the mathematical model that can accurately reflect the dynamic hysteresis characteristics of magneto-rheological (MR) damper. Under the semi-active control law, the structure on the damper can be stabilized at the fastest rate with an optimal current calculated by the identified mathematical model imposed on magneto-rheological (MR) damper. Consequently, vibration reduction can be effectively realized

Vibration modal shapes and strain measurement of the main shaft assembly of a friction hoist

In order to evaluate the reliability of the main shaft unit of a friction hoisting system, strain measurement is a significant method. In this paper, a test rig of a friction hoisting system was built, which could applied periodically changing load on its main shaft unit; The mechanical analysis under the test load was conducted and the boundary limits were obtained; A three dimensional model of the main shaft unit was built in Pro-E and its finite element analysis was performed in ANSYS; With the analytical result, measuring points for strain rosettes were initially selected; Vibration modal shapes of the main shaft unit were analyzed, based on which Modal Assurance Criterion (MAC) was utilized in the Particle Swarm Optimization (PSO) algorithm to make the final decision of the number and positions of the measuring points; A wireless measurement system was developed to acquire strain signals from the optimized measuring positions; The test result verified the efficiency of the methods employed in this paper and revealed how strain of the main shaft unit changes during running process

Pattern recognition of rigid hoisting guides based on vibration characteristics

A test rig is built to simulate the typical fault patterns of rigid hoisting guides and to collect vibration and inclination signals. In this work, we use these signals to perform data mining for fault-pattern recognition. Parameters are initially defined by analyzing collected signals. Then, the importance of each parameter is calculated using the boosting-tree method. Some valuable parameters are retained. To establish a data-mining algorithm that works remarkably for the fault recognition of rigid hoisting guides, six different algorithms including the boosting tree, K-nearest neighbor, MARSpline, neural network, random forest, and support vector machine are compared. Results show that the best performance is that of the boosting-tree algorithm, whose mechanism is then presented in detail

A relative value method for measuring and evaluating cardiac reserve

BACKGROUND: Although a very close relationship between the amplitude of the first heart sound (S1) and the cardiac contractility have been proven by previous studies, the absolute value of S1 can not be applied for evaluating cardiac contractility. However, we were able to devise some indicators with relative values for evaluating cardiac function. METHODS: Tests were carried out on a varied group of volunteers. Four indicators were devised: (1) the increase of the amplitude of the first heart sound after accomplishing different exercise workloads, with respect to the amplitude of the first heart sound (S1)recorded at rest was defined as cardiac contractility change trend (CCCT). When the subjects completed the entire designed exercise workload (7000 J), the resulting CCCT was defined as CCCT(1); when only 1/4 of the designed exercise workload was completed, the result was defined as CCCT(1/4). (2) The ratio of S1 amplitude to S2 amplitude (S1/S2). (3) The ratio of S1 amplitude at tricuspid valve auscultation area to that at mitral auscultation area T1/M1 (4) the ratio of diastolic to systolic duration (D/S). Data were expressed as mean ± SD. RESULTS: CCCT(1/4) was 6.36 ± 3.01 (n = 67), CCCT(1) was 10.36 ± 4.2 (n = 33), S1/S2 was1.89 ± 0.94 (n = 140), T1/M1 was 1.44 ± 0.99 (n = 144), and D/S was 1.68 ± 0.27 (n = 172). CONCLUSIONS: Using indicators CCCT(1/4) and CCCT(1) may be beneficial for evaluating cardiac contractility and cardiac reserve mobilization level, S1/S2 for considering the factor for hypotension, T1/M1 for evaluating the right heart load, and D/S for evaluating diastolic cardiac blood perfusion time

Genome-Wide Association Studies Reveal the Genetic Basis of Ionomic Variation in Rice

Rice (Oryza sativa) is an important dietary source of both essential micronutrients and toxic trace elements for humans. The genetic basis underlying the variations in the mineral composition, the ionome, in rice remains largely unknown. Here, we describe a comprehensive study of the genetic architecture of the variation in the rice ionome performed using genome-wide association studies (GWAS) of the concentrations of 17 mineral elements in rice grain from a diverse panel of 529 accessions, each genotyped at ∼6.4 million single nucleotide polymorphism loci. We identified 72 loci associated with natural ionomic variations, 32 that are common across locations and 40 that are common within a single location. We identified candidate genes for 42 loci and provide evidence for the causal nature of three genes, the sodium transporter gene Os-HKT1;5 for sodium, Os-MOLYBDATE TRANSPORTER1;1 for molybdenum, and Grain number, plant height, and heading date7 for nitrogen. Comparison of GWAS data from rice versus Arabidopsis (Arabidopsis thaliana) also identified well-known as well as new candidates with potential for further characterization. Our study provides crucial insights into the genetic basis of ionomic variations in rice and serves as an important foundation for further studies on the genetic and molecular mechanisms controlling the rice ionome