Analysis of Transverse Vibration Acceleration of a High-Speed Elevator with Random Parameters under Random Excitation

The randomness of a high-speed elevator car system’s parameters was caused by manufacturing and installation error. In order to more accurately evaluate the dynamic behavior of the elevator car, the compound vibration problems containing both random excitation and random parameters were studied. The deterministic part and random part of the acceleration response were derived by the perturbation theory, and the vibration image in the time domain and frequency domain were analyzed. The sensitivity expressions of each parameter to the system response were established in the random vibration system. The acceleration standard deviation due to random excitation was calculated by the pseudo excitation method. The acceleration standard deviation due to the random parameters was obtained according to the displacement response covariance matrix and random parameters covariance matrix. The discrete degree of random excitation and random parameters on the transverse acceleration of the car was analyzed in an example, and the influence degree of each parameter on acceleration responses was quantitatively described by calculating the response sensitivity of random parameters. This paper provides an effective method for the analysis of the vibration characteristics of the high speed elevator car system

Force analysis of an open TBM gripping–thrusting–regripping mechanism

This paper presents an approach for the force analysis of an open TBM gripping–thrusting–regripping mechanism, which is a special parallel mechanism driven by hydraulic actuators and constrained by rocky surroundings. The static equilibrium equations of the cutterhead–mainbeam–saddle subassembly are formulated first by exploring the reaction forces in the cross pin situated between the saddle and the gripper cylinder. This is followed by formulating the static equilibrium equations of the inner closed loops formed by the above subassembly, the torque, and gripper cylinders. Consequently, the linear map between the externally applied wrench imposed on the shield and the equivalent thrust forces of the cylinders is developed. The functionality of the force model developed is twofold, i.e., it can be used either to estimate the thrust forces of the cylinders required to resist against the tunneling loads, or to predict the tunneling loads using the measured thrust forces of these cylinders, thus providing important theoretical basis for the design and control of the mechanism

Free vibration properties of rotate vector reducer

For RV reducer widely used in Robots, this work develops a lumped parameter model to investigate free vibration properties of general description. The dynamic model admits three planar degrees of freedom for each component and includes key factors affecting vibration such as involute and cycloid gear mesh stiffness, crankshaft bending stiffness and bearing stiffness. For the linear case, examine of the associated eigenvalue problem reveals the specific structure of vibration modes. The modes are classified into three types: rotational, translational, and planetary component modes. All vibration modes fall into one of these three categories. The unique properties of each type is examined which is analytically verified with candidate mode method. Furthermore, the work investigates effects of parameters, which include stiffness, mass, moment of inertia and crankshaft eccentricity, on natural frequencies of three vibration modes and crankshaft eccentricity is in particular scrutinized. It is helpful for understanding the relationship between parameters and vibration modes

TLS-bridged co-prediction of tree-level multifarious stem structure variables from worldview-2 panchromatic imagery: a case study of the boreal forest

In forest ecosystem studies, tree stem structure variables (SSVs) proved to be an essential kind of parameters, and now simultaneously deriving SSVs of as many kinds as possible at large scales is preferred for enhancing the frontier studies on marcoecosystem ecology and global carbon cycle. For this newly emerging task, satellite imagery such as WorldView-2 panchromatic images (WPIs) is used as a potential solution for co-prediction of tree-level multifarious SSVs, with static terrestrial laser scanning (TLS) assumed as a ‘bridge’. The specific operation is to pursue the allometric relationships between TLS-derived SSVs and WPI-derived feature parameters, and regression analyses with one or multiple explanatory variables are applied to deduce the prediction models (termed as Model1s and Model2s). In the case of Picea abies, Pinus sylvestris, Populus tremul and Quercus robur in a boreal forest, tests showed that Model1s and Model2s for different tree species can be derived (e.g. the maximum R2 = 0.574 for Q. robur). Overall, this study basically validated the algorithm proposed for co-prediction of multifarious SSVs, and the contribution is equivalent to developing a viable solution for SSV-estimation upscaling, which is useful for large-scale investigations of forest understory, macroecosystem ecology, global vegetation dynamics and global carbon cycle.This work was financially supported in part by the National Natural Science Foundation of China [grant numbers 41471281 and 31670718] and in part by the SRF for ROCS, SEM, China. (41471281 - National Natural Science Foundation of China; 31670718 - National Natural Science Foundation of China; SRF for ROCS, SEM, China)http://www-tandfonline-com.ezproxy.bu.edu/doi/abs/10.1080/17538947.2016.1247473?journalCode=tjde20Published versio

Analyzing Hidden Representations in End-to-End Automatic Speech Recognition Systems

Neural models have become ubiquitous in automatic speech recognition systems. While neural networks are typically used as acoustic models in more complex systems, recent studies have explored end-to-end speech recognition systems based on neural networks, which can be trained to directly predict text from input acoustic features. Although such systems are conceptually elegant and simpler than traditional systems, it is less obvious how to interpret the trained models. In this work, we analyze the speech representations learned by a deep end-to-end model that is based on convolutional and recurrent layers, and trained with a connectionist temporal classification (CTC) loss. We use a pre-trained model to generate frame-level features which are given to a classifier that is trained on frame classification into phones. We evaluate representations from different layers of the deep model and compare their quality for predicting phone labels. Our experiments shed light on important aspects of the end-to-end model such as layer depth, model complexity, and other design choices.Comment: NIPS 201

Spring-IMU Fusion Based Proprioception for Feedback Control of Soft Manipulators

This paper presents a novel framework to realize proprioception and closed-loop control for soft manipulators. Deformations with large elongation and large bending can be precisely predicted using geometry-based sensor signals obtained from the inductive springs and the inertial measurement units (IMUs) with the help of machine learning techniques. Multiple geometric signals are fused into robust pose estimations, and a data-efficient training process is achieved after applying the strategy of sim-to-real transfer. As a result, we can achieve proprioception that is robust to the variation of external loading and has an average error of 0.7% across the workspace on a pneumatic-driven soft manipulator. The realized proprioception on soft manipulator is then contributed to building a sensor-space based algorithm for closed-loop control. A gradient descent solver is developed to drive the end-effector to achieve the required poses by iteratively computing a sequence of reference sensor signals. A conventional controller is employed in the inner loop of our algorithm to update actuators (i.e., the pressures in chambers) for approaching a reference signal in the sensor-space. The systematic function of closed-loop control has been demonstrated in tasks like path following and pick-and-place under different external loads

Marine environmental pollution and offshore aquaculture structure: Evidence from China

The marine environment pollution is becoming an important factor that restricts the sustainable development of mariculture in China. This study takes 10 Chinese coastal provinces (cities) as the study area, based on the rationalization and upgrading dimensions of industrial structure, and innovatively constructs an analytical framework of marine environmental pollution and offshore aquaculture structure to identify the intrinsic relationship between them; and introduces a spatial econometric model to alleviate the estimation bias caused by the public goods attribute of marine environment and improve the reliability of research conclusions. The results show that: (1) The rationalization of the offshore aquaculture structure in China is relatively weak, showing a “concentrated and contiguous” distribution pattern towards the developed aquaculture areas; at the same time, but the differences between regions are expanding; (2) The rationalization and upgrading of the offshore aquaculture structure are affected by the pollution of the marine environment. The degree of upgrading shows different trends; (3) There is a significant spatial adjacency and threshold effect of the negative impact of marine environmental pollution on offshore farming structure. However, due to the limitations of data, the accuracy of our data and the effectiveness of the measurement of industrial structure indicators still need to be improved. Therefore, governmental departments should consider the development of the surrounding areas as well as the pollution emission in the region, and jointly promote the optimization and adjustment of China’s offshore aquaculture structure through the construction of a coordinated management mechanism of marine pollution prevention and treatment

Study on the Optimization of the Formula of Potato Scone andIts Texture Characteristics

In order to enrich potato staple products and improve the sensory quality of scones, the rheological properties of mixed dough of potato flour and wheat flour were studied. With sensory score and texture characteristics as evaluation indexes, the formulation of potato flour scone was optimized by single factor experiments and orthogonal test. The results showed that potato flour could improve the water absorption of wheat flour and shorten the formation time of dough, but it would lead to a decline in the elasticity and strength of the dough, resulting in a decrease in its quality. Therefore, the appropriate substitution ratio for whole potato flour was considered to be 20%. The best process recipe for scones was based on a mixture of wheat flour and whole potato flour quality, with 20% whole potato flour added, 68% water added, 0.8% yeast added and 6% sugar added. The hardness of the scone prepared under the optimal condition was 342.63 g, and the chewiness was 106.76 N. The research results provided a theoretical basis for the quality improvement of the scones and the development of whole potato flour products

Effects of different fertilization conditions and different geographical locations on the diversity and composition of the rhizosphere microbiota of Qingke (Hordeum vulgare L.) plants in different growth stages

IntroductionThe excessive use of chemical fertilizer causes increasing environmental and food security crisis. Organic fertilizer improves physical and biological activities of soil. Rhizosphere microbiota, which consist of highly diverse microorganisms, play an important role in soil quality. However, there is limited information about the effects of different fertilization conditions on the growth of Qingke plants and composition of the rhizosphere microbiota of the plants.MethodsIn this study, we characterized the rhizosphere microbiota of Qingke plants grown in three main Qingke-producing areas (Tibet, Qinghai, and Gansu). In each of the three areas, seven different fertilization conditions (m1–m7, m1: Unfertilized; m2: Farmer Practice; m3: 75% Farmer Practice; m4: 75% Farmer Practice +25% Organic manure; m5: 50% Farmer Practice; m6: 50% Farmer Practice +50% Organic manure; m7: 100% Organic manure) were applied. The growth and yields of the Qingke plants were also compared under the seven fertilization conditions.ResultsThere were significant differences in alpha diversity indices among the three areas. In each area, differences in fertilization conditions and differences in the growth stages of Qingke plants resulted in differences in the beta diversity of the rhizosphere microbiota. Meanwhile, in each area, fertilization conditions, soil depths, and the growth stages of Qingke plants significantly affected the relative abundance of the top 10 phyla and the top 20 bacterial genera. For most of microbial pairs established through network analysis, the significance of their correlations in each of the microbial co-occurrence networks of the three experimental sites was different. Moreover, in each of the three networks, there were significant differences in relative abundance and genera among most nodes (i.e., the genera Pseudonocardia, Skermanella, Pseudonocardia, Skermanella, Aridibacter, and Illumatobacter). The soil chemical properties (i.e., TN, TP, SOM, AN, AK, CEC, Ca, and K) were positively or negatively correlated with the relative abundance of the top 30 genera derived from the three main Qingke-producing areas (p < 0.05). Fertilization conditions markedly influenced the height of a Qingke plant, the number of spikes in a Qingke plant, the number of kernels in a spike, and the fresh weight of a Qingke plant. Considering the yield, the most effective fertilization conditions for Qingke is combining application 50% chemical fertilizer and 50% organic manure.ConclusionThe results of the present study can provide theoretical basis for practice of reducing the use of chemical fertilizer in agriculture