The converging-diverging structure is introduced to extend the lower limit of measurement of vortex flowmeters. As a compact device, the converging-diverging vortex flowmeter is proposed and designed, and its performance is studied experimentally. It is found that, first of all, an up to 51% extension of the lower measurement limit can be realized through the converging-diverging structure, compared with conventional vortex flowmeters; second, the converging-diverging vortex flowmeter with a trapezoidal bluff body has a larger Strouhal number and smaller pressure loss. The results suggest that the converging-diverging vortex flowmeter provides an alternative device especially suitable for the measurement of low-velocity fluids.
It has long been observed that toxic heavy metals at different concentrations can induce root hair development in plants. In oilseed rape we studied ethylene levels and root hair initiation under Cd2+ stress. Growth of the primary root was inhibited but close to root tips the development of subapical root hairs was significantly stimulated by Cd2+ at 30 μM. Versus the control, the distance between the root tip and the root hair zone and the length of the epidermal cell in the elongation zone were significantly reduced by Cd2+ at the same concentration. Exogenous application of Cd2+ and 1-aminocyclopropane-1-carboxylate (ACC) to roots had similar effects on subapical root hair development. Hair density increase and hair elongation in the presence of Cd2+ were reduced by the ethylene inhibitors CoCl2 at 15 μM and aminooxyacetic acid (AOA) at 10 μM. Exposing roots to Cd2+ caused a rapid increase in superoxide radical (O2 ·-) production in the root hair differentiation zone, and at the tips of emerging and newly formed root hairs. Cd2+-induced O2 ·- production at the growing hair tips was blocked in the presence of AOA. Our findings suggest that Cd2+-induced ethylene signaling may act upstream of O2 ·-. Cd2+ promotion of O2 ·- production may operate through an ethylene signaling pathway, and O2 ·- itself may stimulate root hair elongation.
Gas-liquid flows abound in a great variety of industrial processes. Correct recognition of the regimes of a gasliquid flow is one of the most formidable challenges in multiphase flow measurement. Here we put forward a novel approach to the classification of gas-liquid flow patterns. In this method a flow-pattern map is constructed based on the average energy of intrinsic mode function and the volumetric void fraction of gas-liquid mixture. The intrinsic mode function is extracted from the pressure fluctuation across a bluff body using the empirical mode decomposition technique. Experiments adopting air and water as the working fluids are conducted in the bubble, plug, slug, and annular flow patterns at ambient temperature and atmospheric pressure. Verification tests indicate that the identification rate of the flow-pattern map developed exceeds 90%. This approach is appropriate for the gas-liquid flow pattern identification in practical applications.
Noise induced hearing loss (NIHL) is a serious occupational related health problem worldwide. The A-wave impulse noise could cause severe hearing loss, and characteristics of such kind of impulse noise in the joint time-frequency (T-F) domain are critical for evaluation of auditory hazard level. This study focuses on the analysis of A-wave impulse noise in the T-F domain using continual wavelet transforms. Three different wavelets, referring to Morlet, Mexican hat, and Meyer wavelets, were investigated and compared based on theoretical analysis and applications to experimental generated A-wave impulse noise signals. The underlying theory of continuous wavelet transform was given and the temporal and spectral resolutions were theoretically analyzed. The main results showed that the Mexican hat wavelet demonstrated significant advantages over the Morlet and Meyer wavelets for the characterization and analysis of the A-wave impulse noise. The results of this study provide useful information for applying wavelet transform on signal processing of the A-wave impulse noise.
Despite various speech enhancement techniques have been developed for different applications, existing methods are limited in noisy environments with high ambient noise levels. Speech presence probability (SPP) estimation is a speech enhancement technique to reduce speech distortions, especially in low signalto-noise ratios (SNRs) scenario. In this paper, we propose a new two-dimensional (2D) Teager-energyoperators (TEOs) improved SPP estimator for speech enhancement in time-frequency (T-F) domain. Wavelet packet transform (WPT) as a multiband decomposition technique is used to concentrate the energy distribution of speech components. A minimum mean-square error (MMSE) estimator is obtained based on the generalized gamma distribution speech model in WPT domain. In addition, the speech samples corrupted by environment and occupational noises (i.e., machine shop, factory and station) at different input SNRs are used to validate the proposed algorithm. Results suggest that the proposed method achieves a significant enhancement on perceptual quality, compared with four conventional speech enhancement algorithms (i.e., MMSE-84, MMSE-04, Wiener-96, and BTW).
To find effective and practical methods to distinguish gas-liquid two-phase flow patterns, new flow pattern maps are established using the differential pressure through a classical Venturi tube. The differential pressure signal was first decomposed adaptively into a series of intrinsic mode functions (IMFs) by the ensemble empirical mode decomposition. Hilbert marginal spectra of the IMFs showed that the flow patterns are related to the amplitude of the pressure fluctuation. The cross-correlation method was employed to sift the characteristic IMF, and then the energy ratio of the characteristic IMF to the raw signal was proposed to construct flow pattern maps with the volumetric void fraction and with the two-phase Reynolds number, respectively. The identification rates of these two maps are verified to be 91.18% and 92.65%. This approach provides a cost-effective solution to the difficult problem of identifying gas-liquid flow patterns in the industrial field.
Subspace-based methods have been effectively used to estimate enhanced speech from noisy speech samples. In the traditional subspace approaches, a critical step is splitting of two invariant subspaces associated with signal and noise via subspace decomposition, which is often performed by singular-value decomposition or eigenvalue decomposition. However, these decomposition algorithms are highly sensitive to the presence of large corruptions, resulting in a large amount of residual noise within enhanced speech in low signal-to-noise ratio (SNR) situations. In this paper, a joint low-rank and sparse matrix decomposition (JLSMD) based subspace method is proposed for speech enhancement. In the proposed method, we firstly structure the corrupted data as a Toeplitz matrix and estimate its effective rank value for the underlying clean speech matrix. Then the subspace decomposition is performed by means of JLSMD, where the decomposed low-rank part corresponds to enhanced speech and the sparse part corresponds to noise signal, respectively. An extensive set of experiments have been carried out for both of white Gaussian noise and real-world noise. Experimental results show that the proposed method performs better than conventional methods in many types of strong noise conditions, in terms of yielding less residual noise and lower speech distortion.
Conventionally, the filtering technique for attitude estimation is performed using gyros or attitude dynamics models. In order to extend the application range of an attitude filter, this paper proposes a quaternionbased filtering framework for gyroless attitude estimation without an attitude dynamics model. The attitude estimation system is established based on a quaternion kinematic equation and vector observation models. The angular velocity in the system is determined through observation vectors from attitude sensors and the statistical properties of the angular velocity error are analysed. A Kalman filter is applied to estimate the attitude error such that the effect from the angular velocity error is compensated with its statistical properties at each sampling moment. A numerical simulation example is presented to illustrate the performance of the proposed algorithm.
Noise induced hearing loss (NIHL) as one of the major avoidable occupational related health issues has been studied for decades. To assess NIHL, the excitation pattern (EP) has been considered as one of the mechanisms to estimate the movements of the basilar membrane (BM) in the cochlea. In this study, two auditory filters, dual resonance nonlinear (DRNL) filter and rounded-exponential (ROEX) filter are applied to create two EPs, the velocity EP and the loudness EP respectively. Two noise hazard metrics are proposed based on two proposed EPs to evaluate hazardous levels caused by different types of noise. Moreover Gaussian noise and tone signals are simulated to evaluate performances of the proposed EPs and the noise metrics. The results show that both EPs can reflect the responses of the BM to different types of noise. For Gaussian noise there is a frequency shift between the velocity EP and the loudness EP. The results suggest that both EPs can be used for assessment of NIHL.
Reliable estimation of longitudinal force and sideslip angle is essential for vehicle stability and active safety control. This paper presents a novel longitudinal force and sideslip angle estimation method for four-wheel independent-drive electric vehicles in which the cascaded multi-Kalman filters are applied. Also, a modified tire model is proposed to improve the accuracy and reliability of sideslip angle estimation. In the design of longitudinal force observer, considering that the longitudinal force is the unknown input of the electric driving wheel model, an expanded electric driving wheel model is presented and the longitudinal force is obtained by a strong tracking filter. Based on the longitudinal force observer, taking into consideration uncertain interferences of the vehicle dynamic model, a sideslip angle estimation method is designed using the robust Kalman filter and a novel modified tire model is proposed to correct the original tire model using the estimation results of longitudinal tire forces. Simulations and experiments were carried out, and effectiveness of the proposed estimation method was verified.
Lower Carboniferous limestone has been extracted in the “Czatkowice” open-pit hill-slope quarry in southern Poland since 1947, for the needs of metallurgical and building industries, as well as farming. We can distinguish two aquifers in the Czatkowice area: the Quaternary porous aquifer and the Carboniferous fissure-porous one. Two vertical zones representing different hydrodynamic characteristics can be indentified in the Carboniferous formations. One is a weathering zone and the other one the zone of fissures and interbedding planes. Groundwater inflows into the quarry workings have been observed at the lowest mining level (+315 m above the sea level (asl)) for over 30 years. This study concerns two hypotheses of the sources of such inflows originating either from (a) the aeration zone or from (b) the saturation zone. Inflows into the quarry combine into one stream flowing gravitationally to the doline under the pile in the western part of the quarry. This situation does not cause a dewatering need. Extending eastward mining and lowering of the exploitation level lead to increased inflows.
For most precious metal mines, cemented tailings backfill slurry (CTBS) with different cement-sand ratio and solid concentration are transported into the gobs to keep the stability of the stope and mitigate environmental pollution by mine tailing. However, transporting several kinds of CTBS through the same pipeline will increase the risk of pipe plugging. Therefore, the joint impacts of cement-sand ratio and solid concentration on the rheological characteristics of CTBS need a more in-depth study. Based on the experiments of physical and mechanical parameters of fresh slurry, the loss of pumping pressure while transporting CTBS with different cement-sand ratio, flux and solid mass concentration were measured using pumping looping pipe experiments to investigate the joint impacts of cement-sand ratio and solid concentration on the rheological characteristics of CTBS. Meanwhile, the effect of different stopped pumping time on blockage accident was revealed and discussed by the restarting pumping experiments. Furthermore, Fluent software was applied to calculate the pressure loss and velocity distribution in the pipeline to further analysis experimental results. The overall trends of the simulation results were good agreement with the experiment results. Then, the numerical model of the pipeline in the Sanshandao gold mine was conducted to simulate the characteristics of CTBS pipeline transportation. The results show that the pumping pressure of the delivery pump can meet the transportation requirements when there is no blockage accident. This can provide a theoretical method for the parameters optimizing in the pipeline transportation system.
This paper proposes a soft sensing method of least squares support vector machine (LS-SVM) using temperature time series for gas flow measurements. A heater unit has been installed on the external wall of a pipeline to generate heat pulses. Dynamic temperature signals have been collected upstream of the heater unit. The temperature time series are the main secondary variables of soft sensing technique for estimating the flow rate. A LS-SVM model is proposed to construct a non-linear relation between the flow rate and temperature time series. To select its inputs, parameters of the measurement system are divided into three categories: blind, invalid and secondary variables. Then the kernel function parameters are optimized to improve estimation accuracy. The experiments have been conducted both in the single-pulse and multiple-pulse heating modes. The results show that estimations are acceptable.
A large amount of electric vehicles (EVs) charging load will bring significant impact to the power system. An appropriate resource allocation strategy is required for securing the power system safety and satisfying EVs charging demand. This paper proposed a power coordination allocation strategy of EVs’ in distribution systems. The strategy divides the allocation into two stages. The first stage is based on scores assigned to EVs through an entropy method, whereas the second stage allocates energy according to EV’s state of charge. The charging power is delivered in order to maximize EV users’ satisfaction and fairness without violation of grid constraints. Simulation on a typical power-limited residential distribution network proves the effectiveness of the strategy. The analysis re- sults indicate that compared with traditional methods, EVs, which have higher charging requirement and shorter available time will get more energy delivered than others. The root- mean-square-error (RMSE) and standard-deviation (SD) results prove the effectiveness of the methodology for improving the balance of power delivery.