MECHANICAL PULPING.Analysis method of high-consistency chip refiner forces

2012 ◽  
Vol 27 (4) ◽  
pp. 695-701 ◽  
Author(s):  
Antti Fredrikson ◽  
Lauri I. Salminen
Keyword(s):  
Energy Efficient ◽  
Background Noise ◽  
Spatial Information ◽  
New Method ◽  
Force Analysis ◽  
Rotating Machine ◽  
Irregular Data ◽  
High Consistency ◽  
Plate Geometry

Abstract We introduce a new method of processing irregular data rrom any rotating machine, in particular high-consistency pulp refiners. Refiner plate bar forces and rotor absolute angle are acquired synchronously, and a fuzzy gate is exploited to filter instantaneous force events from background noise. Fuzzy gate parameters are partially justified by plate geometry. The method enables the acquisition of quantified and detailed spatial information on refiner plate bar forces, thus supporting the design of more energy efficient refiner plates and bar patterns. The study identifie.s key areas of application for synchronized force analysis in high-consistency pulping research.

Vibration Signal Extraction of Rotating Machines Based on the Analysis of Degree of Cylcostationary

2012 ◽  
Vol 546-547 ◽  
pp. 188-193 ◽  
Author(s):  
Yu Rong Wang ◽  
Tian Xing Wu
Keyword(s):  
Background Noise ◽  
Vibration Signal ◽  
Sampling Frequency ◽  
Hilbert Transformation ◽  
New Method ◽  
Signal Extraction ◽  
Rotating Machines ◽  
End Effect ◽  
Research Results ◽  
Rotating Machine

When early faults occur in rotating machine, the vibration signal being extraction the often contain heavy background noise .In this paper the analysis of degree of cyclostationarity (DCS) was proposed to vibration signal extraction of rotating machine. This method can overcome the shortcoming of Hilbert transformation that will be influenced by many factors, such as end effect, sampling frequency and the added noise in signal. The research results show that the DCS can not only extract vibration signal but also suppress the added noise in the signal. Therefore more accurate fault signal will be extracted and detected through this new method.

scholarly journals An online headphone screening test based on dichotic pitch

2020 ◽  
Author(s):  
Alice E. Milne ◽  
Roberta Bianco ◽  
Katarina C. Poole ◽  
Sijia Zhao ◽  
Andrew J. Oxenham ◽  
...  
Keyword(s):  
False Positive ◽  
Background Noise ◽  
Screening Test ◽  
False Positive Rate ◽  
New Method ◽  
Additional Test ◽  
Positive Rate ◽  
Online Methods ◽  
Perceptual Phenomenon

AbstractOnline experimental platforms can be used as an alternative to, or complement, lab-based research. However, when conducting auditory experiments via online methods, the researcher has limited control over the participants’ listening environment. We offer a new method to probe one aspect of that environment, headphone use. Headphones not only provide better control of sound presentation but can also “shield” the listener from background noise. Here we present a rapid (< 3 min) headphone screening test based on Huggins Pitch (HP), a perceptual phenomenon that can only be detected when stimuli are presented dichotically. We validate this test using a cohort of “Trusted” online participants who completed the test using both headphones and loudspeakers. The same participants were also used to test an existing headphone test (AP test; Woods et al., 2017, Attention Perception Psychophysics). We demonstrate that compared to the AP test, the HP test has a higher selectivity for headphone users, rendering it as a compelling alternative to existing methods. Overall, the new HP test correctly detects 80% of headphone users and has a false-positive rate of 20%. Moreover, we demonstrate that combining the HP test with an additional test–either the AP test or an alternative based on a beat test (BT)–can lower the false-positive rate to ~ 7%. This should be useful in situations where headphone use is particularly critical (e.g., dichotic or spatial manipulations). Code for implementing the new tests is publicly available in JavaScript and through Gorilla (gorilla.sc).

A new method for reverse force analysis of a spatial three-spring system

2001 ◽  
Vol 36 (5) ◽  
pp. 623-632 ◽  
Author(s):  
Limin Fan ◽  
Qizheng Liao ◽  
Chonggao Liang
Keyword(s):  
New Method ◽  
Force Analysis ◽  
Spring System

A New Method for Detecting Altered Text in Document Images

2021 ◽  
pp. 2160010
Author(s):  
Lokesh Nandanwar ◽  
Palaiahnakote Shivakumara ◽  
Umapada Pal ◽  
Tong Lu ◽  
Daniel Lopresti ◽  
...  
Keyword(s):  
Spatial Information ◽  
Feature Vector ◽  
New Method ◽  
Document Images ◽  
Positive And Negative Coefficients ◽  
Digital Format ◽  
Fused Image ◽  
Fusion Operation ◽  
The Relationship ◽  
Text Images

As more and more office documents are captured, stored, and shared in digital format, and as image editing software are becoming increasingly more powerful, there is a growing concern about document authenticity. To prevent illicit activities, this paper presents a new method for detecting altered text in document images. The proposed method explores the relationship between positive and negative coefficients of DCT to extract the effect of distortions caused by tampering by fusing reconstructed images of respective positive and negative coefficients, which results in Positive-Negative DCT coefficients Fusion (PNDF). To take advantage of spatial information, we propose to fuse R, G, and B color channels of input images, which results in RGBF (RGB Fusion). Next, the same fusion operation is used for fusing PNDF and RGBF, which results in a fused image for the original input one. We compute a histogram to extract features from the fused image, which results in a feature vector. The feature vector is then fed to a deep neural network for classifying altered text images. The proposed method is tested on our own dataset and the standard datasets from the ICPR 2018 Fraud Contest, Altered Handwriting (AH), and faked IMEI number images. The results show that the proposed method is effective and the proposed method outperforms the existing methods irrespective of image type.

scholarly journals Multi-TALK: Multi-Microphone Cross-Tower Network for Jointly Suppressing Acoustic Echo and Background Noise

Sensors ◽  
2020 ◽  
Vol 20 (22) ◽  
pp. 6493
Author(s):  
Song-Kyu Park ◽  
Joon-Hyuk Chang
Keyword(s):  
Background Noise ◽  
Spatial Information ◽  
Attention Mechanism ◽  
Convolution Operation ◽  
Speech Distortion ◽  
Acoustic Echo ◽  
Latent Features ◽  
The Cross

In this paper, we propose a multi-channel cross-tower with attention mechanisms in latent domain network (Multi-TALK) that suppresses both the acoustic echo and background noise. The proposed approach consists of the cross-tower network, a parallel encoder with an auxiliary encoder, and a decoder. For the multi-channel processing, a parallel encoder is used to extract latent features of each microphone, and the latent features including the spatial information are compressed by a 1D convolution operation. In addition, the latent features of the far-end are extracted by the auxiliary encoder, and they are effectively provided to the cross-tower network by using the attention mechanism. The cross tower network iteratively estimates the latent features of acoustic echo and background noise in each tower. To improve the performance at each iteration, the outputs of each tower are transmitted as the input for the next iteration of the neighboring tower. Before passing through the decoder, to estimate the near-end speech, attention mechanisms are further applied to remove the estimated acoustic echo and background noise from the compressed mixture to prevent speech distortion by over-suppression. Compared to the conventional algorithms, the proposed algorithm effectively suppresses the acoustic echo and background noise and significantly lowers the speech distortion.

scholarly journals An online headphone screening test based on dichotic pitch

2020 ◽  
Author(s):  
Alice E. Milne ◽  
Roberta Bianco ◽  
Katarina C. Poole ◽  
Sijia Zhao ◽  
Andrew J. Oxenham ◽  
...  
Keyword(s):  
False Positive ◽  
Background Noise ◽  
Screening Test ◽  
False Positive Rate ◽  
New Method ◽  
Additional Test ◽  
Positive Rate ◽  
Online Methods ◽  
Perceptual Phenomenon

AbstractOnline experimental platforms can be used as an alternative, or complement, to lab-based research. However, when conducting auditory experiments via online methods, the researcher has limited control over the participants’ listening environment. We offer a new method to probe one aspect of that environment, headphone use. Headphones not only provide better control of sound presentation but can also “shield” the listener from background noise. Here we present a rapid (< 3 minute) headphone screening test based on Huggins Pitch (HP), a perceptual phenomenon that can only be detected when stimuli are presented dichotically. We validate this test using a cohort of “Trusted” online participants who completed the test using both headphones and loudspeakers. The same participants were also used to test an existing headphone test (AP test; Woods et al., 2017, Attention Perception Psychophysics). We demonstrate that compared to the AP test, the HP test has a higher selectivity for headphone users, rendering it as a compelling alternative to existing methods. Overall, the new HP test correctly detects 80% of headphone users and has a false positive rate of 20%. Moreover, we demonstrate that combining the HP test with an additional test - either the AP test or an alternative based on a beat test (BT) - can lower the false positive rate to ∼7%. This should be useful in situations where headphone use is particularly critical (e.g. dichotic or spatial manipulations). Code for implementing the new tests is publicly available in JavaScript and through Gorilla (gorilla.sc).

scholarly journals Fault Diagnosis for Rotating Machinery Using Multiscale Permutation Entropy and Convolutional Neural Networks

Entropy ◽  
2020 ◽  
Vol 22 (8) ◽  
pp. 851 ◽  
Author(s):  
Hongmei Li ◽  
Jinying Huang ◽  
Xiwang Yang ◽  
Jia Luo ◽  
Lidong Zhang ◽  
...  
Keyword(s):  
Neural Networks ◽  
Fault Diagnosis ◽  
Convolutional Neural Networks ◽  
Spatial Information ◽  
Single Channel ◽  
Rolling Bearing ◽  
Permutation Entropy ◽  
Planetary Gearbox ◽  
Rotating Machine ◽  
Fusion Methods

In view of the limitations of existing rotating machine fault diagnosis methods in single-scale signal analysis, a fault diagnosis method based on multi-scale permutation entropy (MPE) and multi-channel fusion convolutional neural networks (MCFCNN) is proposed. First, MPE quantitatively analyzes the vibration signals of rotating machine at different scales, and obtains permutation entropy (PE) to construct feature vector sets. Then, considering the structure and spatial information between different sensor measurement points, MCFCNN constructs multiple channels in the input layer according to the number of sensors, and each channel corresponds to the MPE feature sets of different monitored points. MCFCNN uses convolutional kernels to learn the features of each channel in an unsupervised way, and fuses the features of each channel into a new feature map. At last, multi-layer perceptron is applied to fuse multi-channel features and identify faults. Through the health monitoring experiment of planetary gearbox and rolling bearing, and compared with single channel convolutional neural networks (CNN) and existing CNN based fusion methods, the proposed method based on MPE and MCFCNN model can diagnose faults with high accuracy, stability, and speed.

scholarly journals ‘effort’ (Energy Efficiency on-site) – A New Method for Planning and Realization of Energy-efficient Neighbourhoods Under the Aspects of Sustainability

2015 ◽  
Vol 118 ◽  
pp. 1288-1295 ◽  
Author(s):  
Kersten Roselt ◽  
Ingo Quaas ◽  
Dieter Genske ◽  
Ulf Klawonn ◽  
Linda Männel ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Energy Efficient ◽  
New Method

Demodulating Method of Frequency Predictable Digital FM Signal

2014 ◽  
Vol 644-650 ◽  
pp. 4595-4598
Author(s):  
Gang Fu ◽  
Jian Hua Lin ◽  
Qian He
Keyword(s):  
Background Noise ◽  
Noise Immunity ◽  
Estimation Method ◽  
New Method ◽  
Signal Estimation ◽  
Signal Phase ◽  
Frequency Signal ◽  
Phase Fluctuations ◽  
Coherent Demodulation ◽  
Demodulation Method

This paper presents a new method for strong background noise of known frequency signal estimation method is then applied to the demodulated digital FM signal. This new method only needs to know the frequency of the demodulated carrier signal phase information without the need to complete the digital FM demodulation signal. Computer simulations show that the method has more than non-coherent demodulation noise immunity, and has a very strong ability of anti-phase fluctuations. Thus, the demodulation method has good prospects for engineering applications.

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