Speech Endpoint Detection in Noisy Environments Using EMD and Teager Energy Operator

Accurate endpoint detection is a necessary capability for speech recognition. A new energy measure method based on the empirical mode decomposition （EMD） algorithm and Teager energy operator （TEO） is proposed to locate endpoint intervals of a speech signal embedded in noise. With the EMD, the noise signals can be decomposed into different numbers of sub-signals called intrinsic mode functions （IMFs）, which is a zero-mean AM-FM component. Then TEO can be used to extract the desired feature of the modulation energy for IMF components. In order to show the effectiveness of the proposed method, examples are presented to show that the new measure is more effective than traditional measures. The present experimental results show that the measure can be used to improve the performance of endpoint detection algorithms and the accuracy of this algorithm is quite satisfactory and acceptable.

HYBRID WAVELET PACKET-TEAGER ENERGY OPERATOR ANALYSIS AND ITS APPLICATION FOR GEARBOX FAULT DIAGNOSIS

Based on wavelet packet decomposition （WPD） algorithm and Teager energy operator （TEO）, a novel gearbox fault detection and diagnosis method is proposed. Its process is expatiated after the principles of WPD and TEO modulation are introduced respectively. The preprocessed sigaaal is interpolated with the cubic spline function, then expanded over the selected basis wavelets. Grouping its wavelet packet components of the signal based on the minimum entropy criterion, the interpolated signal can be decomposed into its dominant components with nearly distinct fault frequency contents. To extract the demodulation information of each dominant component, TEO is used. The performance of the proposed method is assessed by means of several tests on vibration signals collected from the gearbox mounted on a heavy truck. It is proved that hybrid WPD-TEO method is effective and robust for detecting and diagnosing localized gearbox faults.

NEW DEMODULATION TECHNOLOGY OF OPTIMIZING ENERGY OPERATOR AND APPLICATION TO GEAR FAULT DIAGNOSIS

Although many methods have been applied to diagnose the gear thult currently, the sensitivity of them is not very good. In order to make the diagnosis methods have more excellent integrated ability in such aspects as precision, sensitivity, reliability and compact algorithm, and so on, and enlightened by the energy operator separation algorithm （EOSA）, a new demodulation method which is optimizing energy operator separation algorithm （OEOSA） is presented. In the algorithm, the non-linear differential operator is utilized to its differential equation： Choosing the unit impulse response length of filter and fixing the weighting coefficient for inportant points. The method has been applied in diagnosing tooth broden and fatiguing crack of gear faults successfully. It provides demodulation analysis of machine signal with a new approach.

A dynamic phasor estimation algorithm based on angle-shifted energy operator

Under dynamic conditions, the signals of power system have time-varying magnitude and frequency, which might lead to considerable errors for synchrophasor measurement. The traditional discrete Fourier transform (DFT) based algorithms used in Phasor Measurement Unit (PMU) are hard to meet the requirements of measurement accuracy because of the existence of spectral leakage. A dynamic phasor measurement algorithm is proposed in this paper in which the input sampled data are considered as non-stationary signals with amplitude modulation-frequency modulation (AM-FM) form, and the measurement is achieved by AM-FM demodulation. An angle-shifted energy operator (ASEO) is used to extract the instantaneous amplitude and low pass differential filter is introduced for frequency estimation. Simulation results indicate that the proposed algorithm can effectively improve the phasor measurement accuracy and has very short response time for PMU under dynamic conditions.

Time and Energy Operators in Quantum Mechanics

Starting from a time operator, the form of the so called energy operator that is conjugate to the time operator is derived in time representation by analyzing the properties of time translation. This analysis also establishes the commutator between the time and the energy operators. It is seen from the analysis that the energy operator has nothing to do conceptually with the Hamiltonian operator of a system, so that the time operator is not conjugate to the Hamiltonian. Furthermore, it is shown that the Hermiticity of the energy operator requires introducing time integrate inner product. The time energy commutator and the time integral inner product put the time energy uncertainty relation on the same footing as the position momentum uncertainty relation.

Market Operation of Energy Storage System in Smart Grid:A Review

As a flexible resource,energy storage plays an increasingly significant role in stabilizing and supporting the power system,while providing auxiliary services.Still,the current high demand for energy storage contrasts with the fuzzy lack of market-oriented mechanisms for energy storage,the principle of market-oriented operation has not been embodied,and there is no unified and systematic analytical framework for the business model.However,the dispatch management model of energy storage in actual power system operation is not clear.Still,the specific scheduling process and energy storage strategy on the source-load-network side could be more specific,and there needs to be a greater understanding of the collaborative scheduling process of the multilevel scheduling center.On this basis,this paper reviews the energy storage operation model and market-based incentive mechanism,For different functional types and installation locations of energy storage within the power system,the operational models and existing policies for energy storage participation in the market that are adapted to multiple operating states are summarized.From the point of view of the actual scheduling and operation management of energy storage in China,an energy storage regulation and operation management model based on“national,provincial,and local”multilevel coordination is proposed,as well as key technologies in the interactive scenarios of source-load,network and storage.

Energy Storage Operation Modes in Typical Electricity Market and Their Implications for China

As the Chinese government proposes ambitious plans to promote low-carbon transition,energy storage will play a pivotal role in China’s future power system.However,due to the lack of a mature electricity market environment and corresponding mechanisms,current energy storage in China faces problems such as unclear operational models,insufficient cost recovery mechanisms,and a single investment entity,making it difficult to support the rapid development of the energy storage industry.In contrast,European and American countries have already embarked on certain practices in energy storage operation models.Through exploration of key issues such as investment entities,market participation forms,and cost recovery channels in both front and back markets,a wealth of mature experiences has been accumulated.Therefore,this paper first summarizes the existing practices of energy storage operation models in North America,Europe,and Australia’s electricity markets separately from front and back markets,finding that perfect market mechanisms and reasonable subsidy policies are among the main drivers for promoting the rapid development of energy storage markets.Subsequently,combined with the actual development of China’s electricity market,it explores three key issues affecting the construction of costsharing mechanisms for energy storage under market conditions:Market participation forms,investment and operation modes,and cost recovery mechanisms.Finally,in line with the development expectations of China’s future electricitymarket,suggestions are proposed fromfour aspects:Market environment construction,electricity price formation mechanism,cost sharing path,and policy subsidy mechanism,to promote the healthy and rapid development of China’s energy storage industry.

Evaluation of rope shovel operators in surface coal mining using a Multi-Attribute Decision-Making model

Rope shovels are used to dig and load materials in surface mines. One of the main factors that influence the production rate and energy consumption of rope shovels is the performance of the operator. This paper presents a method for evaluating rope shovel operators using the Multi-Attribute Decision-Making （MADM） model. Data used in this research were collected from an operating surface coal mine in the southern United States. The MADM model consists of attributes, their weights of importance, and alter- natives. Shovel operators are considered the alternatives, The energy consumption model was developed with multiple regression analysis, and its variables were included in the MADM model as attributes. Preferences with respect to min/max of the defined attributes were obtained with multi-objective opti- mization. Multi-objective optimization was conducted with the overall goal of minimizing energy con- sumption and maximizing production rate. Weights of importance of the attributes were determined by the Analytical Hierarchy Process （AHP）, The overall evaluation of operators was performed by one of the MADM models, i.e., PROMETHEE If. The research results presented here may be used by mining professionals to held evaluate the performance of rode shovel operators in surface mining.

Effects of Rotor Solidity on the Performance of Impulse Turbine for OWC Wave Energy Converter

Impulse turbine, working as a typical self-rectifying turbine, is recently utilized for the oscillating water column（OWC） wave energy converters, which can rotate in the same direction under the bi-directional air flows. A numerical model established in Fluent is validated by the corresponding experimental results. The flow fields, pressure distribution and dimensionless evaluating coefficients can be calculated and analyzed. Effects of the rotor solidity varying with the change of blade number are investigated and the suitable solidity value is recommended for different flow coefficients.

Evaluating the LCA of a Building with Close Embodied Energy Which Has Different Functions

Annual energy consumption and annual Global Warming Potential （GWP） decreases with the improving of the energy performance of the facade, whereas the embodied energy and embodied GWP increases due to the extra material and products applied. This study analyses the relation between the embodied energy and the energy consumption of a house during the life span of the buildings, and the results represented separately in tables and figures. The study uses Life Cycle Assessment （LCA） framework as a tool to conduct a partial LCA, from cradle to site of the construction and energy consumption during usage phase of the buildings with three different wall types through 50 years usage phase. According to this study, laminated timber and aerated concrete are better choices than cast concrete for both types of buildings because of lower density and lower U value.

A LIFE CYCLE ENERGY COMPARISON OF THREE WORLD EXPO BUILDINGS The Crystal Palace,Shanghai Exhibition Centre,and Dutch Pavilion

Over the last hundred years the booming exhibition industry has promoted development,which in turn has led to environmental damage.The construction of exhibition buildings has been part of this phenomenon.At first sight improvement in energy efficiency techniques would seem to offset the increased energy demand from both exhibitions and exhibition buildings.However,whether energy efficiency technologies truly help to improve building performance to the point where a building is‘environmentally friendly’throughout its whole life-cycle is uncertain.This research is part of investigating whether energy efficiency technologies are really the easiest means to lower costs and energy requirements when the whole useful life of an exhibition building is considered.This article investigates the energy use of three case study buildings based on their operating and embodied energy flows.The results suggest that modern technologies for making exhibition buildings more sustainable may not be as effective as the simpler strategies used over 100 years ago.This suggests a different approach may be needed for sustainable development in the twenty first century.

ENERGY EMBODIED IN,AND TRANSMITTED THROUGH,WALLS OF DIFFERENT TYPES WHEN ACCOUNTING FOR THE DYNAMIC EFFECTS OF THERMAL MASS

Embodied energy is a measure of the energy used in producing,transporting and assembling the materials for a building.Operational energy is the energy used to moderate the indoor environment to make it functional or comfortable-primarily,to heat or cool the building.For many building geometries,the walls make the most significant contribution to the embodied energy of the building,and they are also the path of greatest heat loss or gain through the fabric,as they often have a greater surface area than the roof or floor.Adding insulation reduces the heat flow through the wall,reducing the energy used during operation,but this adds to the embodied energy.The operational energy is not only a function of the wall buildup,but also depends on the climate,occupancy pattern,and heating strategy,making an optimisation for minimum overall energy use non-trivial.This study presents a comparison of typical wall construction types and heating strategies in a temperate maritime climate.The transient energy ratio method is a means to abstract the heat flow through the walls(operational energy for heating),allowing assessment of the influence of walls in isolation(i.e.in a general sense,without being restricted to particular building geometries).Three retrofit scenarios for a solid wall are considered.At very low U-values,overall energy use can increase as the embodied energy can exceed the operational energy;current best practice walls coupled with low building lifetimes mean that this point may be reached in the near future.Substantial uncertainty is present in existing embodied energy data,and given its contribution to total energy use,this is a topic of urgent concern.

Bilevel Optimal Scheduling of Island Integrated Energy System Considering Multifactor Pricing

In this paper,a bilevel optimization model of an integrated energy operator(IEO)–load aggregator(LA)is constructed to address the coordinate optimization challenge of multiple stakeholder island integrated energy system(IIES).The upper level represents the integrated energy operator,and the lower level is the electricity-heatgas load aggregator.Owing to the benefit conflict between the upper and lower levels of the IIES,a dynamic pricing mechanism for coordinating the interests of the upper and lower levels is proposed,combined with factors such as the carbon emissions of the IIES,as well as the lower load interruption power.The price of selling energy can be dynamically adjusted to the lower LA in the mechanism,according to the information on carbon emissions and load interruption power.Mutual benefits and win-win situations are achieved between the upper and lower multistakeholders.Finally,CPLEX is used to iteratively solve the bilevel optimization model.The optimal solution is selected according to the joint optimal discrimination mechanism.Thesimulation results indicate that the sourceload coordinate operation can reduce the upper and lower operation costs.Using the proposed pricingmechanism,the carbon emissions and load interruption power of IEO-LA are reduced by 9.78%and 70.19%,respectively,and the capture power of the carbon capture equipment is improved by 36.24%.The validity of the proposed model and method is verified.

A robust feature extraction approach based on an auditory model for classification of speech and expressiveness

Based on an auditory model, the zero-crossings with maximal Teager energy operator (ZCMT) feature extraction approach was described, and then applied to speech and emotion recognition. Three kinds of experiments were carried out. The first kind consists of isolated word recognition experiments in neutral (non-emotional) speech. The results show that the ZCMT approach effectively improves the recognition accuracy by 3.47% in average compared with the Teager energy operator (TEO). Thus, ZCMT feature can be considered as a noise-robust feature for speech recognition. The second kind consists of mono-lingual emotion recognition experiments by using the Taiyuan University of Technology (TYUT) and the Berlin databases. As the average recognition rate of ZCMT approach is 82.19%, the results indicate that the ZCMT features can characterize speech emotions in an effective way. The third kind consists of cross-lingual experiments with three languages. As the accuracy of ZCMT approach only reduced by 1.45%, the results indicate that the ZCMT features can characterize emotions in a language independent way.

Nonlinear Time-Frequency Distributions of Spectrum Energy Operator in Large Vocabulary Mandarin Speaker Independent Speech Recognition System

This work demonstrates the use of the nonlinear time-frequency distribution (NLTFD) of a discrete time energy operator (DTEO) based on amplitude modulation-frequency modulation demodulation techniques as a feature in speech recognition. The duration distribution based hidden Markov module in a speaker independent large vocabulary mandarin speech recognition system was reconstructed from the feature vectors in the front-end detection stage. The goal was to improve the performance of the existing system by combining new features to the baseline feature vector. This paper also deals with errors associated with using a pre-emphasis filter in the front end processing of the present scheme, which causes an increase in the noise energy at high frequencies above 4 kHz and in some cases degrades the recognition accuracy. The experimental results show that eliminating the pre-emphasis filters from the pre-processing stage and using NLTFD with compensated DTEO combined with Mel frequency cepstrum components give a 21.95% reduction in the relative error rate compared to the conventional technique with 25 candidates used in the test.

A Fault Feature Extraction Model in Synchronous Generator under Stator Inter-Turn Short Circuit Based on ACMD and DEO3S

This paper proposed a new diagnosis model for the stator inter-turn short circuit fault in synchronous generators.Different from the past methods focused on the current or voltage signals to diagnose the electrical fault,the sta-tor vibration signal analysis based on ACMD(adaptive chirp mode decomposition)and DEO3S(demodulation energy operator of symmetrical differencing)was adopted to extract the fault feature.Firstly,FT(Fourier trans-form)is applied to the vibration signal to obtain the instantaneous frequency,and PE(permutation entropy)is calculated to select the proper weighting coefficients.Then,the signal is decomposed by ACMD,with the instan-taneous frequency and weighting coefficient acquired in the former step to obtain the optimal mode.Finally,DEO3S is operated to get the envelope spectrum which is able to strengthen the characteristic frequencies of the stator inter-turn short circuit fault.The study on the simulating signal and the real experiment data indicates the effectiveness of the proposed method for the stator inter-turn short circuit fault in synchronous generators.In addition,the comparison with other methods shows the superiority of the proposed model.

A New Class of Exactly Solvable Models within the Schrodinger Equation with Position Dependent Mass

The study of physical systems endowed with a position-dependent mass (PDM) remains a fundamental issue of quantum mechanics. In this paper we use a new approach, recently developed by us for building the quantum kinetic energy operator (KEO) within the Schrodinger equation, in order to construct a new class of exactly solvable models with a position varying mass, presenting a harmonic-oscillator-like spectrum. To do so we utilize the formalism of supersymmetric quantum mechanics (SUSY QM) along with the shape invariance condition. Recent outcomes of non-Hermitian quantum mechanics are also taken into account.

Automatic spikes detection in seismogram

Data processing for seismic network is very complex and fussy,because a lot of data is recorded in seismicnetwork every day,which make it impossible to process these data all by manual work.Therefore,seismic datashould be processed automatically to produce a initial results about events detection and location.Afterwards,these results are reviewed and modified by analyst.In automatic processing data quality checking is important.There are three main problem data that exist in real seismic records,which include:spike,repeated data and

Novel Automated Paced Fractionation Detection Algorithm for Ablating Ventricular Tachycardia

Catheter ablation therapy has become a key intervention in treatment of ventriculartachycardia (VT). However, current fractionation mapping methods used to isolate the ablation targets in VT patients are done manually, and are therefore time consuming. They also have limited success rates (50% recurrence rate within 2 years). We present a fully automated fractionation detection algorithm for patients with VT which expands on previously defined fractionation features and which substantially decreases associated study times. Paced electrogram signals were collected from six patients during electrophysiologic study according to a modified paced electrogram fractionation analysis protocol. Data were exported and analyzed offline using custom written software. Electrograms from right ventricular pacing catheter were used as reference. Surface electrograms, along with ventricular geometry and relative catheter locations, were used to identify physiological interference and physiologically irrelevant features. A total of 264 electrograms, collected from a roving catheter, were manually and automatically annotated for fractionation as defined by three features: conduction time (CT), electrogram duration (ED), and number of deflections (ND). Of these, 60 were selected manually to have no discernable features and were successfully discarded by our algorithm;yielding a specificity of 100%. Of the remaining 204, 16 were erroneously discarded by our algorithm;yielding a sensitivity of 92.16%. A comparison between annotations showed correlations of 0.98, 0.97, and 0.94 for AL, ED, and ND respectively.

HOW TO AVOID GROUNDHOG DAY...AGAIN!

Albert Einstein is credited with saying, “Insanity: doing the same thing over and over again and expecting different results.” Then in the 1980s, we watched as poor Bill Murray kept waking up to the very same day, very same activities, and same exact results in the comedy “Groundhog Day”. We challenge you to look at the process of design, delivery, and operations for our buildings. Are we all stuck in “insanity” or “Groundhog Day?” We keep doing things the same way and expecting different results. This article explores how the utilization of facility data from design to operations can not only break the paradigm of “insanity,” it can make our facilities more efficient and sustainable to construct and operate. Our basic premise is that if you do not have accurate “data” about your facility it will be very difficult, if not impossible, to operate your facility effectively.