Multi-mode Method Research Articles

Implementation of lumped element multimode modeling for balanced-armature receivers

Lumped element (LE) modeling is one of the simplest and fastest tools for designing and predicting the performance of miniature speakers. Tweeters are being incorporated more frequently to extend the high-frequency range of earphones in the commercial earphone market with balanced armature (BA) receivers being commonly used as tweeters. To support this trend, it is necessary to develop LE models of BAs that are accurate at high frequencies. Developing accurate models has been challenging due to several mechanical and acoustic modes interacting at frequencies over 10 kHz. Based on the work of Sun and Hu [“Lumped element multimode modeling of balanced-armature receiver using modal analysis,” J. Vib. Acoust. 2016 Dec 1;138(6)], a multimode LE modeling method using finite element (FE) modal analysis is implemented and compared with older LE models. The simulation results are compared with experimental data for several production models of BA. The multimode LE method shows significant improvements compared to the old single-mode LE models in predicting BA receiver acoustic response, especially at frequencies above 10 kHz.

Research on High Reliable Multimode Wireless Communication Technology for UAV

High definition image transmission and remote control are typical applications of UAVs, which has spawned a large number of new scenes. This paper proposes a multimode wireless communication method and image transmission strategy for UAV based on the integration of public network and private network. By building at least two wireless communication links including public network and private network, the image data is encoded after obtaining its channel parameters, and the encoded image data is sent through the two links. The experimental results show that the proposed method improves the reliability and efficiency of data transmission.

Multi-mode Control Method Developed for Aircraft System Management

This paper studies the analysis of aircraft system which has the development for multi-mode architecture, as well as the application of multi-mode control, multi-mode monitoring and multi-mode fast parallel management. Through the research and analysis of multi-mode architecture, multi-mode control algorithm, multi-mode health monitoring algorithm and multi-mode rapid parallel test. GigaDevice’s MCU (GD32F450) is used using an MCU, and the FPGA is two Chip Anlu’s AL3A10BGA256, FLASH uses GigaDevice’s GD25Q64CSIG to simulate the aircraft development system. The effectiveness of a multi-mode control management method developed for aircraft was developed. This method changes the single-mode management and disposal scheme of traditional aircraft, and adopts the mode control management of real-time detection. It effectively saves system resource consumption and expenditure in aircraft development.

Multimodal emotion recognition based on fusion with residual connection

To improve the accuracy of emotional identification, a multi-mode fusion emotional recognition method of two-way long and short-term memory network (Bi-LSTM), Multi-Head Attention and Residual Connection blended emotional identification methods. This method performs long-term memory through LSTM, then uses the Attention mechanism to screen out important information, and finally improves the ability of network information transmission through the residual connection. Through this method of concentrated verification, the accuracy rate of emotional classification reaches 61.7%. The experimental results show that compared with models such as CNN, CMN, BC-LSTM, the accuracy and F1 value of the proposed model are effectively improved.

Optimal Multi-Mode Flexibility Operation of CHP Units with Electrode Type Electric Boilers: A Case Study

With the in-depth development of flexibility retrofit in combined heat and power (CHP) units, the unit commitment mode of energy supply equipment in CHP plants is more flexible. This paper presents a multi-mode flexible operation method for CHP plants with electrode electric boilers. Firstly, a simulation model of the operation characteristics of each unit in different operation modes is established, and the corresponding features of electrical and thermal outputs are obtained. Subsequently, a decision-making model of the unit commitment mode of energy supply equipment is set up, and the selection rules of the unit commitment mode of the unit under low heat load, medium heat load, and high heat load are achieved. Finally, under different unit operation combinations, a plant-level optimum load dispatch model is obtained, and the actual operating data of the CHP plant is used for optimization and comparison analysis. The results show that compared to the unit commitment mode of high back pressure and low-pressure cylinder cutting-off (HBP + LPCC), the unit commitment mode of high back pressure and extraction heating (HBP + EH) has more room for energy-saving optimization. Under the premise of safe and reliable operation, the high back pressure (HBP) unit can be loaded as much as possible. While in the combined operating of HBP + EH, the energy-saving space for optimized load dispatching is not large, so a fixed proportion of the electrical load may be considered; under the auxiliary service subsidy policy, the input power of the electric boiler can be appropriately increased; the greater the heat load of the whole plant, the more pronounced the energy-saving effect of optimum load dispatch.

Multi-Mode Huff-Based 2SFCA: Examining Geographical Accessibility to Food Outlets in Austin, Texas

The retail food environment draws much attention from scholars because it can shape individuals’ eating behaviors and health outcomes. Although much progress has been made, current retail food environment assessments mainly use simple food accessibility measures while overlooking the role of multiple transportation modes. This research proposed a multiple-mode Huff-based Two-step Floating Catchment Area (2SFCA) method to measure geographical access to food outlets in Austin, Texas. The spatial accessibility score was calculated with low to high impedance coefficients. Our analyses revealed an urban core-and-peripheral disparity in spatial accessibility to food outlets. We also compared the proposed multiple-mode Huff-based 2SFCA with its single-mode counterpart using t-test and relative difference methods. The comparison illustrates that the difference between the two methods of calculating healthy and unhealthy food accessibility is significant when the impedance coefficient is set to be 1.4 and 1.5, respectively. Our proposed multi-mode Huff-based 2SFCA method accounts for the various transport means and the spatial heterogeneity in population demand for food services; this could support developing intervention strategies to target under-served healthy food areas and over-served unhealthy food areas.

Tri-zone flame spatial structure imaging combined with endogenic polarized scattering.

We propose a multi-mode optical imaging method to retrieve the 2D and 3D spatial structures of the preheating, reaction, and recombination zones of an axisymmetric steady flame. In the proposed method, an infrared camera, a visible light monochromatic camera, and a polarization camera are triggered synchronously to capture 2D flame images, and their corresponding 3D images are reconstructed by combining different projection position images. The results of the experiments conducted indicate that the infrared and visible light images represent the flame preheating and flame reaction zones, respectively. The polarized image can be obtained by computing the degree of linear polarization (DOLP) of raw images captured by the polarization camera. We discover that the highlighted regions in the DOLP images lie outside the infrared and visible light zones; they are insensitive to the flame reaction and have different spatial structures for different fuels. We deduce that the combustion product particles cause endogenic polarized scattering, and that the DOLP images represent the flame recombination zone. This study focuses on the combustion mechanisms, such as the formation of combustion products and quantitative flame composition and structure.

A Monitoring Method Based on FDALM and Its Application in the Sintering Process of Ternary Cathode Material.

In industrial processes, the composition of raw material and the production environment are complex and changeable, which makes the production process have multiple steady states. In this situation, it is difficult for the traditional single-mode monitoring methods to accurately detect the process abnormalities. To this end, a multimode monitoring method based on the factor dynamic autoregressive hidden variable model (FDALM) for industrial processes is proposed in this paper. First, an improved affine propagation clustering algorithm to learn the model modal factors is adopted, and the FDALM is constructed by combining multiple high-order hidden state Markov chains through the factor modeling technology. Secondly, a fusion algorithm based on Bayesian filtering, smoothing, and expectation-maximization is adopted to identify model parameters. The Lagrange multiplier formula is additionally constructed to update the factor coefficients by using the factor constraints in the solving. Moreover, the online Bayesian inference is adopted to fuse the information of different factor modes and obtain the fault posterior probability, which can improve the overall monitoring effect of the model. Finally, the proposed method is applied in the sintering process of ternary cathode material. The results show that the fault detection rate and false alarm rate of this method are improved obviously compared with the traditional methods.

An Improved Multi-Mode Two-Step Floating Catchment Area Method for Measuring Accessibility of Urban Park in Tianjin, China

Parks, as a major infrastructure that provide public service for urban residents, play a vital role in promoting urban livability and public health. Under the framework of spatial equity, more sophisticated accessibility methods were used on measuring urban park accessibility such as multi-mode 2SFCA. However, the accessibility of residential areas near parks was seriously underestimated by using the multi-mode 2SFCA method. Thus, this study aimed to propose an improved multi-mode 2SFCA method to measure urban park accessibility with a more appropriate approach, by taking residential areas of Tianjin central city as the spatial unit. The results indicate that all residential areas can obtain urban park accessibility, but the spatial distribution of urban park accessibility is heterogeneous. The numerical value of urban park accessibility decreases as the travel time from residential areas to urban parks increases; it is shown that the proposed method can provide a more realistic evaluation compared to the traditional multi-mode 2SFCA method. This study provides a comprehensive and realistic insight into acquainting with urban park accessibility and helps urban planners formulate effective policies and strategies to ease spatial imbalance.

Numerical study of the thermocapillary instability in a thin liquid–air film

It is well known that thermal field would cause instability on a two-fluid interface due to the Marangoni effect. This phenomenon is also referred to as thermocapillary flow. A thin liquid/air film experiences thermocapillary instability when it is confined between hot and cold plates. The periodic micro/nano-patterns can generally be observed in the film. Therefore, the thermocapillary instability can be used to fabricate micro/nano-polymeric structures. The present paper proposes a fully nonlinear numerical model based on the phase field method to study the dynamic process of thermocapillary instability. Interfacial evolution and nonlinear effects of the thin liquid film are especially investigated. The impact of the key parameters, e.g., the Marangoni and Reynolds numbers, on the stability are also explored. In addition to the single-mode analysis, the thermocapillary instability is also studied in the multi-mode condition. The conventional single-mode approach facilitates the stability analysis of different wavelengths, while the multi-mode method describes the experiments in a more practical way.

FlexPDR: Fully Flexible Pedestrian Dead Reckoning Using Online Multimode Recognition and Time-Series Decomposition

Smartphone-based pedestrian dead reckoning (PDR) has been widely used indoors for continuous localization. However, the specific tracking solutions under different modes are vulnerable to mode transition and thus degrading performance. The robustness of pedestrian navigation may be weakened due to the mix of smartphone motions and walking patterns. Due to this challenge, most existing PDR methods assume that the smartphone is carried in a certain pose, such as handheld horizontally, swinging, calling, and pocketed, ignoring the short period but negative transition impact on tracking, which limits its flexibility when applying in the Internet of Things (IoT) services. To achieve a fully flexible PDR (i.e., FlexPDR), this article enhances the robustness and smoothness of pedestrian tracking during the transition between several phone poses and regular motion modes for the first time. We propose a Bayesian-based real-time multimode recognition method that does not require any posterior information, together with a time-series decomposition approach for adaptively tracking scheme-switching. The proposed FlexPDR system achieved a real-time smartphone indoor positioning with a high position accuracy of 98.11% on the specific situation that mixed mode-switching happens, which outperformed other state-of-the-art methods.

Flutter control of truss-type suspension bridges with a tuned mass damper based on the mass polar moment of inertia's optimum configuration

In suspension bridges, flutter is the primary source of instability, commonly controlled by a tuned mass damper (TMD). In torsional motions, such as flutter, the shape of the mass block, indicating its distribution around the torsion axis, is critical; indeed, an optimal distribution results in a more effective and lighter device. The flutter analysis of the Vincent Thomas suspension bridge was performed using the multi-mode method in this article. Then, a new optimal configuration was used to avoid it; in addition to common parameters such as mass ratio, damping ratio, and frequency ratio, a set of parameters called shape variables was also considered. These parameters take into account the manner in which mass is distributed around the torsion axis. The performance of the aforementioned configuration was compared to that of the other recommended TMD configurations. Additionally, a general formulation of TMD was represented, which included the other configurations. Finally, the effectiveness of TMD was evaluated in comparison to other control systems. The results indicated that the optimal configuration was reliable and that it reduced the mass ratio by up to 0.2 percent by optimizing its distribution around the torsion axis compared to other existing configurations.

How to Train Intelligent Reflecting Surfaces?

This letter discusses the rationale of Intelligent Reflecting Surface (IRS) based transmission, state-of-the-art methods available for IRS training, and their challenges. Though IRS is known for its ability to constructively combine several multipath components by using their phase information, extracting the phase information for a large number of IRS elements requires extensive training overhead. This work proposes a multi-mode grouping method for low overhead IRS training and moderate combining benefit. Moreover, the letter includes directions to adaptively utilize user’s mobility and(or) quality of service requirement for the appropriate mode selection.

Multimode photon blockade

Interactions are essential for the creation of correlated quantum many-body states. Although two-body interactions underlie most natural phenomena, three- and four-body interactions are important for the physics of nuclei1, exotic few-body states in ultracold quantum gases2, the fractional quantum Hall effect3, quantum error correction4 and holography5,6. Recently, a number of artificial quantum systems have emerged as simulators for many-body physics, featuring the ability to engineer strong interactions. However, the interactions in these systems have largely been limited to the two-body paradigm and require building up multibody interactions by combining two-body forces. Here we implement a scheme to create a higher-order interaction between photons stored in multiple electromagnetic modes of a microwave cavity. The system is dressed such that there is collectively no interaction until a target total photon number is reached across multiple distinct modes, at which point the photons interact strongly. In our demonstration, we create interactions involving up to three bodies and across up to five modes. We harness the interaction to prepare single-mode Fock states and multimode W states, which we verify by introducing a multimode Wigner tomography method. A method to engineer higher-order interactions between photons provides a route to create non-classical and entangled states across multiple modes.

Hybrid geometrical full waveform inversion for ultrasonic defect characterisation

A hybrid geometrical full waveform inversion (GFWI) method is presented in this article for accurate ultrasonic defect characterisation using a phased array. The proposed method combines two steps: (1) A newly developed multi-mode topological energy method (TEM) is used to provide a high-resolution image for defect classification and a good initial defect model for the second step. (2) A GFWI procedure is executed to reconstruct the defect shape through iteratively reducing the mismatch in waveforms between the measurements and synthetic data from the defect model. The GFWI procedure enables direct inversion of the defect shape by deforming the elements attached at its boundaries from finite element formulation, controlled by the preconditioned boundary gradient. To suppress the cross-talk among different geometrical parameters with distinct units, the BFGS and the subspace methods are implemented together with GFWI, which enables reconstructing defects of various shapes by taking all the wave physics into the inversion automatically. Numerical examples are shown with a volumetric defect, a straight crack, a curved crack and a surface-breaking notch, giving accuracy of defect sizing within fractions of a wavelength. Two experiments using an ultrasonic phased array system further demonstrate the feasibility of this method.

Defect Detection and Classification Algorithm of Metal Nanomaterials Based on Deep Learning

With the rapid development of nanotechnology, researchers can prepare nanomaterials by various methods. The rapid development of nanotechnology has greatly promoted the wide application of nano materials in the field of detection and catalysis. Especially the metal nanomolecules have good biocompatibility, absorption of plasma surface resonance, enhanced Raman surface and other properties. Metal nanomolecules have good biocompatibility, absorption of plasma surface resonance and enhanced Raman surface Rice inspection and catalytic application have attracted wide attention. This paper mainly studies the defect detection and classification algorithm of metal nanomaterials based on deep learning. Through the experimental phenomena, we can understand and master the defect detection methods of metal nanomaterials, and review the problems and future development direction of the preparation of metal nanomaterials. Deep learning algorithm the first mock exam deep learning network model, metal defect multi-mode detection method and the classification of metal surface defects are investigated. The defect detection of metal nano materials based on deep learning is realized. The whole defect and the quantitative detection of metal defects are realized. The detection range of traditional single mode nondestructive testing technology is overcome. The deficiency of accurate quantitative detection is difficult. The results show that there are five characteristic parameters for metal nano surface defect detection. In the deep learning based defect detection and classification algorithm, the big data technology is used to analyze the complete defect data, environmental data and working intensity data to complete the prediction of the future development trend of defects, which can play an important role in the maintenance of materials It is also of great significance to the development of metal nano detection technology.

Prediction of pose-dependent modal properties and stability limits in robotic ball-end milling

• A random-forest-based multimode prediction method is first proposed to obtain the pose dependent modal properties. • A tool tip point FRF calculation method for arbitrary tool orientations is presented. • A multiple DOF dynamic equation considering cross FRFs is established on basis of the predicted parameters and then solved for predicting stability limits in the whole workspace. • The stability lobe diagrams are in good agreement with the experimental results. Industrial robots are promising to be used in the light-load machining, especially of non-metallic materials. Nevertheless, chatter is also prone to occur in such operating conditions due to the low stiffness of robot, which deteriorates the surface finish and machining efficiency. It is essential to study the dynamics of robotic ball-end milling process for predicting and suppressing chatter. In this paper, an effective stability prediction model considering variable modal properties is constructed for milling non-metallic curved parts by an industrial robot with high-speed spindle. To obtain the pose-dependent modal parameters of the robot, a random forest based multimode prediction method is proposed, which performs well for stability limit prediction. Not only the diagonal terms but also the cross terms of the modal matrix are predicted. Subsequently, a transformation matrix is constructed to transfer the frequency response functions (FRFs) that fitted by above predicted parameters into the direction of the instantaneous tool orientation. Combined with the pose-independent tool mode linearly, the integrated modal matrix of the tool tip is obtained. Finally, a multiple degree of freedom dynamic equation simultaneously considering the robot mode and tool mode is established and then solved by an extended second-order semi-discretization method (2nd SDM) for stability prediction. Indeed, the effects of robot pose, cross coupling and tool orientation on stability are deeply analyzed, which provide a meaningful guidance for robotic milling operations. The effectiveness of the proposed method is validated by a series of cutting experiments on an industrial robot.

Nonsynchronous Rotor Blade Vibrations in Last Stage of 380 MW LP Steam Turbine at Various Condenser Pressures

This paper presents an analysis of nonsynchronous rotor blade vibrations in the last stage of an LP steam turbine at various condenser pressures. The nonlinear least squares Levenberg–Marquardt method is used in a tip-timing analysis to determine nonsynchronous multimode rotor blade vibrations, which is a novelty. This is done with two sensors in the casing and a once-per-revolution sensor. The accuracy of the nonlinear least squares Levenberg–Marquardt multimode method is compared with the one-mode linear method. The algorithm is verified by comparing it with one-mode tip-timing methods for synchronous and nonsynchronous vibrations. The analysis shows that the rotor blades vibrate simultaneously with two modes in non-nominal conditions, which is also a novelty. The rotor frequencies are unchanged, although the blade vibration amplitudes vary, depending on the pressure in the condenser. Flutter does not appear in the last stage for the various condenser pressures and powers that were tested.

Bacitracin-Functionalized Dextran-MoSe2 with Peroxidase-like and Near-Infrared Photothermal Activities for Low-Temperature and Synergetic Antibacterial Applications.

Bacitracin (an antimicrobial peptide, AMP)-modified dextran-MoSe2 nanosheets (AMP/dex-MoSe2 NSs) were constructed and applied for low-temperature and synergetic antibacterial applications. The near-infrared (NIR) photothermal and peroxidase-like activities of dex-MoSe2 were combined with the bacterial membrane-binding ability of AMP through electrostatic adsorption, and a multimode antibacterial method was realized. H2O2 was converted into a hydroxyl radical (·OH) by AMP/dex-MoSe2, which exhibits a higher antibacterial activity and can avoid the toxicity of a high concentration of H2O2. Importantly, the production of ·OH and the antibacterial efficiency of AMP/dex-MoSe2 were accelerated by low-temperature heat sterilization with NIR irradiation. Owing to the AMP-guided binding and destruction effect to the bacterial membrane, AMP/dex-MoSe2 shows a better antibacterial effect on Gram-negative Escherichia coli under NIR irradiation as compared to catalytic treatment or NIR photothermal sterilization alone. Furthermore, the cytotoxicity and hemolysis of AMP/dex-MoSe2 were weak and in a relatively safe range. This multimode antibacterial strategy based on the AMP/dex-MoSe2 nanozyme will pave a way for the development of more safe and efficient antibacterial applications.

A Multi-mode Power Management Method for Aircraft Convolution

In order to realize the management of the aircraft, it is suitable for the long-term management operation of the aircraft. In this paper, a multi-mode management method for aircraft based on convolution prediction is proposed. Firstly, the historical consumption data of the system over time is collected, and its idle time is sorted into time-dependent historical input data. Secondly, the consumption prediction model based on convolution is established. The historical idle time series of the systemt is input, and the system is output to predict the idle time series. Finally, according to the difference between idle time and mode switching balance time, the corresponding management multi-mode switching is performed.