Multiple Operation Modes Research Articles

A Multimode Anomaly Detection Method Based on OC-ELM for Aircraft Engine System

The practical industrial processes possess the characteristics of multimode, unbalanced data distribution, and complex types of abnormalities, which are challenging to the anomaly detection task of complex industrial systems. In this paper, a novel anomaly detection framework based on one-class extreme learning machine (OC-ELM) for the multimode system is presented. To tackle the multiple operation modes, a clustering algorithm is first applied to distinguish the operation modes of the system. The corresponding detection models are built under different operation modes resulting in the multiple models operated in parallel. In addition, the proposed method constructs the reasonable boundary of the complex data distribution, reflecting the equipment running in the healthy or the normal state. The anomaly detection index is obtained according to the deviation degree between the testing sample and the normal model. As a result, a global monitoring index reflecting the degradation state is obtained by combining the anomaly monitoring indices of the equipment under multiple operation modes. The proposed method is verified on a public dataset of aircraft engines, and the advantages are demonstrated by comparing with the implemented detection model without handling the information of operation modes, and the multiple principal component analysis method.

Investigation of a Haptic Actuator Made with Magneto-Rheological Fluids for Haptic Shoes Applications

This paper presents a magneto-rheological (MR) actuator that can be easily inserted into haptic shoes and can haptically simulate the material properties of the ground. To increase the resistive force of the proposed actuator, we designed a movable piston having multiple operation modes of MR fluids. Further, the design of a solenoid coil was optimized to maximize the resistive force in a limited-sized MR actuator. Simulations were conducted to predict the actuation performance and to show that the magnetic flux flows well by forming a closed loop in the proposed actuator. The quantitative evaluation of the proposed actuator was investigated by measuring the resistive force as a function of the input current and its pressed depth. From the result, we found that the proposed actuator can create over 600 N by adjusting the input current.

Diplexer-Integrated SPDT Switches With Multiple Operating Modes Using Common Fractal Stub-Loaded Resonator

This article presents a method to design new diplexer-integrated single-pole double-throw (SPDT) switches for composite time division duplexing (TDD) and frequency division duplexing (FDD) requirements. The common fractal stub-loaded resonator (F-SLR) is employed to provide four magnetic coupling paths to introduce the mixed electric and magnetic coupling (MEMC) for every channel. Together with the cross-couplings, the ON-state channel with high selectivity bandpass response can be achieved. As examples, a third-order diplexer-integrated SPDT switch and a fourth-order diplexer-integrated SPDT switch operating at 0.9/1.8 GHz are designed and fabricated. These two diplexer-integrated SPDT switches have three major operating modes, i.e., the 0.9-GHz bandpass filter (BPF)-integrated SPDT switch operating mode, the 1.8-GHz BPF-integrated SPDT switch operating mode, and the 0.9-/1.8-GHz diplexer-integrated SPDT switch operating mode. In the design, the loaded positions of p-i-n diodes on the uniform impedance resonators of 0.9-GHz channel are optimized to improve the OFF-state rejection bandwidth. Measured results also show that these two diplexer-integrated SPDT switches have low ON-state passband insertion loss, high port-to-port isolation, and compact circuit size.

Quality oriented multimode processes monitoring based on a novel hierarchical common and specific structure with different order information

Abstract Due to higher demands on product diversity, flexible shift between productions of different products in one equipment becomes a popular solution, resulting in existence of multiple operation modes in a single process. In order to handle such multi-mode process, a novel double-layer structure is proposed and the original data are decomposed into common and specific characteristics according to the relationship between variables among each mode. In addition, both low and high order information are considered in each layer. The common and specific information within each mode can be captured and separated into several subspaces according to the different order information. The performance of the proposed method is further validated through a numerical example and the Tennessee Eastman (TE) benchmark. Compared with previous methods, superiority of the proposed method is validated by the better monitoring results.

Gate‐Controlled Polarity‐Reversible Photodiodes with Ambipolar 2D Semiconductors

AbstractA photosensor with an amplitude‐tunable and polarity‐reversible response under gate modulation has potential as a computational photosensor, which can provide more recognition degree of data to enhance signal processing efficiency. Although, the ambipolar 2D semiconductors possess unique gate‐tunable properties, the question of how to utilize this property to design polarity‐reversible photodiodes for intelligent applications remains unanswered. Here, gate‐controllable polarity‐reversible photodiodes based on ambipolar 2D semiconductors with an asymmetrically metal‐contacted architecture are proposed. By controlling the gate‐field, the local carrier type and density profile can be manipulated in the channel due to the partial shielding feature of the asymmetrically metal‐contacted architecture, resulting in a polarity‐reversible photodiode. The reported WSe2‐based photodiode possesses excellent rectifying behavior with a rectification ratio over 105, photovoltaic performance with 90% external quantum efficiency, and 2.3% power conversion efficiency under gate regulation. Meanwhile, the device exhibits reversible polarity of photovoltage from a negative to positive state under gate control. By utilizing the reversible photovoltage of the WSe2 photodiode, an optoelectronic switch with a photovoltage polarity signal is demonstrated without a bias voltage. This photovoltage‐reversible homodiode paves the way to develop 2D devices with multiple operation modes for potential applications in high‐efficiency photovoltaics, intelligent vision sensors, and logic optoelectronics.

A Novel Multimanifold Joint Projections Model for Multimode Process Monitoring

Complex industrial processes are commonly characterized with multiple operation modes. The existing manifold learning-based process monitoring methods describe each mode individually without capturing the connections among different modes, which may deteriorate the monitoring capability. This article proposes a novel dimensionality reduction model referred as to multimanifold joint projections to monitor the multimode processes, where the intramode and the intermode adjacency matrices are constructed to reflect the underlying features within each mode and among different modes, respectively. The neighboring and nonneighboring structures of data within each mode are captured by the distance and angle information of pairwise points to reveal the intrinsic structure of the original data, thus offering a more faithful representation of multimodal data and further enhancing monitoring performance. During online monitoring, a point to manifold distance criterion is proposed to determine the running-on mode of new samples. Two case studies demonstrated the superior performance of the proposed approach in multimode process monitoring.

Tool-Center-Point Control of a Concrete Pump Using Constrained Quadratic Optimization

Tool-center-point (TCP) control increases the operating comfort of concrete pumps by shifting the control to the task space. The operation is accompanied by various requirements and constraints from the mechanical structure, the hydraulic system, and the operator. They must be taken into account for the efficient and error-free operation of the concrete pump. In this publication, a TCP control algorithm based on constrained quadratic optimization (cQP) is presented, which addresses the requirements and constraints of a mobile concrete pump. The features include boom deformation compensation, multiple operation modes, configuration control, compliant constraints on the joint movement, and hydraulic flow rate constraints. The methods are verified by simulation for a flexible link six degrees of freedom concrete pump. The results include deformation-compensated 2-D/3-D movements of the TCP with different operation modes and configuration control under joint and hydraulic constraints. Note to Practitioners —For effective concrete placement, the tip of the concrete pump needs to move linearly in the task space. Tool-center-point (TCP) control allows the operator to directly specify the tip velocity in the task space instead of separately controlling the axes of the manipulator. In this article, the control task is posed as an inverse kinematic problem, which is solved by quadratic optimization (cQP). The framework of cQP enables the direct inclusion of system constraints while being computational efficient for online implementation on the electronic control unit of the truck. The approach addresses concrete pump specific problems and requirements of the tool center point movement and actuator constraints. Restrictions in the task space are not treated.

EVALUATION OF RELIABILITY OF RADIO-ELECTRONIC DEVICES WITH VARIABLE STRUCTURE

Context. Various radio electronic devices are being continuously developed and refined in order to improve the quality indicators according to the consumers’ requirements for their use in multiple operational modes, each with separate subsets of elements. Given fact is not taken into account when assessing the reliability indicators, which leads to a decrease in their value, and, as a consequence, to an increase in the products cost.Objective. The purpose of the article is to improve the quantification accuracy of reliability values of electronic devices with variable structure by using a new model, which takes into account the operational time of individual subsets of elements of the object in its possible operational modes.Method. The paper analyzes the structures of radio electronic devices and their influence on reliability using methods of set theory, probability theory, discrete search theory and metrology. This allows objective quantification of reliability indicators values depending on the conditions of the product use: operating time for failure, average recovery time and the readiness coefficient.Results. An improved model of reliability of multiple mode objects with variable structure, which takes into account the features of structural design of the product, the features of its intended use (operating time in separate modes), and the influence of the quality of metrological support on the average recovery time has been obtained. This allows increasing the estimation of the real value of the complex indicator of reliability – readiness coefficient, and, as a consequence, reducing the value of the readiness coefficient.Conclusions. The use of the proposed model of quantitative estimation of the reliability indicators’ values of radio electronic devices with variable structure can reduce the cost of products while providing the required values of failure time and the average recovery time by reducing the requirements for the reliability of the base elements. The results obtained should be used in the design of perspective radio electronic devices to justify the choice of element of the minimum cost base while meeting the required requirements for the reliability of the product as a whole. x`x

Model-Based Deterioration Estimation with Cyber Physical System

A key aspect of life cycle management for pursuing sustainability is machine condition prognosis, which requires a condition monitoring system that estimates machine system deterioration to assist engineers in determining which maintenance actions to take. Conventional data-driven methods such as machine learning, have two issues. One is data dependency. The accuracy of a data-driven method depends on the data volume because a data-driven method builds a classification model on the basis of historical data as training data. However, it is difficult to acquire enough data on all deterioration modes, which requires a long time, because deterioration modes are diverse, and some of them rarely happen. The other issue is interpretability. When a condition monitoring system using a data-driven method sends the degree of deterioration (DoD) of the machine system to maintenance engineers, they have difficulty in understanding the results because the method is a black box. The objective of this paper is to address these two issues. We propose a model-based method that simulates machine system deterioration with a cyber physical system (CPS). Model-based methods address these issues in the following manner. First, the methods can simulate the progress of deterioration from an initial condition to failure to estimate the DoD. Second, the methods employ mathematical models that represent machine systems. Engineers create such mathematical models (which we call “physical models”) by referring to various kinds of knowledge like design information and the result of failure mode and effects analysis. A physical model allows us to reason about a machine system to address interpretability. For dealing with machinery that has multiple operation modes, we introduce a state space to clarify the relationship among input, observable state variables, and DoD in a physical model. The CPS estimates DoD by comparing observed data with simulated data in the state space. In our case study, we evaluated our proposed method with a hydraulic pump of a mining machine. First we created a physical model with Modelica, which is a multi-domain modeling language. Then, the method constructed the state space by simulating deterioration with the physical model given all combinations of inputs and DoD. After that, we showed that the estimated DoD tended to increase until the hydraulic pump was replaced, using the observed data from an actual mining machine. As a result, the experimental results revealed that the proposed method succeeded in identifying the DoD with observed data of the hydraulic pump of a mining machine.

Root-cause analysis for time-series anomalies via spatiotemporal graphical modeling in distributed complex systems

Performance monitoring, anomaly detection, and root-cause analysis in complex cyber–physical systems (CPSs) are often highly intractable due to widely diverse operational modes, disparate data types, and complex fault propagation mechanisms. This paper presents a new data-driven framework for root-cause analysis, based on a spatiotemporal graphical modeling approach built on the concept of symbolic dynamics for discovering and representing causal interactions among sub-systems of complex CPSs. We formulate the root-cause analysis problem as a minimization problem via the proposed inference based metric and present two approximate approaches for root-cause analysis, namely the sequential state switching (S3, based on free energy concept of a restricted Boltzmann machine, RBM) and artificial anomaly association (A3, a classification framework using deep neural networks, DNN). Synthetic data from cases with failed pattern(s) and anomalous node(s) are simulated to validate the proposed approaches. Real dataset based on Tennessee Eastman process (TEP) is also used for comparison with other approaches. The results show that: (1) S3 and A3 approaches can obtain high accuracy in root-cause analysis under both pattern-based and node-based fault scenarios, in addition to successfully handling multiple nominal operating modes, (2) the proposed tool-chain is shown to be scalable while maintaining high accuracy, and (3) the proposed framework is robust and adaptive in different fault conditions and performs better in comparison with the state-of-the-art methods.

Multimodal process monitoring based on transition-constrained Gaussian mixture model

Reliable process monitoring is important for ensuring process safety and product quality. A production process is generally characterized by multiple operation modes, and monitoring these multimodal processes is challenging. Most multimodal monitoring methods rely on the assumption that the modes are independent of each other, which may not be appropriate for practical application. This study proposes a transition-constrained Gaussian mixture model method for efficient multimodal process monitoring. This technique can reduce falsely and frequently occurring mode transitions by considering the time series information in the mode identification of historical and online data. This process enables the identified modes to reflect the stability of actual working conditions, improve mode identification accuracy, and enhance monitoring reliability in cases of mode overlap. Case studies on a numerical simulation example and simulation of the penicillin fermentation process are provided to verify the effectiveness of the proposed approach in multimodal process monitoring with mode overlap.

Type synthesis of multi-mode mobile parallel mechanisms based on refined virtual chain approach

Mechanisms with multiple operation and multiple locomotion modes are applied to implementing the different tasks and adapting to the changes in terrains as well. Based on this application, this paper presents a refined virtual chain approach which is applied to the type synthesis of a class of multi-mode mobile parallel mechanisms (PMs). This approach is based on screw theory to synthesize the branches with coaxial rotating components under different constraint conditions. The geometric orientations of the different constraint conditions in a plane can be changed by using coaxial rotating components. Meanwhile, the inactive joints in branches are determined. By means of this approach, a number of symmetrical and asymmetrical reconfigurable PMs with four branches are obtained. The four of the multi-mode PMs are sketched as examples and the operation and locomotion modes for the mechanisms are discussed.

Non-inverting and Non-isolated Magnetically Coupled Buck–Boost Bidirectional DC–DC Converter

A new non-isolated dc–dc converter with non-inverting output and buck–boost operation, named magnetically coupled buck–boost bidirectional (MCB3) converter, is presented in this article. The MCB3 passive components arrangement connects the input and output ports getting an equivalent behavior to that of the dual active bridge (DAB) converter, but in a non-isolated topology. This equivalency allows applying Triple Phase Shift (TPS) modulation to MCB3. TPS is known to minimize conduction losses and to achieve soft switching at any load in the DAB converter. Throughout the article, the features of the DAB converter are used as a reference to show the main features of the proposed converter. Moreover, other modulation strategies based on TPS modulation are used in MCB3 to operate within the minimum losses path. The multiple operation modes found on the MCB3 under TPS modulation are identified, classified, and used to find the operating points that minimize the switching and conduction losses over the power range. The analysis is shown for the boost mode that is the worst case design. MCB3 and DAB topologies are designed and simulated for the same specification to validate the theoretical study. Finally, experimental measurements on 460-W prototypes for both topologies corroborate the equivalent operation and the main features of the MCB3.

Developing of Quaternary Pumped Storage Hydropower for Dynamic Studies

Quaternary pumped storage hydropower (Q-PSH) technology, as one of the new advanced-PSH technology, has been developed by taking advantage of Conventional-PSH (C-PSH) and Adjustable Speed-PSH (AS-PSH). By combining adjustable-speed pump unit and conventional hydropower turbine unit in the quaternary configuration, Q-PSH has the more competitive capability of providing fast power support in the future high renewable penetrated power system. Acting as energy storage (ES), Q-PSH provides promising power supply to deal with the uncertainty and variability from renewable energy generation. This paper focuses on the dynamic modeling of Q-PSH technology employing full-converter machine and the impact of Q-PSH on the frequency response in a system. The detailed model of Q-PSH is developed and implemented in the IEEE 14-bus system based on GE Positive Sequence Load Flow (PSLF) platform, which captures the dynamic of multiple operation modes, especially hydraulic short-circuit (HSC) operation mode. Several cases are set up to reveal the advantages of Q-PSH technology when power electronic based renewable energy generation is deployed in the system. Sensitivity studies of the controller in pump governor show the impact of parameters in pump response performance. The comparison case illustrates the impact of frequency response provided by the Q-PSH in the system.

Flexible cascaded multilevel inverter with multiple operation modes

In this paper, a flexible cascaded multilevel inverter is proposed with a wide operational range. The inverter can change its topology structure to operate in three modes by a bidirectional switch unit. The nine-level or five-level mode of the inverter is adopted to optimize the output waveform when the input power is low. To decrease power losses, the three-level mode of the inverter is adopted to reduce the number of active switch devices when the input power is high. The topology and modulation strategy of the proposed inverter are presented and analyzed. The total losses and current THD of the inverter are calculated. In addition, simulations and experiments are conducted. The obtained simulation and experimental results indicate the correctness and feasibility of the proposed inverter and its modulation strategy.

A cascaded energy management optimization method of multimode power-split hybrid electric vehicles

A novel multimode power-split hybrid electric vehicle demonstrates significant advantages in energy conservation. The complicated structure and multiple operation modes, however, have brought significant challenges to energy management. The problems of operation mode selection, power allocation, and operating point selection need to be solved simultaneously. Traditionally, existing energy management strategies first have determined operation mode and then have solved power allocation and operating points. Moreover, traditional dynamic programming usually has not considered electric energy consumption and has deviated from the optimal solution. To solve these problems, a cascaded energy management strategy that integrates dynamic programming and equivalent consumption minimization strategy (DP + ECMS) is proposed. An iterative method is used to optimize the equivalence factor. A vehicle model based on actual control strategy is established and validated by test results. Then fuel economy simulations are conducted. Results showed that DP + ECMS could achieve 19.9% fuel economy improvement compared with the rule-based strategy for a new European driving cycle. In addition, simulation results of a Worldwide Harmonized Light-Duty Test Cycle demonstrated that DP + ECMS performed well in real road driving conditions. This study introduces a novel multimode power-split hybrid system and provides a global energy management optimization method.

Fast Operation Mode Selection for Highly Efficient IoT Edge Devices

In the emerging paradigm of edge computing (EC) for Internet of Things (IoT), data processing is pushed to the edge of the IoT network (e.g., gateways and embedded IoT devices). IoT devices must support multiple operation modes in order to adapt to varying runtime situations, like preserving energy at low battery, while still maintaining some crucial functionality, etc. Adapting the optimal operation mode is a challenge for edge devices given the limited resources at the edge of the network (both bandwidth and processing power of the shared gateway), various constraints (e.g., battery lifetime), etc. This paper proposes a fast and low-overhead scheme to determine and adapt the operation mode of edge devices at runtime and orchestrate devices in a way that the efficiency of IoT devices is optimized with respect to the gateway’s resource constraints. The proposed scheme breaks the optimization problem into several smaller ones (i.e., subproblems) whose solutions are aggregated to find the final solution. We present a novel memoization technique that determines the solution to a range of subproblems based on subproblems that are already solved. In addition, we present a novel pruning technique that reduces the search space and consequently reduces both memory and execution time overhead. The experimental results show up to 50% reduction in memory overhead and $14 \times $ reduction in execution time overhead compared to the state-of-the-art solution which is a major step toward efficient EC for IoT.

A novel approach for optimal trajectory design with multiple operation modes of propulsion system, part 1

Efficient performance of a number of engineering systems is achieved through different modes of operation - yielding systems described as “hybrid”, containing both real-valued and discrete decision variables. Prominent examples of such systems, in space applications, could be spacecraft equipped with 1) a variable-Isp, variable-thrust engine or 2) multiple engines each capable of switching on/off independently. To alleviate the challenges that arise when an indirect optimization method is used, a new framework — Composite Smooth Control (CSC) — is proposed that seeks smoothness over the entire spectrum of distinct control inputs. A salient aftermath of the application of the CSC framework is that the original multi-point boundary-value problem can be treated as a two-point boundary-value problem with smooth, differentiable control inputs; the latter is notably easier to solve, yet can be made to accurately approximate the former hybrid problem. The utility of the CSC framework is demonstrated through a multi-year, multi-revolution heliocentric fuel-optimal trajectory for a spacecraft equipped with a variable-Isp, variable-thrust engine.

A novel approach for optimal trajectory design with multiple operation modes of propulsion system, part 2

Equipping a spacecraft with multiple solar-powered electric engines (of the same or different types) compounds the task of optimal trajectory design due to presence of both real-valued inputs (power input to each engine in addition to the direction of thrust vector) and discrete variables (number of active engines). Each engine can be switched on/off independently and “optimal” operating power of each engine depends on the available solar power, which depends on the distance from the Sun. Application of the Composite Smooth Control (CSC) framework to a heliocentric fuel-optimal trajectory optimization from the Earth to the comet 67P/Churyumov-Gerasimenko is demonstrated, which presents a new approach to deal with multiple-engine problems. Operation of engine clusters with 4, 6, 10 and even 20 engines of the same type can be optimized. Moreover, engine clusters with different/mixed electric engines are considered with either 2, 3 or 4 different types of engines. Remarkably, the CSC framework allows us 1) to reduce the original multi-point boundary-value problem to a two-point boundary-value problem (TPBVP), and 2) to solve the resulting TPBVPs using a single-shooting solution scheme and with a random initialization of the missing costates. While the approach we present is a continuous neighbor of the discontinuous extremals, we show that the discontinuous necessary conditions are satisfied in the asymptotic limit. We believe this is the first indirect method to accommodate a multi-mode control of this level of complexity with realistic engine performance curves. The results are interesting and promising for dealing with a large family of such challenging multi-mode optimal control problems.

Primary heat transfer system design of the WCCB blanket for multiple operation modes of CFETR

The water cooled ceramic breeder (WCCB) blanket is one of the blanket candidates for Chinese Fusion Engineering Testing Reactor (CFETR). The WCCB blanket design has been updated according to the latest core parameters of CFETR in 2018. The Primary Heat Transfer System (PHTS) of the WCCB blanket is required to remove heat and convert fusion energy under multiple operation modes of CFETR. It is challenging as the heat sources of the PHTS differ greatly with the fusion power ranging from 200 MW to 1.5 GW for multiple operation modes of CFETR. Therefore, the PHTS is designed taking 1.5 GW of fusion power as full power. Then lower fusion power modes can be satisfied with margin. Based on the WCCB blanket module structure, the PHTS is characterized by 2 independent systems, namely Cooling System (CS) 1 for the First Wall (FW), CS 2 for Breeding Zones (BZs). Both systems have two identical and symmetrical loops. Detailed design of the PHTS is performed, including system layout, pipe sizing, system components configuration (e.g., pump, steam generator, pressurizer) and operation schemes. The reliability of the PHTS design is verified by simulation using RELAP5/MOD3.4 under steady states of 200 MW, 500 MW, 1.0 GW and 1.5 GW of fusion power.