Incremental Model Research Articles

Incremental Learning and Conditional Drift Adaptation for Nonstationary Industrial Process Fault Diagnosis

Incremental learning based fault diagnosis is effective to learn from continuous industrial data on an ongoing basis. However, in the case of non-stationary industrial processes, new data distribution often gradually shifts away from that of historical data, due to equipment aging and manufacturing strategies, etc. Thus, conventional incremental methods with the identical independent distribution (i.i.d) assumption may no longer promise satisfied diagnosis performance. This paper concerns the conditional drift phenomenon, a relaxation of the i.i.d assumption, in which the conditional distribution of industrial data changes within different time. From a mathematical point of view, we firstly give the problem formulation of conditional drift and introduce a target mapping strategy for drift adaptation, under the minimum risk criteria. Then, following this strategy, an incremental diagnosis model with adaptation ability is designed. Particularly, a transformation matrix keeps matching the distributions of historical and new data. Thus, our method can quickly adapt to the conditional drift and be more robust against the evolving environment. The proposed method is applied for diagnosing faults in two industrial processes to demonstrate its effectiveness.

RSAL-iMFS: A framework of randomized stacking with active learning for incremental multi-fidelity surrogate modeling

RSAL-iMFS: A framework of randomized stacking with active learning for incremental multi-fidelity surrogate modeling

Capacity Market for Distribution System Operator – With Reliability Transactions – Considering Critical Loads and Microgrids

Conventional distribution system (DS) asset planning methods consider energy only from transmission systems (TS) and not from distributed energy resources (DER), leading to expensive plans. Newer transactive energy DS (TEDS) asset planning models, built on capacity market mechanisms, consider energy from both TS and DERs, leading to lower-cost plans and maximizing social welfare. However, in both methods the cost of higher reliability requirements for some users are socialized across all users, leading to lower social welfare. In this article, a novel transactive energy capacity market (TECM) model is proposed for DS asset planning. It builds on TEDS incremental capacity auction models by provisioning for critical loads to bid and receive superior reliability as a service. The TECM model considers these reliability transactions, in addition, to selling energy transactions from TS and DERs, buying energy transactions from loads, and asset upgrade transactions from the network operator. The TECM model allows for islanded microgrids and network reconfiguration to maximize social welfare. The TECM model is assessed on several case studies, demonstrating that it achieves higher social welfare and a lower plan cost.

Power Supply Planning Based on Simulated Annealing Algorithm

As the global shortage of fossil energy continues to increase, people’s demand for new energy increasingly focuses on the optimal design of power supply planning. The simulated annealing algorithm and the micro-incremental rate model are used to reasonably discuss the optimization goal. To obtain a correct economic evaluation, the funds at different times were converted into funds at the same time and compared. Under the condition, the peak load of the system increases by 30%, the type and number of additional units are planned, and a set of optimal solutions is obtained through multiple calculations using the simulated annealing algorithm. To obtain the optimal load distribution scheme of each unit in the existing system on the 12th and 24th hours of a typical day, the equal incremental rate model is used to solve the problem, and the simulated annealing algorithm is used to improve the accuracy of the data, and finally, the optimization of the power planning scheme is realized.

Adaptive Model Predictive Current Control for PMLSM Drive System

This article proposes an adaptive model predictive current control (AM-MPCC) for surface-mounted permanent magnet linear synchronous motor systems to simultaneously enhance the robustness against permanent magnet flux, inductance, and resistance mismatches. First, the conventional continuous control set model predictive control is analyzed, illustrating that parameter variations will inevitably deteriorate the current regulation performance. Then, an adaptive predictive model, which involves a disturbance term and an optimized current change rate coefficient, is proposed. The optimal coefficient is estimated using a steady-state incremental model and the steepest descent method at each control period. A discrete-time sliding mode disturbance observer is devised based on the adaptive model with updated coefficients to achieve the disturbance term. Finally, an exponential reaching law-based-reference trajectory is defined for the cost function of AM-MPCC to adjust the current approach trajectory. Experimental results verify the excellent robustness performances of the proposed method.

The Potential Of Judicial Review As An Incremental Business Strategy (The Emergence Of Sharing Economy And One-Stop Services Application In Indonesia)

The digital economic system has changed the pattern of relationships between service providers and consumers in conducting transactions. Starting from the opportunity given by the Supreme Court to online taxi service providers as part of Micro, Small, and Medium Enterprises (from now on MSMEs), application services such as Go-Jek and Grab are now becoming new spaces for national economic growth. This study will specifically answer how the judicial review process becomes a form of incremental policy, which is very important for business continuity in the industrial era 4.0. This paper can fill the research gap regarding policy alternatives response in supporting the development of the digital economy in Indonesia. This paper will be portrayed using doctrinal research methods and statutory approaches in descriptive and prescriptive styles. As a result, this paper demonstrates that the Supreme Court, as the judiciary institution, plays a central role in responding to changing societal needs. The rationality of business actors in the theory of economic analysis of law has led them to step up and look for responsive policy alternatives. This condition is proven by the judicial review decision on Case Number 37 P/HUM/2017, which was then able to save MSME actors during the COVID-19 pandemic. The development of an incremental policy model is a form of government response to support national economic growth in the digital era, which demands rapid change.

Two more Firmans on the Reorganisation of the Ottoman Postal System (1101/1690 and 1209/1794) •

The present article publishes the texts and translations of two firmans of Süleyman II (1101/1690) and Selim III (1209/1794) that were taken from copies in the kadi registers (sicil) of Amasya and Damascus. They concerned the reform of the Ottoman courier and post-station (ulaḳ / menzilḫāne) network with regard to the Anatolian routes. In contrast to the wide-ranging reforms featured by two other firmans (1108/1696) that Colin Heywood translated in this journal in 2001, these firman texts feature small-scale, targeted reforms. Read together, these firmans shift our understanding of reform away from singular moments of intervention towards a longer-term, incremental model of maintenance.

Contact of Rough Surfaces: An Incremental Model Accounting for Strain Gradient Plasticity

In the contact of rough surfaces, most contact patches are at the scale of micrometers, and thus, their contact deformation can be dominated by the size-dependent plasticity. In this paper, we propose a new strategy to analyze the role of strain gradient plasticity in the contact response between a realistic rough surface and a rigid plane, which modifies the incremental contact model based on the mechanism-based gradient plasticity (MSGP) theory. For several different rough surfaces with their topography measured experimentally, the relations between applied load and real contact area are derived in a simple but effective way. It is found that strain gradient plasticity significantly increases the level of mean contact pressure. The hardening effect caused by strain gradient plasticity weakens somewhat as the contact area increases. Compared with previous methods, the present model might be more efficient and of wider application.

Multi-vector Robust Model Predictive Current Control for PMSM Based on Incremental Model

Multi-vector Robust Model Predictive Current Control for PMSM Based on Incremental Model

Service-life assessment of aircraft integral structures based on incremental fatigue damage modeling

The Ottosen–Stenström–Ristinmaa (OSR) incremental fatigue damage model is adapted for fatigue-life assessment of integral airframes milled from 7050-T7451 aluminum plates. For validation, variable-amplitude high-cycle fatigue experiments are conducted for circumferentially notched, axisymmetric specimens, and for a geometry similar to an aircraft fuselage frame, with flanges, stiffeners, and web panels. We also describe how the parameters of the OSR model can be modified to account for surface roughness, and for setting acceptable failure probability.

Reviewing Software Testing Models and Optimization Techniques: An Analysis of Efficiency and Advancement Needs

Software testing is a crucial component of software engineering that aims to confirm the intended functionality of software modules and minimize the likelihood of future failures. This paper provides a comprehensive review of various software testing models and optimization techniques available in the literature, emphasizing their performance analysis and related research papers. The paper analyzes and discusses the most commonly used software testing models, including waterfall, incremental, V-model, agile, and spiral models, and identifies several areas for improvement to increase their effectiveness. These areas include using machine learning techniques to automate and optimize testing processes, reducing the number of test cases required, and introducing new metrics to gauge the success of testing. Moreover, the paper suggests developing entirely novel methods to deal with the challenges of contemporary software programs, such as the Internet of Things and artificial intelligence. This paper aims to analyze various software testing models and optimization techniques thoroughly, highlight their advantages and disadvantages, and suggest improvements to increase their efficiency and effectiveness. By continuously improving and optimizing software testing processes, software modules can function as intended, minimizing the likelihood of future failures.

Implementation of a constitutive model for anisotropic rocks based on modified Lade failure criterion

The strength anisotropy for inherent anisotropic rocks presents a challenge to simulate considering the influence of intermediate principal stress. Based on the modified Lade failure criterion, a new anisotropic modified Lade criterion combining an empirical equation is established and verified using published experimental datasets of anisotropic rocks. The incremental constitutive model for anisotropic rocks is derived by using finite difference theory. The dynamic link library (DLL) module of the model is obtained by using the VC++ program, and then the model is validated against various laboratory test results. It is concluded that the proposed criterion and derived model can describe the strength anisotropy of inherent anisotropic rocks well.

Parameters Calibration of the GISSMO Failure Model for SUS301L-MT

With the development of the rail transit industry, more attention has been paid to the passive safety of rail vehicles. Structural damage is one of the main failure behaviors in a rail vehicle collision, but it has been paid little attention to in past research. In this paper, the quasi-static fracture experiments of SUS301L-MT under different stress states were carried out. The mechanical fracture properties of this material were studied, and the corresponding finite element simulation accuracy was improved to guide the design of vehicle crashworthiness. Through the tests, the fracture behavior of materials with wide stress triaxiality was obtained, and each specimen's fracture locations and fracture strains were determined. Parameters of a generalized incremental stress state dependent damage model (GISSMO) of the material were calibrated, and the model's accuracy was verified with test results from a 45° shear specimen. The GISSMO failure model accurately reflected the fracture characteristics of the material. The mesh dependency of this model was modified and discussed. The results show that the simulation agrees well with experimental data for the force-displacement curve after correction, but the strain distribution needs to be further studied and improved.

Towards the goal of zero-carbon building retrofitting with variant application degrees of low-carbon technologies: Mitigation potential and cost-benefit analysis for a kindergarten in Beijing

China's building industry urgently needs to accelerate the deployment of zero-carbon building technologies and zero-carbon project practices to facilitate the net-zero target. This study aims to explore the application potential and benefits of applying low-carbon technologies in existing buildings from a life-cycle perspective to drive zero-carbon building retrofits in China. To illustrate the impacts of the application of low-carbon technologies on zero-carbon building retrofitting, the mitigation values and abatement costs were evaluated for 16 typical low-carbon technologies of buildings, and the comprehensive incremental benefits model considering the environmental, economic and social impacts was developed. The incremental cost-effectiveness ratio index with the time value was proposed to explain the feasibility of building zero-carbon retrofit for different levels of technology application. In this study, a public building (kindergarten) in Beijing was taken as a study case, and the initial life-cycle energy consumption and carbon emissions based energy simulation were considered as the benchmark to compare the effect of zero-carbon transformation of the case building with different degrees of technology application. It is found that the economic benefit of implementing zero-carbon retrofitting of the case building through these low-carbon technologies increases from 42% to 66%, while the environmental benefit decreases from 57% to 32%. The analysis of incremental cost-effectiveness ratio indicates that achieving zero-carbon renovation over the lifetime of the kindergarten is economically feasible, and the comprehensive incremental benefits of the application of low-carbon technologies will exceed the incremental cost. The quantitative research for building low-carbon technologies in this study might provide an effective assistance on technology selection at the project level for better zero-carbon renovation strategies.

Prognostic value of low heart rates in patients admitted with acute myocardial infarction

Introduction and objectivesThe risk prediction scores adopted in acute coronary syndromes (ACS) use incremental models to estimate mortality for heart rate (HR) above 60 bpm. Nonetheless, previous studies reported a nonlinear relationship between HR and events, suggesting that low HR may have an unrecognized prognostic role. We aimed to assess the prognostic impact of low HR in ACS, defined as admission HR <50 bpm. MethodsThis study analyzed data from the AMIS Plus registry, a cohort of hospitalized patients with ACS between 1999 and 2021. The primary endpoint was in-hospital all-cause mortality, while a composite of all-cause mortality, major cardiac/cerebrovascular events was set as the secondary endpoint. A multilevel statistical method was used to assess the prognostic role of low HR in ACS. ResultsThe study included 51 001 patients. Crude estimates showed a bimodal distribution of primary and secondary endpoints with peaks at low and high HR. A nonlinear relationship between HR and in-hospital mortality was observed on restricted cubic spline analysis. An HR of 50 to 75 bpm showed lower mortality than HR <50 bpm (OR, 0.67; 95%CI, 0.47-0.99) only after primary multivariable analysis, which was not confirmed after multiple sensitivity analyses. After propensity score matching, progressive fading of the prognostic role of HR <50 bpm was evident. ConclusionsLow admission HR in ACS is associated with a higher crude rate of adverse events. Nonetheless, after correction for baseline differences, the prognostic role of low HR was not confirmed. Therefore, low HR probably represents a marker of underlying morbidity. These results may be clinically relevant in improving the accuracy of risk scores in ACS.

Experimental study on the load-area relation of rough surfaces and comparison with theoretical model

It is of critical significance to accurately measure or predict the real contact areas between rough solids in engineering. In this study, based on the frustrated total internal reflection technique and an Otsu method, an optical apparatus is designed to capture the real contact areas between rough metallic samples and flat quartz glass. Moreover, an incremental equivalent contact model developed recently by our group is adopted to predict the load-area relationship. For samples of various materials and morphologies, it is found that the proposed contact model agrees well with the experimentally measured results, which verifies the efficiency of the incremental equivalent contact model.

Proportional Integral Predictive Control of High-Order Fully Actuated Networked Multiagent Systems With Communication Delays

This research is devoted to the cooperative control of high-order fully actuated networked multiagent systems (HOFA-NMASs) with communication delays between network node and sensors, and network node and actuators. A proportional integral (PI) predictive control scheme is developed to effectively implement the cooperation among HOFA-NMASs and actively compensate the communication delays. In this scheme, a local PI feedback controller is applied to stabilize the closed-loop nominal HOFA-NMASs, then a Diophantine equation is presented to establish an incremental HOFA prediction model rather than a reduced-order one, so that the optimization of cost function considered cooperative performance and the compensation of communication delays are completed via multistep output predictions, thus the optimal cooperative controllers are constructed. The further discussion provides a simple condition of simultaneous stability and output consensus of closed-loop HOFA-NMASs, which is easy to verify and extend in practice and is independent on communication delays. An experiment of formation control of air-bearing simulators is shown to prove the availability of the proposed PI predictive control scheme.

A practical method for the deformation of long‐stroke hydraulic manipulators in grasping‐handling tasks

AbstractLong‐stroke hydraulic manipulators are utilized in various grasping‐handling tasks, and the flexible deformation of these manipulators is the primary obstacle that affects precise position control of the end‐effectors in Cartesian space. This deformation is manifested in the following three aspects: joint deformation, structural deformation and clearance variation. Due to deformation uncertainty, methods that model the hydraulic manipulator as a combination of flexible multibody systems and hydraulic actuators are unsuitable. In this article, we propose an incremental inverse kinematics model (IIKM) as a new approach to solving the above deformation difficulties. The projection method is used to obtain the inverse kinematic analytical solution of long‐stroke hydraulic manipulators, which is based on the manipulator deformation in the current configuration (current configuration refers to the arrangement of the manipulator links when the manipulator starts to move to the target position). The proposed method avoids complex flexible multibody modeling and parameter identification, allowing long‐stroke hydraulic manipulators to be accurately controlled within a certain neighborhood. An evaluation coefficient is proposed to analyze the calculation accuracy of the IIKM in combination with the success rate obtained from 190 grasping experiments. Through these experiments, we determine the optimal calculation height range of the IIKM in the vertical direction and the optimal calculation position area in the horizontal direction and prove that the IIKM result can guarantee the success of grasping‐handling tasks when the end‐effector is within the optimal calculation height range.

Association of pulmonary transit time by cardiac magnetic resonance with heart failure hospitalization in a large prospective cohort with diverse cardiac conditions

BackgroundLonger pulmonary transit time (PTT) is closely associated with hemodynamic abnormalities. However, the implications on heart failure (HF) risk have not been investigated broadly in patients with diverse cardiac conditions. In this study we examined the long-term risk of HF hospitalization associated with longer PTT in a large prospective cohort with a broad spectrum of cardiac conditions. MethodsAll subjects were prospectively recruited to undergo cardiac magnetic resonance (CMR). The dynamic images of first-pass perfusion were acquired to assess peak-to-peak pulmonary transit time (PTT) which was subsequently normalized to RR interval duration. The risk of HF was examined using Cox proportional hazards models adjusted for baseline confounding risk factors. ResultsAmong 506 consecutively consented patients undergoing clinical cardiac MR with diverse cardiac conditions, the mean age was 63 ± 14 years and 373 (73%) were male. After a mean follow up duration of 4.5 ± 3.0 years, 70 (14%) patients developed hospitalized HF and of these 6 died. A normalized PTT ≥ 8.2 was associated with a significantly increased adjusted HF hazard ratio of 3.69 (95% CI 2.02, 6.73). The HF hazard ratio was 1.26 (95% CI 1.18, 1.33) for each 1 unit increase in PTT which was higher among those preserved (1.70, 95% CI 1.20, 2.41) compared to those with reduced left ventricular ejection fraction (< 50%) (1.18, 95% CI 1.09, 1.27). PTT remained a significant risk factor of hospitalized HF after additional adjustment for N-terminal pro-hormone brain natriuretic peptide (NT-proBNP) or left ventricular global longitudinal strain with additionally demonstrated incremental model improvement through likelihood ratio testing. ConclusionsOur findings support the role of PTT in assessing HF risk among patients with broad spectrum of cardiac conditions with reduced as well as preserved ejection fraction. Longer PTT duration is an incremental risk factor for HF when baseline global longitudinal strain and NT-proBNP are taken into consideration.

An Improved Koopman-MPC Framework for Data-Driven Modeling and Control of Soft Actuators

The challenge of achieving precise control of soft actuators with strong nonlinearity is mainly due to the difficulty of deriving models suitable for model-based control techniques. Fortunately, Koopman operator provides a data-driven method for constructing control-oriented models of nonlinear systems to achieve model predictive control (MPC). It is called the Koopman-MPC framework, which is theoretically effective for soft actuators. Nevertheless, in this framework, a critical challenge is to select correct basis functions for Koopman-based modeling. Furthermore, there is room for improvement in control performance. To overcome these problems, this letter presents an improved Koopman-MPC framework to efficiently implement model-based control techniques for soft actuators. Firstly, we propose a systematic method for selecting the basis functions, which extends the measurement coordinates with derivative and time-delay coordinates and uses the spares identification of nonlinear dynamics (SINDy) algorithm. Secondly, an incremental model predictive control with dynamic constraints (IMPCDC) is developed based on the Koopman model. Finally, several comparative experiments are conducted to verify the utility of the improved Koopman-MPC framework for data-driven modeling and control of soft actuators.