This paper is part 1 of a series dealing with the design integrated interplant water-allocation and heat-exchange networks (IWAHENs), special case network synthesis multiple physical properties. Traditionally, tasks optimizing (WANs) heat exchange (HENs) were either performed individually or studied within single plant. In this paper, novel multiscale state–space superstructure developed to capture all possible configurations for fixed flow rate (FF) IWAHEN designs both direct indirect...

We aim to address the issues of difficult acquisition bearing fault data, few feature data sets, and low efficiency intelligent diagnosis. In this paper, an orthogonal wavelet transform K-nearest neighbor (OWTKNN) diagnosis method has been proposed. The (OWT) extracts peaks each detail signal as training samples uses K-Nearest Neighbor (KNN) for classification. classification results multiple test obtained through rolling tests show that can reach a recognition rate 100%, compared with KNN...

A novel mathematical model for simultaneous optimization of a property-based water-allocation and heat-exchange network (WAHEN) is presented in this work, where both linear nonlinear dependent properties are taken into account. Specifically, state-space representation modified to capture the structural characteristics WAHEN, mixed-integer programming (MINLP) formulated correspondingly minimize total annualized cost (TAC) network. In proposed model, not only property energy integrations...

Control valves are important actuators in process industries. The blockage and leakage of the most common faults harsh environments. This paper proposes a fault diagnosis model based on an enhanced probability neural network (PNN), where modified dung beetle optimization (DBO) algorithm is developed to optimize smooth factors PNN so as improve classification accuracy robustness. Meanwhile, k-medoids clustering applied structure. proposed validated by using dataset from experiments for...

With the increasing attention of networked control, system decomposition and distributed models show significant importance in implementation model-based control strategy. In this paper, a data-driven online subsystem modelling algorithm was proposed for large-scale chemical processes. The key controlled variables are first partitioned by affinity propagation clustering into several clusters. Each cluster can be regarded as subsystem. Then inputs each selected offline canonical correlation...

Abstract The measurement accuracy of MEMS gyroscope is relatively low. Starting from the software level, multi-sensor information fusion technology array (MGA) used to reduce drift gyroscope. Firstly, a signal acquisition and processing system for communicating with ADXRS810 based on field-programmable gate (FPGA) designed. Secondly, collected data preprocessed. long-term trend terms are obtained by ensemble empirical mode decomposition (EEMD) linear function fitting, filtered out obtain...

To improve the accuracy of predicting remaining useful life (RUL) computer numerical control (CNC) machine tool components, this study proposes a novel method. In method, condition monitoring platform for components is built to obtain component operation information. The collected information processed acquire signal features with better trend. Weibull model modified via fusion internal and external operating Accordingly, regression that fully considers established. fminsearch function...

The Gaussian mixture model (GMM) is an unsupervised clustering machine learning algorithm. This procedure involves the combination of multiple probability distributions to describe different sample spaces. Principally, density function (PDF) plays a paramount role by being transformed into local linear regression learn from unknown f failure samples, revealing inherent properties and regularity data, enhancing subsequent identification operating status machine. wavelet transform...

Signal processing algorithms (SPA) play a key role in an imaging IR tracker which is widely used infrared search and track (IRST) system. When being to target detection, recognition tracking, SPA has significant influence on the performance of IRST Due variety complexity field scenes countermeasures, should be robust enough for military use. The question arises as how measure assess efficiently properly. On other hand, study evaluation will not only give assessment specific algorithm, but...

Regulating valves are widely used in process industries. Harsh operating conditions can cause failures, and lead to safety hazards. It is important develop effective fault detection methods for regulating valves. Whereas, real-world industrial scenarios, obtaining data challenging requires a substantial allocation of resources annotation. To address this issue, residual-based method proposed valves, which does not require modeling. Firstly, flow prediction model developed using least-squares...

The precision forming process is currently used for many difficult-to-cut parts such as aero-engine blades. However, satisfying the tolerance requirement of accuracy difficult. Thus, machining to ensure final part. error near-net shape caused by thermal cannot be ignored in process. If cutting tool path generated terms design blade model, it would too difficult satisfy material allowance and blade. In this paper, we propose a new flexible localization method reconstruct to-be-cut surface...

Support vector data description (SVDD) is common supervised learning. Its basic idea to establish a closed and compact area with the objects be described as integrity. The are all included within or far possible. In contrast, other excluded out of inherent nature laws subsequently revealed, thereby distinguishing operation state machine. this paper, an orthogonal wavelet transformation‐support (OWTSVDD) proposed evaluate performance bearings, where peak‐to‐peak value detail signal extracted...