Controlling the dynamic behavior of decentralized cluster through centralized approaches

How to control the dynamic behavior of large-scale artificial active matter is a critical concern in experimental research on soft matter, particularly regarding the emergence of collective behaviors and the formation of group patterns. Centralized systems excel in precise control over individual behavior within a group, ensuring high accuracy and controllability in task execution. Nevertheless, their sensitivity to group size may limit their adaptability to diverse tasks. In contrast, decentralized systems empower individuals with autonomous decision-making, enhancing adaptability and system robustness. Yet, this flexibility comes at the cost of reduced accuracy and efficiency in task execution. In this work, we present a unique method for regulating the centralized dynamic behavior of self-organizing clusters based on environmental interactions. Within this environment-coupled robot system, each robot possesses similar dynamic characteristics, and their internal programs are entirely identical. However, their behaviors can be guided by the centralized control of the environment, facilitating the accomplishment of diverse cluster tasks. This approach aims to balance the accuracy and flexibility of centralized control with the robustness and task adaptability of decentralized control. The proactive regulation of dynamic behavioral characteristics in active matter groups, demonstrated in this work through environmental interactions, holds the potential to introduce a novel technological approach and provide experimental references for studying the dynamic behavior control of large-scale artificial active matter systems.

A HybridManufacturing ProcessMonitoringMethod Using Stacked Gated Recurrent Unit and Random Forest

This study proposed a new real-time manufacturing process monitoring method to monitor and detect process shifts in manufacturing operations.Since real-time production process monitoring is critical in today’s smart manufacturing.The more robust the monitoring model,the more reliable a process is to be under control.In the past,many researchers have developed real-time monitoring methods to detect process shifts early.However,thesemethods have limitations in detecting process shifts as quickly as possible and handling various data volumes and varieties.In this paper,a robust monitoring model combining Gated Recurrent Unit(GRU)and Random Forest(RF)with Real-Time Contrast(RTC)called GRU-RF-RTC was proposed to detect process shifts rapidly.The effectiveness of the proposed GRU-RF-RTC model is first evaluated using multivariate normal and nonnormal distribution datasets.Then,to prove the applicability of the proposed model in a realmanufacturing setting,the model was evaluated using real-world normal and non-normal problems.The results demonstrate that the proposed GRU-RF-RTC outperforms other methods in detecting process shifts quickly with the lowest average out-of-control run length(ARL1)in all synthesis and real-world problems under normal and non-normal cases.The experiment results on real-world problems highlight the significance of the proposed GRU-RF-RTC model in modern manufacturing process monitoring applications.The result reveals that the proposed method improves the shift detection capability by 42.14%in normal and 43.64%in gamma distribution problems.

Tool Condition Monitoring Based on Nonlinear Output Frequency Response Functions and Multivariate Control Chart

Tool condition monitoring(TCM)is a key technology for intelligent manufacturing.The objective is to monitor the tool operation status and detect tool breakage so that the tool can be changed in time to avoid significant damage to workpieces and reduce manufacturing costs.Recently,an innovative TCM approach based on sensor data modelling and model frequency analysis has been proposed.Different from traditional signal feature-based monitoring,the data from sensors are utilized to build a dynamic process model.Then,the nonlinear output frequency response functions,a concept which extends the linear system frequency response function to the nonlinear case,over the frequency range of the tooth passing frequency of the machining process are extracted to reveal tool health conditions.In order to extend the novel sensor data modelling and model frequency analysis to unsupervised condition monitoring of cutting tools,in the present study,a multivariate control chart is proposed for TCM based on the frequency domain properties of machining processes derived from the innovative sensor data modelling and model frequency analysis.The feature dimension is reduced by principal component analysis first.Then the moving average strategy is exploited to generate monitoring variables and overcome the effects of noises.The milling experiments of titanium alloys are conducted to verify the effectiveness of the proposed approach in detecting excessive flank wear of solid carbide end mills.The results demonstrate the advantages of the new approach over conventional TCM techniques and its potential in industrial applications.

A hierarchical architecture of centralized monitoring and controlling system and its high-performance and interoperability protocol

This paper describes a hierarchical architecture and a high-performance and interoperability protocol for centralized monitoring and controlling systems (CMCS) . The protocol we proposed can interoperate different monitoring and controlling systems constructed by different companies, each with different functions and communication protocols. The protocol reduces the amount of traffic and has real-time and high-perfor-mance advantages. The protocol was implemented in CMCS for telecommunication power supply and air-condi-tioner used by the Telecommunication Bureau of Zhejiang Province. This paper deals with the hierarchical architecture and function of CMCS and packet format, command ID, and SDL description of its protocol. We also discuss the properties of the interoperability and performance of the protocol in this paper.

Microseismic monitoring and forecasting of dynamic disasters in underground hydropower projects in southwest China:A review

The underground hydropower projects in Southwest China is characterized by large excavation sizes,high geostresses,complicated geological conditions and multiple construction processes.Various disasters such as collapses,large deformations,rockbursts are frequently encountered,resulting in serious casualties and huge economic losses.This review mainly presents some representative results on microseismic(MS)monitoring and forecasting for disasters in hydropower underground engineering.First,a set of new denoising,spectral analysis,and location methods were developed for better identification and location of MS signals.Then,the tempo-spatial characteristics of MS events were analyzed to understand the relationship between field construction and damages of surrounding rocks.Combined with field construction,geological data,numerical simulation and parametric analysis of MS sources,the focal mechanism of MS events was revealed.A damage constitutive model considering MS fracturing size was put forward and feedback analysis considering the MS damage of underground surrounding rocks was conducted.Next,an MS multi-parameter based risk assessment and early warning method for dynamic disasters were proposed.The technology for control of the damage and deformation of underground surrounding rocks was proposed for underground caverns.Finally,two typical underground powerhouses were selected as case studies.These achievements can provide significant references for prevention and control of dynamic disasters for underground engineering with similar complicated geological conditions.

Underground ground control monitoring and interpretation,and numerical modeling, and shield capacity design

Mine or longwall panel layout is a 3D structure with highly non-uniform stress distribution. Recognition of such fact will facilitate underground problem identification/investigation and solving by numerical modeling through proper model construction. Due to its versatility, numerical modeling is the most popular method for ground control design and problem solving. However numerical modeling results require highly experienced professionals to interpret its validity/applicability to actual mining operations due to complicated mining and geological conditions. Underground ground control monitoring is routinely performed to predict roof behavior such as weighting and weighting interval without matching observation of face mining condition while the mining pressures are being monitored, resulting in unrealistic interpretation of the obtained data on mining pressure. The importance of ground control pressure monitoring and simultaneous observation of mining and geological conditions is illustrated by an example of shield leg pressure monitoring and interpretation in an U.S. longwall coal mine: it was found that the roof strata act like a plate, not an individual block of the size of a shield dimension, as commonly assumed by all researchers and shield capacity is not a fixed property for a longwall panel or a mine or a coal seam. A new mechanism on the interaction between shield's hydraulic leg pressure and roof strata for shield loading is proposed.

Monitoring and Assessment of Water Quality of Centralized Drinking Water Sources in Kaixian County during the " Twelfth Five-year Plan " Period

Based on the monitoring data of water quality of more than 40 centralized drinking water sources in 40 towns （townships or streets） of Kaixian County in the first and second half of each year during the ＂Twelfth Five-year Plan＂ period, the changing rules of the water quality were studied to provide scientific references for the improvement of drinking water safety of urban and rural residents and drinking water quality. The re- sults show that the water quality of centralized drinking water sources in Kaixian County improved year by year during the ＂Twelfth Five-year Plan＂ period, and most monitoring sites with water quality exceeding the standard are distributed in reservoirs. Total phosphorus, total nitrogen, chemical oxygen demand, and permanganate index exceeded the standard obviously. Main pollution sources are domestic pollution and non-point source pol- lution caused by excessive discharge of nitrogen, phosphorus and organic pollutants. To improve drinking water quality, it is suggested that some towns can get drinking water from other reservoirs, surface water or underground water with better quality instead of previous reservoirs with water quality exceeding the standard, and the control of non-point source pollution should be enhanced.

Determination of Monitoring Control Value for Concrete Gravity Dam Spatial Deformation Based on POT Model

Deformation can directly reflect the working behavior of the dam,so determining the deformation monitoring control value can effectively monitor the safety of dam operation.The traditional dam deformation monitoring control value only considers the single measuring point.In order to overcome the limitation,this paper presents a new method to determine the monitoring control value for concrete gravity dam based on the deformations of multi-measuring points.A dam’s comprehensive deformation displacement is determined by the measured values at different measuring points on the positive inverted vertical line and the corresponding weight of eachmeasuring point.The projection pursuit method(PPM)combined with the grey wolf optimization(GWO)algorithm is used to determine the weight of each measuring point according to the spatial correlation distribution characteristics of dam deformation.The peaks over threshold(POT)model based on the extreme value theory is adopted to determine the monitoring control value with the obtained dam comprehensive deformation displacement.In addition,the POTmodel is improved with the automatic threshold determinationmethod based on the 3σcriterion in probability theory and the GWO algorithm,which can avoid subjectivity and randomness in determining the threshold.The results of the engineering application show the feasibility and applicability of the proposed method.

A Multi-Interface Remote Monitoring and Control System Architecture Based on Embedded Server

This paper presents a multi-interface embedded server architecture for remote real-time monitoring system and distributed monitoring applications. In the scheme,an embedded microprocessor( LPC3250 from NXP) is chosen as the CPU of the embedded server with a linux operation system( OS) environment. The embedded server provides multiple interfaces for supporting various application scenarios. The whole network is based on local area network and adopts the Browser / Server( B / S) model. The monitoring and control node is as a browser endpoint and the remote node with an embedded server is as a server endpoint. Users can easily acquire various sensors information through writing Internet protocol address of remote node on the computer browser. Compared with client / server( C / S) mode,B / S model needs less maintain and can be applicable to large user group. In addition,a simple network management protocol( SNMP) is used for management of devices in Internet protocol( IP) networks. The results of the demonstration experiment show that the proposed system gives good support to manage the network from different user terminals and allows the users to better interact with the ambient environment.

Research on Remote Monitoring and Fault Diagnosis Technology of Numerical Control Machine

Based on the internet technology,it has become possible to complete remote monitoring and fault diagnosis for the numerical control machine.In order to capture the micro-shock signal induced by the incipient fault on the rotating parts,the reso- nance demodulation technology is utilized in the system.As a subsystem of the remote monitoring system,the embedded data acquisi- tion instrument not only integrates the demodulation board but also complete the collection and preprocess of monitoring data from different machines.Furthermore,through connecting to the internet,the data can be transferred to the remote diagnosis center and data reading and writing function can be finished in the database.At the same time,the problem of the IP address floating in the dial-up of web server is solved by the dynamic DNS technology.Finally,the remote diagnosis software developed on the Lab VIEW platform can analyze the monitoring data from manufacturing field.The research results have indicated that the equipment status can be monitored by the system effectively.

A UAV-Assisted V2X Network Architecture with Separated Data Transmission and Network Control

With the explosive increasing number of connecting devices such as smart phones, vehicles,drones, and satellites in the wireless networks, how to manage and control such a huge number of networking nodes has become a great challenge. In this paper, we combine the advantages of centralized networks and distributed networks approaches for vehicular networks with the aid of Unmanned Aerial Vehicle(UAV), and propose a Center-controlled Multihop Wireless(CMW) networking scheme consisting of data transmission plane performed by vehicles and the network control plane implemented by the UAV.Besides, we jointly explore the advantages of Medium Access Control(MAC) protocols in the link layer and routing schemes in the network layer to facilitate the multi-hop data transmission for the ground vehicles.Particularly, the network control plane in the UAV can manage the whole network effectively via fully exploiting the acquired network topology information and traffic requests from each vehicle, and implements various kinds of control based on different traffic demands, which can enhance the networking flexibility and scalability significantly in vehicular networks.Simulation results validate the advantages of the proposed scheme compared with existing methods.

A wireless solution for greenhouse monitoring and control system based on ZigBee technology

With the rapid development of wireless technologies, it is possible for Chinese greenhouses to be equipped with wireless sensor networks due to their low-cost, simplicity and mobility. In the current study, we compared the advantages of ZigBee with other two similar wireless networking protocols, Wi-Fi and Bluetooth, and proposed a wireless solution for green- house monitoring and control system based on ZigBee technology. As an explorative application of ZigBee technology in Chinese greenhouse, it may promote Chinese protected agriculture.

Joint Centralized Power Control and Cell Sectoring for Interference Management in CDMA Cellular Systems in a 2D Urban Environment

The interference reduction capability of cell sectoring and power control algorithms have been considered separately as means to decrease the interference in Code Division Multiple Access (CDMA) cellular systems. In this paper, we present Switched-Beam (SB) and Rotatable Equal Sectoring (RES) techniques for CDMA cellular systems in a 2D urban environment. In the SB technique by using a number of fixed, independent, or directional antennas we increase the downlink capacity of the CDMA systems. Also in the RES method, the equal sectors of the base stations are rotating together to decrease the inter-cell and intra-cell interferences. Also in this paper we use centralized power control to overcome the near-far problem. Simulation results indicate that the proposed techniques considerably increase the capacity of the CDMA cellular systems compared to ordinary Equal Sectoring (ES) method.

Performance Monitoring and Diagnosis of Multivariable Model Predictive Control Using Statistical Analysis

A statistic-based benchmark was proposed for performance assessment and monitoring of model predic- tive control; the benchmark was straightforward and achievable by recording a set of output data only when the control performance was good according to the user’s selection. Principal component model was built and an auto- regressive moving average filter was identified to monitor the performance; an improved T2 statistic was selected as the performance monitor index. When performance changes were detected, diagnosis was done by model validation using recursive analysis and generalized likelihood ratio (GLR) method. This distinguished the fact that the per- formance change was due to plant model mismatch or due to disturbance term. Simulation was done about a heavy oil fractionator system and good results were obtained. The diagnosis result was helpful for the operator to improve the system performance.

Monitoring and control technology of solar photovoltaic power generation system

In view of characteristics of solar photovoltaic (PV) power station such as the decentralized layout and massive monitoring and control information, a solar PV power generation monitoring and control system has been designed. The system is designed into three layers namely the sensor and actuator layer, the PLC field monitoring and control layer and the remote network monitoring and control layer. Through ZigBee wireless network, PROFIBUS and GPRS wireless network, the system makes the three layers exchange information rapidly, and the system supervises not only various operational parameters of the power generating system but also weather changes as a way to change the solar tracking strategy of the PV power generating system and reduce the operating energy consumption of the system. Through the hardware redundant design of PLC central controller and the upper computer, the solar PV power station can be more secure and reliable when running.

CONTROLLING AND MONITORING THERMOTE NICAL PARAMETERS OF GLASS MELTING FURNACE

According to the characteristics of the ther-motechnical parameters such as temperature pressure and glass level for glass melting furnace, the design method for monitoring and controlling these parameters is introduced in this paper based on MACROMAX-2 concentrated and dis-tributedcontrol system. The configuration of management information and control loop is described, and research tests were performed to check the functions of system.

Decentralized and overall condition monitoring system for large-scale mobile and complex equipment

It is an urgent project to realize online and overall condition monitoring and timely fault diagnosis for large-scale mobile and complex equipment. Moreover, most of the existing large-scale complex equipment has quite insufficient accessibility of examination, although it still has quite a long service life. The decentralized and overall condition monitoring, as a new concept, is proposed from the point of view of the whole system. A set of complex equipment is divided into several parts in terms of concrete equipment. Every part is processed via one detecting unit, and the main detecting unit is connected with other units. The management work and communications with the remote monitoring center have been taken on by it. Consequently, the difficulty of realizing a condition monitoring system and the complexity of processing information is reduced greatly. Furthermore, excellent maintainability of the condition monitoring system is obtained because of the modularization design. Through an application example, the design and realization of the decentralized and overall condition monitoring system is introduced specifically. Some advanced technologies, such as, micro control unit （MCU）, advanced RISC machines （ARM）, and control area network （CAN）, have been adopted in the system. The system＇s applicability for the existing large-scale mobile and complex equipment is tested.

Development and experience in the monitoring,assessment and control of environmentalpollutants in Hong Kong

The late start of environmental protection in Hong Kong was discussed in the light of problems encountered during the development of environmental protection legislation in Hong Kong for the past 20 years. The collaboration in monitoring and assessment of environmental pollutants between the University of Hong Kong and various governments were descrbed in parallel with the progress in environmental protection in Hong Kong. The developments of new analytical techniques for environmental monitoring and analysis is given and their application in environmental control described. The joint projects in assessment and control of environmental pollutants carried out in collaboration with local industries and other organizations within and without the university are given and discussed. The problems and possible solution facing Hong Kong in development control equipment for small scale industries are discussed and areas of development identified. The development and experience in the monitoring assessment and control of environmental pollutants in Hong Kong are summarized and areas of difficulties are illustrated.

Application of ArtificialNeural Network to Real-Time Condition Monitoring Control and Usual Trouble Diagnosis during Driling

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Risk assessment of high-speed railway CTC system based on improved game theory and cloud model

Purpose-In order to solve the problem of inaccurate calculation of index weights,subjectivity and uncertainty of index assessment in the risk assessment process,this study aims to propose a scientific and reasonable centralized traffic control(CTC)system risk assessment method.Design/methodologylapproach-First,system-theoretic process analysis(STPA)is used to conduct risk analysis on the CTC system and constructs risk assessment indexes based on this analysis.Then,to enhance the accuracy of weight calculation,the fuzzy analytical hierarchy process(FAHP),fuzzy decision-making trial and evaluation laboratory(FDEMATEL)and entropy weight method are employed to calculate the subjective weight,relative weight and objective weight of each index.These three types of weights are combined using game theory to obtain the combined weight for each index.To reduce subjectivity and uncertainty in the assessment process,the backward cloud generator method is utilized to obtain the numerical character(NC)of the cloud model for each index.The NCs of the indexes are then weighted to derive the comprehensive cloud for risk assessment of the CTC system.This cloud model is used to obtain the CTC system's comprehensive risk assessment.The model's similarity measurement method gauges the likeness between the comprehensive risk assessment cloud and the risk standard cloud.Finally,this process yields the risk assessment results for the CTC system.Findings-The cloud model can handle the subjectivity and fuzziness in the risk assessment process well.The cloud model-based risk assessment method was applied to the CTC system risk assessment of a railway group and achieved good results.Originality/value-This study provides a cloud model-based method for risk assessment of CTC systems,which accurately calculates the weight of risk indexes and uses cloud models to reduce uncertainty and subjectivity in the assessment,achieving effective risk assessment of CTC systems.It can provide a reference and theoretical basis for risk management of the CTC system.