Remote Performance Monitoring Research Articles

Maintenance and asset management practices of industrial assets: importance of tribological practices and digital tools

There are a large number of rotating and sliding parts in industrial assets. Tribological behaviour plays a significant role in influencing friction and wear, and in turn, the life of these parts. There are issues and challenges in understanding the tribological aspects and behaviour of machine components by maintenance professionals so that informed decisions can taken to improve performance and productivity. An understanding of tribology helps in developing and applying the tools and techniques necessary for better maintenance. In recent years, remote performance monitoring (RPM), internet of things (IoT), machine learning, artificial intelligence and data analytics have made a significant contribution to maintenance and asset management. This paper reviews the tribological aspects related to maintenance, reliability and asset management. The findings of this study will be useful to engineers and managers to understand and appreciate the relationship between tribology, maintenance, reliability and availability for better asset management.

Beyond signal quality: The value of unmaintained pH, dissolved oxygen, and oxidation-reduction potential sensors for remote performance monitoring of on-site sequencing batch reactors

Sensor maintenance is time-consuming and is a bottleneck for monitoring on-site wastewater treatment systems. Hence, we compare maintained and unmaintained sensors to monitor the biological performance of a small-scale sequencing batch reactor (SBR). The sensor types are ion-selective pH, optical dissolved oxygen (DO), and oxidation-reduction potential (ORP) with platinum electrode. We created soft sensors using engineered features: ammonium valley for pH, oxidation ramp for DO, and nitrite ramp for the ORP. Four soft sensors based on unmaintained pH sensors correctly identified the completion of the ammonium oxidation (89–91 out of 107 cycles), about as many times as soft sensors based on a maintained pH sensor (91 out of 107 cycles). In contrast, the DO soft sensor using data from a maintained sensor showed slightly better (89 out of 96 cycles) detection performance than that using data from two unmaintained sensors (77, respectively 82 out of 96 correct). Furthermore, the DO soft sensor using maintained data is much less sensitive to the optimisation of cut-off frequency and slope tolerance than the soft sensor using unmaintained data. The nitrite ramp provided no useful information on the state of nitrite oxidation, so no comparison of maintained and unmaintained ORP sensors was possible in this case. We identified two hurdles when designing soft sensors for unmaintained sensors: i) Sensors’ type- and design-specific deterioration affects performance. ii) Feature engineering for soft sensors is sensor type specific, and the outcome is strongly influenced by operational parameters such as the aeration rate. In summary, the results with the provided soft sensors show that frequent sensor maintenance is not necessarily needed to monitor the performance of SBRs. Without sensor maintenance monitoring small-scale SBRs becomes practicable, which could improve the reliability of unstaffed on-site treatment systems substantially.

Robotics Application in Remote Data Acquisition and Control for Solar Ponds

This paper presents one application of industrial robots in the automation of renewable energy production. The robot supports remote performance monitoring and maintenance of salinity gradient solar ponds. The details of the design, setup and the use of the robot sampling station and the remote Data Acquisition (DAQ) system are given here. The use of a robot arm, to position equipment and sensors, provides accurate and reliable real time data needed for autonomous monitoring and control of this type of green energy production. Robot upgrade of solar ponds can be easily integrated with existing systems. Data logged by the proposed system can be remotely accessed, plotted and analysed. Thus the simultaneous and remote monitoring of a large scale network of ponds can be easily implemented. This provides a fully automated solution to the monitoring and control of green energy production operations, which can be used to provide heat and electricity to buildings. Remote real time monitoring will facilitate the setup and operations of several solar ponds around cities.

Remote Performance Monitoring of Photovoltaic Systems with Battery Storage

not Available.

Program Control Language: a programming language for adaptive distributed applications

Many distributed applications must meet stringent performance requirements even when the performance characteristics of the underlying systems and networks vary significantly at runtime. Runtime adaptation can be used to tolerate such changes, but sophisticated adaptive distributed programs can be extremely challenging to design, implement and debug. This paper proposes a language called Program Control Language (PCL) that provides a novel means of specifying adaptations in distributed applications. PCL is based on an abstract, global representation of a distributed program (a static task graph), which enables a programmer to reason about and to describe a wide range of application-specific adaptation strategies at a high level, using a few key mechanisms. PCL provides simple high-level syntax for local and remote adaptation operations, local and remote performance monitoring (and aggregation), and for performing adaptations synchronously or asynchronously with respect to the execution of the application process initiating the adaptation. The global task graph representation enables remote performance metrics and adaptation operations to be specified in simple global terms by any process, and the compiler and runtime system automatically perform the communication and synchronization required for the remote operations. The paper describes the conceptual adaptation framework, the PCL language, and our implementation of the PCL compiler and runtime system. The paper uses three adaptative applications examples to illustrate the capabilities and benefits of PCL, and to show experimentally that the performance overheads of using PCL for implementing an adaptive application are negligible.

Gas Well Production Optimization with Remote Performance Monitoring

Abstract Monitoring gas production with mechanical chart recorders and the associated business practices results in significant loss of earnings due to data inaccuracies, late identification of well shutdown, and operational inefficiencies. To solve this, several current technologies have now been integrated into a low cost end-to-end system called FINE. This technical note describes FINE and provides field data demonstrating the benefits. Introduction Gas flow measurement has been dominated by 100-year-old circular chart technology. "Charts" record differential pressures generated across an orifice plate (and the static pressures and inflow temperatures) at a gas meter. These differential pressures are converted into flow rates by standardized AGA flow calculations(1,2). The process of chart measurement involves a laborious cycle of collecting charts, chart integration and data entry, which often takes weeks to return information to the decision makers. This mechanical measurement necessarily involves lost earnings due to data inaccuracies, late identification of well shutdown, and operational inefficiencies. Electronic flow measurement (EFM) has been an alternative to charts for many years. It is based upon electronic gas measurement standards established by the American Petroleum Institute(3). However, the cost and construct of acquisition and dissemination with engineered SCADA (Supervisory Control and Data Acquisition) solutions have prevented widespread acceptance or use by a large number of stakeholders within an organization who could add value. Integrated technologies now permit practical acquisition of electronic gas flow measurement from every well, and dissemination for use by everyone within an organization. These technologies all adhere to a basic system structure T. Ito calls "FINE"(4). FINE Technology FINE stands for Field Instrument (FI), Network (N) and End user (E). FINE is a seamless system design that, in spite of the measurement complexity, simplifies data acquisition so that monitoring costs are similar to that of a chart, and dissemination is seamless to everyone from managers to investors on their PCs. (See Figure 1.) FINE's structure is revolutionary, involving end-to-end, internet- based metrology systems and preferably built on autonomous networkable transmitters. FINE integrates:transmitters with digital sensor cores,public wireless communications,high performance embedded processors, micro-power electronics (FI), and solar power operation,central digital nervous system (N), anddatabase and web interface tools (E). The transmitter connects wirelessly through a network to an Internet information delivery system using full-duplex asynchronous communication made possible by embedded processors. Increase Revenues, Reduced Costs When gas producers and transmission companies apply FINE systems to gas well monitoring, they can realize increased revenues and reduced operating costs. Revenues are increased by:Reduced downtime (e.g., by exception alarming)Improved allocations (e.g., by higher accuracy)Optimized field production (e.g., by daily monitoring of wells, well testing, and regular gas-in-place estimates) FINE reduces costs by:Improved operator efficiency (e.g., focusing on operations)

Design of a new airport surveillance radar (ASR-9)

The ASR-9 marks a significant departure from earlier ASR designs [1]. Major operational benefits are realized by applying modern digital technology and advanced processing concepts. It is evolutionary in that it retains the desirable features of its predecessors. This paper will focus on the principal characteristics that make its design unique. The following topics are covered: aircraft detection in clutter, range resolution, azimuth resolution, weather contouring, remote performance monitoring and control.