6 resultados para predictive maintenance
em Universidade Federal do Rio Grande do Norte(UFRN)
Resumo:
In the artificial lift method by Electrical Submersible Pump (ESP), the energy is transmitted for the well´s deep through a flat electric handle, where it is converted into mechanical energy through an engine of sub-surface, which is connected to a centrifugal pump. This transmits energy to the fluid under the pressure form, bringing it to the surface In this method the subsurface equipment is basically divided into: pump, seal and motor. The main function of the seal is the protect the motor, avoiding the motor´s oil be contaminated by oil production and the consequent burning of it. Over time, the seal will be wearing and initiates a contamination of motor oil, causing it to lose its insulating characteristics. This work presents a design of a magnetic sensor capable of detecting contamination of insulating oil used in the artificial lift method of oil-type Electrical Submersible Pump (ESP). The objective of this sensor is to generate alarm signal just the moment when the contamination in the isolated oil is present, enabling the implementation of a predictive maintenance. The prototype was designed to work in harsh conditions to reach a depth of 2000m and temperatures up to 150°C. It was used a simulator software to defined the mechanical and electromagnetic variables. Results of field experiments were performed to validate the prototype. The final results performed in an ESP system with a 62HP motor showed a good reliability and fast response of the prototype.
Resumo:
Induction motors are one of the most important equipment of modern industry. However, in many situations, are subject to inadequate conditions as high temperatures and pressures, load variations and constant vibrations, for example. Such conditions, leaving them more susceptible to failures, either external or internal in nature, unwanted in the industrial process. In this context, predictive maintenance plays an important role, where the detection and diagnosis of faults in a timely manner enables the increase of time of the engine and the possibiity of reducing costs, caused mainly by stopping the production and corrective maintenance the motor itself. In this juncture, this work proposes the design of a system that is able to detect and diagnose faults in induction motors, from the collection of electrical line voltage and current, and also the measurement of engine speed. This information will use as input to a fuzzy inference system based on rules that find and classify a failure from the variation of thess quantities
Resumo:
This work was motivated by the importance of conducting a study of vehicle emissions in captive fleets with diesel engine, coupled with the predictive maintenance plan. This type of maintenance includes techniques designed to meet the growing market demand to reduce maintenance costs by increasing the reliability of diagnoses, which has increased interest in automated predictive maintenance on diesel engines, preventing problems that might evolve into routine turn into serious situations, solved only with complex and costly repairs, the Reliability Centered Maintenance, will be the methodology that will make our goal is reached, beyond maintaining the vehicles regulated as fuel consumption and emissions. To Therefore, technical improvements were estimated capable of penetrating the automotive market and give the inshore fleet emission rates of opacity of the vehicles, being directly related to the conditions of the lubricating oil thus contributing to reducing maintenance costs by contributing significantly to emissions of pollutants and an improvement in the air in large cities. This criterion was adopted and implemented, em 241 buses and produced a diagnosis of possible failures by the correlation between the characterization of used lubricating oils and the analysis of opacity, with the objective of the aid the detection and solution of failures for the maintenance of sub-systems according to design criteria, and for this to be a deductive methodology to determine potential causes of failures, has been automated to implement a predictive maintenance system for this purpose was used in our study a mobile unit equipped with a opacimeter and a kit for collection and analysis of lubricating oil and the construction of the network diagnostics, we used a computer program in Microsoft Office Access 2007 platform tool is indispensable for creating a database data, this method is being used and successfully implemented in seven (7) bus companies from the city of Natal (RN) Brazil
Resumo:
The simulation of SES-Natal Ponta Negra: mitigation of environmental risks and predictive maintenance strategy was developed in the context of several operational irregularities in the pumping stations and sewage systems in the system Ponta Negra. Thus, the environmental risks and complaints against the company due to overflows of sewage into the public thoroughfare became common. This neighborhood has shown in recent years an increase of resident higher than the initial expectation of growth. In this sense presumed the large population growth and generation of sewers higher than expected, associated to the use of corrective maintenance and misuse of the system may be the main causes of operational failures occurring in the SES. This study aimed at analyzing the hydraulic behavior of SES Ponta Negrathrough numerical simulation of its operation associated to future scenarios of occupation. The SES Ponta Negra has a long lengthof collection networks and 6 pumping stations interconnected, being EE 1, 2, 4 coastal way, and beach Shopping interconnected EE3 to receives all sewers pumped from the rest pumping station and pumped to the sewage treatment station of neighborhood which consists of a facultative pond followed by three maturation ponds with disposal of treated effluent into infiltration ditches. Oncethey are connected with each other, the study was conducted considering the days and times of higher inflow for all lifts. Furthermore, with the aim of measuring the gatherer network failures were conducted data survey of on the networks. Thephysical and operational survey data was conducted between January/2011 and janeiro/2012. The simulation of the SES was developed with the aim ofdemonstrating its functioning, eithercurrently and in the coming years, based in population estimates and sewage flow. The collected data represents the current framework of the pumping stations of the SES Ponta Negra and served as input to the model developed in MS Excel ® spreadsheet which allowed simulating the behavior of SES in future scenarios. The results of this study show thatBeach Shopping Pumping Station is actually undersized and presents serious functioning problemsthatmay compromise the environmental quality of surrounding area. The other pumping stations of the system will reach itsmaximum capacity between 2013 and 2015, although the EE1 and EE3 demonstrateoperation capacity, even precariously, until 2017. Moreover, it was observed that the misuse of the network system, due to the input of both garbage and stormwater, are major factors of failures that occur in the SES. Finally, it was found that the corrective maintenance appliance, rather than predictive,has proven to beinefficient because of the serious failuresin the system, causing damage to the environment and health risks to users
Resumo:
With the heavy use of bearings in various segments of the industry, there are a large number of necessary interruptions in industrial processes to perform maintenance on these devices, with the case study wind turbines. The growth of the wind energy sector, encouraged to conduct research that helps to solve this problem. To contribute to predictive maintenance has been carried out a signal analysis using techniques which allow detection and location of the problem in order to prevent accidents caused and losses due to unexpected equipment failures, whereas low system rotation complicates the detection of the failure. To work around this problem, there was the indication of standard signals for defects in the bearings, making diagnosis of possible failures. With this diagnosis can be performed predictive maintenance, identifying the failure of the system that were tested, such as the introduction of grains of sand in the bearing, wear on the outer race of the bearing and bearing rust. By processing signals it is possible to construct graphs developing a mapping of defects by different peaks in the frequency band.
Resumo:
In the artificial lift method by Electrical Submersible Pump (ESP), the energy is transmitted for the well´s deep through a flat electric handle, where it is converted into mechanical energy through an engine of sub-surface, which is connected to a centrifugal pump. This transmits energy to the fluid under the pressure form, bringing it to the surface In this method the subsurface equipment is basically divided into: pump, seal and motor. The main function of the seal is the protect the motor, avoiding the motor´s oil be contaminated by oil production and the consequent burning of it. Over time, the seal will be wearing and initiates a contamination of motor oil, causing it to lose its insulating characteristics. This work presents a design of a magnetic sensor capable of detecting contamination of insulating oil used in the artificial lift method of oil-type Electrical Submersible Pump (ESP). The objective of this sensor is to generate alarm signal just the moment when the contamination in the isolated oil is present, enabling the implementation of a predictive maintenance. The prototype was designed to work in harsh conditions to reach a depth of 2000m and temperatures up to 150°C. It was used a simulator software to defined the mechanical and electromagnetic variables. Results of field experiments were performed to validate the prototype. The final results performed in an ESP system with a 62HP motor showed a good reliability and fast response of the prototype.