Preventive Maintenance for Roller and Journal Bearings of Induction Motor Based on the Diagnostic Signature Analysis

1986 ◽  
Vol 108 (1) ◽  
pp. 26-31 ◽  
Author(s):  
T. Koizumi ◽  
M. Kiso ◽  
R. Taniguchi
Keyword(s):  
Preventive Maintenance ◽  
Diagnostic Procedure ◽  
Failure Modes ◽  
Induction Motors ◽  
Early Stage ◽  
Diagnostic System ◽  
Journal Bearings ◽  
Diagnostic Signature ◽  
Almost All ◽  
Practical Field

This paper is concerned with the preventive maintenance of roller and journal bearings installed in induction motors. Almost all kinds of failure modes happening on both roller and journal bearings have been reproduced and classified using time and frequency domain data analysis. Diagnostic procedure also has been derived using these analyzed results and statistical method. Finally, an actual diagnostic system for the early stage detection of defected roller bearings has been developed for practical field use.

scholarly journals Automatic Fault Diagnostic System for Induction Motors under Transient Regime Optimized with Expert Systems

Electronics ◽  
2018 ◽  
Vol 8 (1) ◽  
pp. 6 ◽  
Author(s):  
Jordi Burriel-Valencia ◽  
Ruben Puche-Panadero ◽  
Javier Martinez-Roman ◽  
Angel Sapena-Bano ◽  
Manuel Pineda-Sanchez ◽  
...  
Keyword(s):  
Fault Diagnosis ◽  
Expert Systems ◽  
Induction Motors ◽  
Early Stage ◽  
Diagnostic System ◽  
Transient Regime ◽  
Economic Losses ◽  
Diagnostic Systems ◽  
Time Frequency ◽  
Cage Induction Motor

Induction machines (IMs) power most modern industrial processes (induction motors) and generate an increasing portion of our electricity (doubly fed induction generators). A continuous monitoring of the machine’s condition can identify faults at an early stage, and it can avoid costly, unexpected shutdowns of production processes, with economic losses well beyond the cost of the machine itself. Machine current signature analysis (MCSA), has become a prominent technique for condition-based maintenance, because, in its basic approach, it is non-invasive, requires just a current sensor, and can process the current signal using a standard fast Fourier transform (FFT). Nevertheless, the industrial application of MCSA requires well-trained maintenance personnel, able to interpret the current spectra and to avoid false diagnostics that can appear due to electrical noise in harsh industrial environments. This task faces increasing difficulties, especially when dealing with machines that work under non-stationary conditions, such as wind generators under variable wind regime, or motors fed from variable speed drives. In these cases, the resulting spectra are no longer simple one-dimensional plots in the time domain; instead, they become two-dimensional images in the joint time-frequency domain, requiring highly specialized personnel to evaluate the machine condition. To alleviate these problems, supporting the maintenance staff in their decision process, and simplifying the correct use of fault diagnosis systems, expert systems based on neural networks have been proposed for automatic fault diagnosis. However, all these systems, up to the best knowledge of the authors, operate under steady-state conditions, and are not applicable in a transient regime. To solve this problem, this paper presents an automatic system for generating optimized expert diagnostic systems for fault detection when the machine works under transient conditions. The proposed method is first theoretically introduced, and then it is applied to the experimental diagnosis of broken bars in a commercial cage induction motor.

scholarly journals Increasing Electric Vehicles Reliability by Non-Invasive Diagnosis of Motor Winding Faults

Energies ◽  
2021 ◽  
Vol 14 (9) ◽  
pp. 2510
Author(s):  
Konrad Górny ◽  
Piotr Kuwałek ◽  
Wojciech Pietrowski
Keyword(s):  
Electric Vehicles ◽  
Diagnostic Method ◽  
Induction Motors ◽  
Early Stage ◽  
Short Circuit ◽  
Damage Classification ◽  
Non Invasive ◽  
Signal Features ◽  
Empirical Wavelet Transform ◽  
Simulation Results

The article proposes a proprietary approach to the diagnosis of induction motors allowing increasing the reliability of electric vehicles. This approach makes it possible to detect damage in the form of an inter-turn short-circuit at an early stage of its occurrence. The authors of the article describe an effective diagnostic method using the extraction of diagnostic signal features using an Enhanced Empirical Wavelet Transform and an algorithm based on the method of Ensemble Bagged Trees. The article describes in detail the methodology of the carried out research, presents the method of extracting features from the diagnostic signal and describes the conclusions resulting from the research. Phase current waveforms obtained from a real object as well as simulation results based on the field-circuit model of an induction motor were used as a diagnostic signal in the research. In order to determine the accuracy of the damage classification, simple metrics such as accuracy, sensitivity, selectivity, precision as well as complex metrics weight F1 and macro F1 were used.

scholarly journals Evaluation of Energy Absorption Capabilities of Polyethylene Foam under Impact Deformation

Materials ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3613
Author(s):  
Baohui Yang ◽  
Yangjie Zuo ◽  
Zhengping Chang
Keyword(s):  
Energy Absorption ◽  
Failure Modes ◽  
High Strain ◽  
Early Stage ◽  
High Energy ◽  
Test Method ◽  
Test Theory ◽  
Strain Rates ◽  
Impact Properties ◽  
The Impact

Foams are widely used in protective applications requiring high energy absorption under impact, and evaluating impact properties of foams is vital. Therefore, a novel test method based on a shock tube was developed to investigate the impact properties of closed-cell polyethylene (PE) foams at strain rates over 6000 s−1, and the test theory is presented. Based on the test method, the failure progress and final failure modes of PE foams are discussed. Moreover, energy absorption capabilities of PE foams were assessed under both quasi-static and high strain rate loading conditions. The results showed that the foam exhibited a nonuniform deformation along the specimen length under high strain rates. The energy absorption rate of PE foam increased with the increasing of strain rates. The specimen energy absorption varied linearly in the early stage and then increased rapidly, corresponding to a uniform compression process. However, in the shock wave deformation process, the energy absorption capacity of the foam maintained a good stability and exhibited the best energy absorption state when the speed was higher than 26 m/s. This stable energy absorption state disappeared until the speed was lower than 1.3 m/s. The loading speed exhibited an obvious influence on energy density.

Characteristics and attitudes of family planners in Khartoum, Sudan

1982 ◽  
Vol 14 (1) ◽  
pp. 7-16 ◽  
Author(s):  
M. A. Khalifa
Keyword(s):  
Family Planning ◽  
Birth Control ◽  
Early Stage ◽  
Significant Proportion ◽  
Large Family ◽  
Capital City ◽  
Age Group ◽  
African Countries ◽  
The Mean ◽  
Almost All

SummaryIn a survey of 1475 urban Moslem wives in the age group 15–49 living in the capital city of the Sudan, knowledge of birth control was reported by almost all respondents while a significant proportion had used contraception at least once. The mean age of the users was 32·8 years, their duration of marriage was 15·1 years and their mean number of surviving children was 4·6. Those who had never used contraception had a higher mean age, a longer duration of marriage and more surviving children. Most of the users had an urban residential background and belonged to the high socioeconomic class. They held favourable attitudes to family planning. Although they thought that having a large family (more than five children) was not desirable, their mean preferred family size was no different from that of the never users.The results indicate that contraception is used for the purpose of spacing births rather than limiting their ultimate number. At this early stage of contraceptive adoption in Sudan, the characteristics of the pioneer acceptors are similar to those observed in other African countries.

Sample selection of prognostics validation test based on multi-stage Wiener process

2018 ◽  
Vol 233 (4) ◽  
pp. 605-614
Author(s):  
Zhiao Zhao ◽  
Yong Zhang ◽  
Guanjun Liu ◽  
Jing Qiu
Keyword(s):  
Wiener Process ◽  
Process Model ◽  
Failure Modes ◽  
Early Stage ◽  
Sample Selection ◽  
Degradation Process ◽  
Time Interval ◽  
Degradation Data ◽  
Multi Stage ◽  
Selection Of

Sample allocation and selection technology is of great significance in the test plan design of prognostics validation. Considering the existing researches, the importance of prognostics samples of different moments is not considered in the degradation process of a single failure. Normally, prognostics samples are generated under the same time interval mechanism. However, a prognostics system may have low prognostics accuracy because of the small quantity of failure degradation and measurement randomness in the early stage of a failure degradation process. Historical degradation data onto equipment failure modes are collected, and the degradation process model based on the multi-stage Wiener process is established. Based on the multi-stage Wiener process model, we choose four parameters to describe different degradation stages in a degradation process. According to four parameters, the sample selection weight of each degradation stage is calculated and the weight of each degradation stage is used to select prognostics samples. Taking a bearing wear fault of a helicopter transmission device as an example, its degradation process is established and sample selection weights are calculated. According to the sample selection weight of each degradation process, we accomplish the prognostics sample selection of the bearing wear fault. The results show that the prognostics sample selection method proposed in this article has good applicability.

Evaluation of Performance of Various Coolant Grades When Turning Ti-6Al-4V Alloy With Uncoated Carbide Tools Under High-Pressure Coolant Supplies

2018 ◽  
Vol 141 (1) ◽  
Author(s):  
Emmanuel O. Ezugwu ◽  
Rosemar B. da Silva ◽  
John Bonney ◽  
Eder S. Costa ◽  
Wisley F. Sales ◽  
...  
Keyword(s):  
High Pressure ◽  
Failure Modes ◽  
Physical Damage ◽  
Evaluation Of Performance ◽  
Life Tool ◽  
Resistance To Oxidation ◽  
Tension Properties ◽  
Almost All ◽  
Coolant Delivery ◽  
High Pressure Coolant

This work presents the evaluation of three commercially available coolant grades (dicyclohexylamine-based coolant, a triethanolamine-based coolant, and an ester-based coolant) when machining Ti-6Al-4V alloy with high-pressure coolant delivery. The evaluations were based on tool life, tool failure modes, surface integrity, and chip formation. The dicyclohexylamine-based coolant was the more effective coolant when machining at the highest pressure of 20.3 MPa due to its stability at elevated temperature, whereas the triethanolamine-based coolant performed effectively at a pressure of 11 MPa due to its low surface tension properties. Deterioration of the ester-based coolant was found in almost all coolant pressures due to its low resistance to oxidation. Surfaces generated when machining with all coolants grades were generally acceptable with negligible physical damage.

scholarly journals Smart-Sensors to Estimate Insulation Health in Induction Motors via Analysis of Stray Flux

Energies ◽  
2019 ◽  
Vol 12 (9) ◽  
pp. 1658 ◽  
Author(s):  
Israel Zamudio-Ramirez ◽  
Roque Alfredo Osornio-Rios ◽  
Miguel Trejo-Hernandez ◽  
Rene de Jesus Romero-Troncoso ◽  
Jose Alfonso Antonino-Daviu
Keyword(s):  
Induction Motors ◽  
Early Stage ◽  
Industrial Sector ◽  
Smart Sensors ◽  
Discrete Wavelet ◽  
Electrical Machine ◽  
Smart Sensor ◽  
Time Frequency ◽  
Essential Components ◽  
Winding Insulation

Induction motors (IMs) are essential components in industrial applications. These motors have to perform numerous tasks under a wide variety of conditions, which affects performance and reliability and gradually brings faults and efficiency losses over time. Nowadays, the industrial sector demands the necessary integration of smart-sensors to effectively diagnose faults in these kinds of motors before faults can occur. One of the most frequent causes of failure in IMs is the degradation of turn insulation in windings. If this anomaly is present, an electric motor can keep working with apparent normality, but factors such as the efficiency of energy consumption and mechanical reliability may be reduced considerably. Furthermore, if not detected at an early stage, this degradation could lead to the breakdown of the insulation system, which could in turn cause catastrophic and irreversible failure to the electrical machine. This paper proposes a novel methodology and its application in a smart-sensor to detect and estimate the healthiness of the winding insulation in IMs. This methodology relies on the analysis of the external magnetic field captured by a coil sensor by applying suitable time-frequency decomposition (TFD) tools. The discrete wavelet transform (DWT) is used to decompose the signal into different approximation and detail coefficients as a pre-processing stage to isolate the studied fault. Then, due to the importance of diagnosing stator winding insulation faults during motor operation at an early stage, this proposal introduces an indicator based on wavelet entropy (WE), a single parameter capable of performing an efficient diagnosis. A smart-sensor is able to estimate winding insulation degradation in IMs using two inexpensive, reliable, and noninvasive primary sensors: a coil sensor and an E-type thermocouple sensor. The utility of these sensors is demonstrated through the results obtained from analyzing six similar IMs with differently induced severity faults.

scholarly journals Flexural Behavior of Fire-Damaged Prefabricated RC Hollow Slabs Strengthened with CFRP versus TRM

Materials ◽  
2020 ◽  
Vol 13 (11) ◽  
pp. 2556
Author(s):  
Zheng-Ang Sui ◽  
Kun Dong ◽  
Jitong Jiang ◽  
Shutong Yang ◽  
Kexu Hu
Keyword(s):  
Failure Modes ◽  
Early Stage ◽  
Load Capacity ◽  
Peak Load ◽  
Flexural Behavior ◽  
Masonry Building ◽  
Fire Exposure ◽  
Standard Fire ◽  
Four Point Bending ◽  
Strengthening Technique

In this paper, carbon fiber reinforced polymer (CFRP) and textile reinforced mortar (TRM) strengthening techniques were proposed to retrofit and strengthen fire-damaged prefabricated concrete hollow slabs. A total of six slabs, from an actual multi-story masonry building, were tested to investigate the flexural performance of reinforced concrete (RC) hollow slabs strengthened with TRM and CFRP. The investigated parameters included the strengthening method (CFRP versus TRM), the number of CFRP layers, and with or without fire exposure. One unstrengthened slab and one TRM strengthened slab served as the control specimens without fire exposure. The remaining four slabs were first exposed to ISO-834 standard fire for 1 h, and then three of them were strengthened with CFRP or TRM. Through the four-point bending tests at ambient temperature, the failure modes, load and deformation response were recorded and discussed. Both CFRP and TRM strengthening methods can significantly increase the cracking load and peak load of the fire-damaged hollow slabs, as well as the stiffness in the early stage. The prefabricated hollow slabs strengthened by CFRP have better performance in the ultimate bearing capacity, but the ductility reduced with the increase of CFRP layers. Meanwhile, the TRM strengthening technique is a suitable method for the performance improvement of fire-damaged hollow slabs, in terms of not only the load capacity, especially the cracking load, but also the flexural stiffness and deformation capacity.

scholarly journals Bipolar Outflows and Stellar Jets

1987 ◽  
Vol 115 ◽  
pp. 213-237 ◽  
Author(s):  
Ronald L. Snell
Keyword(s):  
Physical Properties ◽  
High Velocity ◽  
Molecular Clouds ◽  
Early Stage ◽  
Young Stellar Objects ◽  
Molecular Gas ◽  
Bipolar Outflows ◽  
Stellar Objects ◽  
Stellar Jets ◽  
Almost All

A wealth of data is now available on the energetic mass outflows that are associated with young stellar objects. This phenomenon is thought to occur at a very early stage in the evolution of stars of almost all masses. The discovery of this energetic event was first made through observations of the rapidly expanding molecular gas that surrounds many of these young stellar objects. A review of the physical properties, including the energetics and morphology, of the expanding molecular gas is presented in this paper. In addition, the role these energetic winds play in affecting the dynamics of the parental molecular clouds is also discussed. Finally, the results of detailed studies of the structure and kinematics of the high velocity molecular gas are reviewed and the evidence for existance of wind-swept cavities and molecular shells within the clouds are presented.

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