Application of the FSOM to Machine Vibration Monitoring

Fuzzy Control ◽  
2000 ◽  
pp. 397-405 ◽  
Author(s):  
Ingo Jossa ◽  
Uwe Marschner ◽  
Wolf-Joachim Fischer
Keyword(s):  
Vibration Monitoring ◽  
Machine Vibration

scholarly journals Towards Industrial Ultra-Wideband Networks: Experiments for Machine Vibration Monitoring

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 42576-42583
Author(s):  
Jorge F. Schmidt ◽  
Denis Chernov ◽  
Christian Bettstetter
Keyword(s):  
Ultra Wideband ◽  
Vibration Monitoring ◽  
Machine Vibration

scholarly journals Rotary machine vibration monitoring and smart balance correction

2020 ◽  
Vol 12 (6) ◽  
pp. 168781402093603
Author(s):  
Chao-Hui Ou ◽  
Cheung-Hwa Hsu ◽  
Gui-Jie Fan ◽  
Wei-Yu Chen
Keyword(s):  
Vibration Monitoring ◽  
Machine Vibration ◽  
Rotary Machine ◽  
Double Frequency ◽  
Correction Rate ◽  
Amplitude Correction ◽  
Current Health Status ◽  
Frequency Correction ◽  
Machine Interface ◽  
Balance Correction

During the rotary machine operation process, seemingly small amounts of abnormal vibration can often cause serious damage to the machinery over time and even increase the risk of accidents. Although professional vibration engineers can determine the current health status of a machine by interpreting the vibration spectrum information and predicting which components will fail, if even ordinary operators can send feedback regarding the vibration signals reaching the human–machine interface through a system when an abnormality is detected in the machine, the abnormality can be made known and processed in time. This can prevent the magnified impact of rotary inertia, thereby lowering the risk of major damage and the failure of machinery and equipment, as well as effectively saving on equipment maintenance costs. This study mainly adopted LabVIEW and Arduino IDE to develop a control program and human–machine monitoring interface. As the initial experiment on rotary machine vibration monitoring and smart balance correction, the measurement system setup in this study was applied to determine vibration abnormality as well as to carry out continuous online automatic balance correction. Experimental verification was carried out using active correction and smart correction. In terms of active online balance correction, the amplitude correction rate was 96%, the double-frequency correction rate was 102.9%, and the correction process was performed in 5 min. In terms of smart balance correction, the amplitude correction rate was 103.8%, the double-frequency correction rate was 103.3%, and the correction process was performed in 3 min. Through feedback signaling, the operator can effectively learn the current health status of the mechanical equipment from the human–machine interface.

scholarly journals A Methodology for Protective Vibration Monitoring of Hydropower Units Based on the Mechanical Properties

2013 ◽  
Vol 135 (4) ◽  
Author(s):  
Mattias Nässelqvist ◽  
Rolf Gustavsson ◽  
Jan-Olov Aidanpää
Keyword(s):  
Mechanical Properties ◽  
Mechanical Vibration ◽  
International Organization ◽  
Vibration Monitoring ◽  
Design Criteria ◽  
Hydraulic Power ◽  
Load Measurement ◽  
Machine Vibration ◽  
International Organization For Standardization ◽  
Shape Deviations

It is important to monitor the radial loads in hydropower units in order to protect the machine from harmful radial loads. Existing recommendations in the standards regarding the radial movements of the shaft and bearing housing in hydropower units, ISO-7919-5 (International Organization for Standardization, 2005, “ISO 7919-5: Mechanical Vibration—Evaluation of Machine Vibration by Measurements on Rotating Shafts—Part 5: Machine Sets in Hydraulic Power Generating and Pumping Plants,” Geneva, Switzerland) and ISO-10816-5 (International Organization for Standardization, 2000, “ISO 10816-5: Mechanical Vibration—Evaluation of Machine Vibration by Measurements on Non-Rotating Parts—Part 5: Machine Sets in Hydraulic Power Generating and Pumping Plants,” Geneva, Switzerland), have alarm levels based on statistical data and do not consider the mechanical properties of the machine. The synchronous speed of the unit determines the maximum recommended shaft displacement and housing acceleration, according to these standards. This paper presents a methodology for the alarm and trip levels based on the design criteria of the hydropower unit and the measured radial loads in the machine during operation. When a hydropower unit is designed, one of its design criteria is to withstand certain loads spectra without the occurrence of fatigue in the mechanical components. These calculated limits for fatigue are used to set limits for the maximum radial loads allowed in the machine before it shuts down in order to protect itself from damage due to high radial loads. Radial loads in hydropower units are caused by unbalance, shape deviations, dynamic flow properties in the turbine, etc. Standards exist for balancing and manufacturers (and power plant owners) have recommendations for maximum allowed shape deviations in generators. These standards and recommendations determine which loads, at a maximum, should be allowed before an alarm is sent that the machine needs maintenance. The radial bearing load can be determined using load cells, bearing properties multiplied by shaft displacement, or bearing bracket stiffness multiplied by housing compression or movement. Different load measurement methods should be used depending on the design of the machine and accuracy demands in the load measurement. The methodology presented in the paper is applied to a 40 MW hydropower unit; suggestions are presented for the alarm and trip levels for the machine based on the mechanical properties and radial loads.

Sign in / Sign up

Export Citation Format

Share Document