The use of different sensor technologies is important for diagnosing asset health. Learn about the sensor technologies and algorithms InsightCM works with to help machine analysts find and diagnose faults before they cause a production stoppage.
One of the most well-known approaches to monitoring, vibration is the predominant diagnostic technology for rotating machinery. Analysts use vibration data to catch failure modes such as misalignment, rolling-element bearing faults, looseness, bent shafts, and gear mesh issues on assets such as turbines, motors, pumps, grinders, rollers, shredders, gear boxes, and many others that use a rotating shaft.
Many vibration sensors, such as accelerometers, velocity sensors, and proximity probes, can ultimately provide the same type of information. Vibration signals consist of multifrequency components, and each component represents part of the vibration. These individual vibration components add up to create the overall vibration signal.
You can perform two types of vibration analysis using InsightCM: vibration levels to describe the waveform and spectral bands to describe the spectrum (essentially, a fast Fourier transform of the waveform).
Vibration analysis focuses on either levels that describe the waveform or spectral calculations that describe specific frequency content. InsightCM includes several default level and band calculations, and you can create custom bands to trend bands that correlate with known faults such as a bearing or gear mesh issues. You can calculate these features on Continuous Monitoring Systems to immediately detect fault conditions and trigger data collections based on the asset operating state.
Several industry-standard vibration analyses can help you identify faults. For example, you can use an orbit plot to see how a shaft is rotating in a bearing on a turbine and identify worn bearings or inadequate lubrication. Envelope (demodulation) analysis is commonly used for rolling-element bearings to better identify impacting frequencies that correlate with bearing faults.
InsightCM includes these viewers:
Continuous Monitoring Systems for MCSA uses voltage and current signals to determine motor faults including rotor bar damage, misalignment, eccentricity, mechanical looseness, or bearing problems. To measure voltage and current signatures, you use potential transducers (PTs) and current transducers (CTs), respectively, to monitor the signals. InsightCM is optimized to detect rotor bar damage in three-phase AC induction electric motors.
Figure 4 shows the installation of a Continuous Monitoring System for MCSA. Each monitoring system is designed to monitor a single voltage bus that contains up to nine AC induction motors. Continuous Monitoring Systems for MCSA are intended to be installed near the motor control cabinet, which contains access to the power and protective relays for each of the motors.
You use PTs to monitor the phases of the voltage bus. With InsightCM, you can configure two- or three-phase wye or delta wiring. Then you use CTs to monitor current flow to each motor as it progresses through a protective relay.
For MCSA, InsightCM focuses predominantly on rotor bar damage, though you can observe bearing problems in the electrical signals if the issues grow severe. NI also focuses heavily on three-phase AC induction motors. Continuous Monitoring Systems for MCSA are not designed to be used with variable frequency drive motors at this time.
|Line RMS, phasor phase and magnitude; motor line frequency, unbalance, derating factor, efficiency, speed, effective service factor, rotor bar sideband, power, load, torque, and torque ripple||Startup current waveform, startup time, startup peak amps|
Continuous Monitoring Systems for MCSA compute a different set of algorithms specific to electrical data and motors. You can calculate the phasors from the raw voltage and current waveforms. In addition, you can analyze the voltage and current waveforms together as a set to determine motor health parameters. Continuous Monitoring Systems for MCSA also can collect the startup current to help you compute startup parameters and ensure you are not starting up motors without the appropriate load.
Note that conducting MCSA requires a different set of expertise compared with vibration analysis.
InsightCM includes these MCSA viewers:
Sometimes you cannot install temperature sensors on certain assets, such as transformers, breakers, motors, and switchgear. Thermal imaging, or thermography, is a technology that allows you to noninvasively measure temperature by measuring thermal energy. This is ideal for locations where access is risky or impractical. You can detect a variety of mechanical and electrical anomalies using thermal imaging because it involves trending temperature values. Examples of anomalies you can detect include improper lubrication, misalignment, friction points, or insulation breakdown.
Thermal imaging analysis is more straightforward than vibration analysis or MCSA. You specify regions of interest (ROIs) from which the maximum, minimum, and average of those ROIs are calculated. With a delta feature, you can calculate the temperature difference between any number of ROIs to help you normalize for environmental conditions. If you are monitoring a transformer, for instance, you may want to trend the temperature of the individual bushings and the delta between all the bushings. If one of the bushings heats up more than the others, this may be an indication of insulation breakdown.
On the hardware side, note that thermal cameras have different resolutions and fields of view. You need to select the proper camera to achieve the right coverage and accuracy for the area you are monitoring.
InsightCM provides a thermal imaging viewer you can use to review the radiographic image with the configured ROIs displayed.
|Regions of Interest||Delta|
|Minimum, maximum, and average temperature||Difference between selected ROIs|
EMSA is used to monitor energized, high-voltage assets (typically generators and transformers). It monitors high-frequency portions of a spectrum (from 30 kHz to 100 kHz) for recognizable signatures. Examples of abnormalities you can detect with EMSA are arcing, corona, gap discharges, partial discharge, noise, and sparking.
EMSA uses a high-frequency current transformer (HFCT) that is often clamped around the ground connection. Typically, you clamp the radio frequency current transformer (RFCT) around an insulator (such as a PVC pipe split down the middle) in case there is a high voltage on the ground cable during a fault and you don’t want to damage the CT.
Continuous Monitoring Systems for EMSA sweep across the frequency spectrum to acquire high-frequency data and then calculate the power values for specific bands that correlate with known faults of the energized asset. You can use InsightCM to trend the band values and view the spectra via a waterfall for visual interpretation of how they have changed over time.
|Default Bands (User Configurable)|
|30 kHz - 500 kHz|
|500 kHz - 5 MHz|
|5 MHz - 30 MHz|
|30 MHz - 100 MHz|
|Total Power in Band|