Predictive Maintenance and Wind Turbine Efficiency
Vibration Monitoring Boosts Operating Efficiency
Predictive maintenance based on vibration monitoring can raise the efficiency of wind turbines, by preventing catastrophic failure and unscheduled downtime.
The cost of maintenance in the wind turbine industry is escalating because the number of turbines is increasing, including many older turbines that require more frequent maintenance. For an offshore wind farm, around one quarter of total cost is accounted for by operation and maintenance.
Introducing sophisticated condition monitoring technology can help keep these costs under control. Employing vibration monitoring to keep track of a turbine’s rotating parts helps maintenance teams to spot potential problems and carry out necessary repairs at the earliest opportunity in order to avoid breakdowns.
In this technique, the vibration signature of bearings and other moving parts is monitored using vibration sensors, also known as accelerometers. Any variation from the norm can indicate early signs of failure, allowing small problems to be corrected before they spiral out of control.
Growth and Demands of the Wind Power Industry
Wind power is a rapidly expanding area of engineering. In 2017, global capacity for wind turbines reached 539,581 according to the Global Wind Energy Council, and this figure is expected to grow significantly over the next decade.
Despite this growth, wind power remains highly demanding. To achieve profitability, operators must maximise efficiency by increasing output while controlling costs. Preventing unscheduled downtime, such as that caused by catastrophic component failure, is critical.
Wind turbines must operate under punishing conditions. In recent years, high winds have caused turbine failures due to gear damage. In addition to repair costs, operators may face fines and compensation claims.
Benefits of Advanced Vibration Monitoring
While sensors used in high specification applications such as wind turbines are top of the range, their cost has reduced sufficiently to justify the use of multiple sensors. This enhances data collection and improves fault detection.
Using multiple sensors also supports techniques such as acceleration enveloping, which extracts the vibration signal of a failing bearing by filtering out noise from other components.
Downtime Costs and Predictive Maintenance
Unscheduled downtime is not limited to the wind turbine industry. A joint survey by plantservices.com and ARC Advisory Group estimated that unscheduled downtime costs global process industries around 20 billion dollars per year.
The survey found that nearly 90 percent of companies using predictive maintenance aimed to increase uptime, while more than half sought to reduce maintenance and operational costs.
The survey recommended integrating predictive maintenance systems with plant wide control systems and linking system performance to financial incentives. This approach is particularly relevant for wind energy, where maintenance is difficult, costly, and efficiency is critical.
Historically, some engineers believed it was cheaper to continue running worn equipment rather than invest in replacements. However, when the true cost of unscheduled downtime is considered, this approach is shown to be ineffective.
Machines exhibiting defects are at greater risk of failure and downtime. Condition monitoring systems allow engineers to plan maintenance and replace defective components before failures occur.
Sensor Installation on Wind Turbines
When mounted in key positions on mechanical equipment, vibration sensors provide continuous monitoring and analysis. While this requires investment, the cost is minimal compared with the potential cost of wind turbine downtime.
There are two main types of industrial accelerometer: AC accelerometers and 4 to 20 milliamp accelerometers.
AC accelerometers are typically used with data collectors for vibration monitoring of critical or complex machines such as gearboxes and turbines, making them the preferred choice for wind turbines. In contrast, 4 to 20 milliamp sensors are commonly used with PLC systems to monitor lower value assets such as pumps and motors.
Modern vibration sensors operate over wide temperature ranges and measure both high and low frequencies with high accuracy and low hysteresis. Robust stainless steel housings protect against moisture, dust, oils, and other contaminants.
Accelerometers can be mounted on casings to measure casing vibration and the radial and axial vibration of rotating shafts. Analysis focuses on specific frequencies associated with mechanical components or fault types, such as imbalance or misalignment. For example, rolling element bearings show increasing vibration at characteristic frequencies as wear progresses.
Specifying Vibration Accelerometers for Wind Turbines
Correct specification of vibration accelerometers requires consideration of vibration levels, frequency ranges, mounting constraints, and environmental conditions. Working closely with an experienced supplier is recommended.
For wind turbine applications, low frequency accelerometers are ideal for detecting anomalies. Commonly used models include 100 millivolt per g sensors, with higher sensitivity options of 250 or 500 millivolt per g for low speed components such as generator output shafts.
In many wind turbine projects involving Hansford Sensors, a local junction box is installed at the top of the turbine to house accelerometer cabling. Signals are transmitted to ground level using multi core screened twisted pair cable, connecting to an online monitoring system.
This arrangement allows operators to monitor turbine condition in real time using handheld devices with internet access, enabling faults to be identified and corrective action taken before failure occurs.
Acceleration Enveloping for Early Fault Detection
Although modern accelerometers are highly sophisticated, isolating the signal of a malfunctioning bearing within a wind turbine can be challenging due to background vibration.
Acceleration enveloping is an effective signal processing technique that filters out low level repetitive vibrations to isolate the sound of a bearing. It is widely used to detect early bearing defects by separating fault signals from background noise.
A defect in a rolling element generates repeated impacts that excite resonant frequencies in surrounding machine structures. Although these signals decay between impacts, they influence the overall vibration response of the machine.
Acceleration enveloping enhances accelerometer signals through a two step process. First, a band pass filter isolates the frequency range where the defect signal exists. This reveals repeating high frequency impacts caused by rolling elements contacting defects.
Second, the signal is rectified and demodulated to produce an envelope that highlights the defect signal. This envelope makes regularly spaced fault signals stand out from random noise such as shaft rub.
Once filtered, vibration data is collected and analysed by specialists, who can determine whether immediate maintenance is required or if repairs can be scheduled.
