Acoustic Wave (Acoustic Emission)
Monitoring of Wind Turbines
A wind turbine’s gearbox, bearing, generator, and blades are the focus of intensive maintenance because they’re subject to a lot of stress and wear, and they are costly parts to repair.
The monitoring and testing of wind power equipment are mainly divided into two categories:
- Structural Monitoring and Testing (blades, tower, bolts).
- Condition Monitoring and Testing of the Rotating Machines (lubrication, wear, damage, etc.).
Solution and Technology
The latest RAEM AE monitoring system from Qingcheng Ltd. can effectively monitor the status of each wind turbine component.
Collect the AE signals of the wind turbine parts by AE sensors and upload the data to the specified cloud server through wireless communication after analysis and processing by the RAEM. Users can check the status of the equipment in real time on the cloud platform. At the same time, RAEM can carry out the intensity, activity, and comprehensive rating of the collected signals. When the rating results exceed the alarm threshold, the cloud server triggers the alarm and sends it to the user through email or SMS.
Cloud platform data display
Phone alarm push notifications
|Position||Model and Features||Qty||Principles|
|Inside the blades||
Access to the wind power network system; Use the tower internal power supply
|Multiple (close to blade root)||The system continuously monitors the acoustic signals generated by significant damage processes such as blade debonding, fiber fracture and crack growth, and evaluates the health of the blades.|
|Suitable positions on the rotating machines||
2-meter sensor spacing on each rotating machine; access to the wind power network system
|Multiple||The wear, pits, cracks and other faults of the rotating machines lead to characteristic acoustic signals. The system collects and analyzes the acoustic signals regularly to obtain fault information and get the damage status of the rotating equipment.|
|Impurities in lubricating oil and dry grinding caused by lack of oil can generate acoustic waves that are different from normal lubrication. The system regularly collects and analyzes acoustic wave signals, and judges the lubrication status of wind turbines based on the certain variation patterns of acoustic wave characteristic parameters with changes in lubrication status.|
|Bolts, adjacent to flanges, including tower bolts and bearings||
Access to the wind power network system for the RAEM1 inside the tower; through NB-IoT to the cloud servers for those outside the tower. Battery or DC power supply.
|Multiple (One for each bolt)||The system receives and analyzes the transient elastic waves when the wind turbine bolt cracks, breaks, loosens and other defects, and obtains the defect status information of the bolt.|
|The monitoring parts of the inner tower cylinder||
Monitors the interested parts of the tower. Access to the wind power network system. Battery or DC power supply.
|Multiple||Weak acoustic waves are often generated in the damage process of wind tower, such as deformation, cracking and crack propagation. The system receives and analyzes these acoustic waves to evaluate the health state of the tower.|
System Connection and Communication
A variety of data output communication modes (Wi-Fi, 4G, LoRa, RS485, etc.) are available for selection, according to users’ requirements in order to achieve the regular testing, or the local long-term monitoring detection, or the remote long-term monitoring detection, or other application purposes.
*Choose the appropriate communication method according to the local conditions
Four Data Communication Methods:
1)Onsite operation and display:
2)Control room operation and display
3)Remote network direct communication system
4)Remote networking communication system:
Note: The above systems have the mobile phone app with Bluetooth communication functions for patrol inspection and field debugging settings.
Main Hardware and Software Introduction
|Applications||Blade damages||Tower damages Bolt damages||Rotating devices (damages & lubrication)|
|Sensor||40KHz series/td>||150KHz series||40KHz series|
|Acquisition||Acquisition & Processor||Analog filters, digital filter, ADC etc.|
|Bluetooth (Mobile phone APP)|
|Cloud platform||Qingcheng IoT cloud platform|
|AWS (Amazon Web Services)|
|Software||SWAE analysis Software|
|RAEM Configuration Software|
|Data Format||AE Parameters||Amplitude, counts, duration, energy, rise counts, rise time, RMS, ASL, etc.||Amplitude, energy, RMS, ASL|
|Waveform||Sensor output waveform in time domain|
|Ratings||Evaluations of the results to trigger different alarm levels|
Qingcheng IOT cloud platform, Alibaba Cloud, AWS are available options. Customers can choose the Qingcheng IoT Cloud Platform, or the private cloud platforms based on their requirements.
The data can be downloaded from the cloud for further analysis using Qingcheng SWAE software, or sent directly to SWAE software for real-time analysis and processing to understand the defect details. SWAE has various analysis functions. There is location analysis, parameter analysis, correlation graph analysis, waveform analysis, fast Fourier transform, wavelet transform, rating analysis and so on.
Advantages and Conclusions
- Online --- acoustic wave (acoustic emission) monitoring system is installed on the monitoring objects surface to achieve any time any day of condition monitoring and diagnosis with online and historic data storage and displays.
- Intelligent --- auto process the monitoring data without manual controls; auto alarming for abnormal conditions; auto analyses the leak rate of the pipeline valves; auto analyses the leak areas. The whole monitoring process and result evaluations are automatic.
- Remote --- with the help of the Internet of Things technology, users can obtain the monitoring results of the monitoring points from any unlimited distance ranges at any locations.
It can achieve acoustic wave (acoustic emission) monitoring and detection of damage and lubrication status of blades, towers, bolts, rotating equipment, etc., and automatically pushed alarm information to users, facilitating timely maintenance and extending the lifespan of wind power equipment, and preventing losses and accidents caused by accumulated damage development.