Condition Monitoring Systems Of Wave Energy Converters - RiaSor
Condition Monitoring Systems of Wave Energy Converters June 2018 CorPower C3 WEC at EMEC Scapa Flow wave test site, Orkney Colin Keldie
Project Information Project title Reliability in a Sea of Risk 2 Project Acronym RiaSoR 2 Duration 24 months Month 1 September 2016 Project manager Johannes Hüffmeier RISE Work package leader Othmane El Mountassir Offshore Renewable Energy Catapult Work package number/name WP 5 Objective Condition monitoring system Framework and Data Processing Requirements of Condition Monitoring Systems for Wave Energy Converters Date of submission 19/06/2018 Revision Revision no. Revision Text Initials 1.0 Draft report 1 to be issued for comments/ additional contribution OEM 2.0 Complete and update the report CSM/OEM RiaSoR 2018 Date 17/05/2018 i
Contents 1 Introduction 1.1 RiaSoR background 1 1 2 Aim of condition-based monitoring 2 3 Condition monitoring systems in offshore wind 2 3.1 CMS based techniques & methods 2 3.2 Condition monitoring of offshore wind turbine main components 4 3.3 Typical measurement parameters of condition monitoring systems in an offshore wind turbine 5 3.4 4 Wave Energy Converters 4.1 5 Commercially available condition monitoring systems Wave devices types 7 8 8 4.2.1 Attenuator 9 4.2.2 Point absorber 9 4.2.3 Pressure differential 9 4.2.4 Oscillating wave surge 9 4.2.5 Oscillating water column 9 4.2.6 Overtopping 10 4.3 Wave energy extraction 10 4.4 Failure modes of WEC 11 WEC condition monitoring system requirements 12 5.1 General specification 12 5.2 Detection methods 13 5.2.1 Structural Sensing Methods 14 5.2.2 Hydraulic Sensing Methods 16 5.2.3 Electrical Sensing Methods 17 5.2.4 Mooring Sensing Methods 18 5.2.5 Instrumentation Methods 19 5.3 Standards 19 5.4 Signal Properties 21 5.4.1 Signal Conditioning 22 5.4.2 Sampling rate 23 5.4.3 Aliasing 23 5.5 Data acquisition of the WEC 23 5.5.1 DAQ Device 24 5.5.2 Analogue-to-Digital Converter (ADC) 25 5.5.3 DAQ resolution 25 RiaSoR 2018 ii
5.5.4 Absolute Accuracy 25 5.5.5 Data Storage 26 5.5.6 DAQ Software 27 5.6 Signal Processing 5.6.1 6 Digital Filters Communication Architecture 28 29 29 6.1 Wave Energy Converter Area network 30 6.2 Farm Area Network 31 6.3 Control Area Network 31 7 Conclusion 32 8 References 33 Appendix A: RiaSoR 2018 35 iii
List of Figures Figure 1 RiaSoR 1 & RiaSoR 2 overview . 1 Figure 2 Wave energy converters design concept [3] . 8 Figure 3 Wave energy extraction concept [3] . 10 Figure 4 Simplified diagram of the power take off concepts [4] . 10 Figure 5 Common failure modes present in WECs . 12 Figure 6 Failure modes sensing technologies . 13 Figure 7 Flow chart of a Data Acquisition system [12] . 24 Figure 8 Comparison of 3-bit and 16-bit [13] . 25 Figure 9 Condition monitoring. Communication architecture . 30 List of Tables Table 1 Typical component defects within wind turbine nacelle and common condition monitoring/ inspection techniques employed . 5 Table 2 Typical wind turbine monitoring requirements. 6 Table 3 Core reasons for WEC failures . 13 Table 4 ISO Standards. 20 Table 5 IEC Standards . 20 Table 6 VDI Standards (Association of German Engineers) . 20 Table 7 Signal Measurements. 21 Table 8 Signal conditioning per type of sensor and measurements . 23 Table 9 Hardware and circuitry of the DAQ device [12] . 24 Table 10 Condition monitoring data storage example. 26 RiaSoR 2018 iv
Executive Summary There is a progression towards lowering the price of offshore renewable energy including the wave energy sector. Accessibility is a challenge with offshore generation devices including wave energy converters (WEC) and this is why the deployment of condition-based monitoring systems will be crucial to support operation activities. Condition monitoring systems are used to optimise maintenance and provide early detection while also reducing access constraints. This report study provides an insight into condition monitoring of Wave Energy Converters. There is a wide range of wave energy technologies, each using different solutions to absorb energy from waves depending on the water depth and location. There is little convergence amongst the wave energy technologies, however, the industry shows many different alternatives to harnessing wave power under different conditions. It is believed that existing monitoring systems within the wave devices developed to date draw directly from current technologies and advances made in the wind and other industries. Defects and errors can affect the operation or structural integrity of the wave energy device. Failure modes are the various ways in which the WEC could possibly fail and monitoring systems are often used to anticipate complete failure and for fault detection. Based on literature key WECs failure modes identified include, mechanical, electrical, structural and marine environment impact. Based on these failure modes, a number of sensing technologies and systems were proposed to monitor the integrity of the WEC device. The proposed sensors and method of detection must be able to provide effective failure detection and meet the requirements of accuracy, cost effectiveness and long-term stability. CMS uses detection methods with analogue signals which must be conditioned before being digitised. Signal conditioning is the next stage of processing where the signal is made available for data analyses. Signal conditioning requirements in terms of amplification, attenuation and filtering to improve signal accuracy were also addressed in this report. Based on IEC 61400-25 standard which addresses all aspects of communication architecture for the monitoring and control of wind power plants, an example of a WEC device communication architecture concept was proposed including the positioning of the monitoring, protection and control information equipment at different location within the device. The concept divides the whole architecture of the WEC into multiple segments where; (i) the device front end (PTO) is equipped with a number of sensing and monitoring equipment, (ii) the controller is located behind the generator and (iii) the grid compliant generated power, metering and user control interface. General procedures which must be considered when setting up condition monitoring within sub-assemblies of machines like wave energy converters. As such a number of relevant standards and procedures for condition monitoring were summarised. It is believed that the communications for monitoring and control of wind power plants (IEC 61400-25) is conveniently compatible with WEC applications. The basic concept of this IEC is a breakdown of compliant services and the different communication profiles available for data interchange, allowing all data from the devices to follow the same format. RiaSoR 2018 v
1 Introduction 1.1 RiaSoR background The goal of the RiaSoR project is to consistently learn from the physical interactions between the devices and their environments, while embedding this understanding and building robustness into marine energy technology designs to improve reliability. Marine energy devices operate in harsh environments but still need to perform reliably and produce an expected amount of energy, which gives rise to huge engineering challenges. The OceanERANET-funded RiaSoR 2 project will use the theoretical reliability assessment guideline for wave and tidal energy converters (WEC/TEC) developed in RiaSoR1 and apply it to the field. This will enable WEC/TEC developers to validate their findings, and establish a practical condition based monitoring platform to prepare for future arrays where big data handling and processing will be vital to drive down operational expenditures (OPEX). Figure 1 RiaSoR 1 & RiaSoR 2 overview The RiaSoR 1 reliability guideline built upon established practices from the automotive industry where a monitoring framework is applied to a fleet of test-vehicles. Through design iterations, the reliability is improved and a final reduced set of sensors are deployed in the commercial vehicle. For RiaSoR 2, the chosen components for monitoring are equipped with several sensors to collect the required data, which will then be fed into the reliability process to reduce uncertainties. Sea tests act as case studies to feed the methodologies and training into the guideline. The findings from this will then be trialled with the other developers. The key objective of the RiaSoR 2 project is to offer a comprehensive suite of testing methodologies to wave and tidal developers that will enable a systematic approach to achieve optimal reliability and performance, while minimising cost and time-to-market. RiaSoR 2018 P a g e 1
2 Aim of condition-based monitoring In the offshore renewable sector operating and maintenance organisation plays an important role to maintain the operations and efficiency of offshore devices like a WEC. Conditionbased monitoring contributes to the safety and economy of the WEC plant. Condition-based monitoring is used to evade downtime and faults due to unexpected failures in the WEC and to reduce the costs related to maintenance. Typical aims of the conditionbased monitoring system include: Diagnosis of potential anomalies within the plants Avoidance of unplanned production downtimes Reduce the need for repairs and optimise planned maintenance Increased availability Planning of repair Plant/system protection Reduction of maintenance costs Preventive and predictive maintenance (CBM) Knowledge driven product development 3 Condition monitoring systems in offshore wind Condition monitoring systems have been implemented successfully in the offshore wind industry using an extensive array of measurement techniques and analysis methods where both offline visual inspections and online oil, vibration, speed and power quality measurements were used. Typical CMS currently being used in the wind energy sector include vibration measurement to evaluate and quantify gearbox and bearing health, acoustic emission measurement for noise and stress levels of rotating machinery, and oil monitoring to analyse oil moisture, temperature and debris content. There are different analysis and techniques on which monitoring systems are based upon, these are presented in the following sections. 3.1 CMS based techniques & methods Vibration analysis Currently the most extensive technology applied for condition monitoring, especially for rotating equipment. In the case of wind turbines, it has been applied for gearbox, generator bearing and main bearing CM. Generally, a baseline sample of vibration levels is collected for a healthy wind turbine, from which operating vibrations are compared. An “out of range” vibration will signify a fault, which can be further diagnosed by analysing the frequency of the vibration. Acoustic Emission Acoustic Emission (AE) is related to vibration monitoring but with a different principle because in the acoustic monitoring case, the acoustic sensors “listen” to the component RiaSoR 2018 P a g e 2
instead of registering its local motion. AE sensors detect the stress waves that are generated during crack initiation and propagation within materials. AE has been shown to detect some faults earlier than vibration analysis. AE has been applied successfully to gearboxes, bearings and blades. The AE technique does not require trending like the vibration method. Although now AE has found limited use so far in the wind energy industry largely due to the lack of sufficient experience with the application of this technique for WT gearbox monitoring, it is predicted this will change in the near future. Oil analysis Oil analysis is mainly carried out offline by taking oil samples for laboratory evaluation. However, for safeguarding the oil quality, application of on-line sensors is increasing since various oil analysis sensors are nowadays available at an acceptable price including wear debris detectors and moisture sensors which measure the presence of water in the lubricant oil of the WT gearbox. Characterisation of parts is often only performed in case of abnormalities. Practically all utility scale WTs employ oil temperature sensors nowadays to avoid overheating of the lubricating oil which may result in combustion and subsequently loss of a WT due to fire. Thermography Thermography is often used for monitoring electrical and electronic components; in particular it could be applied to monitor failure prone power electronics. Currently, this technique is only applied off-line, but the development of on-line monitoring techniques will likely induce a larger uptake of this technology for turbine monitoring. Strain measurement Strain measurement of turbine blades is generally performed with strain gauges; however, the development of a cost effective optical fibre strain measurement device will likely increase the use of strain measurements for turbine monitoring. Ultrasonic Widely used for the analysis of turbine towers and blades, ultrasonic techniques can evaluate the structural integrity of the turbine by detailing the size and location of defects within the material. Eddy current inspection Eddy current sensors are a well-established technology that are commonly used within NDT technology. Using either a permanent or oscillating magnetic field, the passing of conducting material induces eddy currents into the material. This in turn generates an opposing magnetic field, which leads to a change in voltage within the sensing coil. Eddy current inspection can be applied for the detection of fatigue cracks on the WT tower. However, encircling coils have been lately applied for detection of debris in the lubricant as mentioned earlier in this section. Any metallic debris ferrous or non-ferrous passing through the encircling coil will change its impedance response. Depending on the amount and type of change in the impedance response of the encircling coil the nature of the particle, ferrous or non-ferrous that caused the variation in the electromagnetic field within the sensor can be ascertained together with its dimensional range. Radiography RiaSoR 2018 P a g e 3
Taking X-rays of blades and towers is very rarely undertaken in the wind industry, although it can provide useful information regarding the structural condition of the turbine. Portable radiography-based systems will reduce the cost of this technique which may increase its use within industry. Shock Pulse Method Only occasionally used within industry, the shock pulse method detects shock waves when a rolling element in a bearing comes into contact with a damaged area of the raceway or debris. Electrical Effects Motor Current Signature Analysis or MCSA is used to detect unusual phenomena in electrical components. Deflection based methods Sections of the device which are loaded with a weight or can move free-standing will be subject to warping of some extent. Measuring deflections can be achieved by calculating the relevant distances. 3.2 Condition monitoring of offshore wind turbine main components Table 1 summarises typical defects commonly detected by wind turbine operators within the nacelle as well as the techniques used to evaluate them. In addition to condition monitoring, periodic inspection of main turbine components is also carried out as part of the maintenance regime. It is anticipated that with current evolution of condition monitoring systems that regular visual inspection will probably be phased out completely in the forthcoming years. Table 1 Key A: Severity in case of occurrence, B: Interest in improving detection method; (1 lowest, 5 highest) Component CM & Inspection Severity A B Vibration analysis and inspection every 12 months 5 5 Housing cracks Standard preventive inspection every 6 months 5 3 Bearings Vibration analysis, inspection every 6 months (video scope) 4 5 Gears Vibration analysis, inspection every 6 months (video scope) 5 5 Lubricant Oil analysis and 6 months inspection 4 5 Main bearings Gearbox Coupling RiaSoR 2018 P a g e 4
Vibration analysis and alignment every 24 months 3 5 Bearing Vibration analysis and inspection every 12 months 4 5 Unbalance Vibration analysis and inspection every 12 months 3 3 Other Vibration analysis and inspection every 12 months 3 5 Yaw Drive Standard preventive inspection every 6 months 2 4 5 3 5 3 5 5 4 5 misalignment Generator Yaw Yaw gear Yaw Bearing Blades bearings Hydraulic system Standard visual inspection every 6 months Vibration analysis and standard visual inspection every 6 months Standard preventive inspection every 6 months Oil analysis and 6 months preventive inspection Table 1 Typical component defects within wind turbine nacelle and common condition monitoring/ inspection techniques employed 3.3 Typical measurement parameters of condition monitoring systems in an offshore wind turbine To effectively monitor all components within a wind turbine using conventional CM systems it is conceivable that the requirements stated in Table 2 may be required. The data presented in the table illustrates the amount of data that would typically be collected per day for monitoring a single wind turbine, although the use of sensors with lower class types may result in lower sampling rate and thus a reduced amount of data. Component Measurement Sample Rate (Sa/s) Quantity Blade 1 Load (X&Y) 1000 2 Blade 2 Load (X&Y) 1000 2 Blade 3 Load (X&Y) 1000 2 Main Bearing Vibration (X&Y&Z) 2000 6 Main Bearing Temperature 1 4 RiaSoR 2018 P a g e 5
Gearbox LSS Bearing Vibration (X&Y&Z) 2000 3 Gearbox LSS Bearing Temperature 1 4 Low Speed Shaft Torque 1000 1 Gearbox Stage 3 Vibration (X&Y) 2000 2 Gearbox Stage 3 Temperature 1 4 Gearbox Stage 2 Vibration (X&Y) 2000 2 Gearbox Stage 2 Temperature 1 4 Gearbox Stage 1 Vibration (X&Y) 2000 2 Gearbox Stage 1 Temperature 1 4 Gearbox HSS Bearing Vibration (X&Y) 2000 3 Gearbox HSS Bearing Temperature 1 4 Generator DE Bearing Vibration (X&Y) 2000 2 Generator DE Bearing Temperature 1 4 Generator NDE Bearing Vibration (X&Y) 2000 2 Generator NDE Bearing Temperature 1 4 Generator winding Temperature 1 12 Encoder Shaft Speed 10 1 Tower X,Y,Z Sway 1000 3 Converter Voltage 25000 3 Converter Current 25000 3 Total samples Total data per day (32 bit storage) 207654 72 GB per day Table 2 Typical wind turbine monitoring requirements RiaSoR 2018 P a g e 6
Clearly, transferring 72GB of data daily per turbine would be inefficient for turbine monitoring as it would add significantly to the technical complexity of any system, and therefore increasing system cost. For this reason, many systems have adopted on-site analysis of data and transfer only a reduced amount of raw or aggregated data. Furthermore, key parameter indicators (KPIs) can be established for certain components being monitored. In the event where the value of one or more KPIs exceed a certain threshold an alarm can be given and the signal which provided the alarm can be downloaded and assessed further. Certain commercial systems such as the Bruel and Kjaer’s Vibro system transfer high resolution data once readings have passed a pre-defined threshold, which can then be monitored at a central data analysis centre. Another method of reducing data transfer requirements includes Gram and Juhl’s turbine condition monitoring. This system uses multiple sensors that feed into an on-site processing unit on the turbine. The results of the analysis are then reported back to the wind farm server system, rather than the raw data. 3.4 Commercially available condition monitoring systems There are several wind turbine condition monitoring systems which are commercial today. Several of the available commercial wind turbine condition monitoring systems have been certified by DNV GL or other certification organisations. Manufacturers of wind turbine condition monitoring systems can be found from all over the world with a significant number of them based in Europe. The list of available commercial wind turbine condition monitoring products is constantly growing with more organisations trying to enter the market. There is a particular interest from SMEs in entering the wind turbine condition monitoring market which is currently dominated by larger industrial organisations. Wind turbines condition monitoring market is particularly competitive and cost remains a key factor during selection. In the future other factors including stricter insurance company requirements will play a significant role in the selection of CMS and components being monitored. Practically all industrial wind turbines make use of some sort of CMS which in most cases includes vibration analysis capability apart from temperature measurements. Depending on the system used and the available signal analysis methodologies the reliability of the resulting information gained from the CMS can vary significantly. Sampling rates, types of sensors number of sensors used and signal processing methodologies may differ substantially for CMS provided by different manufacturers. It is important to minimise the number of sensors required to monitor critical components such as the gearbox, generator, main bearing or power electronics in order to keep the cost of the CMS as low as possible. An acceptable CMS cost cannot exceed 10,000-15,000 for most large scale commercial WTs under the current status quo. In certain cases, operators may opt for manual measurements rather than continuous monitoring. It is important to acknowledge the effect of variable wind speed and wind turbulence during vibration, AE and oil analysis measurements related to the gearbox and generator. The RiaSoR 2018 P a g e 7
value, efficiency and reliability of CMS is yet to be proven due to the very unpredictable and variable loading conditions under which WTs operate. However, insurance policies do require by default the use of CMS and therefore operators and manufacturers have no other option than to use such systems. However, in the future insurance requirements will become stricter and the exact output of CMS will be taken into account whenever claims are filed. Also, operators will probably become more interested in verifying the exact condition of WTs that pass to their responsibility after the guarantee from the manufacturer has ended. Previous research efforts [1], [2] have identified commercially available condition monitoring systems, which have been analysed in terms of the monitoring technology and analysis methods. Summary of his previous work is detailed in Appendix A and has been expanded upon with more up-to-date sources. 4 Wave Energy Converters 4.1 Wave devices types There is a wide range of wave energy technologies, each using different solutions to absorb energy from waves depending on the water depth and location. There is little convergence amongst the wave energy technologies, however, the industry shows many different alternatives to harnessing wave power under different conditions. Wave energy devices can be categorised into six main types: (i) Attenuator; (ii) Point absorber; (iii) Oscillating wave surge converter; (iv) Oscillating water column; (v) Overtopping device; (vi) Submerged pressure differential. Figure 2, presents the concept of the different main types of wave energy converters which were defined by the RiaSoR I project as follow: Figure 2 Wave energy converters design concept [3] RiaSoR 2018 P a g e 8
4.2.1 Attenuator An attenuator is a floating device which operates parallel to the predominant wave direction and effectively rides the waves. These devices capture energy from the relative motion of the two arms as the wave passes them. These technologies typically follow the design of long multi-segment structures with each segment following oncoming waves from the crest to trough. The floating pontoons are usually located either side of some form of power converting module. The relative motion between each pontoon can be converted to mechanical power in the power module, through either a hydraulic circuit or some form of mechanical gear train 4.2.2 Point absorber A point absorber is a floating structure which absorbs energy from all directions through its movements at/near the water surface. It converts the motion of the buoyant top relative to the base into electrical power. The power take-off system may take a number of forms, depending on the configuration of displacers/reactors. A point absorber typically possesses small dimensions relative to the incident wavelength. The structure can heave up and down on the surface of the water or be submerged below the surface relying on pressure differential. 4.2.3 Pressure differential Submerged pressure differential devices are submerged point absorbers that are typically located near shore and attached to the seabed. The motion of the waves causes the sea level to rise and fall above the device, including a pressure differential in the device. This water pressure above the device compresses the air within the cylinder, moving the upper cylinder down. The alternating pressure pumps fluid through a system to generate electricity. 4.2.4 Oscillating wave surge An oscillating wave surge converter extracts energy from wave surges and the movement of water particles within them. The arm oscillates as a pendulum mounted on a pivoted joint in response to the movement of water in the waves which then moves in a back and forth motion, exploiting the horizontal particle velocity of the wave. The design typically comprises of a surge displacer which can be hinged at the top or bottom. It can be attached on the seabed, or near the shore. Energy is usually extracted using hydraulic converters secured to a reactor. If the device is used on the shoreline it is common to hinge the displacer above the water, enabling the incoming surge waves to impact on the displacer first, and then be captured within the device to form a water column. 4.2.5 Oscillating water column An oscillating water column is a partially submerged, hollow structure. It is open to the sea below the water line, enclosing a column of air on top of a column of water. Waves cause the water column to rise and fall, which in turn compresses and decompresses the air column. This trapped air can flow to and from the atmosphere via a turbine. A low-pressure Wells turbine is commonly used in conjunction with this device as it rotates in the same direction irrespective of the airflow direction. The rotation of the turbine is used to generate electricity. RiaSoR 2018 P a g e 9
4.2.6 Overtopping Overtopping devices capture water as waves break into a storage reservoir. The water is then returned to the sea passing through a conventional low-head turbine which generates power. An overtopping device may use ‘collectors’ to concentrate the wave energy. 4.3 Wave energy extraction Current WEC designs differ widely in their energy extraction method but all require a power take-off unit (PTO) to convert the irregular mechanical motion of the primary wave interface into electrical generation. Current devices use pneumatically, hydraulically, and mechanically power take off. Figure 3 and Figure 4 present the concept of the different conversion stages of the main different types of WECs and a simplified concept diagram of the PTO options respectively. Figure 3 Wave energy extraction concept [3] Figure 4 Simplified diagram of the power take off concepts [4] RiaSoR 2018 P a g e 10
It is believed that existing monitoring systems within the wave devices developed to date draw directly from current technologies and advances made in the wind and other industries. Monitoring techniques include the monitoring of generators, gearboxes and bearings using a range of sensors such as vibration, acoustic, temperature, speed, oil, current and voltage outputs. In addition, due to the mechanical loading to which most of the WECs are subjected to, sufficient structural health monitoring is required to be in place to detect any potential deformations or fractures of the mechanical structures. More importantly, the monitoring of the functionalities of the control and safety systems needs to be well designed to ensure the WECs are able to respond to system operation and potential faults. Reliability Centred Maintenance relies on determining the maintenance requirements of a functional system in its operating context while a failure modes and effect analysis (FMEA) is used in order to determine critical failure modes, their consequences and root causes. Using this analysis, measures can be identified to predict and prevent potential failures. As such, due to the various design types of WECs and req
3 Condition monitoring systems in offshore wind 2 3.1 CMS based techniques & methods 2 3.2 Condition monitoring of offshore wind turbine main components 4 3.3 Typical measurement parameters of condition monitoring systems in an offshore wind turbine 5 3.4 Commercially available condition monitoring systems 7 4 Wave Energy Converters 8
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