Wind Turbine Drivetrain Vibration Analysis
Evaluates drivetrain vibration health across three subsystems: main bearing, gearbox, and generator.
When to Use
Load this skill when the user wants to:
- - Assess drivetrain vibration health from CMS or SCADA data
- Interpret RMS, peak-to-peak, or spectral findings for main bearing, gearbox, or generator
- Correlate vibration alarms with operational events
- Decide whether to continue operating, increase monitoring, or shut down
Drivetrain Components
| Component | Sensor Location | Key Frequencies |
|---|
| Main Bearing | Non-drive end, drive end | BPFO, BPFI, BSF, FTF |
| Gearbox LSS |
Low speed shaft | Gear mesh (LSS x teeth), bearing defect freqs |
| Gearbox IMS | Intermediate shaft | IMS gear mesh harmonics |
| Gearbox HSS | High speed shaft | HSS gear mesh, bearing defect freqs |
| Generator NDE | Non-drive end bearing | Electrical harmonics, bearing defect freqs |
| Generator DE | Drive end bearing | Bearing defect freqs, rotor unbalance |
Vibration Thresholds (ISO 10816 / CMS Reference)
| Location | Normal | Warning | Critical |
|---|
| Main Bearing RMS (g) | < 0.3 | 0.3 - 0.8 | > 0.8 |
| Gearbox HSS RMS (g) |
< 0.5 | 0.5 - 1.5 | > 1.5 |
| Gearbox LSS/IMS RMS (g) | < 0.3 | 0.3 - 1.0 | > 1.0 |
| Generator RMS (g) | < 0.5 | 0.5 - 1.2 | > 1.2 |
| Peak-to-peak step change | < 10% | 10-30% | > 30% |
Note: Always evaluate against site-specific baseline. A 20% rise from stable baseline is more significant than an absolute value alone.
Frequency Fault Signatures
| Fault | Frequency Signature |
|---|
| Bearing outer race (BPFO) | (N/2) x (1 - d/D x cos a) x RPM |
| Bearing inner race (BPFI) |
(N/2) x (1 + d/D x cos a) x RPM |
| Gear mesh | number of teeth x shaft RPM |
| Gear mesh sidebands | GMF +/- shaft frequency |
| Rotor unbalance | 1x RPM dominant |
| Misalignment | 2x RPM dominant, axial component |
| Looseness | Sub-harmonics (0.5x, 1.5x) or high harmonic content |
Severity Scale
| Severity | Label | Description | Action |
|---|
| 1 | Healthy | All values normal, stable trend | Continue normal operation |
| 2 |
Early warning | 1-2 parameters in warning zone, stable | Increase CMS polling frequency |
| 3 | Moderate | Multiple warning flags or single critical | Inspect within 2 weeks |
| 4 | Significant | Critical zone or rapid trend growth | Plan shutdown within 48-72 hours |
| 5 | Critical | Multiple critical flags, step-change | Immediate shutdown required |
Procedure
- 1. Collect inputs: CMS trend (last 30-90 days), current RMS and peak-to-peak per component, frequency spectrum findings, SCADA alarms, operational context.
- Evaluate RMS values against thresholds. Flag Warning or Critical zones.
- Analyze trend:
- Stable: value in warning zone but flat for >30 days = lower urgency
- Gradual rise: value increasing steadily = schedule inspection
- Step change: sudden jump >30% = treat as Critical regardless of absolute value
- 4. Interpret frequency spectrum if available:
- Match dominant peaks to fault signatures table
- Note sidebands around gear mesh frequencies
- Note sub-harmonics or 1x/2x dominance
- 5. Correlate with SCADA alarms and operational events.
- Assign severity per component, then determine drivetrain-level severity as highest.
- Generate output report using the format below.
Output Format
=== DRIVETRAIN VIBRATION REPORT ===
ASSET : [Turbine ID]
SITE : [Site name]
DATA PERIOD : [Date range of CMS/SCADA data]
MISSING DATA : [List any unavailable inputs]
MAIN BEARING:
RMS : [value] g - [Normal / Warning / Critical]
Trend : [Stable / Gradual rise / Step change]
Spectrum : [Key findings or not available]
SCADA Alarms : [Count and type]
Severity : [1-5] - [Label]
GEARBOX (LSS / IMS / HSS):
RMS : LSS [value] g / IMS [value] g / HSS [value] g
Trend : [per shaft]
Spectrum : [Key findings]
SCADA Alarms : [Count and type]
Severity : [1-5] - [Label]
GENERATOR (DE / NDE):
RMS : DE [value] g / NDE [value] g
Trend : [per bearing]
Spectrum : [Key findings]
SCADA Alarms : [Count and type]
Severity : [1-5] - [Label]
DRIVETRAIN SEVERITY : [1-5] - [Label]
SHUTDOWN : [Yes / No / Conditional]
FAULT HYPOTHESIS:
- [e.g., HSS bearing outer race defect - BPFO peak confirmed at X Hz]
- [e.g., Gear mesh sideband modulation - possible gear wear or load variation]
RECOMMENDED ACTIONS:
- [e.g., Increase CMS polling to daily for HSS channel]
- [e.g., Oil sample with ferrography within 72 hours]
- [e.g., Plan HSS bearing replacement at next scheduled outage]
ESCALATION TRIGGERS:
- [e.g., RMS exceeds 1.5 g on HSS - immediate shutdown]
- [e.g., Step change >30% on any channel - treat as critical]
- [e.g., New BPFO or BPFI peak confirmed in spectrum - escalate to Severity 4]
Cross-Skill Correlation
If gearbox visual data is available, load wind-turbine-gearbox skill and cross-correlate:
- - High Fe ppm + rising HSS vibration = active wear confirmation
- Spalling in borescope + BPFO peak in spectrum = bearing failure progression
- Normal oil + rising vibration = early fault not yet generating debris (higher urgency)
If blade inspection data is available, check for rotor imbalance:
- - 1x RPM dominant in main bearing spectrum + blade damage = aerodynamic imbalance
- Asymmetric blade damage across A/B/C = mass or aerodynamic imbalance source
Pitfalls
- - Do not evaluate vibration in isolation. Cross-reference with oil analysis and visual inspection.
- A single high RMS reading during a storm or grid fault is not a fault indicator. Check operational context.
- Spectrum analysis requires RPM-normalized data. Raw frequency peaks are meaningless without shaft RPM.
- Generator electrical faults can appear as vibration. Check electrical data before attributing to mechanical cause.
- Stable high RMS is less urgent than rapidly rising moderate RMS. Trend rate matters more than absolute value.
Verification
After generating the report, confirm with the user:
- - Does the severity match CMS system alerts or OEM recommendations?
- Is shaft RPM data available to normalize spectrum frequencies?
- Are there recent maintenance events that could explain vibration changes?
- Is SCADA power curve deviation consistent with vibration findings?
风力发电机传动链振动分析
评估三个子系统的传动链振动健康状态:主轴承、齿轮箱和发电机。
使用时机
当用户希望以下情况时加载此技能:
- - 通过CMS或SCADA数据评估传动链振动健康状态
- 解读主轴承、齿轮箱或发电机的RMS、峰峰值或频谱分析结果
- 将振动报警与运行事件相关联
- 决定是否继续运行、加强监测或停机
传动链组件
| 组件 | 传感器位置 | 关键频率 |
|---|
| 主轴承 | 非驱动端、驱动端 | 外圈故障频率、内圈故障频率、滚动体故障频率、保持架故障频率 |
| 齿轮箱低速轴 |
低速轴 | 齿轮啮合频率(低速轴×齿数)、轴承缺陷频率 |
| 齿轮箱中间轴 | 中间轴 | 中间轴齿轮啮合谐波 |
| 齿轮箱高速轴 | 高速轴 | 高速轴齿轮啮合频率、轴承缺陷频率 |
| 发电机非驱动端 | 非驱动端轴承 | 电气谐波、轴承缺陷频率 |
| 发电机驱动端 | 驱动端轴承 | 轴承缺陷频率、转子不平衡 |
振动阈值(ISO 10816 / CMS参考值)
| 位置 | 正常 | 警告 | 临界 |
|---|
| 主轴承RMS(g) | < 0.3 | 0.3 - 0.8 | > 0.8 |
| 齿轮箱高速轴RMS(g) |
< 0.5 | 0.5 - 1.5 | > 1.5 |
| 齿轮箱低速轴/中间轴RMS(g) | < 0.3 | 0.3 - 1.0 | > 1.0 |
| 发电机RMS(g) | < 0.5 | 0.5 - 1.2 | > 1.2 |
| 峰峰值阶跃变化 | < 10% | 10-30% | > 30% |
注意:始终对照现场特定基准值进行评估。稳定基准值上升20%比单独绝对值更具意义。
频率故障特征
| 故障 | 频率特征 |
|---|
| 轴承外圈(外圈故障频率) | (N/2) × (1 - d/D × cos a) × 转速 |
| 轴承内圈(内圈故障频率) |
(N/2) × (1 + d/D × cos a) × 转速 |
| 齿轮啮合 | 齿数 × 轴转速 |
| 齿轮啮合边带 | 齿轮啮合频率 +/- 轴频率 |
| 转子不平衡 | 1倍转速主导 |
| 不对中 | 2倍转速主导,轴向分量 |
| 松动 | 次谐波(0.5倍、1.5倍)或高谐波含量 |
严重程度等级
| 严重程度 | 标签 | 描述 | 措施 |
|---|
| 1 | 健康 | 所有值正常,趋势稳定 | 继续正常运行 |
| 2 |
早期预警 | 1-2个参数处于警告区,趋势稳定 | 增加CMS轮询频率 |
| 3 | 中度 | 多个警告标志或单个临界值 | 2周内检查 |
| 4 | 显著 | 临界区或趋势快速上升 | 计划48-72小时内停机 |
| 5 | 临界 | 多个临界标志,阶跃变化 | 立即停机 |
操作流程
- 1. 收集输入:CMS趋势(最近30-90天)、各组件当前RMS和峰峰值、频谱分析结果、SCADA报警、运行背景信息。
- 对照阈值评估RMS值。标记警告或临界区。
- 分析趋势:
- 稳定:值在警告区但超过30天持平 = 紧急程度较低
- 逐渐上升:值稳定增长 = 安排检查
- 阶跃变化:突然跳变>30% = 无论绝对值如何均视为临界
- 4. 如有频谱数据则进行解读:
- 将主导峰值与故障特征表匹配
- 注意齿轮啮合频率周围的边带
- 注意次谐波或1倍/2倍转速主导
- 5. 与SCADA报警和运行事件关联。
- 按组件分配严重程度,然后确定传动链整体严重程度为最高值。
- 使用以下格式生成输出报告。
输出格式
=== 传动链振动报告 ===
资产 : [风机编号]
站点 : [站点名称]
数据周期 : [CMS/SCADA数据日期范围]
缺失数据 : [列出任何不可用的输入]
主轴承:
RMS : [值] g - [正常 / 警告 / 临界]
趋势 : [稳定 / 逐渐上升 / 阶跃变化]
频谱 : [关键发现或不可用]
SCADA报警 : [数量和类型]
严重程度 : [1-5] - [标签]
齿轮箱(低速轴 / 中间轴 / 高速轴):
RMS : 低速轴 [值] g / 中间轴 [值] g / 高速轴 [值] g
趋势 : [按轴]
频谱 : [关键发现]
SCADA报警 : [数量和类型]
严重程度 : [1-5] - [标签]
发电机(驱动端 / 非驱动端):
RMS : 驱动端 [值] g / 非驱动端 [值] g
趋势 : [按轴承]
频谱 : [关键发现]
SCADA报警 : [数量和类型]
严重程度 : [1-5] - [标签]
传动链严重程度 : [1-5] - [标签]
停机 : [是 / 否 / 有条件]
故障假设:
- [例如:高速轴轴承外圈缺陷 - 外圈故障频率峰值在X Hz确认]
- [例如:齿轮啮合边带调制 - 可能的齿轮磨损或负载变化]
建议措施:
- [例如:将高速轴通道的CMS轮询频率增加至每日]
- [例如:72小时内进行铁谱油样分析]
- [例如:计划在下一次计划停运时更换高速轴轴承]
升级触发条件:
- [例如:高速轴RMS超过1.5 g - 立即停机]
- [例如:任何通道阶跃变化>30% - 视为临界]
- [例如:频谱中确认新的外圈故障频率或内圈故障频率峰值 - 升级至严重程度4]
跨技能关联
如果齿轮箱视觉数据可用,加载风力发电机齿轮箱技能并进行交叉关联:
- - 高铁含量ppm + 高速轴振动上升 = 确认主动磨损
- 内窥镜剥落 + 频谱中外圈故障频率峰值 = 轴承故障进展
- 油品正常 + 振动上升 = 早期故障尚未产生碎屑(紧急程度更高)
如果叶片检查数据可用,检查转子不平衡:
- - 主轴承频谱中1倍转速主导 + 叶片损伤 = 气动不平衡
- A/B/C叶片不对称损伤 = 质量或气动不平衡源
常见陷阱
- - 不要孤立评估振动。与油品分析和目视检查交叉参考。
- 风暴或电网故障期间的单个高RMS读数不是故障指标。检查运行背景。
- 频谱分析需要转速归一化数据。没有轴转速的原始频率峰值毫无意义。
- 发电机电气故障可能表现为振动。在归因于机械原因之前检查电气数据。
- 稳定的高RMS比快速上升的中等RMS紧急程度低。趋势速率比绝对值更重要。
验证
生成报告后,与用户确认:
- - 严重程度是否与CMS系统警报或OEM建议一致?
- 是否有轴转速数据可用于归一化频谱频率?
- 近期是否有维护事件可以解释振动变化?
- SCADA功率曲线偏差是否与振动发现一致?