Gearbox ventilation quantity monitoring and early warning system and method

Abstract

The invention provides a gearbox ventilation quantity monitoring and early warning system and method, and belongs to the technical field of wind power generation. The system comprises a wind speed and flow sensing module, a data processing module and an early warning module; the wind speed and flow sensor module is installed on an air duct of the gearbox heat dissipation system and used for measuring the flow speed of air flowing through the gearbox heat dissipation system in real time and outputting the original wind speed. The data processing module is connected with the wind speed and flow sensing module, and is used for receiving the original wind speed signal and performing filtering and calculation processing to obtain a smooth wind speed value; the early warning module is connected with the data processing module and used for comparing and analyzing the smooth wind speed value and a preset wind speed threshold value, outputting a ventilation state judgment result and triggering an early warning signal of the corresponding level according to the ventilation state judgment result. The ventilation quantity of the gearbox is monitored in real time, the filter screen blockage problem is early warned in advance, the service life of key components such as a temperature control valve is prolonged, the maintenance strategy is optimized, non-planned shutdown is reduced, and the overall reliability of equipment is improved.

Description

Technical Field

[0001] This application belongs to the field of wind power generation technology, specifically relating to a gearbox ventilation volume monitoring and early warning system and method. Background Technology

[0002] The gearbox is the core power transmission component of a wind turbine generator set. Its operating environment is extremely harsh, subjecting it to high torque, variable loads, and complex environmental factors. The cooling system, especially the air-cooled cooling system (including the cooling system itself and filters), is crucial for maintaining stable internal gearbox temperatures, preventing lubricant oxidation and deterioration, and ensuring long-term reliable operation of the equipment.

[0003] Currently, gearbox cooling systems generally suffer from the following problems: First, the filters in the cooling system are easily clogged by dust, oil, and other contaminants, leading to reduced ventilation and low cooling efficiency. Second, insufficient ventilation causes the gearbox oil temperature to rise continuously, especially under high load or high temperature environments, easily exceeding design limits. This not only accelerates lubricating oil aging but may also cause the gearbox to operate at limited power or even shut down. Third, maintenance for clogged filters is mostly limited to fixed-cycle inspections and cleaning, lacking an intelligent early warning mechanism based on the actual filter clogging status. Fourth, traditional monitoring methods that rely solely on temperature sensors to monitor oil or bearing temperatures are lagging and cannot provide timely warnings of ventilation system problems. Fifth, as a key component for regulating lubricating oil flow, the temperature control valve, if operating under harsh conditions of poor heat dissipation and high oil temperature for extended periods, will experience accelerated fatigue and wear of its internal temperature sensing elements and actuators, leading to decreased regulation accuracy and shortened service life.

[0004] Therefore, there is an urgent need for a system and method that can monitor ventilation status in real time, provide early warnings, and guide maintenance in order to improve equipment reliability and maintenance efficiency. Summary of the Invention

[0005] In a first aspect, embodiments of this application provide a gearbox ventilation volume monitoring and early warning system, including a wind speed and flow sensing module, a data processing module, and an early warning module; The wind speed and flow rate sensor module is installed on the air duct of the gearbox cooling system to measure the air flow rate through the gearbox cooling system in real time and output the raw wind speed. The data processing module is connected to the wind speed and flow rate sensing module to receive the raw wind speed signal and perform filtering and calculation to obtain a smoothed wind speed value. The early warning module is connected to the data processing module to compare and analyze the smoothed wind speed value with the preset wind speed threshold, output the ventilation status judgment result, and then trigger the corresponding level of early warning signal based on the ventilation status judgment result.

[0006] Furthermore, the wind speed and flow rate sensor module adopts a thermal wind speed sensor, an impeller-type wind speed sensor, or an ultrasonic wind speed sensor. The wind speed and flow rate sensor module is installed in one of the following locations: In the air duct between the downstream of the filter screen and the cooling fan in the gearbox cooling system; The location of the cooling fan's exhaust vent.

[0007] Furthermore, the data processing module includes: The core processor is used to run filtering algorithms to process the raw wind speed signal and perform comparative analysis; A data storage unit is used to store preset wind speed thresholds, historical wind speed data, and early warning event records. The preset wind speed thresholds include normal thresholds, early warning thresholds, and alarm thresholds. The communication interface unit is used for data interaction with the early warning module.

[0008] Furthermore, the early warning module includes: A local early warning unit is used to provide on-site early warning through visual or auditory elements; the visual element is an indicator light, and the auditory element is a buzzer; the indicator light includes a red indicator light, a green indicator light, and a yellow indicator light; The remote communication unit is used to send early warning signals to remote monitoring terminals or designated maintenance personnel via wired or wireless networks; The early warning module executes tiered early warnings, with the specific early warning logic as follows: When the smooth wind speed value reaches the normal threshold of high pressure, no warning is issued, and the green indicator light remains on. When the smooth wind speed value is lower than the normal threshold but higher than the warning threshold, a level-of-concern warning is triggered, the green indicator light stays on, and the attention reminder is only displayed through the user interface. When the smooth wind speed value is lower than the warning threshold but higher than the alarm threshold, a warning level is triggered, the yellow indicator light stays on, and a warning reminder is displayed through the user interface. At the same time, information is sent to the remote monitoring terminal through the remote communication unit, and the event is recorded. When the smooth wind speed value is lower than the alarm threshold, an alarm-level warning is triggered, the red indicator light flashes, and the buzzer sounds at a set frequency. At the same time, an alarm reminder is displayed through the user interface, and information is sent to the remote monitoring terminal and designated maintenance personnel through the remote communication unit, and the event is recorded.

[0009] Secondly, embodiments of this application also provide a method for monitoring and early warning of gearbox ventilation volume, comprising the following steps: S1. Install the wind speed and flow sensor on the air duct of the gearbox cooling system, and connect the signal of the wind speed and flow sensor to the data processing module; S2. Based on the gearbox model, cooling system design parameters, and operating conditions, set the normal threshold for the fan speed. Warning threshold and alarm threshold ; S3. The wind speed and flow sensor operates according to a preset sampling period. Continuously collect raw data on airflow speed in the gearbox cooling duct. ; S4. Raw wind speed data collected. The wind speed value is obtained by filtering. ; S5. Smooth the wind speed value With the normal threshold of wind speed Warning threshold and alarm threshold Compare the data and determine the current ventilation status based on the comparison results; like This is considered a normal state. like It is marked as being under watch. like The status is determined to be a warning state; like The status is determined to be an alarm state; S6. Based on the current ventilation status, trigger the corresponding level of warning signal and record the time, type, and relevant parameters of the warning event; S7. Receive the manual reset command and reset the system status from the warning or alarm status to the normal monitoring status. At the same time, record the time of this maintenance event and the reset operation.

[0010] Furthermore, the specific steps in step S4 are as follows: S41. Collect raw wind speed data The following moving average filtering algorithm is used for filtering:

[0011] Where N is the sampling window size, and its value is the number of sampling points within the sampling period. This is the raw wind speed data for the i-th sampling point; S42. Use the timestamp at the center of the sampling window as the current timestamp, and then use the smoothed wind speed value. Store the current timestamp in the historical database.

[0012] Furthermore, step S5 also includes adjusting the ambient temperature. and gearbox load Dynamically adjust the normal threshold of wind speed Warning threshold and alarm threshold :

[0013]

[0014]

[0015] in, This is the adjusted normal threshold. This is the adjusted warning threshold. This is the adjusted alarm threshold. , , This is a correction factor related to ambient temperature and load.

[0016] Furthermore, it also includes the following steps: Periodically retrieve historical wind speed data from the historical database and calculate the wind speed decrease rate. ; Based on the rate of decrease in wind speed Assess the rate of filter clogging and generate a maintenance recommendation report.

[0017] Furthermore, the normal threshold for wind speed in step S2 Warning threshold and alarm threshold The settings are achieved through an experimental calibration method based on benchmark values. The specific steps are as follows: S21. Under the rated operating conditions of the gearbox and with the filter screen clean, collect the reference wind speed value in the air duct. ; S22. Based on the aforementioned reference wind speed value The initial wind speed threshold is calculated according to a predetermined proportional relationship, which is determined based on the design parameters of the gearbox cooling system, including: Normal threshold ; Warning threshold ; alarm threshold ; in, , , The preset scaling factor, and ; S23. Put the determined wind speed threshold into trial operation, and adjust the scaling factor based on the early warning records and maintenance feedback data during actual operation. , , or normal threshold Warning threshold and alarm threshold Fine-tuning and optimization were carried out.

[0018] Furthermore, it also includes the following steps: S8. Predict the health status of the filter. The specific steps are as follows: S81. Based on the smoothed wind speed values ​​in the historical database. And timestamp, extract within a set time period Characteristics of the decreasing wind speed within ; The characteristics of the decreasing wind speed Including linear fit slope, wind speed standard deviation, and values ​​below normal threshold. The cumulative percentage of time; S82. The wind speed decreasing trend characteristics The input is fed into a pre-trained filter health assessment model, which outputs a health index that characterizes the current degree of filter clogging. ; S83. Based on the aforementioned health index Historical rate of change Calculate when the filter health drops to a preset maintenance threshold. The required prediction time is the remaining effective lifespan of the filter. ; S84. When the health index Below the health warning threshold or remaining effective lifespan Below the time warning threshold At that time, predictive maintenance early warning information is generated and sent to the early warning module; The warning information includes a suggested maintenance time window.

[0019] As can be seen from the above technical solutions, this application has the following advantages: The gearbox ventilation monitoring and early warning system and method provided in this application can issue early warnings at the early stages of filter blockage or fan performance degradation by directly monitoring ventilation volume or wind speed. Compared with the prevention of abnormal oil temperature caused by insufficient ventilation, it provides a time window for prevention. By ensuring that the heat dissipation system is always in an efficient working state, the gearbox oil temperature is reduced, the heat load and wear of core components such as temperature control valves, bearings and gears are reduced, and the service life is extended. It transforms periodic maintenance into intelligent maintenance based on actual conditions, avoiding unnecessary component replacement and maintenance operations, and reducing maintenance costs. At the same time, it prevents serious failures caused by untimely maintenance, improves maintenance efficiency, reduces the number of high-temperature power-limited operations and unplanned shutdowns caused by poor heat dissipation, and improves the overall availability and power generation efficiency of wind turbine generators. Attached Figure Description

[0020] To more clearly illustrate the technical solution of this application, the accompanying drawings used in the description will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 This is a schematic diagram of the gearbox ventilation volume monitoring and early warning system of the present invention.

[0022] Figure 2 This is a schematic flowchart of the gearbox ventilation volume monitoring and early warning system method of the present invention. Detailed Implementation

[0023] The gearbox ventilation monitoring and early warning system will be described in detail below, and various embodiments of this disclosure will be described more fully. This disclosure may have various embodiments, and adjustments and changes may be made therein. However, it should be understood that there is no intention to limit the various embodiments of this disclosure to the specific embodiments disclosed herein, but rather this disclosure should be understood to cover all adjustments, equivalents, and / or alternatives falling within the spirit and scope of the various embodiments of this disclosure.

[0024] For example, in the field of wind power generation, the gearbox, as a core component, bears the heavy responsibility of power transmission, but often faces severe challenges due to high torque, variable loads, and harsh environments. Its cooling system, especially the air-cooled section, is crucial for stabilizing internal temperature, preventing lubricant deterioration, and ensuring the equipment's long-term reliability. However, existing cooling systems suffer from frequent problems: filters are easily clogged by dust and oil, causing a sharp drop in ventilation and significantly reducing cooling efficiency; insufficient ventilation leads to soaring oil temperatures, especially under high load or high temperature conditions, easily exceeding the design temperature limit, accelerating lubricant aging, and even forcing the equipment to operate at limited power or shut down; filter maintenance relies heavily on fixed-cycle inspections, lacking intelligent early warning systems and struggling to cope with sudden blockages; traditional monitoring methods, relying solely on temperature sensors, are lagging and unable to promptly detect early ventilation system faults; and temperature control valves, operating for extended periods in environments with poor heat dissipation and high oil temperatures, are prone to fatigue and wear of internal components, resulting in decreased adjustment accuracy and shortened lifespan. Therefore, developing a system that can monitor ventilation status in real time, provide intelligent early warnings, and guide precise maintenance is particularly urgent for improving gearbox reliability and maintenance efficiency.

[0025] To address the aforementioned issues, this embodiment provides a gearbox ventilation volume monitoring and early warning system. By providing real-time monitoring, intelligent early warning, and maintenance guidance for gearbox ventilation volume, it solves the problems faced by existing gearbox cooling systems, such as filter clogging, insufficient ventilation, outdated traditional monitoring methods, and unreasonable maintenance strategies. This improves the operational reliability, maintenance efficiency, and production benefits of wind turbine generator sets, while reducing equipment failure rates and maintenance costs.

[0026] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0027] Please see Figure 1 The diagram shown is a schematic of a gearbox ventilation volume monitoring and early warning system in a specific embodiment. The system includes a wind speed and flow rate sensing module, a data processing module, and an early warning module. The wind speed and flow rate sensor module is installed on the air duct of the gearbox cooling system to measure the air flow rate through the gearbox cooling system in real time and output the raw wind speed. It should be noted that the wind speed and flow rate sensor module can measure the air speed or flow rate through the heat dissipation system in real time and accurately, providing raw data support for subsequent data processing and analysis; the measurement results directly reflect the ventilation status of the heat dissipation system and are the basis for the data source of the entire monitoring and early warning system. The data processing module is connected to the wind speed and flow rate sensing module to receive the raw wind speed signal and perform filtering and calculation to obtain a smoothed wind speed value. It should be noted that the raw wind speed signal output by the wind speed and flow rate sensing module is received and processed by a filtering algorithm to effectively eliminate random noise and instantaneous fluctuation interference in the signal, resulting in a smoother and more stable wind speed value. This improves data quality and makes it easier to accurately reflect the actual operating status of the ventilation system, providing data support for subsequent ventilation status judgment. The early warning module is connected to the data processing module to compare and analyze the smoothed wind speed value with the preset wind speed threshold, output the ventilation status judgment result, and then trigger the corresponding level of early warning signal based on the ventilation status judgment result. It should be noted that by comparing and analyzing the smoothed wind speed value processed by the data processing module with the preset wind speed threshold, the current ventilation status of the gearbox cooling system can be quickly and accurately determined based on the comparison results. This enables real-time assessment of the ventilation status, providing a basis for decision-making to promptly detect ventilation anomalies and take corresponding measures. Based on the ventilation status judgment results, graded early warnings are executed to achieve effective protection and refined management of the equipment.

[0028] This embodiment uses a wind speed and flow rate sensing module to collect ventilation data in real time. After analysis and judgment by the data processing module, the early warning module issues multi-level early warning signals, realizing real-time monitoring, accurate judgment and timely early warning of the gearbox ventilation status. This provides decision-making basis for operation and maintenance personnel and effectively prevents equipment failures caused by insufficient ventilation.

[0029] Furthermore, as a refinement and extension of the specific implementation of the above embodiments, in order to fully illustrate the specific implementation process in this embodiment, another gearbox ventilation volume monitoring and early warning system is provided, which includes a wind speed and flow rate sensing module, a data processing module, and an early warning module. The wind speed and flow rate sensor module is installed on the air duct of the gearbox cooling system to measure the air flow rate through the gearbox cooling system in real time and output the raw wind speed. The data processing module is connected to the wind speed and flow rate sensing module to receive the raw wind speed signal and perform filtering and calculation to obtain a smoothed wind speed value. The early warning module is connected to the data processing module to compare and analyze the smoothed wind speed value with the preset wind speed threshold, output the ventilation status judgment result, and then trigger the corresponding level of early warning signal based on the ventilation status judgment result. The wind speed and flow rate sensor module adopts a thermal wind speed sensor, an impeller-type wind speed sensor or an ultrasonic wind speed sensor. The wind speed and flow rate sensor module is installed in one of the following locations: In the air duct between the downstream of the filter screen and the cooling fan in the gearbox cooling system; It should be noted that this location can monitor the effective airflow of the system after passing through the filter and before being sucked in by the fan; the airflow at this location has become relatively stable, and the measured value can accurately reflect the actual airflow capacity of the cooling system; the airflow data collected from this location can be directly used to assess the cleanliness of the filter; as the filter becomes more clogged, the wind speed measured at this location will show a significant downward trend, thereby achieving early warning and predictive maintenance of filter clogging; Location of the cooling fan's exhaust vent; It should be noted that this location allows for direct monitoring of the fan's airflow to assess its performance; the airflow velocity is highest at this location, making it easy to detect; by monitoring the wind speed at this location, it can be linked with the fan speed signal for analysis, thereby effectively diagnosing whether the fan has faults such as blade wear, breakage, foreign object obstruction, or reduced efficiency. The data processing module includes: The core processor is used to run filtering algorithms to process the raw wind speed signal and perform comparative analysis; A data storage unit is used to store preset wind speed thresholds, historical wind speed data, and early warning event records. The preset wind speed thresholds include normal thresholds, early warning thresholds, and alarm thresholds. The communication interface unit is used for data interaction with the early warning module; The early warning module includes: A local early warning unit is used to provide on-site early warning through visual or auditory elements; the visual element is an indicator light, and the auditory element is a buzzer; the indicator light includes a red indicator light, a green indicator light, and a yellow indicator light; The remote communication unit is used to send early warning signals to remote monitoring terminals or designated maintenance personnel via wired or wireless networks; The early warning module executes tiered early warnings, with the specific early warning logic as follows: When the smooth wind speed value reaches the normal threshold of high pressure, no warning is issued, and the green indicator light remains on. When the smooth wind speed value is lower than the normal threshold but higher than the warning threshold, a level-of-concern warning is triggered, the green indicator light stays on, and the attention reminder is only displayed through the user interface. When the smooth wind speed value is lower than the warning threshold but higher than the alarm threshold, a warning level is triggered, the yellow indicator light stays on, and a warning reminder is displayed through the user interface. At the same time, information is sent to the remote monitoring terminal through the remote communication unit, and the event is recorded. When the smooth wind speed value is lower than the alarm threshold, an alarm-level warning is triggered, the red indicator light flashes, and the buzzer sounds at a set frequency. At the same time, an alarm reminder is displayed through the user interface, and information is sent to the remote monitoring terminal and designated maintenance personnel through the remote communication unit, and the event is recorded.

[0030] like Figure 2 As shown, the following are embodiments of the gearbox ventilation volume monitoring and early warning method provided in this disclosure. This method and the gearbox ventilation volume monitoring and early warning system of the above embodiments belong to the same inventive concept. For details not described in detail in the embodiments of the gearbox ventilation volume monitoring and early warning method, please refer to the embodiments of the gearbox ventilation volume monitoring and early warning system described above.

[0031] The method includes the following steps: S1. Install the wind speed and flow sensor on the air duct of the gearbox cooling system, and connect the signal of the wind speed and flow sensor to the data processing module; It should be noted that by correctly installing the wind speed and flow sensor at a key location in the air duct of the gearbox cooling system, a foundation is provided for real-time monitoring of ventilation volume or wind speed data, ensuring accurate acquisition of ventilation information during the operation of the cooling system, and providing raw data support for subsequent data processing and early warning analysis; connecting the sensor signal to the data processing module enables information flow between the various components of the monitoring system, ensuring that data can be smoothly transmitted from the acquisition end to the processing end, thereby providing a guarantee for subsequent ventilation status judgment and early warning signal triggering; S2. Based on the gearbox model, cooling system design parameters, and operating conditions, set the normal threshold for the fan speed. Warning threshold and alarm threshold ; It should be noted that, taking into full account the differences in gearbox models, the design characteristics of the heat dissipation system, and various factors such as actual operating conditions, a wind speed threshold is set for each gearbox. This ensures that the monitoring and early warning system is more in line with the actual operating needs of the equipment, improves the accuracy of the early warning, and avoids false alarms or missed alarms caused by using a general threshold. The set wind speed threshold provides a clear quantitative standard for the subsequent data processing module to judge the ventilation status. S3. The wind speed and flow sensor operates according to a preset sampling period. Continuously collect raw data on airflow speed in the gearbox cooling duct. ; It should be noted that, based on the preset sampling period, the wind speed and flow sensor can continuously and stably collect raw wind speed data in the gearbox cooling duct, realizing real-time monitoring of the ventilation status. This ensures that even small changes in ventilation volume or wind speed can be captured in a timely manner, providing continuous data resources for subsequent data processing and analysis. This allows maintenance personnel to keep abreast of the operating status of the cooling system. As the gearbox's operating conditions change, the raw wind speed data will also change dynamically accordingly. By continuously collecting this data, the system can reflect the dynamic characteristics of the cooling system's ventilation status in real time, promptly detect abnormal fluctuations in ventilation volume, and provide the possibility for early warning and fault prevention, thus enhancing the sensitivity to changes in equipment operating status. S4. Raw wind speed data collected. The wind speed value is obtained by filtering. ; It should be noted that using a filtering algorithm to process the collected raw wind speed data can effectively remove random noise and instantaneous fluctuations, resulting in smoother and more stable wind speed values. This not only improves the quality and reliability of the data but also facilitates a more accurate reflection of the actual operating status of the ventilation system, avoiding misjudgments caused by excessive data fluctuations and providing a data foundation for subsequent ventilation status assessments. In actual operating environments, raw wind speed data is often affected by various factors, such as equipment vibration and electromagnetic interference. Through filtering, the system can reduce the impact of these interference factors on data accuracy, improve anti-interference capabilities and stability, and ensure normal and stable operation under complex working conditions, thus providing a guarantee for the safe and reliable operation of the gearbox. S5. Smooth the wind speed value With the normal threshold of wind speed Warning threshold and alarm threshold Compare the data and determine the current ventilation status based on the comparison results; like This is considered a normal state. like It is marked as being under watch. like The status is determined to be a warning state; like The status is determined to be an alarm state; It should be noted that by comparing the smoothed wind speed value with preset normal threshold, warning threshold, and alarm threshold one by one, the current ventilation status of the gearbox cooling system can be quickly and accurately determined, including normal status, watch status, warning status, and alarm status. This determination method is simple, intuitive, and easy to implement, and can provide maintenance personnel with clear ventilation status information, making it easy to quickly understand the equipment's operating status and take appropriate measures in a timely manner. Based on the comparison results, an early warning signal can be issued at an early stage when the ventilation status deviates from the normal range, reminding maintenance personnel to pay attention to abnormal ventilation and carry out inspection and maintenance, thereby avoiding further deterioration of insufficient ventilation problems, preventing failures such as excessively high gearbox oil temperature and accelerated component wear caused by poor heat dissipation, reducing equipment failure rate and maintenance costs, and improving equipment reliability. S6. Based on the current ventilation status, trigger the corresponding level of warning signal and record the time, type, and relevant parameters of the warning event; It should be noted that, based on the ventilation status assessment, the system can promptly trigger corresponding level of early warning signals. These signals, delivered visually, audibly, or via remote communication, alert maintenance personnel to abnormal ventilation in the gearbox cooling system. This ensures that maintenance personnel receive early warning information immediately, respond promptly, and take appropriate measures to prevent further escalation of the fault, reducing equipment downtime and maintenance costs. Simultaneously with triggering the early warning signal, the system records the time, type, and relevant parameters of the warning event. This not only facilitates the querying, statistical analysis, and analysis of historical early warnings by maintenance personnel but also helps identify frequent or trending problems in the ventilation system. This provides data support for optimizing system operating parameters and improving maintenance strategies. Furthermore, it allows for rapid tracing of early warning information when equipment malfunctions, providing a basis for fault diagnosis and root cause analysis, thus improving system maintainability and management efficiency. S7. Receive the manual reset command and reset the system status from the warning or alarm status to the normal monitoring status. At the same time, record the time of this maintenance event and the reset operation. It should be noted that after maintenance personnel complete the inspection and maintenance of the gearbox cooling system, the system can restore its status from the warning or alarm state to the normal monitoring state by receiving a manual reset command. This allows the system to resume real-time monitoring and analysis of ventilation volume, ensuring that the system can promptly reflect the operational status of the equipment after maintenance. This avoids disruption to normal data collection and analysis due to the system being in a warning or alarm state, thus guaranteeing the continuity and reliability of the monitoring and early warning system. By recording the time of maintenance events and reset operations, maintenance personnel can easily understand the historical status of equipment maintenance, assess the timeliness and effectiveness of maintenance work, and provide a reference for subsequent equipment operation assessments and maintenance plan development, achieving closed-loop management of the equipment maintenance process.

[0032] This embodiment enables precise monitoring, real-time early warning, and efficient maintenance of gearbox ventilation status, thereby improving the operational reliability and maintenance management level of wind turbine generator sets.

[0033] Furthermore, as a refinement and extension of the specific implementation of the above embodiments, in order to fully illustrate the specific implementation process in this embodiment, another gearbox ventilation volume monitoring and early warning method is provided, which includes the following steps: S1. Install the wind speed and flow sensor on the air duct of the gearbox cooling system, and connect the signal of the wind speed and flow sensor to the data processing module; S2. Based on the gearbox model, cooling system design parameters, and operating conditions, set the normal threshold for the fan speed. Warning threshold and alarm threshold ; Normal threshold for wind speed in step S2 Warning threshold and alarm threshold The settings are achieved through an experimental calibration method based on benchmark values. The specific steps are as follows: S21. Under the rated operating conditions of the gearbox and with the filter screen clean, collect the reference wind speed value in the air duct. ; S22. Based on the aforementioned reference wind speed value The initial wind speed threshold is calculated according to a predetermined proportional relationship, which is determined based on the design parameters of the gearbox cooling system, including: Normal threshold ; Warning threshold ; alarm threshold ; in, , , The preset scaling factor, and ; Specifically, the predetermined proportional relationship is determined based on the design ventilation volume of the gearbox cooling system, the heat load of the radiator, and the safety margin. By analyzing wind tunnel experiments and field test data of different gearbox cooling systems, the following general range of initial proportional coefficient values ​​can be derived: Normal threshold (attention threshold) ratio coefficient The value is generally between 0.80 and 0.90. Setting Basis: When the ventilation volume drops to about 85% of the design value, the heat dissipation efficiency has already noticeably decreased, and the lubricating oil temperature rise begins to accelerate; setting this point as the lower limit of the normal range (i.e., the attention-level warning point) can attract the attention of maintenance personnel as early as possible; for equipment operating in harsh environments or that is very sensitive to temperature, it is recommended to take a higher value (e.g., 0.90); for systems with good operating conditions and large redundancy, a lower value (e.g., 0.80) can be taken. Early warning threshold ratio coefficient The value is generally between 0.65 and 0.75. Setting basis: When the ventilation volume drops to about 70% of the design value, the heat dissipation capacity is significantly insufficient. Under high load or ambient temperature, the oil temperature is likely to approach or exceed the safety limit. Triggering an early warning at this point can reserve sufficient time window for planned maintenance. Alarm threshold ratio coefficient The value is generally between 0.45 and 0.55. Setting Basis: When the ventilation volume drops to 50% of the design value, the heat dissipation system has seriously failed, and the gearbox faces an immediate risk of overheating. Immediate intervention is necessary; otherwise, it may lead to power limitation or emergency shutdown of the equipment. This threshold provides a last line of defense. For example, in an application of a certain type of gearbox, the reference wind speed under a brand new filter was measured. =10 m / s; Considering the windy and sandy environment in which it operates, a conservative coefficient is selected: , , Therefore, the following calculations are made: Normal threshold =0.85×10=8.5 m / s Warning threshold =0.65×10=6.5 m / s alarm threshold =0.50×10=5.0 m / s; S23. Put the determined wind speed threshold into trial operation, and adjust the scaling factor based on the early warning records and maintenance feedback data during actual operation. , , or normal threshold Warning threshold and alarm threshold Make fine-tuning and optimization; For example, take 85%, Take 70%, Take 50%; S3. The wind speed and flow sensor operates according to a preset sampling period. Continuously collect raw data on airflow speed in the gearbox cooling duct. ; S4. Raw wind speed data collected. The wind speed value is obtained by filtering. The specific steps in step S4 are as follows: S41. Collect raw wind speed data The following moving average filtering algorithm is used for filtering:

[0034] Where N is the sampling window size, which is the number of sampling points within the sampling period (e.g., 60s). This is the raw wind speed data for the i-th sampling point; S42. Use the timestamp at the center of the sampling window as the current timestamp, and then use the smoothed wind speed value. Store the current timestamp in the historical database; S5. Smooth the wind speed value With the normal threshold of wind speed Warning threshold and alarm threshold Compare the data and determine the current ventilation status based on the comparison results; like This is considered a normal state. like It is marked as being under watch. like The status is determined to be a warning state; like The status is determined to be an alarm state; Step S5 also includes adjusting the ambient temperature. and gearbox load Dynamically adjust the normal threshold of wind speed Warning threshold and alarm threshold :

[0035]

[0036]

[0037] in, This is the adjusted normal threshold. This is the adjusted warning threshold. This is the adjusted alarm threshold. , , This is a correction factor related to ambient temperature and load; S6. Based on the current ventilation status, trigger the corresponding level of warning signal and record the time, type, and relevant parameters of the warning event; S7. Receive the manual reset command and reset the system status from the warning or alarm status to the normal monitoring status. At the same time, record the time of this maintenance event and the reset operation. It also includes the following steps: Periodically retrieve historical wind speed data from the historical database and calculate the wind speed decrease rate. ; Based on the rate of decrease in wind speed Assess the rate of filter clogging and generate a maintenance recommendation report.

[0038] In another embodiment of the present invention, unlike the embodiments described above, the following steps are also included: S8. Predict the health status of the filter. The specific steps are as follows: S81. Based on the smoothed wind speed values ​​in the historical database. And timestamp, extract within a set time period Characteristics of the decreasing wind speed within ; The characteristics of the decreasing wind speed Including linear fit slope, wind speed standard deviation, and values ​​below normal threshold. The cumulative percentage of time; S82. The wind speed decreasing trend characteristics The input is fed into a pre-trained filter health assessment model, which outputs a health index that characterizes the current degree of filter clogging. ; It should be noted that the goal of the filter health assessment model is to establish a mapping relationship between the trend of decreasing wind speed and the actual degree of filter blockage, and output a health index H of 0-100%, where 100% represents a brand new and clean filter and 0% represents a completely blocked filter. I. The input for training the filter health assessment model is determined to be multi-dimensional wind speed decline trend features extracted from historical databases. Specifically, it includes: (1) Slope of linear fitting : In the set time window ( Within 7 days, the smoothed wind speed value ( The slope obtained by performing linear regression reflects the rate of decrease in wind speed, and the calculation formula is as follows:

[0039] Where n is the number of sampling points within the time window, The timestamp of the i-th sampling point (converted to a continuous value, such as the number of hours since the start time). This represents the smoothed wind speed value at the i-th sampling point; (2) Slope of linear fitting This reflects the degree of wind speed fluctuation within a time window. The more severe the filter blockage, the greater the impact of airflow disturbance on wind speed, and the higher the standard deviation is typically. The calculation formula is:

[0040] in, This is the average smoothed wind speed within the time window, i.e. ; (3) Percentage of cumulative time below the normal threshold This reflects the frequency of wind speeds consistently falling outside the normal range. A higher percentage indicates a more severe filter clogging problem. The calculation formula is:

[0041] in, The normal threshold for wind speed after dynamic adjustment. This is an indicator function; I = 1 when the condition inside the parentheses is true, and I = 0 otherwise. II. Constructing the Training Dataset (1) Data collection and labeling Data Acquisition: Collect historical operating data of the gearbox cooling systems of at least 50 wind turbine generator sets of the same model. Each unit must include: smoothed wind speed data for 12 consecutive months. and corresponding timestamp; ambient temperature at the same time. Gearbox load L data used for dynamically adjusting thresholds; maintenance records (e.g., filter cleaning / replacement time, actual filter clogging level score at replacement time); Labeling: A combination of expert scoring and physical indicators is used to label the filter status for each time window with a true health status label. : If there are filter replacement records within this time window, use the characteristic data from the hour prior to the replacement as a sample, and label it according to the dust coverage rate on the filter surface and the ventilation resistance test value. : Dust coverage ≤10%, ventilation resistance ≤120% of design value: ; Dust coverage 10%-30%, ventilation resistance 120%-150% ; Dust coverage 30%-50%, ventilation resistance 150%-200% ; Dust coverage > 50%, ventilation resistance > 200% ; If no replacement record is available, take the characteristic data from the time interval between two adjacent maintenance cycles and label it according to the baseline wind speed attenuation rate. :

[0042] in The reference airflow speed for filter cleaning; (2) Data preprocessing Outlier removal: The 3σ criterion is used to remove extreme outliers in the wind speed data (such as zero values ​​caused by sensor failure or abnormally high values ​​far exceeding the design range). Feature standardization: Z-score standardization is applied to the three input features to eliminate the influence of units. The formula is as follows:

[0043] Where x is the original feature value (slope of the linear fit) linear fitting slope or the percentage of cumulative time below the normal threshold ), This represents the mean of the corresponding feature in the training set. The standard deviation of the corresponding feature in the training set; Dataset partitioning: The preprocessed samples are divided into a training set for model parameter learning, a validation set for hyperparameter tuning, and a test set for model generalization ability evaluation in a ratio of 7:2:1. III. Model Selection: The filter health assessment model adopts the gradient boosting tree model; The model structure is as follows: Input layer: 3 standardized features (linear fitting slope) linear fitting slope or the percentage of cumulative time below the normal threshold ); Weak learner: CART regression tree is used as the basic weak learner, and the maximum depth (max_depth) of each tree is determined by optimization on the validation set; Ensemble strategy: Iterative training through gradient boosting, adding one tree in each iteration, minimizing the loss function of the current model (e.g., using mean squared error, MSE). The training parameters are as follows: The learning rate, which is used as the step size, ranges from 0.01 to 0.3, with 0.05 being optimal. The number of weak learners as a percentage of the number of trees. The value range is 100-1000, with 500 being the optimal value. The maximum depth of a single tree, max_depth, can range from 3 to 10, with 6 being the optimal value. The minimum sample weight of the leaf node and min_child_weight, with a value range of 1-10, are optimally set to 3. The subsample, used as the sampling ratio for training samples in row sampling, ranges from 0.5 to 1.0, with 0.8 being optimal. The feature sampling ratio colsample_bytree used for column sampling has a value range of 0.5-1.0, with 0.9 being optimal. The L1 regularization coefficient reg_alpha has a value range of 0-10, with 2 being optimal. The L2 regularization coefficient reg_lambda has an extreme value range of 0-10, with 5 being optimal. The specific training steps are as follows: Initialize the model: using the mean of the true health labels of all samples in the training set. As the initial predicted value, i.e. , where x is the sample feature vector; Iterative training of weak learners: For the t-th iteration (t=1,2,..., ): Calculate the negative gradient as a residual: ,in Let be the residual of the i-th sample in the t-th iteration. Let be the predicted value of the model for the i-th sample in the (t-1)th round; Using residuals As a new label, train the t-th CART regression tree. This makes the tree's predicted values ​​as close as possible to the residuals; Calculate the weights of the tree and adjust the learning rate accordingly:

[0044] Where L is the mean squared error loss function. ; Update the model: Hyperparameter tuning: A grid search is used to traverse the range of parameter values ​​on the validation set, with the goal of minimizing the root mean square error (RMSE) of the validation set, to determine the optimal combination of parameters (i.e., the optimal value of the parameters). Model evaluation: Calculate the model's evaluation metrics on the test set. Training is complete if the following requirements are met: Coefficient of determination

[0045] The coefficient of determination reflects the explanatory power of the model. The closer to 1, the better; Mean Absolute Error ; MAE reflects the average deviation between the predicted value and the actual value.

[0046] IV. Deployment and updating of the filter health assessment model Model Deployment: Export the trained XGBoost model as a binary file (e.g., .model format) and integrate it into the data processing module; during system operation, extract wind speed data from the historical database for the past 7 days every hour, calculate 3 input features and standardize them, then input them into the model to obtain the real-time health index H; Model update: Collect new operation and maintenance data containing filter replacement records and real labels every 6 months, add the new samples to the training set, and repeat the above training steps to iteratively update the model to ensure that the model adapts to environmental changes during long-term operation (such as local air quality deterioration, equipment aging, etc.). S83. Based on the aforementioned health index Historical rate of change Calculate when the filter health drops to a preset maintenance threshold. The required prediction time is the remaining effective lifespan of the filter. ; S84. When the health index Below the health warning threshold or remaining effective lifespan Below the time warning threshold At that time, predictive maintenance early warning information is generated and sent to the early warning module; The warning information includes a suggested maintenance time window.

[0047] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0048] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A gearbox ventilation monitoring and warning system, characterized in that, The wind speed flow sensor module is installed on the air duct of the gear box heat dissipation system, is used for measuring the air flow rate flowing through the gear box heat dissipation system in real time, and outputs the original wind speed; The data processing module is connected with the wind speed flow sensor module, is used for receiving the original wind speed signal, and performs filtering and calculation processing to obtain a smooth wind speed value; The warning module is connected with the data processing module, is used for comparing and analyzing the smooth wind speed value with a preset wind speed threshold value, outputs a ventilation state judgment result, and triggers a corresponding level of warning signal according to the ventilation state judgment result. The wind speed flow sensor module adopts a thermal type wind speed sensor, a vane type wind speed sensor or an ultrasonic wind speed sensor; 2. The gearbox ventilation monitoring and warning system of claim 1, wherein, The installation position of the wind speed flow sensor module is arranged at one of the following positions: The air duct between the filter screen downstream of the gear box heat dissipation system and the heat dissipation fan; The air outlet position of the heat dissipation fan. The data processing module comprises:

3. The gearbox ventilation monitoring and alerting system of claim 1, wherein, A core processor, which is used for running a filtering algorithm to process the original wind speed signal, and performing comparison and analysis; A data storage unit, which is used for storing a preset wind speed threshold value, historical wind speed data and warning event records, and the preset wind speed threshold value comprises a normal threshold value, a warning threshold value and an alarm threshold value; A communication interface unit, which is used for data interaction with the warning module. The warning module comprises:

4. The gearbox ventilation monitoring and warning system of claim 1 or 3, wherein, A local warning unit, which is used for on-site warning through a visual element or an auditory element; the visual element adopts an indicator light, and the auditory element adopts a buzzer; the indicator light comprises a red indicator light, a green indicator light and a yellow indicator light; A remote communication unit, which is used for sending the warning signal to a remote monitoring terminal or designated operation and maintenance personnel through a wired or wireless network; The warning module performs hierarchical warning, and the specific warning logic is as follows: When the smooth wind speed value is higher than the normal threshold value, no warning is performed, and the green indicator light is controlled to be always on; When the smooth wind speed value is lower than the normal threshold value but higher than the warning threshold value, a concern level warning is triggered, the green indicator light is controlled to be always on, and only a concern reminder is displayed through a user interface; When the smooth wind speed value is lower than the warning threshold value but higher than the alarm threshold value, a warning level warning is triggered, the yellow indicator light is controlled to be always on, a warning reminder is displayed through the user interface, information is sent to the remote monitoring terminal through the remote communication unit, and an event is recorded; When the smooth wind speed value is lower than the alarm threshold value, an alarm level warning is triggered, the red indicator light is controlled to flash, the buzzer is controlled to beep at a set frequency, an alarm reminder is displayed through the user interface, information is sent to the remote monitoring terminal and the designated operation and maintenance personnel through the remote communication unit, and an event is recorded. The method comprises the following steps:

5. A gear box ventilation monitoring and warning method, characterized in that, S1. installing a wind speed flow sensor on the air duct of the gear box heat dissipation system, and connecting the signal of the wind speed flow sensor to a data processing module; S6. triggering a warning signal of a corresponding level according to the current ventilation state judgment result, and recording the time, type and related parameters of the warning event; S2. According to the gearbox model, the heat dissipation system design parameters and the operation condition, set the normal threshold value, the early warning threshold value and the alarm threshold value of the air speed ​​​ S3. The wind speed flow sensor collects wind speed raw data in the gear box heat dissipation air duct according to a preset sampling period ; and ; S4. Filtering the collected wind speed raw data to obtain smoothed wind speed values ;​ S5. comparing the smoothed wind speed value with normal threshold values , pre-warning threshold values and alarm threshold values for the wind speed, and determining the current ventilation state from the comparison result; If , the normal state is determined; If , the attention state is determined; If , the early warning state is determined; If , the alarm state is determined; S7. receiving a manual reset instruction, resetting the system state from the warning or alarm state to the normal monitoring state, and recording the time and reset operation of the current maintenance event. The specific steps in step S4 are as follows:

6. The gearbox ventilation monitoring and alerting method of claim 5, wherein, The method further comprises the following steps: S41. Collecting wind speed original data The filtering process is performed by using the following sliding average filtering algorithm: Wherein, N is the sampling window size, the value is the number of sampling points in the sampling period, is the wind speed raw data of the i th sampling point; S42. Store the timestamp of the center of the sampling window as the current timestamp, the smoothed wind speed value and the current timestamp to the history database.

7. The gearbox ventilation monitoring and alerting method of claim 5, wherein, In step S5 it is also included to adjust the normal threshold value for the wind speed dynamically depending on the ambient temperature and the gearbox load In step S5 it is also included to adjust the normal threshold value for the wind speed dynamically depending on the ambient temperature , the pre-warning threshold value and the alarm threshold value : wherein, is the adjusted normal threshold value, is the adjusted early warning threshold value, is the adjusted alarm threshold value, , , is a correction factor related to ambient temperature and load.

8. The gearbox ventilation monitoring and alerting method of claim 5, wherein, ​ Periodically acquire historical wind speed data in the historical database, calculate the wind speed drop rate ; According to the wind speed drop rate The filter screen clogging development rate is evaluated and a maintenance recommendation report is generated.

9. The gearbox ventilation monitoring and alerting method of claim 5, wherein, Normal threshold for wind speed in step S2 Warning threshold and alarm threshold The settings are achieved through an experimental calibration method based on benchmark values. The specific steps are as follows: S21. Collect the reference wind speed value in the air duct under the rated operation condition of the gearbox and under the clean state of the filter screen ; S22. According to the reference wind speed value calculating an initial wind speed threshold value in a predetermined proportional relationship, the proportional relationship being determined based on design parameters of the gearbox heat dissipation system, comprising: Normal threshold ; Early warning threshold ; Alarm threshold ; wherein, , , is a preset proportion coefficient, and ; S23. Put the determined wind speed threshold into commissioning, and fine-tune the proportionality coefficient according to the pre-warning records and maintenance feedback data in actual operation 、 、 or normal threshold , pre-warning threshold and alarm threshold .

10. The gearbox ventilation monitoring and alerting method of claim 5, wherein, Further comprising the following steps: S8. Predicting the health status of the filter screen, and the specific steps are as follows: S81. Based on the smoothed wind speed values ​​in the historical database. And timestamp, extract within a set time period Characteristics of the decreasing wind speed within ; The wind speed downward trend feature Including linear fitting slope, wind speed standard deviation, cumulative time proportion below normal threshold ; S82. The wind speed decreasing trend feature is input to the pre-trained filter health assessment model, and a health index representing the current clogging degree of the filter is output ; S83. Based on the aforementioned health index Historical rate of change Calculate when the filter health drops to a preset maintenance threshold. The required prediction time is the remaining effective lifespan of the filter. ; S84. generating predictive maintenance alert information and sending to an alert module when the health index is below a health alert threshold , or the remaining useful life is below a time alert threshold . The early warning information includes a recommended maintenance time window.

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