A wind turbine intelligent early warning method and fire-fighting linkage control system

Abstract

The application discloses a kind of wind turbine intelligent early warning method and fire-fighting linkage control system, its method includes the control host of wind turbine fire-fighting linkage control system access wind turbine main control system, real-time monitoring wind turbine each operation data, carries out three-level fire early warning, three-level fire early warning includes the early warning when wind turbine fire-fighting linkage control system discovers data anomaly, data anomaly cannot be automatically handled when interim early warning and limit early warning when smoke or open fire appears in cabin.The application establishes complete wind turbine intelligent early warning and fire-fighting linkage control system, responds to the data anomaly processing possibly caused by fire by the way of three-level early warning, and can realize graded response measures, face different situation intelligent research and judge response measures, independently open fire extinguishing system.

Description

Technical Field

[0001] This invention relates to the field of wind turbine fire protection technology, and in particular to an intelligent early warning method and fire linkage control system for wind turbines. Background Technology

[0002] Wind power generation is considered an important way to utilize clean energy and has received attention from countries around the world. my country has abundant wind energy resources, especially concentrated in the northwest region, and in recent years, the speed of wind power installation and stock have repeatedly reached new highs.

[0003] Wind turbines are often located in remote areas with harsh environments and high wind speeds. Due to their complex rotating mechanical structure, they are prone to failure. Wind turbine nacelle fires are considered one of the most serious malfunctions. With nacelles over 100 meters high, once a fire breaks out, the only options are remote control systems and nacelle fire extinguishing devices. Ground maintenance personnel lack effective firefighting measures, which can lead to huge economic losses and safety hazards.

[0004] There are many causes of wind turbine fires, mainly including electrical equipment failure, mechanical friction overheating, human error, and natural disasters (lightning strikes). Specific causes include aging cables, short circuits, and leakage due to component aging; abnormal friction in the mechanical braking system, inadequate lubrication of rotating machinery such as the main bearings of the generator gearbox, and oil leaks; unauthorized use of open flames by workers, leaving cigarette butts inside the nacelle; and malfunctions in the lightning protection system.

[0005] Existing firefighting methods typically include fire extinguishers, monitoring systems, and automatic fire suppression systems installed inside the engine compartment. Engine compartment fires generally occur inside the engine compartment, often caused by electrical or mechanical failures, or natural disasters. Maintenance personnel are usually not on-site and cannot use fire extinguishers. Traditional automatic fire suppression systems generally suffer from delays in processing and responding to anomalies in monitoring data, rely too heavily on manual operation, and cannot accurately and quickly activate the fire suppression system autonomously to cool and extinguish fires in the engine compartment, potentially leading to significant economic losses. Summary of the Invention

[0006] The purpose of this invention is to overcome the shortcomings of the prior art and provide a fire early warning and fire-fighting linkage system for wind turbine units.

[0007] The objective of this invention is achieved through the following technical solution:

[0008] A method for intelligent early warning of wind turbines is provided, wherein the control host of the wind turbine fire linkage control system is connected to the main control system of the wind turbine, and the wind turbine's various operating data are monitored in real time to provide three-level fire warnings. The three-level fire warnings include an initial warning when the wind turbine fire linkage control system detects abnormal data, a mid-term warning when the abnormal data cannot be automatically processed, and an extreme warning when dense smoke or open flames appear in the nacelle.

[0009] Furthermore, the initial warning specifically includes the following steps:

[0010] S101: When the fire protection linkage control system of the wind turbine detects abnormal data, the fire protection linkage control system of the wind turbine analyzes whether the abnormal data is within the controllable range.

[0011] S102: If the situation is under control, take equipment maintenance measures until the fan operating data returns to normal;

[0012] If the data is determined to be abnormal and beyond control, activate the pneumatic brake of the wind turbine to reduce the rotor speed, immediately trigger the abnormal alarm in the central control room, and start the thermal imaging scanning system.

[0013] Furthermore, the intermediate-term early warning specifically includes the following steps:

[0014] S201: When data anomalies cannot be automatically processed, the thermal imaging scanning system and heat-sensitive fire detectors inside the wind turbine nacelle are activated to determine the heat concentration point.

[0015] S202: If the temperature rise rate and the maximum temperature exceed a certain threshold, an emergency power outage will be initiated to shut down the machine and perform targeted water spray cooling.

[0016] Furthermore, the extreme warning specifically includes the following steps:

[0017] S301: When the linear smoke detector detects that the smoke concentration exceeds the threshold, and the infrared dome camera collects open flames or dense smoke, the wind turbine fire-fighting linkage control system will issue an alarm.

[0018] S302: The automatic S-type aerosol fire extinguishing device in the engine compartment is activated in conjunction with the fire extinguishing mechanism.

[0019] S303: After the fire is extinguished, maintenance personnel are dispatched to the tower to analyze the cause of the accident and establish protective measures.

[0020] Furthermore, the main control system of the wind turbine includes a wind turbine drive chain vibration monitoring system, a hydraulic lubrication system, an electrical protection system, a mechanical overheat protection system, and a wind farm remote monitoring system.

[0021] Furthermore, the various operating data of the wind turbine include the wind turbine's operating status, operating time, power generation, frequency and current, voltage, wind speed, wind direction, rotor speed, active and reactive power curves, and temperature parameters.

[0022] Furthermore, a wind turbine intelligent early warning method also includes optimizing the judgment ability of the wind turbine fire linkage control system to accumulate data on abnormal handling through self-learning.

[0023] A wind turbine fire-fighting linkage control system includes a control host, a thermal imaging scanning system, a heat-sensing fire detector, a linear smoke detector, an infrared dome camera, a water sprinkler system, and a wind turbine main control system; the control host is electrically connected to the thermal imaging scanning system, the heat-sensing fire detector, the linear smoke detector, the infrared dome camera, the water sprinkler system, and the wind turbine main control system.

[0024] The beneficial effects of this invention are:

[0025] This invention employs a multi-parameter detection, effective linkage, and multi-level protection early warning and fire-fighting system, which improves the accuracy of fire early warning, reduces the risk of large-scale fires in wind turbine nacelles, and effectively ensures the safety of wind turbines. Attached Figure Description

[0026] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the structures shown in these drawings without creative effort.

[0027] Figure 1 This is the logic diagram of the three-level fire early warning system for wind turbine generators of the present invention;

[0028] Figure 2 This is the logic diagram of the automatic fire control system for wind turbine generators of the present invention. Detailed Implementation

[0029] It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the scope of the invention.

[0030] 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 a part of the embodiments of the present invention, and not all of them. 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. In addition, the technical solutions of the various embodiments can be combined with each other, but this must be based on the ability of those skilled in the art to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be considered that such combination of technical solutions does not exist and is not within the scope of protection claimed by the present invention.

[0031] like Figure 1As shown, this invention divides the wind turbine fire early warning and fire-fighting linkage system into three levels: initial warning, intermediate warning, and extreme warning. Each level of warning corresponds to a specific action. The initial warning mainly alerts to abnormal operating data, triggering an alarm in the central control room and activating the pneumatic brakes. The intermediate warning mainly alerts to abnormal temperature readings such as exceeding temperature limits or rapid temperature rise by temperature sensors, triggering mechanical brakes and the fixed-point water sprinkler system. The extreme warning is a comprehensive alert triggered by smoke detectors, temperature sensors, thermal imaging, and monitoring observations of dense smoke or even open flames, activating the S-type aerosol automatic fire extinguishing system.

[0032] (1) Initial warning

[0033] The initial warning is a data anomaly alert. The wind turbine fire protection system connects to various operational data from the wind turbine's main control system, including the wind turbine drivetrain vibration monitoring system, hydraulic lubrication system, electrical protection, mechanical overheat protection system, and wind farm remote monitoring system. It performs real-time analysis of operational data such as wind turbine operating status, operating time, power generation, frequency and current, voltage, wind speed, wind direction, rotor speed, active and reactive power curves, and temperature.

[0034] When an anomaly is detected, the fire control system can intelligently determine whether the anomaly is within a controllable range through data processing and self-learning functions. If it is, appropriate measures are taken until the wind turbine operating data returns to normal. During system operation, the control system continuously improves the reliability of data anomaly handling through intelligent algorithm learning. If the anomaly is determined to be uncontrollable, the pneumatic brake of the wind turbine is activated to reduce the rotor speed, improve the unit's operational stability, immediately trigger the central control room's anomaly alarm, and activate the thermal imaging scanning system.

[0035] (2) Mid-term early warning

[0036] Mid-term early warning falls under the category of fault early warning. When data anomalies cannot be intelligently processed, the thermal imaging scanning system inside the nacelle is activated to determine the heat concentration point. Subsequently, point-type heat-sensing fire detectors locate the heat concentration point, measure the real-time temperature, and analyze the temperature rise rate. Temperature rise rate and maximum temperature exceeding certain thresholds are set as trigger conditions for emergency shutdown. Monitoring various operational data connected to the wind turbine's main control system reveals that, aside from natural disasters, the occurrence of critical fire hazard indicators such as exceeding temperature and temperature rise rate limits is always accompanied by anomalies in the wind turbine's drive, electrical systems, and braking systems. Data anomalies will appear within the main control system, requiring the fire control system to respond quickly, identify the faulty component, immediately cut off power, and activate the mechanical brakes. Different countermeasures are taken based on the determined cause of the fault; for example, for mechanical overheating, spray cooling can be used after power is cut off.

[0037] (3) Extreme warning and action fire linkage system

[0038] An extreme warning indicates the presence of dense smoke or even open flames inside the nacelle. At this point, the equipment inside has been damaged, seriously threatening the safety of the wind turbine. All necessary measures must be taken to extinguish the flames and cool the nacelle. When an extreme warning is triggered, linear smoke detectors detect excessive smoke concentration and a rapid rise in temperature. An infrared dome camera can then detect open flames or dense smoke. The turbine loses power, the controller issues an alarm, and activates the S-type aerosol automatic fire extinguishing system inside the nacelle. This system utilizes the oxidation-reduction reaction of the S-type thermal aerosol extinguishing agent to form a large amount of cohesive extinguishing aerosol, accelerating the extinguishing of the flames and lowering the surrounding temperature. An inert gas is used to create an oxygen-free environment. The automatic fire extinguishing system is required to activate within 2 seconds of the appearance of dense smoke or open flames and to spray all extinguishing agent around the key fire area within 30 seconds to prevent reignition.

[0039] S-type thermal aerosol fire extinguishing agent has the advantages of being harmless to the human body, having high fire extinguishing efficiency, requiring a small amount of extinguishing agent, saving weight and space, and being environmentally friendly. After moisture-proof treatment, the extinguishing agent can be stored for up to 11 years, avoiding the hassle of frequent replacements and having excellent reliability.

[0040] Wind turbine nacelles are typically located over 100 meters above the ground, and the automatic fire suppression system within the nacelle is the last line of defense against fire in the nacelle. After the wind turbine's fire suppression system activates and extinguishes the fire, maintenance personnel must be immediately dispatched to the tower to analyze the cause of the accident, implement appropriate protective measures, and immediately conduct a thorough inspection of all wind turbines of the same batch and manufacturer within the area to assess the fire risk, learn from the experience, and prevent future fires.

[0041] Traditional wind turbine fire suppression systems are slow to process and respond to data anomalies that could potentially cause a fire, and they rely excessively on human control and activation, which is clearly unreliable in the face of rapidly changing fire conditions.

[0042] This invention utilizes intelligent algorithms to continuously learn and accumulate data on anomaly handling, optimizing the judgment capability of intelligent early warning systems in the engine room and improving the accuracy of fire protection system warnings, thereby ensuring the safe operation of the unit with minimal cost and means. Specifically, it includes:

[0043] Database construction:

[0044] With a knowledge base at its core, it accesses SCADA safety data from three zones of wind turbine units to achieve vibration monitoring and temperature monitoring data collection for wind turbine equipment (main shaft, bearings, couplings, generators, control cabinets, etc.); it also collects natural meteorological data from the site, thereby enabling data transmission and processing, data storage, data monitoring, intelligent alarms, accident tracing, topology coloring, trend curves, and comprehensive query and statistics functions.

[0045] The analog and state quantities of the data are set with offsets, and the CRC (Cyclic Redundancy Check) function is used to perform restriction checks and rationality checks on the data, and to extract abnormal feature data.

[0046] Modeling process:

[0047] The model building process includes business understanding, data platform construction, test environment analysis, and algorithm model building. Business understanding mainly involves operations and maintenance personnel using their experience to understand the causes and specific aspects of equipment overheating, including the fire risk corresponding to each cause, diagnosing operational data related to this phenomenon, comparing it with normal data in the data platform, using the test environment to preprocess, process, and integrate abnormal data, and using different analysis methods (such as statistical algorithms, logical rules, signal analysis, design mechanisms, and commonly used machine learning algorithms) for feature classification and prediction to build the model.

[0048] Algorithm self-learning:

[0049] The CTED algorithm is used to solve the optimization objective. The CTED algorithm is based on the TED algorithm, which introduces an auxiliary variable and uses lasso regression to constrain the solution. It is an algorithm that can find the global optimal solution. After the abnormal data is extracted, it can perform convex optimization on the time series data before and after it based on the correlation. By comparing the constructed model with the existing database, it continuously learns and solves the analysis of abnormal data trends, thereby improving the accuracy of the judgment of dangerous data trends and fault diagnosis.

[0050] Unsupervised active learning algorithms represent a future trend in algorithm optimization. They primarily design algorithms based on the structural information of the data, aiming to maximize model performance while minimizing the number of samples required. Specifically, in real-world scenarios, the goal is to prioritize labeling more valuable samples using active learning algorithms, while still meeting model performance requirements, thereby minimizing the number of labeled samples needed and addressing the issue of excessively high labeling or training costs.

[0051] This invention establishes a complete intelligent early warning and fire-fighting linkage control system for wind turbine units. It can quickly respond to data anomalies that may cause fires through a three-level early warning system, and can implement graded response measures. It can intelligently assess and respond to different situations and autonomously activate the fire extinguishing system.

[0052] The above description is merely a preferred embodiment of the present invention. It should be understood that the present invention is not limited to the forms disclosed herein and should not be construed as excluding other embodiments. It can be used in various other combinations, modifications, and environments, and can be altered within the scope of the concept described herein through the above teachings or related technologies or knowledge. Modifications and variations made by those skilled in the art that do not depart from the spirit and scope of the present invention should be within the protection scope of the appended claims.

Claims

1. A method for intelligent early warning of wind turbine generators, characterized in that, The control host of the wind turbine fire-fighting linkage control system is connected to the main control system of the wind turbine, monitors various operating data of the wind turbine in real time, and performs three-level fire warnings. The three-level fire warnings include the initial warning when the wind turbine fire-fighting linkage control system detects abnormal data, the intermediate warning when the abnormal data cannot be automatically processed, and the extreme warning when there is dense smoke or open flame in the nacelle. The initial warning specifically includes the following steps: S101: When the fire protection linkage control system of the wind turbine detects abnormal data, the fire protection linkage control system of the wind turbine analyzes whether the abnormal data is within a controllable range. S102: If the situation is within a controllable range, take equipment maintenance measures until the fan operating data returns to normal; If the data is judged to be abnormal and beyond control, activate the pneumatic brake of the wind turbine to reduce the rotor speed, immediately trigger the abnormal alarm in the central control room, and start the thermal imaging scanning system. The intermediate-term early warning specifically includes the following steps: S201: When data anomalies cannot be automatically processed, the thermal imaging scanning system and heat-sensitive fire detectors inside the wind turbine nacelle are activated to determine the heat concentration point. S202: If the temperature rise rate and the maximum temperature exceed a certain threshold, an emergency power outage will be initiated to stop the machine and perform targeted water spray cooling. The extreme warning specifically includes the following steps: S301: When the linear smoke detector detects that the smoke concentration exceeds the threshold, and the infrared dome camera collects open flames or dense smoke, the wind turbine fire-fighting linkage control system will issue an alarm. S302: The automatic S-type aerosol fire extinguishing device in the engine compartment is activated in conjunction with the fire extinguishing mechanism. S303: After the fire is extinguished, maintenance personnel are dispatched to the tower to analyze the cause of the accident and establish protective measures.

2. The intelligent early warning method for wind turbine generators according to claim 1, characterized in that, The main control system of the wind turbine includes a wind turbine drive chain vibration monitoring system, a hydraulic lubrication system, an electrical protection system, a mechanical overheat protection system, and a wind farm remote monitoring system.

3. The intelligent early warning method for wind turbine generators according to claim 1, characterized in that, The wind turbine's operating data includes the turbine's operating status, operating time, power generation, frequency and current, voltage, wind speed, wind direction, rotor speed, active and reactive power curves, and temperature parameters.

4. The intelligent early warning method for wind turbine generators according to claim 1, characterized in that, It also includes the ability of the wind turbine fire-fighting linkage control system to improve its judgment of intelligent early warning of the nacelle by accumulating data on abnormal handling through self-learning.

5. A wind turbine fire-fighting linkage control system, employing the intelligent early warning method for wind turbines as described in any one of claims 1-4, characterized in that, It includes a control host, a thermal imaging scanning system, a heat-sensing fire detector, a linear smoke detector, an infrared dome camera, a water sprinkler system, and a wind turbine main control system; the control host is electrically connected to the thermal imaging scanning system, the heat-sensing fire detector, the linear smoke detector, the infrared dome camera, the water sprinkler system, and the wind turbine main control system, respectively.

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