Alarm control method for reducing failure rate of wind turbine equipment in wind farms

Abstract

The present invention relates to the field of fault alarm control, and in particular, to an alarm control method for reducing the failure rate of wind turbine equipment in a wind farm. It includes the following steps: S1, using sensors to monitor wind turbine data in real time, and sending abnormal data to an information processing system when the wind turbine data is abnormal; S2, the information processing system classifies the fault according to the fault information data based on the fault classification unit; S3, the information processing system manages the fault according to the upgrade and downgrade rules to dynamically adjust the fault level; S4, the alarm unit receives the fault information data sent down, and matches different alarm modes to alarm according to the fault level. By calculating the severity of the fault, the severity of the fault is managed in a graded manner, the priority of the fault is determined and the maintenance plan is optimized, and the time factor is introduced to dynamically adjust the fault level, accurately reflect the change of the current fault, minimize the damage to the wind turbine, and thus reduce the failure rate of the wind turbine equipment.

Description

Technical Field

[0001] The present invention relates to the technical field of fault alarm control, and in particular to an alarm control method for reducing the failure rate of wind turbine equipment in a wind power plant. Background Art

[0002] Wind turbine equipment failure refers to problems in wind farms that lead to wind turbine equipment shutdown, energy loss, equipment damage, and even safety hazards. Timely discovery, diagnosis, and processing of wind turbine equipment failures are crucial to ensure the normal operation and reliability of wind farms. Wind turbine equipment failure alarm control is to reduce the failure rate of wind turbine equipment, improve production efficiency, and ensure the safe operation of wind turbine equipment by monitoring, analyzing, and responding to failures.

[0003] In the existing alarms for wind turbine equipment failures, there is a lack of priority processing order for failures of different severity. In the case of limited resources, there is a lack of judgment on the severity of the failures, and high-risk failures cannot be handled in a timely manner, resulting in serious damage to the wind turbine or interruption of the production process. In view of this, an alarm control method for reducing the failure rate of wind turbine equipment in a wind farm is provided. Summary of the invention

[0004] The object of the present invention is to provide an alarm control method for reducing the failure rate of wind turbine equipment in a wind farm, so as to solve the problems proposed in the above-mentioned background technology, such as lack of priority processing order for faults of different severity, lack of judgment of the severity of faults in the case of limited resources, and failure to handle high-risk faults in time, resulting in serious damage to the wind turbine or interruption of the production process.

[0005] To achieve the above object, the present invention aims to provide an alarm control method for reducing the failure rate of wind turbine equipment in a wind farm, comprising the following steps:

[0006] S1. Use sensors to monitor wind turbine data in real time, and send abnormal data to the information processing system when the wind turbine data is abnormal;

[0007] S2, the information processing system classifies the fault according to the fault information data based on the fault classification unit;

[0008] Among them, the fault information data classifies the faults according to the severity of the faults;

[0009] S3, the information processing system manages the fault upgrade and downgrade according to the upgrade and downgrade rules to dynamically adjust the fault level;

[0010] S4. The alarm unit receives the fault information data sent down, and matches different alarm modes to issue an alarm according to the fault level.

[0011] As a further improvement of the technical solution, in S1, the fan data includes temperature data, vibration data, current, and voltage data of the fan;

[0012] Among them, abnormal temperature data of the fan indicates that the temperature increase in some parts of the equipment may indicate insufficient lubrication, circuit problems or component damage;

[0013] Abnormal vibration data from the fan, indicating that sudden or sustained vibrations outside the normal range may indicate a component failure;

[0014] The fan's current and voltage data are abnormal, indicating that there is an electrical system problem with the fan.

[0015] As a further improvement of the technical solution, in S2, the fault classification unit includes a data processing module and a downgrade module;

[0016] The information processing system also includes a fault sending module, which is used to send the classified fault information data to the alarm unit.

[0017] As a further improvement of the technical solution, in S2, the fault information data includes the monitored fault type M and fault indicator data;

[0018] Among them, the fault indicator data includes fault duration S, number of faults A, number of fault maintenance times B and downtime C caused by the fault; the severity of the fault is measured according to the fault duration S, number of faults A, number of fault maintenance times B and downtime C caused by the fault.

[0019] As a further improvement of the technical solution, the fault classification unit calculates the fault severity of the fault type M based on the fault indicator data. The specific expression is as follows:

[0020] ;

[0021] in, Represents the impact weight of fault duration S on fault type M; Indicates the impact weight of the number of faults A on the fault type M; Indicates the impact weight of the fault maintenance times B on the fault type M; Represents the impact weight of downtime C on fault type M.

[0022] As a further improvement of this technical solution, the fault severity The severity of the fault is classified into levels. The specific fault classification rules involved are:

[0023] Severity level of fault type M ;

[0024] The fault severity is divided into levels, and the threshold ranges of each level are as follows:

[0025] Level 1 Severity: ;

[0026] Level 2 Severe: ;

[0027] Level 3 severity: ;

[0028] in, and These are all set thresholds.

[0029] As a further improvement of the technical solution, in S3, the fault classification unit calculates the real-time fault severity based on the monitored real-time fault indicator data. , fault indicator data accumulates or decreases over time, affecting the severity of the fault , so the severity is dynamically adjusted by introducing a time decay factor , its specific expression is:

[0030] ;

[0031] in, represents a function that decays over time; Indicates fault indicator data; Indicates time; Indicates the fault duration A function that decays over time; Indicates the number of faults A function that decays over time; Indicates the number of fault maintenance times A function that decays over time; Indicates downtime A function that decays over time.

[0032] As a further improvement of this technical solution, the The specific function expression is:

[0033] ;

[0034] in, is a constant; A constant representing the decay rate, used to control the decay speed; Indicates time; Represents fault indicator data; over time As the value of the function increases, it gradually decreases, indicating that the early data gradually reduce the impact on the fault severity, while the most recent data has a greater impact on the calculation of the fault severity. The impact is greater.

[0035] As a further improvement of the technical solution, the upgrade and downgrade single module adjusts the real-time fault severity based on the upgrade and downgrade rules. The fault levels are reclassified, and the upgrade and downgrade rules involved are as follows:

[0036] S6.1. When When the upgrade logic is adopted, that is:

[0037] like When the fault level is adjusted to level 3, it means that the severity of the fault has increased significantly and requires immediate emergency treatment or repair;

[0038] like In range If the fault level is within 200, the fault level will be adjusted to level 2 severe;

[0039] like In range If the fault level is within the range of 1, the fault level will be adjusted to level 1 severity;

[0040] S6.2: When , the degradation logic is adopted, that is:

[0041] like When the fault level is adjusted to level 3 severity;

[0042] like When, and In range If the fault level is within 200, the fault level is adjusted to Level 2, which means that the severity of the fault has been reduced, but it still requires continuous attention and monitoring;

[0043] like , and in the range If the fault level is within 100%, the fault level is adjusted to level 1 severity, indicating that the severity of the fault has been further reduced, indicating that the fault has been repaired or improved;

[0044] S6.5. For each time point t , persistence and threshold and Compare and dynamically adjust according to the above rules Real-time fault level.

[0045] The logic of upgrading and downgrading rules can more accurately reflect the changing trend of fault severity, thereby triggering appropriate warnings or handling measures; downgrading rules mean that the system can more easily return to a lighter state from a serious fault; while upgrading rules mean that the system faces greater risks, so it is necessary to capture changes in severity more sensitively and respond to warnings more quickly to better protect the system from more serious faults.

[0046] As a further improvement of the technical solution, in S4, the alarm unit includes a display unit and an audible and visual alarm module;

[0047] Wherein, the display unit is used to display fault information data, and the fault information data is displayed in descending order based on the fault severity level;

[0048] The sound and light alarm module includes a lighting module and a voice alarm module, and the lighting module sets different colors of light display according to the level of fault severity; wherein the fault sending module matches lights of different colors according to the level of fault severity, and controls lights of different colors to light up at different levels, and the voice alarm module is used to remind people about specific events or emergencies through voice prompts or alarms.

[0049] Compared with the prior art, the present invention has the following beneficial effects:

[0050] 1. In the alarm control method for reducing the failure rate of wind turbine equipment in a wind farm, by calculating the severity of the fault and performing graded management on the severity of the fault, the priority of the fault can be determined and the maintenance plan can be optimized. The time factor is introduced to dynamically adjust the fault level, more accurately reflect the change of the current fault, minimize the damage to the wind turbine, and thus reduce the failure rate of the wind turbine equipment.

[0051] 2. In the alarm control method for reducing the failure rate of wind turbine equipment in wind farms, severity grading can help workers handle faults more effectively, thereby indirectly reducing the failure rate and improving the reliability of wind turbine equipment, and helping to prioritize faults that may cause serious damage to the wind turbine or safety problems, thereby ensuring the safety of equipment and personnel and reducing interruptions in the production process. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 The figure is a flow chart of the overall method of the present invention. DETAILED DESCRIPTION

[0053] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0054] Example:

[0055] See also Figure 1 As shown, this embodiment provides an alarm control method for reducing the failure rate of wind turbine equipment in a wind farm, comprising the following steps:

[0056] S1. Use sensors to monitor wind turbine data in real time, and send abnormal data to the information processing system when the wind turbine data is abnormal;

[0057] In this embodiment, the fan data includes temperature data, vibration data, current, and voltage data of the fan;

[0058] Among them, abnormal temperature data of the fan indicates that the temperature increase in some parts of the equipment may indicate insufficient lubrication, circuit problems or component damage;

[0059] Abnormal vibration data from the fan, indicating that sudden or sustained vibrations outside the normal range may indicate a component failure;

[0060] The fan's current and voltage data are abnormal, indicating that there is an electrical system problem with the fan.

[0061] S2, the information processing system classifies the fault according to the fault information data based on the fault classification unit;

[0062] Among them, the fault information data classifies the faults according to the severity of the faults;

[0063] The fault classification unit includes a data processing module and an upgrade and downgrade module;

[0064] Specifically, the information processing system further includes a fault sending module, which is used to send the classified fault information data to the alarm unit.

[0065] In this embodiment, the fault information data includes the monitored fault type M and fault indicator data, and the fault type M includes at least abnormal vibration, abnormal temperature, current fluctuation, voltage fluctuation and frequent shutdown;

[0066] Among them, the fault indicator data at least includes fault duration S, number of faults A, number of fault maintenance times B and downtime C caused by the fault; the severity of the fault is measured according to the fault duration S, number of faults A, number of fault maintenance times B and downtime C caused by the fault.

[0067] Specifically, the fault classification unit calculates the fault severity of the fault type M based on the fault indicator data. The specific expression is as follows:

[0068] ;

[0069] in, Represents the impact weight of fault duration S on fault type M; Indicates the impact weight of the number of faults A on the fault type M; Indicates the impact weight of the fault maintenance times B on the fault type M; Represents the impact weight of downtime C on fault type M.

[0070] According to the calculation of fault severity of fault type M , the priorities between different fault types M can be determined, and the fault severity can be According to the fault level, the faults are prioritized for repair.

[0071] The severity of the fault The severity of the fault is classified into levels. The specific fault classification rules involved are:

[0072] Severity level of fault type M ;

[0073] The fault severity is divided into levels, and the threshold ranges of each level are as follows:

[0074] Level 1 Severity: ;

[0075] Level 2 Severe: ;

[0076] Level 3 severity: ;

[0077] in, and These are all set thresholds.

[0078] Level 1 emergency (serious): Failures that may threaten the safety of the wind turbine or damage the main components of the wind turbine. Specific fault types include severe vibration, electrical system failure, and abnormal heat (overheating);

[0079] Level 2 emergency (more serious): may cause the fan to shut down or affect the fan performance, but will not immediately cause serious safety problems. Specific fault types include abnormal temperature, abnormal partial vibration, and early signs of electrical problems.

[0080] Level 3 Emergency (General): It may manifest as some minor problems or abnormalities that will not temporarily affect the normal operation of the fan. Specific fault types include low-level vibration and voltage fluctuation.

[0081] Among them, the response measures required for the first level of emergency (serious) are: immediate shutdown, immediate repair or replacement is required;

[0082] The response measures required for the second level emergency (more serious) are: planned shutdown and maintenance in the shortest possible time;

[0083] Level 3 emergency (general) requires the following response measures: Operations can continue, but monitoring and planned maintenance are required.

[0084] Ensure that appropriate actions can be taken when handling faults to minimize damage to the wind turbine and ensure safety and reliability.

[0085] Furthermore, according to the severity of the fault The fault level helps to reasonably allocate resources and manpower to deal with the repair and maintenance of the fault; for fault type M with a higher fault level, it can be treated as a priority to reduce the negative impact on the system or process; by understanding the impact of different factors on the fault, measures can be taken to reduce the duration of the fault, reduce the number of faults, optimize the maintenance frequency and reduce downtime, thereby improving the stability and efficiency of the system; effective management and repair of serious fault types helps to reduce maintenance costs and production interruption time, effectively manage fault handling, optimize resource utilization, and continuously improve system operation efficiency.

[0086] S3. The information processing system manages the faults according to the upgrade and downgrade rules to dynamically adjust the fault level. Since the fault levels are divided according to the severity, the faults will gradually deteriorate or be repaired over time. By introducing the time factor, the system can more accurately reflect the evolution of the faults, so as to take appropriate measures to deal with the faults in a more timely manner. In this embodiment, the fault classification unit calculates the real-time fault severity based on the real-time fault indicator data monitored. , fault indicator data accumulates or decreases over time, affecting the severity of the fault Therefore, by introducing the time decay factor, the time decay factor gradually reduces the weight of the fault indicator data that occurred earlier, and the weight of the most recent data is higher, thereby dynamically adjusting the severity , its specific expression is:

[0087] ;

[0088] in, represents a function that decays over time; Indicates fault indicator data; Indicates time; Indicates the fault duration A function that decays over time; Indicates the number of faults A function that decays over time; Indicates the number of fault maintenance times A function that decays over time; Indicates downtime A function that decays over time.

[0089] Specifically, the The specific function expression is:

[0090] ;

[0091] in, is a constant; A constant representing the decay rate, used to control the decay speed; Indicates time; Indicates fault indicator data. As the value of the function increases, it gradually decreases, indicating that the early data gradually reduce the impact on the fault severity, while the most recent data has a greater impact on the calculation of the fault severity. The impact is greater; based on the real-time fault indicator data and time decay factor, the real-time fault severity is dynamically calculated .

[0092] In this embodiment, the upgrade and downgrade module adjusts the severity of the real-time fault based on the upgrade and downgrade rules. The fault levels are reclassified, and the upgrade and downgrade rules involved are as follows:

[0093] S6.1. When When the upgrade logic is adopted, that is:

[0094] like When the fault level is adjusted to level 3, it means that the severity of the fault has increased significantly and requires immediate emergency treatment or repair;

[0095] like In range If the fault level is within 200, the fault level will be adjusted to level 2 severe;

[0096] like In range If the fault level is within the range of 1, the fault level will be adjusted to level 1 severity;

[0097] S6.2: When , the degradation logic is adopted, that is:

[0098] like When the fault level is adjusted to level 3 severity;

[0099] like When, and In range If the fault level is within 200, the fault level is adjusted to Level 2, which means that the severity of the fault has been reduced, but it still requires continuous attention and monitoring;

[0100] like , and in the range If the fault level is within 100%, the fault level is adjusted to level 1 severity, indicating that the severity of the fault has been further reduced, indicating that the fault has been repaired or improved;

[0101] S6.5. For each time point t , persistence and threshold and Compare and dynamically adjust according to the above rules Real-time fault level.

[0102] Specifically, the logic of upgrading and downgrading rules can more accurately reflect the changing trend of fault severity, thereby triggering appropriate warnings or handling measures; downgrading rules mean that the system can more easily return from a serious fault to a lighter state; while upgrading rules mean that the system faces greater risks, so it is necessary to more sensitively capture changes in severity and respond to warnings more quickly to better protect the system from more serious faults.

[0103] S4. The alarm unit receives the fault information data sent down, matches different alarm modes according to the fault level, distinguishes and displays them according to different color lights, and issues a voice alarm at the same time.

[0104] In this embodiment, the alarm unit includes a display unit and an audible and visual alarm module;

[0105] Wherein, the display unit is used to display fault information data, and the fault information data is displayed in descending order based on the fault severity level;

[0106] The sound and light alarm module includes a lighting module and a voice alarm module, and the lighting module sets different colors of light display according to the level of fault severity; wherein the fault sending module matches lights of different colors according to the level of fault severity, and controls lights of different colors to light up at different levels, and the voice alarm module is used to remind people about specific events or emergencies through voice prompts or alarms.

[0107] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments. The above embodiments and descriptions are only preferred examples of the present invention and are not intended to limit the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. An alarm control method for reducing the failure rate of wind turbine equipment in a wind farm, characterized in that: The following steps are involved: S1. Use sensors to monitor wind turbine data in real time, and send abnormal data to the information processing system when the wind turbine data is abnormal; S2, the information processing system classifies the fault according to the fault information data based on the fault classification unit; S3, the information processing system manages the fault upgrade and downgrade according to the upgrade and downgrade rules to dynamically adjust the fault level; S4, the alarm unit receives the fault information data sent down, and matches different alarm modes to alarm according to the fault level; In S3, the fault classification unit calculates the real-time fault severity based on the monitored real-time fault indicator data. And dynamically adjust the severity by introducing a time decay factor Its specific expression is: Where, f(x, t) represents the function that decays over time; x represents the fault indicator data; t represents time; f(x s , t) represents the function of fault duration S decaying with time; f(x A , t) represents the function of the number of failures A decaying with time; f(x B , t) represents the function of the failure maintenance frequency B decaying with time; f(x C , t) represents the function of downtime C decaying with time; The specific function expression of f(x, t) is: f(x,t)=e -βt ×x; Among them, e is a constant; β represents the constant of the decay rate; t represents time; and x represents fault indicator data.

2. The alarm control method for reducing the failure rate of wind turbine equipment in a wind farm according to claim 1, characterized in that: In S1, the fan data includes temperature data, vibration data, current, and voltage data of the fan.

3. The alarm control method for reducing the failure rate of wind turbine equipment in a wind farm according to claim 1, characterized in that: In S2, the fault classification unit includes a data processing module and a downgrade module; The information processing system also includes a fault sending module, which is used to send the classified fault information data to the alarm unit.

4. The alarm control method for reducing the failure rate of wind turbine equipment in a wind farm according to claim 3 is characterized in that: In said S2, the fault information data includes the monitored fault type M and fault indicator data; Among them, the fault indicator data includes fault duration S, number of faults A, number of fault maintenance B and downtime C caused by the fault.

5. The alarm control method for reducing the failure rate of wind turbine equipment in a wind farm according to claim 4, characterized in that: The fault classification unit calculates the fault severity of the fault type M based on the fault index data. The specific expression is as follows: P M =w1×S+w2×A+w3×B+w4×C; Among them, w1 represents the impact weight of fault duration S on fault type M; w2 represents the impact weight of fault number A on fault type M; w3 represents the impact weight of fault maintenance number B on fault type M; w4 represents the impact weight of downtime C on fault type M.

6. The alarm control method for reducing the failure rate of wind turbine equipment in a wind farm according to claim 5, characterized in that: The fault severity P M The fault severity level P M The specific fault classification rules involved are: The fault severity is divided into levels, and the threshold ranges of each level are as follows: Level 1 severity: [0, T1]; Level 2 severe: (T1, T2]; Level 3 severity: (T2,∞); Wherein, T1 and T2 are both set thresholds.

7. The alarm control method for reducing the failure rate of wind turbine equipment in a wind farm according to claim 6, characterized in that: The upgrade and downgrade single module adjusts the real-time fault severity P′ based on the upgrade and downgrade rules. M The fault levels are reclassified, and the upgrade and downgrade rules involved are as follows: S6.

1. When P′ M >P M When the upgrade logic is adopted, that is: If P′ M >T2, the fault level is adjusted to level 3 severity; If P′ M Within the range (T1, T2], the fault level is adjusted to level 2 severity; If P′ M In the range [0, T1], the fault level is adjusted to level one severity; S6.2, when P′ M <P M When , the degradation logic is adopted, that is: If P′ M >T2, the fault level is adjusted to level 3 severity; If P′ M <T2, and P′ M Within the range (T1, T2], the fault level is adjusted to level 2 severity; If P′ M <T1, and within the range [0, T1], the fault level is adjusted to level 1 severity; S6.

5. For each time point t, P′ M , continuously compare with thresholds T1 and T2, and dynamically adjust P′ according to the above rules M Real-time fault level.

8. The alarm control method for reducing the failure rate of wind turbine equipment in a wind farm according to claim 1, characterized in that: In S4, the alarm unit includes a display unit and an audible and visual alarm module; Wherein, the display unit is used to display fault information data; The sound and light alarm module includes a light module and a voice alarm module.

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