A wind power gear box filter element life determination method, device, equipment and medium

Abstract

The application discloses a wind power gear box filter element life determination method, device, equipment and medium, and relates to the technical field of wind power generation. The scheme pre-constructs a multi-dimensional filter element life model containing time loss degree, filtering area loss degree, flow loss degree and pressure difference attenuation degree, can depict the performance degradation state of the gear box filter element from different dimensions, thereby avoiding the inaccuracy of judging the remaining life by using a single parameter, and making the model have engineering interpretability and be able to adapt to actual needs under different operating conditions; when performing remaining life prediction, only the operating parameters of the gear box filter element during operation need to be collected and input into the pre-constructed multi-dimensional filter element life model, so that the remaining life index of the gear box filter element can be determined immediately, the accurate determination of the clogging state and actual life of the filter element is realized, and the problems of inaccurate replacement depending on a fixed cycle or untimely replacement depending on pressure difference alarm are effectively solved.

Description

Technical Field

[0001] This application relates to the field of wind power generation technology, and in particular to a method, apparatus, equipment and medium for determining the lifespan of a wind turbine gearbox filter element. Background Technology

[0002] Currently, the mainstream structure of wind turbine gearbox filter elements typically consists of a gearbox outer cylinder, a filter element inner cavity, and filter element rings connected in series. Gearbox oil flows through the fiber filter media to effectively filter impurities generated during operation. This design has become a mature solution for gearbox filtration systems in the wind power industry and is widely used in various turbine models.

[0003] However, gearbox filters are critical consumables in routine maintenance and require regular replacement, but the frequency of replacement directly impacts maintenance costs. Currently, determining the timing of replacement mainly relies on two methods: one is based on the installation date, following the manufacturer's recommended fixed replacement cycle, which may result in the filter being prematurely discarded before its lifespan is fully exhausted; the other is relying on a differential pressure indicator, replacing the filter only when a low differential pressure is detected, but by this time the filter may already be in a performance degradation phase, exhibiting a certain degree of lag.

[0004] Given the above, how to solve the problem that the remaining life of gearbox filter elements cannot be directly determined, and that replacement relies on fixed cycles or differential pressure alarms, which easily leads to premature replacement and waste or makes it difficult to detect performance degradation in time, is an urgent problem for technicians in this field. Summary of the Invention

[0005] The purpose of this application is to provide a method, device, equipment and medium for determining the life of wind turbine gearbox filter elements, so as to solve the problem that the remaining life of gearbox filter elements cannot be directly determined, and replacement relies on fixed cycles or differential pressure alarms, which easily leads to premature replacement, resulting in waste or difficulty in timely detection of performance degradation.

[0006] To address the aforementioned technical problems, this application provides a method for determining the lifespan of a wind turbine gearbox filter element, comprising:

[0007] The operating parameters of the gearbox filter element during operation are collected; wherein, the operating parameters include at least the current usage time, flow rate, filter area, and filter pressure difference;

[0008] The operating parameters are input into a pre-constructed multi-dimensional filter life model to determine the remaining life index of the gearbox filter element. The construction process of the multi-dimensional filter life model includes: establishing multi-dimensional loss indicators for the gearbox filter element; the multi-dimensional loss indicators include at least time loss, filtration area loss, flow rate loss, and pressure differential attenuation; determining the weights corresponding to each of the multi-dimensional loss indicators, and constructing weight functions for each of the multi-dimensional loss indicators based on these weights; and establishing the multi-dimensional filter life model based on these weight functions.

[0009] On the one hand, establish multi-dimensional loss indicators for the gearbox filter element, including:

[0010] The RFID chip of the gearbox filter element is read to determine the time reference value, filtration area reference value, flow rate reference value and differential pressure reference value of the gearbox filter element in the initial state;

[0011] The time loss rate is established based on the actual usage time of the gearbox filter element and the time reference value.

[0012] The filter area loss rate is established based on the current effective filtration area of ​​the gearbox filter element and the filter area reference value;

[0013] The flow loss rate is established based on the current effective flow rate of the gearbox filter element and the flow reference value;

[0014] The differential pressure attenuation is established based on the current filtration differential pressure, the maximum operating differential pressure, and the differential pressure reference value of the gearbox filter element.

[0015] On the other hand, determining the weights corresponding to each of the aforementioned multi-dimensional loss indicators includes:

[0016] Obtain historical operating data of filter elements of the same type as the gearbox filter element; the historical operating data shall at least include the actual service life of the filter element and the actual values ​​of various multi-dimensional loss indicators.

[0017] The ratio of the actual service life of the filter element to the corresponding rated service life is determined as the observed value of the filter element's service life.

[0018] A normalized loss index is generated based on the actual values ​​of the various multi-dimensional loss indicators of the filter element.

[0019] A prediction model is established based on the normalized loss index and weight parameters; wherein, the weight parameters include the weights corresponding to each of the multi-dimensional loss indexes.

[0020] The values ​​of the weight parameters are adjusted using the least squares method until the sum of squared errors between the predicted values ​​output by the prediction model and the observed values ​​of filter life reaches the minimum value. Then, the current weight parameters are determined as the weights corresponding to each of the multi-dimensional loss indicators.

[0021] On the other hand, a weight function is constructed based on each weight for each of the multi-dimensional loss indicators, including:

[0022] Each weight is multiplied by the corresponding multi-dimensional loss index to generate the weight function corresponding to each multi-dimensional loss index; the weight function includes a time loss weight function, a filter area loss weight function, a flow rate loss weight function, and a pressure difference attenuation weight function.

[0023] Correspondingly, the multi-dimensional filter life model is established based on each of the weight functions, including:

[0024] Based on the time loss weight function, the filter area loss weight function, the flow loss weight function, and the pressure difference attenuation weight function, the multi-dimensional filter life model is established.

[0025] On the other hand, the operating parameters of the gearbox filter element during operation are collected, including:

[0026] The RFID chip of the gearbox filter element is read to determine the current usage time of the gearbox filter element;

[0027] The flow rate and filtration speed of the gearbox filter element during operation are collected using a turbine flow meter.

[0028] The filtration area of ​​the gearbox filter element is determined based on the flow rate and the filtration speed.

[0029] Obtain the filter pipe length, filter pipe resistance coefficient, filter pipe inner diameter, and fluid density;

[0030] The filtration pressure drop of the gearbox filter element is determined based on the filter pipe length, the filter pipe resistance coefficient, the filter pipe inner diameter, the fluid density, and the flow rate.

[0031] On the other hand, after determining the remaining life index of the gearbox filter element, the process also includes:

[0032] Obtain the remaining life index ranges of the gearbox filter element; wherein each remaining life index range corresponds to different maintenance method information;

[0033] Determine the target remaining lifetime index range within each of the remaining lifetime index ranges;

[0034] Maintenance of the gearbox filter element is performed according to the maintenance method information corresponding to the target remaining life index range.

[0035] On the other hand, maintenance of the gearbox filter element is performed according to the maintenance method information corresponding to the target remaining life index range, including:

[0036] When the target remaining life index range is within the first remaining life index range, the remaining life index of the gearbox filter element is continuously monitored.

[0037] When the target remaining life index range is within the second remaining life index range, an alarm message indicating that the gearbox filter element is clogged is triggered;

[0038] When the target remaining life index range is within the third remaining life index range, the gearbox filter element shall be replaced according to plan.

[0039] When the target remaining life index range is the fourth remaining life index range, the gearbox filter element should be replaced immediately.

[0040] Among them, the lower limit of the first remaining life index range is not less than the upper limit of the second remaining life index range, the lower limit of the second remaining life index range is not less than the upper limit of the third remaining life index range, and the lower limit of the third remaining life index range is not less than the upper limit of the fourth remaining life index range.

[0041] To address the aforementioned technical problems, this application also provides a device for determining the lifespan of a wind turbine gearbox filter element, comprising:

[0042] The data acquisition module is used to acquire the operating parameters of the gearbox filter element during operation; wherein, the operating parameters include at least the current usage time, flow rate, filter area, and filter pressure difference;

[0043] The prediction module is used to input the operating parameters into a pre-built multi-dimensional filter life model to determine the remaining life index of the gearbox filter element. The construction process of the multi-dimensional filter life model includes: establishing multi-dimensional loss indicators for the gearbox filter element; the multi-dimensional loss indicators include at least time loss, filtration area loss, flow rate loss, and differential pressure attenuation; determining the weights corresponding to each of the multi-dimensional loss indicators, and constructing weight functions corresponding to each of the multi-dimensional loss indicators based on the weights; and establishing the multi-dimensional filter life model based on the weight functions.

[0044] To address the aforementioned technical problems, this application also provides a device for determining the lifespan of a wind turbine gearbox filter element, comprising:

[0045] Memory, used to store computer programs;

[0046] A processor is used to execute the computer program to implement the steps of the above-described method for determining the lifespan of a wind turbine gearbox filter element.

[0047] To address the aforementioned technical problems, this application also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the above-described method for determining the lifespan of a wind turbine gearbox filter element.

[0048] The method for determining the lifespan of wind turbine gearbox filters provided in this application pre-constructs a multi-dimensional filter lifespan model that includes time loss, filtration area loss, flow loss, and differential pressure decay. This model can characterize the performance degradation state of the gearbox filter from different dimensions, thus avoiding the inaccuracy of using a single parameter to determine the remaining lifespan. Furthermore, the model is both engineering interpretable and adaptable to the actual needs under different operating conditions. When performing the remaining lifespan prediction, it is only necessary to collect the operating parameters of the gearbox filter during operation and input them into the pre-constructed multi-dimensional filter lifespan model to immediately determine the remaining lifespan index of the gearbox filter. This achieves accurate determination of the filter's clogging state and actual lifespan, effectively solving the problems of inaccuracy when relying on fixed-cycle replacement or untimely replacement relying on differential pressure alarms.

[0049] In addition, this application also provides a device, equipment and medium for determining the life of a wind turbine gearbox filter element, with the same effect as above. Attached Figure Description

[0050] To more clearly illustrate the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. Obviously, the 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.

[0051] Figure 1 A flowchart illustrating a method for determining the lifespan of a wind turbine gearbox filter element, provided in this application embodiment;

[0052] Figure 2 A schematic diagram illustrating the life prediction principle of wind turbine gearbox filter elements provided in this application embodiment;

[0053] Figure 3 A schematic diagram illustrating the acquisition of operating parameters for a gearbox filter element provided in an embodiment of this application;

[0054] Figure 4 A schematic diagram of a wind turbine gearbox filter element life determination device provided in an embodiment of this application;

[0055] Figure 5This is a structural diagram of a wind turbine gearbox filter element life determination device provided in an embodiment of this application. Detailed Implementation

[0056] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the protection scope of this application.

[0057] The core of this application is to provide a method, device, equipment and medium for determining the life of wind turbine gearbox filter elements, so as to solve the problem that the remaining life of gearbox filter elements cannot be directly determined, and replacement relies on fixed cycles or differential pressure alarms, which easily leads to premature replacement, resulting in waste or difficulty in timely detection of performance degradation.

[0058] To enable those skilled in the art to better understand the present application, the present application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0059] Figure 1 A flowchart illustrating a method for determining the lifespan of a wind turbine gearbox filter element, provided as an embodiment of this application. Figure 1 As shown, the method includes:

[0060] S10: Collect operating parameters of the gearbox filter element during operation.

[0061] The operating parameters should include at least the current usage time, flow rate, filter area, and filter pressure difference.

[0062] Due to the high viscosity and impurity content of the lubricating oil in wind turbine gearboxes, to improve filtration efficiency, wind turbine gearbox filters are generally dual-precision filter elements. Typically, a coarse filter element (usually 25µm or 50µm) and a fine filter element (10µm) are connected in series. To determine the remaining lifespan of the wind turbine gearbox, this embodiment first collects the operating parameters of the gearbox filter element during operation.

[0063] It should be noted that the operating parameters include at least the current usage time, flow rate, filter area, and filtration differential pressure. The current usage time is the total cumulative operating time of the filter element since installation; the flow rate is the total amount of gear oil passing through the filter element per unit time, reflecting the circulation speed of the oil in the filtration system; the filter area is the total effective filtration area of ​​the internal fiber filter media, determining how many impurities the filter element can hold; the filtration differential pressure is the pressure difference formed between the inlet and outlet when the oil flows through the filter element due to the filter media blocking impurities, used to measure the degree of clogging of the filter element. This embodiment does not limit the specific type or method of obtaining the operating parameters; it depends on the specific implementation situation.

[0064] S11: Input the operating parameters into the pre-built multi-dimensional filter life model to determine the remaining life index of the gearbox filter element.

[0065] Subsequently, the operating parameters are input into a pre-built multi-dimensional filter life model to determine the remaining life index of the gearbox filter element.

[0066] It is worth noting that the construction process of the multi-dimensional filter life model specifically includes establishing multi-dimensional loss indicators for the gearbox filter element. These multi-dimensional loss indicators include at least time loss, filtration area loss, flow rate loss, and pressure differential decay. Time loss characterizes the impact of the filter element's cumulative operating time on performance; filtration area loss characterizes the degree to which the effective filtration area of ​​the filter element decreases due to impurities clogging it; flow rate loss characterizes the degree to which the actual flow rate decreases relative to the initial design flow rate; and pressure differential decay characterizes the change in pressure differential caused by the increase in the filter element's internal resistance over time. This application uses these indicators to characterize the filter element's performance degradation state from different dimensions, avoiding the inaccuracy of judging by a single parameter. This embodiment does not limit the method of establishing each multi-dimensional loss indicator; it depends on the specific implementation. Further, the weights corresponding to each multi-dimensional loss indicator are determined, and weight functions corresponding to each multi-dimensional loss indicator are constructed based on these weights. Finally, a multi-dimensional filter life model is established based on these weight functions. It should be noted that this embodiment does not restrict the method of determining the weights corresponding to each multi-dimensional loss index. They can be determined directly based on empirical values, or the optimal weights can be determined through optimization methods, depending on the specific implementation situation.

[0067] In this embodiment, a multi-dimensional filter life model is pre-constructed, incorporating time loss, filter area loss, flow rate loss, and differential pressure decay. This model can characterize the performance degradation state of the gearbox filter from different dimensions, thus avoiding the inaccuracy of using a single parameter to determine the remaining life. Furthermore, the model possesses both engineering interpretability and adaptability to actual needs under different operating conditions. When performing remaining life prediction, it is only necessary to collect the operating parameters of the gearbox filter during operation and input them into the pre-constructed multi-dimensional filter life model to immediately determine the remaining life index of the gearbox filter. This achieves accurate determination of the filter's clogging state and actual life, effectively solving the problems of inaccuracy relying on fixed-cycle replacement or untimely replacement relying on differential pressure alarms.

[0068] Figure 2 A schematic diagram illustrating the principle of wind turbine gearbox filter life prediction provided in this application embodiment. Based on the above embodiments, in some embodiments, such as... Figure 2 As shown, a multi-dimensional loss index for gearbox filter elements is established, including:

[0069] S101: Read the RFID chip of the gearbox filter element to determine the time reference value, filtration area reference value, flow rate reference value and differential pressure reference value of the gearbox filter element in the initial state.

[0070] S102: Establish time loss rate based on the actual usage time and time reference value of the gearbox filter element.

[0071] S103: Establish the filter area loss rate based on the current effective filter area and the filter area baseline value of the gearbox filter element.

[0072] S104: Establish flow loss rate based on the current effective flow rate and flow reference value of the gearbox filter element.

[0073] S105: Establish the differential pressure decay rate based on the current filtration differential pressure, maximum operating differential pressure, and differential pressure reference value of the gearbox filter element.

[0074] It should be noted that the gearbox filter element provided in this application is equipped with a unique Radio Frequency Identification (RFID) chip, which binds and stores the filter element's factory information, installation time, cumulative running time, historical replacement records, and operating parameters, realizing the identification and data association of the filter element throughout its entire life cycle. In this embodiment, in order to construct multi-dimensional loss indicators, it is first necessary to obtain the benchmark values ​​related to these multi-dimensional loss indicators.

[0075] Specifically, the RFID chip of the gearbox filter element is read to determine the time reference value, filtration area reference value, flow rate reference value, and differential pressure reference value corresponding to the initial state of the gearbox filter element. It is important to note that these reference values ​​are essentially the rated values; for example, the time reference value is the rated lifespan of the filter element, the filtration area reference value is the initial total filtration area of ​​the filter element, the flow rate reference value is the rated initial flow rate of the filter element, and the differential pressure reference value is the initial differential pressure of the filter element. Furthermore, various multi-dimensional loss indicators are established based on the above reference values:

[0076] (1) The time loss rate is established based on the actual usage time and time reference value of the gearbox filter element, and the formula is as follows:

[0077] ;

[0078] Among them, T t t represents the time loss rate; t represents the actual usage time of the gearbox filter element (s); T0 represents the time reference value, i.e., the rated time life of the filter element (s).

[0079] (2) The filter area loss rate is established based on the current effective filter area and the filter area reference value of the gearbox filter element, and the formula is as follows:

[0080] ;

[0081] Among them, A a A represents the filtration area loss rate; A represents the current effective filtration area (L / min); A0 represents the baseline value of the filtration area, i.e., the initial total filtration area of ​​the filter element (L / min).

[0082] (3) Establish the flow loss rate based on the current effective flow rate and the flow reference value of the gearbox filter element, using the following formula:

[0083] ;

[0084] Among them, F f Q represents the flow loss rate; Q represents the current effective flow rate (m). 3 / s); Q0 is the flow rate baseline value, i.e., the initial rated flow rate of the filter element (m³ / s). 3 / s).

[0085] (4) Establish the differential pressure attenuation rate based on the current filtration differential pressure, maximum operating differential pressure, and differential pressure reference value of the gearbox filter element, using the following formula:

[0086] ;

[0087] Among them, D p This refers to the differential pressure attenuation rate. The current filtration pressure difference (Pa); Maximum operating differential pressure (Pa); This is the differential pressure reference value, i.e., the initial differential pressure (Pa) of the filter element.

[0088] Understandably, since the baseline values ​​for each of the multi-dimensional loss indicators are all known quantities, the values ​​of each multi-dimensional loss indicator can be directly determined when the corresponding current values ​​are determined. In summary, this establishes a multi-dimensional loss indicator system, which characterizes the filter element's performance degradation state from different dimensions, avoiding the inaccuracies of judging based on a single parameter.

[0089] Based on the above embodiments, in some embodiments, the weights corresponding to each multi-dimensional loss index are determined, including:

[0090] S111: Obtain historical operating data of filter elements of the same type as gearbox filter elements; historical operating data shall include at least the actual service life of the filter element and the actual values ​​of various multi-dimensional loss indicators.

[0091] S112: The ratio of the actual service life of the filter element to the corresponding rated service life is determined as the observed value of the filter element's service life.

[0092] S113: Generate normalized loss indicators based on the actual values ​​of various multi-dimensional loss indicators of the filter element.

[0093] S114: Establish a prediction model based on normalized loss index and weight parameters; whereby the weight parameters include the weights corresponding to each multi-dimensional loss index.

[0094] S115: Use the least squares method to adjust the values ​​of the weight parameters until the sum of squared errors between the predicted values ​​output by the prediction model and the observed values ​​of filter life reaches the minimum value. Then, determine the current weight parameters as the weights corresponding to each multi-dimensional loss index.

[0095] Since each weighting function is used to reflect the relative importance of different loss indicators in the filter life assessment, its weight can be adaptively adjusted by least squares based on the filter type and the operating conditions of the wind turbine unit using real data.

[0096] Specifically, in this embodiment, historical operating data of a filter element of the same type as the gearbox filter element is first obtained. This historical operating data includes at least the actual service life of the filter element and the corresponding actual values ​​of various multi-dimensional wear indicators, i.e., T. t (i), A a (i), F f (i), D p (i), where i is the number of data entries, and the total number of data entries is N. Simultaneously, the ratio of the actual service life of the filter element to its corresponding rated service life is defined as the filter element life observation value RUL. obs (i).

[0097] Furthermore, a normalized loss index is generated based on the actual values ​​of various multi-dimensional loss indicators of the filter element, as follows:

[0098] ;

[0099] Where, x i This is a normalized loss index.

[0100] A prediction model is established based on the normalized loss index and weight parameters, as shown in the following formula:

[0101] ;

[0102] Where RUL(i) is the prediction model, and the weight parameters are... It includes the weights corresponding to various multi-dimensional loss indicators.

[0103] Finally, the values ​​of the weight parameters are adjusted using the least squares method until the sum of squared errors between the predicted values ​​output by the prediction model and the observed values ​​of filter life reaches its minimum. The current weight parameters are then determined as the weights corresponding to each multi-dimensional loss index, as shown in the following formula:

[0104] ;

[0105] In this way, the statistically optimal weights were obtained, enabling adaptive matching of different filter types and wind turbine operating conditions.

[0106] Based on the above embodiments, in some embodiments, a weight function corresponding to each multi-dimensional loss index is constructed based on each weight, including:

[0107] S121: Multiply each weight by the corresponding multi-dimensional loss index to generate the weight function corresponding to each multi-dimensional loss index; the weight function includes the time loss weight function, the filter area loss weight function, the flow loss weight function, and the pressure difference attenuation weight function.

[0108] To determine the weighting functions corresponding to each multi-dimensional loss index, this embodiment specifically multiplies each weight by its corresponding multi-dimensional loss index to generate the weighting function for each multi-dimensional loss index. The weighting functions include the time loss weighting function, the filter area loss weighting function, the flow rate loss weighting function, and the pressure drop attenuation weighting function, and the specific formulas are as follows:

[0109] ;

[0110] ;

[0111] ;

[0112] ;

[0113] in, The time loss weighting function is used. For the corresponding weights; This is the weighting function for filter area loss. For the corresponding weights; The flow loss weighting function is... For the corresponding weights; The pressure differential attenuation weighting function is... For the corresponding weights.

[0114] Correspondingly, a multi-dimensional filter lifespan model is established based on each weight function, including:

[0115] S122: A multi-dimensional filter life model is established based on the time loss weight function, filter area loss weight function, flow loss weight function, and pressure difference attenuation weight function.

[0116] The formula for the multi-dimensional filter life model is as follows:

[0117] ;

[0118] in, .

[0119] In this way, a multi-dimensional filter life model was constructed.

[0120] Based on the above embodiments, in some embodiments, the operating parameters of the gearbox filter element during operation are collected, including:

[0121] S131: Read the RFID chip of the gearbox filter element to determine the current usage time of the gearbox filter element.

[0122] S132: Collects the flow rate and filtration velocity of the gearbox filter element during operation via a turbine flow meter.

[0123] S133: Determine the filtration area of ​​the gearbox filter element based on the flow rate and filtration speed.

[0124] S134: Obtain the filter pipe length, filter pipe resistance coefficient, filter pipe inner diameter, and fluid density.

[0125] S135: Determine the filtration pressure drop of the gearbox filter element based on the filter pipe length, filter pipe resistance coefficient, filter pipe inner diameter, fluid density, and flow rate.

[0126] As can be seen from the above embodiments, in the established multi-dimensional filter life model, the actual usage time of the gearbox filter element, the current effective filtration area, the current effective flow rate, and the current filtration differential pressure are the independent variables for predicting the remaining life of the filter element. Therefore, when collecting the operating parameters of the gearbox filter element during operation, it is necessary to collect these parameters.

[0127] Figure 3 This is a schematic diagram illustrating the acquisition of operating parameters for a gearbox filter element provided in an embodiment of this application. Figure 3 As shown, firstly, the RFID chip of the gearbox filter element is read. Since it records the cumulative operating time of the filter element, the current usage time of the gearbox filter element can be directly determined, that is, the actual usage time of the gearbox filter element. Further, the flow rate Q (m³) of the gearbox filter element during operation is collected using a turbine flow meter. 3 / s) and filtration velocity v (m 3 / h). It can be understood that the flow rate Q here is the current effective flow rate of the gearbox filter element. Subsequently, the filtration area of ​​the gearbox filter element is determined based on the flow rate and filtration velocity, using the following formula:

[0128] ;

[0129] Where A represents the filtration area (L / min). It can be understood that the filtration area A here is the current effective filtration area of ​​the gearbox filter element.

[0130] Finally, obtain the filter pipe length, filter pipe resistance coefficient, filter pipe inner diameter, and fluid density (this can also be determined by directly reading the RFID chip on the gearbox filter element). Based on the filter pipe length, filter pipe resistance coefficient, filter pipe inner diameter, fluid density, and flow rate, determine the filtration pressure drop of the gearbox filter element using the following formula:

[0131] ;

[0132] in, L represents the filtration pressure drop (Pa) of the gearbox filter element, and L represents the length of the filter pipe (m). d is the filter pipe resistance coefficient, and d is the filter pipe inner diameter (m). Fluid density (kg / m³) 3 Understandably, the filtration pressure drop here... This is the current filtration pressure difference of the gearbox filter element.

[0133] This enables the complete collection of operating parameters of the gearbox filter element during operation, facilitating the prediction of its remaining lifespan.

[0134] Based on the above embodiments, in some embodiments, after determining the remaining life index of the gearbox filter element, the method further includes:

[0135] S141: Obtain the remaining life range of each indicator of the gearbox filter element; where each remaining life range corresponds to different maintenance method information.

[0136] S142: Determine the target remaining life index range within each remaining life index range.

[0137] S143: Perform maintenance on the gearbox filter element according to the maintenance method information corresponding to the target remaining life index range.

[0138] To achieve on-demand maintenance and replacement of the gearbox filter element, this embodiment, after determining the remaining life index of the gearbox filter element, further obtains the range of each remaining life index. It should be noted that each remaining life index range corresponds to different maintenance method information. This embodiment does not restrict the division of each remaining life index range or the corresponding maintenance method information, and it depends on the specific implementation. Subsequently, the target remaining life index range is determined within each remaining life index range. Finally, maintenance of the gearbox filter element is performed according to the maintenance method information corresponding to the target remaining life index range. In this way, on-demand maintenance and replacement of the gearbox filter element are achieved. An example is given below:

[0139] The filter element for the gearbox of a wind turbine in a certain wind farm has the following baseline information: rated time T0 = 365 days; filtration area A0 = 300 L / min; filter flow rate Q0 = 0.003 m³ / min. 3 / s; Filter element pressure drop ∆P0 = 3.5 bar. Current filter element operating information: Current usage time: 6 months since installation; Current effective filtration area A = 200 L / min; Current filter element flow rate Q = 0.002 m³ / s. 3 / s; Current filter element pressure drop ∆P = 4 bar; Current filter element pressure drop ∆P max =5.5 bar. 1000 sets of RUL were actually observed. obs The weights were calculated by back-calculating using the least squares method. =0.40, =0.15, =0.20, =0.25, then the following loss indexes exist:

[0140] Time loss ;

[0141] Filter area loss ;

[0142] Flow loss ;

[0143] Pressure differential attenuation ;

[0144] Finally, the remaining lifespan index is calculated based on the current weights, as follows:

[0145] ;

[0146] Meanwhile, in order to determine the actual maintenance method for the gearbox filter element, a reference range of remaining life index is given below.

[0147] Table 1. Range of Remaining Life Indicators

[0148]

[0149] As shown in Table 1, there are four different remaining life indicator ranges. In specific implementation, when the target remaining life indicator range is the first remaining life indicator range (100%-90%), the remaining life indicator of the gearbox filter element is continuously monitored. When the target remaining life indicator range is the second remaining life indicator range (90%-70%), an alarm message indicating that the gearbox filter element is clogged is triggered. When the target remaining life indicator range is the third remaining life indicator range (70%-40%), a planned replacement of the gearbox filter element is performed. When the target remaining life indicator range is the fourth remaining life indicator range (40%-30%), the gearbox filter element is replaced immediately. It can be understood that, as shown in Table 1, the lower limit of the first remaining life indicator range is not less than the upper limit of the second remaining life indicator range, the lower limit of the second remaining life indicator range is not less than the upper limit of the third remaining life indicator range, and the lower limit of the third remaining life indicator range is not less than the upper limit of the fourth remaining life indicator range.

[0150] In the above embodiments, the method for determining the life of wind turbine gearbox filter elements has been described in detail. This application also provides embodiments of the wind turbine gearbox filter element life determination device.

[0151] Figure 4 This is a schematic diagram of a wind turbine gearbox filter element life determination device provided in an embodiment of this application. Figure 4 As shown, the device includes:

[0152] The data acquisition module 10 is used to acquire the operating parameters of the gearbox filter element during operation; the operating parameters include at least the current usage time, flow rate, filter area, and filter pressure difference.

[0153] The prediction module 11 is used to input operating parameters into a pre-built multi-dimensional filter life model to determine the remaining life index of the gearbox filter element. The construction process of the multi-dimensional filter life model includes: establishing multi-dimensional loss indicators for the gearbox filter element; the multi-dimensional loss indicators include at least time loss, filtration area loss, flow loss, and pressure drop attenuation; determining the weights corresponding to each multi-dimensional loss indicator, and constructing a weight function corresponding to each multi-dimensional loss indicator based on each weight; and establishing a multi-dimensional filter life model based on each weight function.

[0154] In some embodiments, establishing multi-dimensional loss indicators for the gearbox filter element includes: reading the RFID chip of the gearbox filter element to determine the time reference value, filtration area reference value, flow rate reference value, and differential pressure reference value corresponding to the gearbox filter element in its initial state; establishing a time loss rate based on the actual usage time and time reference value of the gearbox filter element; establishing a filtration area loss rate based on the current effective filtration area and filtration area reference value of the gearbox filter element; establishing a flow rate loss rate based on the current effective flow rate and flow rate reference value of the gearbox filter element; and establishing a differential pressure attenuation rate based on the current filtration differential pressure, maximum operating differential pressure, and differential pressure reference value of the gearbox filter element.

[0155] In some embodiments, determining the weights corresponding to each multi-dimensional loss index includes: acquiring historical operating data of a filter element of the same type as the gearbox filter element; the historical operating data includes at least the actual service life of the filter element and the actual values ​​of the corresponding multi-dimensional loss indexes; determining the ratio of the actual service life of the filter element to the corresponding rated service life as the observed value of the filter element life; generating normalized loss indexes based on the actual values ​​of the multi-dimensional loss indexes of the filter element; establishing a prediction model based on the normalized loss indexes and weight parameters; wherein, the weight parameters include the weights corresponding to each multi-dimensional loss index; adjusting the value of the weight parameters using the least squares method until the sum of squared errors between the predicted value output by the prediction model and the observed value of the filter element life reaches the minimum value, and then determining the current weight parameters as the weights corresponding to each multi-dimensional loss index.

[0156] In some embodiments, constructing weight functions corresponding to each multi-dimensional loss index based on each weight includes: multiplying each weight by the corresponding multi-dimensional loss index to generate weight functions corresponding to each multi-dimensional loss index; the weight functions include time loss weight function, filter area loss weight function, flow rate loss weight function, and pressure drop attenuation weight function; correspondingly, establishing a multi-dimensional filter life model based on each weight function includes: establishing a multi-dimensional filter life model based on the time loss weight function, filter area loss weight function, flow rate loss weight function, and pressure drop attenuation weight function.

[0157] In some embodiments, the acquisition module 10 includes:

[0158] The reading module is used to read the RFID chip of the gearbox filter element to determine the current usage time of the gearbox filter element;

[0159] The first acquisition submodule is used to acquire the flow rate and filtration speed of the gearbox filter element during operation via a turbine flow meter;

[0160] The first calculation submodule is used to determine the filtration area of ​​the gearbox filter element based on the flow rate and filtration speed;

[0161] The first acquisition submodule is used to acquire the filter pipe length, filter pipe resistance coefficient, filter pipe inner diameter, and fluid density;

[0162] The second calculation submodule is used to determine the filtration pressure drop of the gearbox filter element based on the filter pipe length, filter pipe resistance coefficient, filter pipe inner diameter, fluid density, and flow rate.

[0163] In some embodiments, it also includes:

[0164] The second acquisition submodule is used to acquire the remaining life index range of each gearbox filter element; wherein each remaining life index range corresponds to different maintenance method information.

[0165] The first determination submodule is used to determine the target remaining life index range in which the remaining life index is located within each remaining life index range.

[0166] The maintenance execution submodule is used to perform maintenance on the gearbox filter element according to the maintenance method information corresponding to the target remaining life index range.

[0167] In some embodiments, the maintenance execution submodule includes:

[0168] The first execution submodule is used to continuously monitor the remaining life index of the gearbox filter element when the target remaining life index range is within the first remaining life index range.

[0169] The second execution submodule is used to trigger an alarm message indicating that the gearbox filter element is clogged when the target remaining life index range is within the second remaining life index range.

[0170] The third execution submodule is used to perform planned replacement of the gearbox filter element when the target remaining life index range is within the third remaining life index range.

[0171] The fourth execution submodule is used to immediately replace the gearbox filter element when the target remaining life index range is within the fourth remaining life index range.

[0172] Among them, the lower limit of the first remaining life index range is not less than the upper limit of the second remaining life index range, the lower limit of the second remaining life index range is not less than the upper limit of the third remaining life index range, and the lower limit of the third remaining life index range is not less than the upper limit of the fourth remaining life index range.

[0173] Since the embodiments of the apparatus and the embodiments of the method correspond to each other, please refer to the description of the embodiments of the method for the embodiments of the apparatus, which will not be repeated here.

[0174] Figure 5This is a structural diagram of a wind turbine gearbox filter element life determination device provided in an embodiment of this application. Figure 5 As shown, the equipment for determining the lifespan of wind turbine gearbox filter elements includes:

[0175] Memory 20 is used to store computer programs;

[0176] The processor 21 is used to execute a computer program to implement the steps of the method for determining the lifespan of the wind turbine gearbox filter element as mentioned in the above embodiments.

[0177] The device for determining the lifespan of wind turbine gearbox filters provided in this embodiment may include, but is not limited to, smartphones, tablets, laptops, or desktop computers.

[0178] The processor 21 may include one or more processing cores, such as a quad-core processor or an octa-core processor. The processor 21 may be implemented using at least one of the following hardware forms: Digital Signal Processor (DSP), Field-Programmable Gate Array (FPGA), or Programmable Logic Array (PLA). The processor 21 may also include a main processor and a coprocessor. The main processor, also known as the Central Processing Unit (CPU), is used to process data in the wake-up state; the coprocessor is a low-power processor used to process data in the standby state. In some embodiments, the processor 21 may integrate a Graphics Processing Unit (GPU), which is responsible for rendering and drawing the content to be displayed on the screen. In some embodiments, the processor 21 may also include an Artificial Intelligence (AI) processor, which handles computational operations related to machine learning.

[0179] The memory 20 may include one or more computer-readable storage media, which may be non-transitory. The memory 20 may also include high-speed random access memory and non-volatile memory, such as one or more disk storage devices or flash memory devices. In this embodiment, the memory 20 is used to store at least the following computer program 201, which, after being loaded and executed by the processor 21, is capable of implementing the relevant steps of the wind turbine gearbox filter element life determination method disclosed in any of the foregoing embodiments. In addition, the resources stored in the memory 20 may also include an operating system 202 and data 203, and the storage method may be temporary or permanent storage. The operating system 202 may include Windows, Unix, Linux, etc. The data 203 may include, but is not limited to, the data involved in the wind turbine gearbox filter element life determination method.

[0180] In some embodiments, the wind turbine gearbox filter element life determination device may further include a display screen 22, an input / output interface 23, a communication interface 24, a power supply 25, and a communication bus 26.

[0181] Those skilled in the art will understand that Figure 5 The structure shown does not constitute a limitation on the device for determining the lifespan of wind turbine gearbox filters and may include more or fewer components than shown.

[0182] Finally, this application also provides an embodiment corresponding to a computer-readable storage medium. The computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps described in the above method embodiments.

[0183] It is understood that if the methods in the above embodiments are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and executes all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0184] The foregoing provides a detailed description of a method, apparatus, device, and medium for determining the lifespan of a wind turbine gearbox filter element. The various embodiments in the specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the apparatus disclosed in the embodiments, since it corresponds to the method disclosed in the embodiments, the description is relatively simple; relevant parts can be referred to in the method section. It should be noted that those skilled in the art can make several improvements and modifications to this application without departing from the principles of this application, and these improvements and modifications also fall within the protection scope of this application.

[0185] It should also be noted that, in this specification, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

Claims

1. A method for determining the lifespan of a wind turbine gearbox filter element, characterized in that, include: The operating parameters of the gearbox filter element during operation are collected; wherein, the operating parameters include at least the current usage time, flow rate, filter area, and filter pressure difference; The operating parameters are input into a pre-constructed multi-dimensional filter life model to determine the remaining life index of the gearbox filter element. The construction process of the multi-dimensional filter life model includes: establishing multi-dimensional loss indicators for the gearbox filter element; the multi-dimensional loss indicators include at least time loss, filtration area loss, flow rate loss, and pressure differential attenuation; determining the weights corresponding to each of the multi-dimensional loss indicators, and constructing weight functions for each of the multi-dimensional loss indicators based on these weights; and establishing the multi-dimensional filter life model based on these weight functions.

2. The method for determining the lifespan of a wind turbine gearbox filter element according to claim 1, characterized in that, Establish multi-dimensional loss indicators for the gearbox filter element, including: The RFID chip of the gearbox filter element is read to determine the time reference value, filtration area reference value, flow rate reference value and differential pressure reference value of the gearbox filter element in the initial state; The time loss rate is established based on the actual usage time of the gearbox filter element and the time reference value. The filter area loss rate is established based on the current effective filtration area of ​​the gearbox filter element and the filter area reference value; The flow loss rate is established based on the current effective flow rate of the gearbox filter element and the flow reference value; The differential pressure attenuation is established based on the current filtration differential pressure, the maximum operating differential pressure, and the differential pressure reference value of the gearbox filter element.

3. The method for determining the lifespan of a wind turbine gearbox filter element according to claim 1, characterized in that, Determine the weights corresponding to each of the aforementioned multi-dimensional loss indicators, including: Obtain historical operating data of filter elements of the same type as the gearbox filter element; the historical operating data shall at least include the actual service life of the filter element and the actual values ​​of various multi-dimensional loss indicators. The ratio of the actual service life of the filter element to the corresponding rated service life is determined as the observed value of the filter element's service life. A normalized loss index is generated based on the actual values ​​of the various multi-dimensional loss indicators of the filter element. A prediction model is established based on the normalized loss index and weight parameters; wherein, the weight parameters include the weights corresponding to each of the multi-dimensional loss indexes. The values ​​of the weight parameters are adjusted using the least squares method until the sum of squared errors between the predicted values ​​output by the prediction model and the observed values ​​of filter life reaches the minimum value. Then, the current weight parameters are determined as the weights corresponding to each of the multi-dimensional loss indicators.

4. The method for determining the lifespan of a wind turbine gearbox filter element according to claim 1, characterized in that, Based on each weight, a weight function is constructed corresponding to each of the multi-dimensional loss indicators, including: Each weight is multiplied by the corresponding multi-dimensional loss index to generate the weight function corresponding to each multi-dimensional loss index; the weight function includes a time loss weight function, a filter area loss weight function, a flow rate loss weight function, and a pressure difference attenuation weight function. Correspondingly, the multi-dimensional filter life model is established based on each of the weight functions, including: Based on the time loss weight function, the filter area loss weight function, the flow loss weight function, and the pressure difference attenuation weight function, the multi-dimensional filter life model is established.

5. The method for determining the lifespan of a wind turbine gearbox filter element according to claim 1, characterized in that, The operating parameters of the gearbox filter element during operation are collected, including: The RFID chip of the gearbox filter element is read to determine the current usage time of the gearbox filter element; The flow rate and filtration speed of the gearbox filter element during operation are collected using a turbine flow meter. The filtration area of ​​the gearbox filter element is determined based on the flow rate and the filtration speed. Obtain the filter pipe length, filter pipe resistance coefficient, filter pipe inner diameter, and fluid density; The filtration pressure drop of the gearbox filter element is determined based on the filter pipe length, the filter pipe resistance coefficient, the filter pipe inner diameter, the fluid density, and the flow rate.

6. The method for determining the lifespan of a wind turbine gearbox filter element according to any one of claims 1 to 5, characterized in that, After determining the remaining life index of the gearbox filter element, the process also includes: Obtain the remaining life index ranges of the gearbox filter element; wherein each remaining life index range corresponds to different maintenance method information; Determine the target remaining lifetime index range within each of the remaining lifetime index ranges; Maintenance of the gearbox filter element is performed according to the maintenance method information corresponding to the target remaining life index range.

7. The method for determining the lifespan of a wind turbine gearbox filter element according to claim 6, characterized in that, Maintenance of the gearbox filter element is performed according to the maintenance method information corresponding to the target remaining life index range, including: When the target remaining life index range is within the first remaining life index range, the remaining life index of the gearbox filter element is continuously monitored. When the target remaining life index range is within the second remaining life index range, an alarm message indicating that the gearbox filter element is clogged is triggered; When the target remaining life index range is within the third remaining life index range, the gearbox filter element shall be replaced according to plan. When the target remaining life index range is the fourth remaining life index range, the gearbox filter element should be replaced immediately. Among them, the lower limit of the first remaining life index range is not less than the upper limit of the second remaining life index range, the lower limit of the second remaining life index range is not less than the upper limit of the third remaining life index range, and the lower limit of the third remaining life index range is not less than the upper limit of the fourth remaining life index range.

8. A device for determining the lifespan of a wind turbine gearbox filter element, characterized in that, include: The data acquisition module is used to acquire the operating parameters of the gearbox filter element during operation; wherein, the operating parameters include at least the current usage time, flow rate, filter area, and filter pressure difference; The prediction module is used to input the operating parameters into a pre-built multi-dimensional filter life model to determine the remaining life index of the gearbox filter element. The construction process of the multi-dimensional filter life model includes: establishing multi-dimensional loss indicators for the gearbox filter element; the multi-dimensional loss indicators include at least time loss, filtration area loss, flow rate loss, and differential pressure attenuation; determining the weights corresponding to each of the multi-dimensional loss indicators, and constructing weight functions corresponding to each of the multi-dimensional loss indicators based on the weights; and establishing the multi-dimensional filter life model based on the weight functions.

9. A device for determining the lifespan of a wind turbine gearbox filter element, characterized in that, include: Memory, used to store computer programs; A processor, configured to execute the computer program to implement the steps of the method for determining the lifespan of a wind turbine gearbox filter element as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the steps of the method for determining the lifespan of a wind turbine gearbox filter element as described in any one of claims 1 to 7.

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