A method and system for diagnosing a leakage fault of a hydraulic torque converter

Abstract

The present application belongs to the technical field of leakage fault diagnosis of hydraulic torque converter, and specifically discloses a leakage fault diagnosis method and system of hydraulic torque converter. Based on the mechanism analysis of the leakage fault of hydraulic torque converter under non-stationary excitation, an evaluation index based on the kinetic stiffness characteristics of the pump wheel and turbine is introduced. On the one hand, the kinetic stiffness angle difference between the pump wheel and turbine is used to quantitatively evaluate the kinetic energy change degree of the system, and then the running state of the hydraulic torque converter is judged. On the other hand, the kinetic stiffness characteristics of the hydraulic torque converter are analyzed in depth based on the fuzzy clustering algorithm. The distance between the clustering points and the clustering center of the to-be-tested kinetic stiffness characteristics is calculated to determine the membership of each kinetic stiffness characteristic clustering point to each operating state, so as to accurately diagnose the fault degree of the system. The accuracy and efficiency of fault diagnosis are improved, and scientific basis is provided for the maintenance and optimization of the hydraulic torque converter, which significantly improves the overall performance and reliability of the engineering machinery.

Description

Technical Field

[0001] This invention belongs to the field of hydraulic torque converter fault diagnosis technology, specifically relating to a method and system for diagnosing leakage faults in hydraulic torque converters. Background Technology

[0002] With the widespread application of modern construction machinery, the hydraulic torque converter, as a key power transmission component, plays a crucial role in ensuring the stability and reliability of its performance, which is essential for the overall operational efficiency and safety of the machinery. In complex operating environments, hydraulic torque converters in construction machinery often face severe challenges, such as load fluctuations, temperature changes, and contamination. These factors can all lead to leaks and other malfunctions in the hydraulic torque converter, thus affecting its normal operation.

[0003] Traditional fault diagnosis methods for hydraulic torque converters rely heavily on experience-based judgment and routine maintenance, lacking real-time monitoring and precise evaluation capabilities. This not only increases maintenance costs but also makes it difficult to detect and address potential faults in a timely manner, potentially leading to equipment performance degradation or even accidents.

[0004] In view of this, this invention is hereby proposed. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of the prior art and provide a method and system for diagnosing leakage faults in hydraulic torque converters. Based on the mechanism analysis of leakage faults in hydraulic torque converters under non-stationary excitation, an evaluation index based on the kinetic stiffness characteristics of the pump impeller and turbine is innovatively introduced. On the one hand, by accurately measuring and calculating the difference in the kinetic stiffness angle between the pump impeller and the turbine, the degree of kinetic energy change of the system is quantitatively evaluated, thereby determining the operating state of the hydraulic torque converter. On the other hand, based on the fuzzy clustering algorithm, the kinetic stiffness characteristics of the hydraulic torque converter are analyzed in depth. By calculating the distance between the cluster points of the measured kinetic stiffness characteristics and the cluster center, the membership degree of each kinetic stiffness characteristic cluster point for each operating state is determined, thereby achieving accurate diagnosis of the fault degree of the hydraulic torque converter.

[0006] The objective of this invention is achieved through the following technical solution:

[0007] On one hand, the present invention provides a method for diagnosing leakage faults in a hydraulic torque converter, comprising the following steps:

[0008] Step S1: Obtain the operating data of the pump impeller and turbine in the hydraulic torque converter, and establish a fault diagnosis model;

[0009] Step S2: Determine the fault evaluation indicators of the hydraulic torque converter using the operating data and fault diagnosis model;

[0010] Step S3: Obtain the test operating data of the pump impeller and turbine in the hydraulic torque converter to be tested, and determine the test leakage evaluation value of the hydraulic torque converter to be tested according to the fault diagnosis model;

[0011] Step S4: Determine the fault status of the hydraulic torque converter based on the fault evaluation index and the leakage evaluation value to be tested. If no fault occurs, continue operation; if a fault occurs, diagnose the fault type.

[0012] Further, in step S1, the fault diagnosis model includes a first fault diagnosis model and a second fault diagnosis model. The first fault diagnosis model is based on the kinetic stiffness angle of the pump wheel and turbine in the hydraulic torque converter as a feature for fault diagnosis, and the second fault diagnosis model is based on the flow rate and rotational speed of the pump wheel and turbine in the hydraulic torque converter as a feature for fault diagnosis.

[0013] In step S2, the fault evaluation index includes the first fault evaluation index corresponding to the first fault diagnosis model and the second fault evaluation index corresponding to the second fault diagnosis model.

[0014] Furthermore, the first fault diagnosis model is as follows:

[0015]

[0016] Wherein, FD is the leakage evaluation value of the hydraulic torque converter. D represents the average degree of kinetic energy change of the pump impeller and turbine in the hydraulic torque converter under test. z This represents the degree of kinetic energy change of the pump impeller and turbine of the hydraulic torque converter in the initial state.

[0017] The formula for calculating the degree of kinetic energy change of the hydraulic torque converter is as follows:

[0018] D=|σ t σ b |

[0019] Where D represents the degree of kinetic energy change of the hydraulic torque converter, and σ t σ is the kinetic stiffness angle of the turbine. b The angle is the kinetic stiffness angle of the pump impeller.

[0020] Furthermore, the process for determining the first fault evaluation index is as follows:

[0021] The kinetic stiffness angles of each turbine and pump impeller of the hydraulic torque converter under normal and severe leakage fault conditions are obtained from the operating data respectively. These angles are used to calculate the degree of kinetic energy change of the hydraulic torque converter under normal and severe leakage fault conditions. The degree of kinetic energy change of the hydraulic torque converter under normal and severe leakage fault conditions is substituted into the first fault diagnosis model to obtain thresholds z and y, where z is less than y. The z and y are used as the first fault evaluation index.

[0022] The first fault evaluation index is as follows: when the leakage evaluation value FD is less than or equal to z, the hydraulic torque converter under test is in normal condition; when the leakage evaluation value FD is greater than z and less than y, the hydraulic torque converter under test is in a slight leakage fault state; when the leakage evaluation value FD is greater than or equal to y, the hydraulic torque converter under test is in a serious leakage fault state.

[0023] Furthermore, the second fault diagnosis model is shown below:

[0024]

[0025] Among them, v j Let represent the leakage evaluation value of the j-th kinetic stiffness feature cluster point, i represent the index of the operating state category, n represent the number of operating state categories, j represent the index of the kinetic stiffness feature cluster point, m represent the fuzzy constant, and u ij x represents the membership degree of the j-th kinetic stiffness feature to the i-th type of operating state. i This represents the number of kinetic stiffness feature cluster points for the i-th type of operating state;

[0026] The membership degree is calculated as follows:

[0027]

[0028] Where c represents the number of cluster points of kinetic energy stiffness feature, d kj This represents the distance between the j-th kinetic stiffness feature cluster point and the k-th kinetic stiffness feature cluster point in the i-th category, where k represents the index of the kinetic stiffness feature cluster point in the i-th category excluding the j-th kinetic stiffness feature cluster point, and d represents the distance between the j-th kinetic stiffness feature cluster point and the k-th kinetic stiffness feature cluster point in the i-th category. l This represents the minimum distance between the cluster points of each kinetic stiffness feature in the i-th category.

[0029] Furthermore, the process for determining the second fault evaluation index is as follows:

[0030] The kinetic stiffness feature clusters in the normal state, minor leakage fault state and severe leakage fault state in the operating data are obtained respectively. The membership degree of each kinetic stiffness feature cluster in each category is calculated by the distance between the obtained kinetic stiffness feature clusters. The second fault evaluation index of the hydraulic torque converter under different fault states is determined by the calculated membership degree and the second fault diagnosis model.

[0031] The second fault evaluation index is as follows: when the leakage evaluation value of the cluster points of the measured kinetic stiffness feature exceeds the set proportion [w1, w2], the operating state of the hydraulic torque converter under test is normal; when the leakage evaluation value of the cluster points of the measured kinetic stiffness feature exceeds the set proportion [w3, w4], the operating state of the hydraulic torque converter under test is a minor leakage fault state; when the leakage evaluation value of the cluster points of the measured kinetic stiffness feature exceeds the set proportion [w5, w6], the operating state of the hydraulic torque converter under test is a serious leakage fault state.

[0032] Among them, w1 < w2, w3 < w4, w5 < w6.

[0033] Furthermore, the test operation data is acquired and input into the fault diagnosis model to obtain the test leakage evaluation value;

[0034] When the leakage evaluation value under test is within the normal state evaluation index range, the operating state of the hydraulic torque converter under test is normal.

[0035] When the leakage evaluation value under test is within the range of the minor leakage fault state evaluation index, the operating state of the hydraulic torque converter under test is a minor leakage fault state.

[0036] When the leakage evaluation value under test is within the range of the evaluation index for severe leakage fault state, the operating state of the hydraulic torque converter under test is a severe leakage fault state.

[0037] Furthermore, when the fault state of the hydraulic torque converter under test is normal, the hydraulic torque converter continues to operate normally;

[0038] When the fault condition of the hydraulic torque converter under test is a minor leakage fault, the pump wheel in the hydraulic torque converter can still drive the turbine to rotate, and the hydraulic torque converter can continue to operate, but it needs to be repaired in time within a set time.

[0039] When the fault condition of the hydraulic torque converter under test is a serious leakage fault, the pump wheel after the flow leakage is difficult to drive the turbine to rotate for operation. It is necessary to immediately shut down the hydraulic torque converter and replace the parts in the hydraulic torque converter immediately.

[0040] On the other hand, the present invention also provides a leakage fault diagnosis system for a length hydraulic torque converter based on the aforementioned leakage fault diagnosis method, including a data acquisition module, a status evaluation module, a fault diagnosis module, and a decision support module;

[0041] Data acquisition module: used to collect operating data of pump impeller and turbine in hydraulic torque converter. The operating data specifically includes the kinetic stiffness angle of pump impeller and turbine or the flow rate and speed of pump impeller and turbine.

[0042] Condition evaluation module: used to establish a fault diagnosis model and determine fault evaluation indicators based on the acquired pump impeller and turbine operating data;

[0043] Fault diagnosis module: used to diagnose faults in the hydraulic torque converter under test using the test operation data and fault diagnosis model;

[0044] Decision support module: Based on the fault diagnosis results, the hydraulic torque converter under test is processed accordingly, so that the hydraulic torque converter can operate normally.

[0045] Compared with the prior art, the present invention has the following beneficial effects:

[0046] The present invention provides a method for diagnosing leakage faults and a method for diagnosing faults in hydraulic torque converters. It establishes two fault diagnosis models based on different characteristic data, and innovatively introduces evaluation indicators based on the kinetic energy stiffness characteristics of the pump wheel and turbine. It also determines the fault evaluation indicators based on historical data, and inputs the operating data to be tested into the model to obtain the system state corresponding to the operating data to be tested. This not only improves the accuracy and efficiency of fault diagnosis, but also provides a scientific basis for the maintenance and optimization of hydraulic torque converters, thereby significantly improving the overall performance and reliability of engineering machinery. Attached Figure Description

[0047] The accompanying drawings are incorporated in and form part of this specification, and together with the description serve to explain the principles of the invention.

[0048] 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, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0049] Figure 1 This is a flowchart of the leakage fault diagnosis method for the hydraulic torque converter of the present invention;

[0050] Figure 2 This is a graph showing the changing trend of the kinetic stiffness change rate of the pump wheel and turbine under minor faults in the leakage fault diagnosis method of the hydraulic torque converter of the present invention.

[0051] Figure 3 This is a graph showing the changing trend of the kinetic stiffness circles of the pump wheel and turbine when there is a minor fault in the leakage fault diagnosis method of the hydraulic torque converter of the present invention.

[0052] Figure 4 This is a graph showing the changing trend of the kinetic stiffness angle between the pump impeller and the turbine during a minor fault in the leakage fault diagnosis method of the hydraulic torque converter of the present invention.

[0053] Figure 5This is a graph showing the changing trend of the kinetic stiffness change rate of the pump wheel and turbine under severe faults in the leakage fault diagnosis method of the hydraulic torque converter of the present invention.

[0054] Figure 6 This is a graph showing the changing trend of the kinetic stiffness circle of the pump wheel and turbine during a severe fault in the leakage fault diagnosis method of the hydraulic torque converter of the present invention.

[0055] Figure 7 This is a graph showing the changing trend of the kinetic stiffness angle between the pump impeller and the turbine during a severe fault in the leakage fault diagnosis method of the hydraulic torque converter of the present invention.

[0056] Figure 8 This is a distribution diagram of kinetic stiffness cluster points under normal conditions in the leakage fault diagnosis method of the hydraulic torque converter of the present invention;

[0057] Figure 9 This is a distribution diagram of kinetic stiffness clustering points in the leakage fault diagnosis method of the hydraulic torque converter of the present invention when there is a minor leakage fault;

[0058] Figure 10 This is a distribution diagram of kinetic stiffness clustering points in the leakage fault diagnosis method of the hydraulic torque converter of the present invention during a severe leakage fault. Detailed Implementation

[0059] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Rather, they are merely examples of apparatuses consistent with some aspects of the invention as detailed in the appended claims.

[0060] To enable those skilled in the art to better understand the technical solutions of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments.

[0061] Please see Figures 1-10 This invention provides a method for diagnosing leakage faults in a hydraulic torque converter, such as... Figure 1 As shown, the kinetic stiffness characteristic value of the hydraulic torque converter is first obtained. A fault diagnosis model is established based on the value and quantity of the kinetic stiffness characteristic value. Two fault diagnosis models are established in this application, and the operating status of the hydraulic torque converter is determined by the two different fault diagnosis models.

[0062] Step S1: Obtain the operating data of the pump impeller and turbine in the hydraulic torque converter, and establish a fault diagnosis model.

[0063] The fault diagnosis model proposed in this application includes a first fault diagnosis model based on the kinetic stiffness angle of the turbine and pump impeller in the hydraulic torque converter, and a second fault diagnosis model based on fuzzy clustering algorithm and the flow rate and rotational speed of the turbine and pump impeller in the hydraulic torque converter.

[0064] For the first fault diagnosis model:

[0065] First, the kinetic stiffness angles of each turbine and pump impeller under normal conditions, under minor fault conditions, and under severe fault conditions of the hydraulic torque converter are obtained respectively. Then, the kinetic stiffness angles of the turbine and pump impeller in the hydraulic torque converter under the initial state are obtained.

[0066] Then, the first fault diagnosis model is established, and the model expression is as follows:

[0067]

[0068] Wherein, FD is the leakage evaluation value of the hydraulic torque converter. D represents the average degree of kinetic energy change of the pump impeller and turbine in the hydraulic torque converter under test. z This represents the degree of kinetic energy change of the pump impeller and turbine of the hydraulic torque converter in the initial state.

[0069] The formula for calculating the degree of kinetic energy change in a hydraulic torque converter is as follows:

[0070] D=|σ t -σ b |

[0071] Where D represents the degree of kinetic energy change of the hydraulic torque converter, and σ t σ is the kinetic stiffness angle of the turbine. b The angle is the kinetic stiffness angle of the pump impeller.

[0072] For the second fault diagnosis model:

[0073] First, the flow rate and speed of each turbine and pump impeller under normal conditions, under minor fault conditions, and under severe fault conditions of the hydraulic torque converter are obtained respectively. The speed difference between each pump impeller and turbine under each operating condition is taken as a kinetic stiffness feature cluster point. The speed difference between multiple pump impellers and turbines under each operating condition corresponding to each speed is also taken as multiple kinetic stiffness feature cluster points.

[0074] Then, a second fault diagnosis model is established, with the following model expression:

[0075]

[0076] Among them, v jLet represent the leakage evaluation value of the j-th kinetic stiffness feature cluster point, i represent the index of the operating state category, n represent the number of operating state categories, j represent the index of the kinetic stiffness feature cluster point, m represent the fuzzy constant, and u ij x represents the membership degree of the j-th kinetic stiffness feature to the i-th type of operating state. i This represents the number of kinetic stiffness feature cluster points for the i-th type of operating state;

[0077] The membership degree is calculated as follows:

[0078]

[0079] Where c represents the number of cluster points of kinetic energy stiffness feature, d kj This represents the distance between the j-th kinetic stiffness feature cluster point and the k-th kinetic stiffness feature cluster point in the i-th category, where k represents the index of the kinetic stiffness feature cluster point in the i-th category excluding the j-th kinetic stiffness feature cluster point, and d represents the distance between the j-th kinetic stiffness feature cluster point and the k-th kinetic stiffness feature cluster point in the i-th category. l This represents the minimum distance between the cluster points of each kinetic stiffness feature in the i-th category.

[0080] Step S2: Determine the fault evaluation index of the hydraulic torque converter using the operating data and fault diagnosis model.

[0081] Since this application includes a first fault diagnosis model and a second fault diagnosis model, each model corresponds to a fault evaluation index. Therefore, this application also includes a first fault evaluation index corresponding to the first fault diagnosis model and a second fault evaluation index corresponding to the second fault diagnosis model.

[0082] For the first fault evaluation index:

[0083] The kinetic stiffness angles of the pump wheel and turbine under normal conditions are obtained from historical operating data and the difference is calculated as the degree of kinetic energy change under normal conditions. The kinetic stiffness angles of the pump wheel and turbine under initial conditions are obtained and the difference is calculated as the standard kinetic energy change. The degree of kinetic energy change under normal conditions and the standard kinetic energy change are substituted into the first fault diagnosis model to obtain the leakage evaluation value z of the hydraulic torque converter under normal conditions. In this application, z is not limited and can be determined according to the historical data of the hydraulic torque converter tested in actual conditions. Preferably, z is set to 0.2 in this application.

[0084] The kinetic stiffness angles of the pump wheel and turbine under severe leakage fault conditions in historical operating data are obtained and the difference is calculated as the degree of kinetic energy change under severe leakage fault conditions. The kinetic stiffness angles of the pump wheel and turbine under the initial state are obtained and the difference is calculated as the standard kinetic energy change. The degree of kinetic energy change under severe leakage fault conditions and the standard kinetic energy change are substituted into the first fault diagnosis model to obtain the leakage evaluation value y of the hydraulic torque converter under severe leakage fault conditions. In this application, y is not limited and can be determined according to the historical data of the hydraulic torque converter under actual testing. Preferably, in this application, y is set to 0.5.

[0085] Under normal conditions, the pump impeller and turbine are functioning correctly, and the difference in their kinetic stiffness angles is small. However, in a severe leakage fault condition, the pump impeller leaks significantly and cannot drive the turbine to rotate. In this case, the difference in their kinetic stiffness angles is also large. Therefore, the smaller the leakage evaluation value of the hydraulic torque converter, the lower the probability and severity of the leakage fault. Thus, based on the leakage evaluation values ​​z and y obtained from the above steps, we can conclude that when the leakage evaluation value FD obtained from the tested operating data is less than or equal to z, the hydraulic torque converter under test... When the torque converter is in normal condition, if the leakage evaluation value FD obtained from the test operating data is greater than z and less than y, the torque converter under test is in a state of slight leakage failure. If the leakage evaluation value FD obtained from the test operating data is greater than or equal to y, the torque converter under test is in a state of serious leakage failure. Therefore, this application preferably sets the first fault evaluation index as follows: when FD≤0.2, the torque converter under test is in normal condition; when 0.2<FD<0.5, the torque converter under test is in a state of slight leakage failure; and when FD≥0.5, the torque converter under test is in a state of serious leakage failure.

[0086] For the second fault evaluation index:

[0087] The speed difference between the pump impeller and turbine under normal conditions is obtained from historical data and the difference is calculated. Each speed difference is used as a kinetic stiffness feature cluster point, and multiple flow differences between the pump impeller and turbine corresponding to the speed of each pump impeller and turbine are used as multiple kinetic stiffness feature cluster points to obtain the kinetic stiffness feature cluster points under normal conditions. Similarly, the kinetic stiffness feature cluster points under minor leakage fault conditions and under severe leakage fault conditions are obtained.

[0088] Substituting each kinetic stiffness feature cluster point under normal conditions into the second fault diagnosis model yields the interval [w1, w2] to which the leakage evaluation value belongs under normal conditions, where w1 is the minimum leakage evaluation value of the kinetic stiffness feature cluster point under normal conditions, and w2 is the maximum leakage evaluation value of the kinetic stiffness feature cluster point under normal conditions. Substituting each kinetic stiffness feature cluster point under minor leakage fault conditions into the second fault diagnosis model yields the interval [w3, w4] to which the leakage evaluation value belongs under minor leakage fault conditions, where w3 is the minimum leakage evaluation value of the kinetic stiffness feature cluster point under minor leakage fault conditions, and w4 is the maximum leakage evaluation value of the kinetic stiffness feature cluster point under minor leakage fault conditions. Substituting each kinetic stiffness feature cluster point under severe leakage fault conditions into the second fault diagnosis model yields the interval [w5, w6] to which the leakage evaluation value belongs under severe leakage fault conditions, where w5 is the minimum leakage evaluation value of the kinetic stiffness feature cluster point under severe leakage fault conditions. The minimum leakage evaluation value of the stiffness feature cluster points is w6, and the maximum leakage evaluation value of the kinetic stiffness feature cluster points under severe leakage fault conditions is w6. [w1, w2] are taken as the cluster center under normal conditions, [w3, w4] are taken as the cluster center under slight leakage fault conditions, and [w5, w6] are taken as the cluster center under severe leakage fault conditions. Thus, the second fault evaluation index is obtained. This application does not limit the second fault evaluation index. The specific index value is determined according to the historical data of the hydraulic torque converter to be tested. Preferably, this application sets the second fault evaluation index as follows: under normal conditions, the leakage evaluation value of the kinetic stiffness feature cluster points is [0.18, 0.21], under slight leakage fault conditions, the leakage evaluation value of the kinetic stiffness feature cluster points is [0.47, 0.51], and under severe leakage fault conditions, the leakage evaluation value of the kinetic stiffness cluster points is [0.64, 0.75].

[0089] Step S3: Obtain the test operating data of the pump impeller and turbine in the hydraulic torque converter to be tested, and determine the test leakage evaluation value of the hydraulic torque converter to be tested according to the fault diagnosis model.

[0090] For the first fault diagnosis model:

[0091] The kinetic stiffness angles of the pump impeller and turbine at different speeds in the hydraulic torque converter under test are obtained. The degree of kinetic energy change of the hydraulic torque converter under test is calculated by using the kinetic stiffness angles of the pump impeller and turbine at different speeds, so as to make the test results more accurate. The difference between the kinetic stiffness angles of the pump impeller and turbine is used as the degree of kinetic energy change. The average value of the degree of kinetic energy change is substituted into the calculation of the leakage evaluation value of the hydraulic torque converter under test.

[0092] For the second fault diagnosis model:

[0093] The flow rate and rotational speed of the pump impeller and turbine in the hydraulic torque converter under test are obtained as the test operating data. The speed difference between each group of pump impeller and turbine is used as a kinetic stiffness feature cluster point, and the flow rate difference between each group of pump impeller and turbine corresponding to the rotational speed of that group of pump impeller and turbine is used as a kinetic stiffness feature cluster point. All the test kinetic stiffness feature cluster points of the hydraulic torque converter under test are obtained. Each test kinetic stiffness feature cluster point is substituted into the second fault diagnosis model to obtain the leakage evaluation value of each test kinetic stiffness feature cluster point.

[0094] Step S4: Determine the fault status of the hydraulic torque converter based on the fault evaluation index and the leakage evaluation value to be tested. If no fault occurs, continue operation; if a fault occurs, diagnose the fault type.

[0095] For the first fault diagnosis model:

[0096] When the leakage evaluation value of the hydraulic torque converter under test is less than or equal to the leakage evaluation value z of the hydraulic torque converter under normal conditions, the hydraulic torque converter under test is in normal condition; when the leakage evaluation value of the hydraulic torque converter under test is less than the leakage evaluation value y of the hydraulic torque converter under severe conditions but greater than the leakage evaluation value z of the hydraulic torque converter under normal conditions, the hydraulic torque converter under test is in a minor leakage fault state; when the leakage evaluation value of the hydraulic torque converter under test is greater than or equal to the leakage evaluation value y of the hydraulic torque converter under severe conditions, the hydraulic torque converter under test is in a severe leakage fault state.

[0097] For the second fault diagnosis model:

[0098] If a set proportion or more of the clusters of all tested kinetic stiffness feature clusters have leakage evaluation values ​​that fall within the normal state cluster center, then the hydraulic torque converter under test is in a normal state. If a set proportion or more of the clusters of all tested kinetic stiffness feature clusters have leakage evaluation values ​​that fall within the minor leakage fault state cluster center, then the hydraulic torque converter under test is in a minor leakage fault state. If a set proportion or more of the clusters of all tested kinetic stiffness feature clusters have leakage evaluation values ​​that fall within the severe leakage fault state cluster center, then the hydraulic torque converter under test is in a severe leakage fault state. It should be noted that this application does not limit the set proportion, and it can be adaptively modified according to historical data based on actual conditions. This application preferably sets the set proportion to 80%.

[0099] For fault diagnosis models, regardless of whether the first or second fault diagnosis model is used, once the fault type is diagnosed, appropriate actions are taken based on that fault type. It should be noted that when the torque converter under test is in a normal state, no action is taken, and the system continues to operate. When the torque converter under test has a minor leakage fault, the pump impeller can still drive the turbine, but damaged components within the torque converter cause a certain amount of leakage from the pump impeller; the damaged components within the torque converter need to be replaced promptly. When the torque converter under test has a severe leakage fault, the pump impeller leakage is significant and cannot drive the turbine; the torque converter under test needs to be shut down immediately, and the damaged components replaced.

[0100] Example 1

[0101] This embodiment uses a first fault diagnosis model to diagnose the faults in the hydraulic torque converter under test, acquiring the test operation data and historical operation data of the hydraulic torque converter under test. Specifically, when the pump impeller speed is 1600 r / min, the kinetic stiffness angle of the pump impeller, the corresponding speed of the turbine, and the kinetic stiffness angle of the turbine corresponding to the turbine speed are acquired. Keeping the pump impeller speed constant, the input flow rate of the pump impeller is reduced, and the kinetic stiffness angles of the pump impeller and turbine corresponding to different pump impeller input flow rates are acquired, resulting in multiple sets of corresponding kinetic stiffness angles. Then, the pump impeller speed is modified to 2000 r / min, and multiple sets of corresponding kinetic stiffness angles are acquired again. The multiple sets of corresponding kinetic stiffness angles obtained in the two tests are used as the test operation data.

[0102] Multiple sets of kinetic stiffness angles under normal, minor leakage fault, and severe leakage fault conditions from historical operating data are substituted into the first fault diagnosis model to obtain the first fault evaluation index. Specifically, when the leakage evaluation value is less than or equal to 0.2, the hydraulic torque converter is in normal condition; when the leakage evaluation value is greater than or equal to 0.5, the hydraulic torque converter is in severe leakage fault condition; and when the leakage evaluation value is greater than 0.2 and less than 0.5, the hydraulic torque converter is in minor leakage fault condition.

[0103] The test operating data is substituted into the first fault diagnosis model to obtain the leakage evaluation value of the hydraulic torque converter under test. The leakage evaluation value of the hydraulic torque converter under test is compared with the first fault evaluation index to determine the fault state of the hydraulic torque converter under test.

[0104] When the hydraulic torque converter under test is in a state of minor leakage fault, such as Figure 2 As shown, because the changes in the positive kinetic energy stiffness of the pump impeller and turbine are relatively small, meaning the slopes of the kinetic energy change rates of the pump impeller and turbine are quite similar, but there are still some differences, the degree of failure is relatively low; for example... Figure 3As shown, the positive kinetic energy stiffness loss of the pump impeller and turbine is small, meaning the area difference between the annular rings formed by the pump impeller and turbine is small, thus the failure degree is low; as Figure 4 As shown, since the leakage of the pump wheel is small, the pump wheel can still drive the turbine to rotate. That is, the kinetic stiffness angles of the pump wheel and the turbine are relatively close and the difference is small. Therefore, the leakage evaluation value is smaller and the degree of failure is lower.

[0105] When the hydraulic torque converter under test is in a state of severe leakage fault, such as Figure 5 As shown, due to the large variation in the positive kinetic energy stiffness of the pump impeller and turbine, i.e., the significant difference in the slope of the rate of change of kinetic energy between the pump impeller and turbine, the failure degree is relatively high; for example... Figure 6 As shown, the positive kinetic energy stiffness loss of the pump impeller and turbine is relatively large, meaning that the area of ​​the annulus formed by the pump impeller and turbine differs significantly, thus leading to a higher degree of failure; for example... Figure 7 As shown, due to the large leakage of the pump wheel, the pump wheel cannot drive the turbine to rotate. The difference in kinetic stiffness angle between the turbine and the pump wheel is large, so the leakage evaluation value is large and the degree of failure is higher.

[0106] Example 2

[0107] This embodiment uses a second fault diagnosis model to diagnose the faults in the hydraulic torque converter under test, acquiring the test operation data and historical operation data of the hydraulic torque converter under test. Specifically, when the pump impeller speed in the hydraulic torque converter under test is 1600 r / min, the input flow rate of the pump impeller is changed, and the flow rate of each pump impeller and turbine is acquired. The difference in flow rate between each pump impeller and turbine is used as a kinetic stiffness feature, and the difference in speed between the pump impeller and turbine at this pump impeller speed is also used as a kinetic stiffness feature. Each kinetic stiffness feature is used as a kinetic stiffness feature cluster point, resulting in multiple kinetic stiffness feature cluster points. Then, the pump impeller speed is modified to 2000 r / min, and multiple kinetic stiffness feature cluster points are acquired again. The multiple kinetic stiffness feature cluster points obtained in the two tests are used as the test operation data.

[0108] The test data is substituted into the second fault diagnosis model to obtain the leakage evaluation value of each kinetic stiffness feature cluster point. The leakage evaluation value of each kinetic stiffness feature cluster point is compared with the second fault evaluation index to determine the fault state of the hydraulic torque converter under test.

[0109] When the hydraulic torque converter under test is in normal condition, such as Figure 8 As shown, since the cluster points of the kinetic stiffness features under test are close to the cluster center of the kinetic stiffness features under normal conditions, most of the cluster points of the kinetic stiffness features under test of the hydraulic torque converter under test are close to the cluster center of the kinetic stiffness features under normal conditions.

[0110] When the hydraulic torque converter under test is in a state of minor leakage fault, such as Figure 9As shown, since the cluster points of the measured kinetic stiffness features are close to the cluster center of the kinetic stiffness features under the minor leakage fault state, most of the cluster points of the measured kinetic stiffness features of the hydraulic torque converter under test are close to the cluster center of the kinetic stiffness features under the minor leakage fault state.

[0111] When the hydraulic torque converter under test is in a state of severe leakage fault, such as Figure 10 As shown, the cluster points of the measured kinetic stiffness features are close to the cluster center of the kinetic stiffness features under severe leakage fault conditions. Most of the cluster points of the measured kinetic stiffness features of the hydraulic torque converter under test are close to the cluster center of the kinetic stiffness features under severe conditions.

[0112] It should be noted that, regarding the first and second fault diagnosis models, the first fault diagnosis model determines the degree of kinetic energy change solely through the kinetic stiffness angle between the pump impeller and the turbine, resulting in a relatively large range of first fault evaluation indicators. The second fault diagnosis model, however, determines the kinetic energy change through the flow rate difference and speed difference between the pump impeller and the turbine, and introduces a fuzzy clustering algorithm to perform fuzzy clustering on the kinetic stiffness feature cluster points, further refining the second fault evaluation indicators and making the fault types derived by the second fault diagnosis model more accurate. However, since the evaluation values ​​for each state in the second fault evaluation indicators fall within the range of the evaluation values ​​for each state corresponding to the first fault evaluation indicators, the fault types derived by the two fault diagnosis models must be the same. It is impossible for the same test data to yield different fault types through different fault diagnosis models.

[0113] This application also includes a leakage fault diagnosis system for hydraulic torque converters based on the above-mentioned leakage fault diagnosis method. This system includes a data acquisition module, a condition evaluation module, a fault diagnosis module, and a decision support module. The data acquisition module collects operating data of the pump impeller and turbine in the hydraulic torque converter, specifically including the kinetic stiffness angle of the pump impeller and turbine, or the flow rate and rotational speed of the pump impeller and turbine. The condition evaluation module establishes a fault diagnosis model and determines fault evaluation indicators based on the acquired operating data of the pump impeller and turbine. The fault diagnosis module performs fault diagnosis on the hydraulic torque converter under test using the operating data and the fault diagnosis model. The decision support module processes the hydraulic torque converter under test according to the fault diagnosis results, thereby enabling the hydraulic torque converter to operate normally.

[0114] The above description is merely a specific embodiment of the present invention, enabling those skilled in the art to understand or implement the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention.

[0115] It should be understood that the present invention is not limited to the content already described above, and various modifications and changes can be made without departing from its scope. The scope of the present invention is limited only by the appended claims.

Claims

1. A method for diagnosing leakage faults in a hydraulic torque converter, characterized in that, Includes the following steps: Step S1: Obtain the operating data of the pump impeller and turbine in the hydraulic torque converter, and establish a fault diagnosis model; the fault diagnosis model includes a first fault diagnosis model and a second fault diagnosis model. The first fault diagnosis model is based on the kinetic stiffness angle of the pump impeller and turbine in the hydraulic torque converter as a feature for fault diagnosis, and the second fault diagnosis model is based on the flow rate and rotational speed of the pump impeller and turbine in the hydraulic torque converter as features for fault diagnosis. Step S2: Determine the fault evaluation index of the hydraulic torque converter using the operating data and the fault diagnosis model; the fault evaluation index includes the first fault evaluation index corresponding to the first fault diagnosis model and the second fault evaluation index corresponding to the second fault diagnosis model; Step S3: Obtain the kinetic stiffness angle of the turbine and pump wheel of the hydraulic torque converter to be tested, or the flow rate and speed of the turbine and pump wheel, and determine the test leakage evaluation value of the hydraulic torque converter to be tested according to the characteristics corresponding to the first fault diagnosis model or the second fault diagnosis model. Step S4: Determine the fault status of the hydraulic torque converter based on the fault evaluation index and the leakage evaluation value to be tested. If no fault occurs, continue operation; if a fault occurs, diagnose the fault type. The first fault diagnosis model is shown below: in, This is the leakage evaluation value for the hydraulic torque converter. This represents the average change in kinetic energy between the pump impeller and the turbine in the hydraulic torque converter under test. This represents the degree of kinetic energy change of the pump impeller and turbine of the hydraulic torque converter in the initial state. The formula for calculating the degree of kinetic energy change of the hydraulic torque converter is as follows: in, The degree of kinetic energy change in the hydraulic torque converter. The kinetic stiffness angle of the turbine. The kinetic stiffness angle of the pump impeller; The second fault diagnosis model is shown below: Specifically, the speed difference between each pump impeller and turbine under each operating condition is defined as a kinetic stiffness feature cluster point. Indicates the first Leakage evaluation value of each kinetic stiffness characteristic cluster point The index indicating the category of running status. The number of categories representing the running status. This indicates the index of the cluster point representing the kinetic energy stiffness characteristic. Represents fuzzy constants. Indicates the first The kinetic stiffness characteristic of the first Membership degree of class runtime state, Indicates the first The number of cluster points for the kinetic stiffness characteristics of the class of operating states; The membership degree is calculated as follows: in, This indicates the number of cluster points representing the kinetic energy stiffness characteristic. Indicates the first The first in the category The kinetic stiffness characteristic cluster point and the first The distance between cluster points of kinetic stiffness characteristics Indicates the first Except for the first category The index of the kinetic stiffness feature cluster points. Indicates the first The minimum distance between cluster points of each kinetic stiffness feature in each category.

2. The method for diagnosing leakage faults in a hydraulic torque converter according to claim 1, characterized in that, The process for determining the first fault evaluation index is as follows: The kinetic stiffness angles of each turbine and pump impeller of the hydraulic torque converter under normal and severe leakage fault conditions are obtained from the operating data respectively. These angles are used to calculate the degree of kinetic energy change of the hydraulic torque converter under normal and severe leakage fault conditions. The degree of kinetic energy change of the hydraulic torque converter under normal and severe leakage fault conditions is substituted into the first fault diagnosis model to obtain thresholds z and y, where z is less than y. The z and y are used as the first fault evaluation index. The first fault evaluation index is as follows: when the leakage evaluation value FD is less than or equal to z, the hydraulic torque converter under test is in normal condition; when the leakage evaluation value FD is greater than z and less than y, the hydraulic torque converter under test is in a slight leakage fault state; when the leakage evaluation value FD is greater than or equal to y, the hydraulic torque converter under test is in a serious leakage fault state.

3. The leakage fault diagnosis method for a hydraulic torque converter according to claim 1, characterized in that, The process for determining the second fault evaluation index is as follows: The kinetic stiffness feature clusters in the normal state, minor leakage fault state and severe leakage fault state in the operating data are obtained respectively. The membership degree of each kinetic stiffness feature cluster in each category is calculated by the distance between the obtained kinetic stiffness feature clusters. The second fault evaluation index of the hydraulic torque converter under different fault states is determined by the calculated membership degree and the second fault diagnosis model. The second fault evaluation index is as follows: when the leakage evaluation value of the cluster points of the measured kinetic stiffness feature exceeds the set proportion [w1, w2], the operating state of the hydraulic torque converter under test is normal; when the leakage evaluation value of the cluster points of the measured kinetic stiffness feature exceeds the set proportion [w3, w4], the operating state of the hydraulic torque converter under test is a minor leakage fault state; when the leakage evaluation value of the cluster points of the measured kinetic stiffness feature exceeds the set proportion [w5, w6], the operating state of the hydraulic torque converter under test is a serious leakage fault state. Among them, w1 < w2, w3 < w4, w5 < w6.

4. The method for diagnosing leakage faults in a hydraulic torque converter according to any one of claims 1-3, characterized in that, Acquire the operational data to be tested, input the operational data to be tested into the fault diagnosis model, and obtain the evaluation value of the leakage to be tested; When the leakage evaluation value under test is within the normal state evaluation index range, the operating state of the hydraulic torque converter under test is normal. When the leakage evaluation value under test is within the range of the minor leakage fault state evaluation index, the operating state of the hydraulic torque converter under test is a minor leakage fault state. When the leakage evaluation value under test is within the range of the evaluation index for severe leakage fault state, the operating state of the hydraulic torque converter under test is a severe leakage fault state.

5. The method for diagnosing leakage faults in a hydraulic torque converter according to claim 4, characterized in that, When the fault status of the hydraulic torque converter under test is normal, the hydraulic torque converter continues to operate normally; When the fault condition of the hydraulic torque converter under test is a minor leakage fault, the pump wheel in the hydraulic torque converter can still drive the turbine to rotate, and the hydraulic torque converter can continue to operate, but it needs to be repaired in time within a set time. When the fault condition of the hydraulic torque converter under test is a serious leakage fault, the pump wheel after the flow leakage is difficult to drive the turbine to rotate for operation. It is necessary to immediately shut down the hydraulic torque converter and replace the components in the hydraulic torque converter immediately.

6. A leakage fault diagnosis system for a hydraulic torque converter, characterized in that, The leakage fault diagnosis system is based on the leakage fault diagnosis method according to any one of claims 1-5, and includes a data acquisition module, a status evaluation module, a fault diagnosis module, and a decision support module. Data acquisition module: used to collect operating data of pump impeller and turbine in hydraulic torque converter. The operating data specifically includes the kinetic stiffness angle of pump impeller and turbine or the flow rate and speed of pump impeller and turbine. Condition evaluation module: used to establish a fault diagnosis model and determine fault evaluation indicators based on the acquired pump impeller and turbine operating data; Fault diagnosis module: used to diagnose faults in the hydraulic torque converter under test using the test operation data and fault diagnosis model; Decision support module: Based on the fault diagnosis results, the hydraulic torque converter under test is processed accordingly, so that the hydraulic torque converter can operate normally.

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