Method, device, equipment and storage medium for extracting steady-state performance points of turboshaft engine

Abstract

The present invention relates to the technical field of turboshaft engine performance, and discloses a method, device, equipment, and storage medium for extracting the steady-state performance point of a turboshaft engine, including: calculating the absolute value of the data change of each test channel parameter corresponding to each test data; filtering the absolute value of the data change, processing the filtered absolute value of the data change using a maximum sliding window, and obtaining a second data set by union; determining a state mutation point; determining an initial optimal steady-state performance point; selecting a first number of test data before the initial optimal steady-state performance point in the second data set as a third data set for averaging, converting according to standard environmental conditions, and obtaining steady-state performance point data. The present invention realizes automated, efficient, fast, and easy-to-configure extraction of the steady-state performance point of a turboshaft engine. Since it does not involve the configuration of statistical data, it has greater versatility, is easier to debug, and can be quickly applied to engines and test benches of different models.

Description

Technical Field

[0001] The present invention relates to the technical field of turboshaft engine performance, and in particular to a method, device, equipment and storage medium for extracting steady-state performance points of a turboshaft engine. Background Art

[0002] The steady-state performance point (SPS) of a turboshaft engine is a key characteristic reflecting its performance. Extracting these SPS points is crucial for turboshaft engine performance analysis, improvement, and evaluation. Currently, there are two main methods for extracting SPS points: manual recording by test operators during the test, and manual selection of SPS points by designers using test data after the test.

[0003] In related technologies, Document 1, "A Rapid Method for Extracting Control System Performance Indicators" (Information Technology, 2012, Issue 12, pp. 19-21), discloses a method for extracting control performance indicators. This method extracts performance indicators based on ideal control performance curves, using noisy test data that cannot be used to extract corresponding performance indicators. Document 2, "A Method for Extracting Turboshaft Engine Control Performance Indicators Based on Test Data," discloses a method for extracting turboshaft engine control performance indicators based on test data. This method uses statistical methods to analyze test data and determine steady-state and dynamic processes.

[0004] During turboshaft engine testing, due to the engine's unfrozen state and test bench equipment limitations, the turboshaft engine test data in Reference 1 cannot represent an ideal, noise-free state. Furthermore, due to differences in the performance of different test bench equipment, the fluctuations in the engine's high and low states during steady-state testing can vary significantly during the same test, resulting in significant discrepancies in the statistical indicators of steady-state performance points. The statistical indicators in Reference 2 often fail to intuitively reflect their physical meaning, making debugging and configuration difficult for users. Summary of the Invention

[0005] In view of this, the present invention provides a method, device, equipment and storage medium for extracting the steady-state performance point of a turboshaft engine to solve the existing problem of difficulty in determining the steady-state performance point of a turboshaft engine.

[0006] In a first aspect, the present invention provides a method for extracting steady-state performance points of a turboshaft engine, the method comprising:

[0007] Determine the test channel parameters of the steady-state test channel of the engine and collect test data corresponding to each test channel parameter;

[0008] Calculate the absolute value of the data change of each test channel parameter corresponding to each test data;

[0009] Based on a preset data change threshold, the absolute value of the data change is filtered to obtain the filtered absolute value of the data change;

[0010] Based on the sampling rate of the engine data acquisition system, the absolute value of the filtered data change is processed using a maximum sliding window to obtain a first data set corresponding to each test channel parameter;

[0011] Calculating a union of the first data sets to obtain a second data set;

[0012] Screening the second data set to determine a state mutation point, where the state mutation point is a state mutation point at which the engine changes from a steady state to a transition state;

[0013] Determine the initial optimal steady-state performance point based on the sampling rate and the state mutation point;

[0014] Taking the initial best steady-state performance point as a starting point, selecting a first number of test data before the initial best steady-state performance point in the second data set as a third data set, and averaging the third data set to obtain an average steady-state performance point;

[0015] According to the standard environmental conditions, the average steady-state performance point is converted to obtain the steady-state performance point data under the standard environmental conditions.

[0016] In the present invention, by calculating the data variation of the test data corresponding to each test channel parameter, filtering the data variation using the data variation threshold of each test channel parameter, and using maximum sliding window processing, the state mutation point from the engine steady state to the transition state is determined, and the selection range of the optimal steady-state performance point is determined based on the state mutation point, and all steady-state performance point data is obtained, thereby achieving automated, efficient, fast, and easy-to-configure extraction of the steady-state performance point of the turboshaft engine. Because the process of extracting the steady-state performance point of the turboshaft engine does not involve the configuration of statistical data, the method is more versatile and easier to debug. It can be quickly applied to different types of engines and different test bench equipment, reducing the difficulty of engine steady-state performance testing.

[0017] In an optional implementation, filtering the absolute value of the data change based on a preset data change threshold to obtain the filtered absolute value of the data change includes:

[0018] Determine whether the absolute value of the current data change is less than the preset data change threshold;

[0019] When the absolute value of the current data change is less than the preset data change threshold, the current data change is set to 0;

[0020] When the absolute value of the current data change is not less than the preset data change threshold, the current data change is maintained until all the absolute values ​​of the data change are traversed to obtain the filtered absolute value of the data change.

[0021] In this method, by setting the data change threshold of each test channel parameter, the absolute value of the data change of each test data point is filtered, so that the physical meaning of the filtered data change is more intuitive and it is easier to configure the extraction of the steady-state performance point of the turboshaft engine.

[0022] In an optional embodiment, the length of the maximum value sliding window is determined based on the stabilization time for the engine to maintain stable operation and the sampling rate of the engine data acquisition system.

[0023] In this way, by setting a maximum sliding window to process the absolute value of the data transformation amount after filtering of each relevant channel parameter, smoothing of the test data is achieved, while ensuring the stable operation time of each test channel parameter.

[0024] In an optional embodiment, screening the second data set based on preset conditions to determine the state mutation point includes:

[0025] Determine whether the second data at the current moment is equal to 0, and whether the second data at the next moment is greater than 0;

[0026] When the second data at the current moment is equal to 0 and the second data at the next moment is greater than 0, the second data at the current moment is determined to be a state mutation point;

[0027] When the second data at the current moment is not equal to 0, or the second data at the next moment is not greater than 0, it is determined that the second data at the current moment is not a state mutation point.

[0028] In this method, the state mutation point represents the point at which the engine has been running in the stable state for the longest time, which can be used to determine the selection of the optimal steady-state performance point, making it easier to subsequently use the state mutation point to screen the optimal steady-state performance point.

[0029] In an optional embodiment, determining the initial optimal steady-state performance point based on the sampling rate and the state mutation point includes:

[0030] Determining a first preset period before a state mutation point based on an actual condition of the engine;

[0031] determining a second number based on the sampling rate and the first predetermined period;

[0032] Taking the state mutation point as a starting point, a second number of test data before the state mutation point is selected in the second data set as an initial optimal steady-state performance point.

[0033] In this method, due to the influence of the engine state and the accuracy of the test equipment, the data near the state mutation point from the steady state to the transition state of the engine is often unstable. Therefore, by selecting the data of the first preset time period before the state mutation point as the initial optimal steady-state performance point, the stability of the selection of the initial optimal steady-state performance point is improved, and the data accuracy of the optimal steady-state performance point is ensured.

[0034] In an optional embodiment, the first quantity is determined as follows:

[0035] determining a second preset period before the initial optimal steady-state performance point based on the actual condition of the engine;

[0036] A first quantity is determined based on the sampling rate and a second predetermined period.

[0037] In this method, in order to avoid excessive random errors that may be caused by a single data point, the data within the experimental data sequence number range before the initial optimal steady-state performance point are averaged, which further improves the accuracy and reliability of the steady-state performance point data.

[0038] In a second aspect, the present invention provides a device for extracting a steady-state performance point of a turboshaft engine, the device comprising:

[0039] A data acquisition module is used to determine the test channel parameters of the steady-state test channel of the engine and collect test data corresponding to each test channel parameter;

[0040] The absolute value calculation module of the variation is used to calculate the absolute value of the data variation of each test channel parameter corresponding to each test data;

[0041] A data filtering module is used to filter the absolute value of the data change based on a preset data change threshold to obtain the filtered absolute value of the data change;

[0042] A sliding processing module is used to process the absolute value of the filtered data change using a maximum sliding window based on the sampling rate of the engine data acquisition system to obtain a first data set corresponding to each test channel parameter;

[0043] a data union module, configured to union the first data sets to obtain a second data set;

[0044] a state mutation point determination module, configured to screen the second data set and determine a state mutation point, where the state mutation point is a state mutation point at which the engine changes from a steady state to a transition state;

[0045] A steady-state performance point determination module is used to determine the initial optimal steady-state performance point based on the sampling rate and the state mutation point;

[0046] a data averaging module, configured to use the initial optimal steady-state performance point as a starting point, select a first number of test data before the initial optimal steady-state performance point from the second data set as a third data set, and average the third data set to obtain an average steady-state performance point;

[0047] The data conversion module is used to convert the average steady-state performance point according to the standard environmental conditions to obtain the steady-state performance point data under the standard environmental conditions.

[0048] In a third aspect, the present invention provides a computer device comprising: a memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, and the processor executing the method for extracting the steady-state performance point of a turboshaft engine according to the first aspect or any corresponding embodiment thereof by executing the computer instructions.

[0049] In a fourth aspect, the present invention provides a computer-readable storage medium having computer instructions stored thereon, the computer instructions being used to enable a computer to execute the method for extracting the steady-state performance point of a turboshaft engine according to the first aspect or any corresponding embodiment thereof.

[0050] In a fifth aspect, the present invention provides a computer program product comprising computer instructions for causing a computer to execute the method for extracting the steady-state performance point of a turboshaft engine according to the first aspect or any corresponding embodiment thereof. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the specific embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0052] Figure 1 4 is a flow chart of a method for extracting steady-state performance points of a turboshaft engine according to an embodiment of the present invention.

[0053] Figure 2 The present invention is a flowchart of a method for extracting steady-state performance points from turboshaft engine test data according to an embodiment of the present invention.

[0054] Figure 3a 3 is a schematic diagram of the data change amount and the absolute value of the data change amount between each data point and the data points 50 apart in an NGRR parameter according to an embodiment of the present invention.

[0055] Figure 3b3 is a schematic diagram of the data change amount and the absolute value of the data change amount between each data point and the data points 50 apart in a CLP parameter according to an embodiment of the present invention.

[0056] Figure 4a 3 is a schematic diagram of a data change between each data point and 50 data points apart and an absolute value of the filtered data change in an NGRR parameter according to an embodiment of the present invention.

[0057] Figure 4b 3 is a schematic diagram of a data change between each data point and 50 data points apart in a CLP parameter and the absolute value of the filtered data change according to an embodiment of the present invention.

[0058] Figure 5a According to an embodiment of the present invention, a method for calculating the absolute value V of the data transformation amount by using a maximum sliding window is used. fNGR Processing to obtain V fsNGR Schematic diagram of .

[0059] Figure 5b According to an embodiment of the present invention, a method for calculating the absolute value V of the data transformation amount by using a maximum sliding window is used. fCLP Processing to obtain V fsCLP Schematic diagram of .

[0060] Figure 6 2 is a schematic diagram of determining a state mutation point according to an embodiment of the present invention.

[0061] Figure 7 4 is a flow chart of another method for extracting steady-state performance points of a turboshaft engine according to an embodiment of the present invention.

[0062] Figure 8 4 is a flow chart of another method for extracting steady-state performance points of a turboshaft engine according to an embodiment of the present invention.

[0063] Figure 9 4 is a structural block diagram of a device for extracting steady-state performance points of a turboshaft engine according to an embodiment of the present invention.

[0064] Figure 10 Schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0065] To make the purpose, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making creative efforts shall fall within the scope of protection of the present invention.

[0066] In related technologies, Document 1, "A Rapid Method for Extracting Control System Performance Indicators" (Information Technology, 2012, Issue 12, pp. 19-21), discloses a method for extracting control performance indicators. This method extracts performance indicators based on ideal control performance curves, using noisy test data that cannot be used to extract corresponding performance indicators. Document 2, "A Method for Extracting Turboshaft Engine Control Performance Indicators Based on Test Data," discloses a method for extracting turboshaft engine control performance indicators based on test data. This method uses statistical methods to analyze test data and determine steady-state and dynamic processes.

[0067] During turboshaft engine testing, due to the engine's unfrozen state and test bench equipment limitations, the turboshaft engine test data in Reference 1 cannot represent an ideal, noise-free state. Furthermore, due to differences in the performance of different test bench equipment, the fluctuations in the engine's high and low states during steady-state testing can vary significantly during the same test, resulting in significant discrepancies in the statistical indicators of steady-state performance points. The statistical indicators in Reference 2 often fail to intuitively reflect their physical meaning, making debugging and configuration difficult for users.

[0068] To solve the above problems, an embodiment of the present invention provides a method for extracting the steady-state performance point of a turboshaft engine, which is used in a computer device. It should be noted that its execution subject can be a device for extracting the steady-state performance point of a turboshaft engine. The device can be implemented as part or all of a computer device through software, hardware, or a combination of software and hardware. The computer device can be a terminal, a client, or a server. The server can be a single server or a server cluster composed of multiple servers. The terminal in the embodiment of the present application can be a smart phone, a personal computer, a tablet computer, or other intelligent hardware devices. In the following method embodiments, the execution subject is a computer device as an example for explanation.

[0069] The computer device in this embodiment is suitable for use in scenarios where the steady-state performance points of an engine are extracted during a turboshaft engine test. The present invention provides a method for extracting the steady-state performance points of a turboshaft engine. By calculating the data variation of the test data corresponding to each test channel parameter, filtering the data variation using the data variation threshold of each test channel parameter, and using the maximum sliding window process, the state mutation point from the steady state to the transition state of the engine is determined, and the selection range of the optimal steady-state performance point is determined based on the state mutation point, all steady-state performance point data is obtained, and an automated, efficient, fast, and easy-to-configure extraction of the steady-state performance points of the turboshaft engine is achieved. Since the extraction process of the steady-state performance points of the turboshaft engine does not involve the configuration of statistical data, the method is more versatile and easier to debug. It can be quickly applied to engines of different models and different test bench equipment, reducing the difficulty of engine steady-state performance testing.

[0070] According to an embodiment of the present invention, an embodiment of a method for extracting steady-state performance points of a turboshaft engine is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0071] In this embodiment, a method for extracting steady-state performance points of a turboshaft engine is provided, which can be used in the above-mentioned computer device. Figure 1 FIG. 1 is a flow chart of a method for extracting a steady-state performance point of a turboshaft engine according to an embodiment of the present invention. Figure 1 As shown, the process includes the following steps:

[0072] Step S101 : determining test channel parameters of a steady-state test channel of the engine, and collecting test data corresponding to each test channel parameter.

[0073] In one example, relative speed (NGR) and load bar angle (CLP) are selected as test channel parameters for steady-state performance point calculation. More parameters, such as pre-turbine temperature, torque, and power, can be selected based on the actual engine conditions. The calculation method is the same as that for the test parameters in the embodiment of the present invention. The selection of test parameters is not limited in the present invention.

[0074] Step S102 : calculating and obtaining the absolute value of the data variation of each test channel parameter corresponding to each test data.

[0075] In one example, the absolute value of the data change between each data point and the data points n apart of the test channel parameters A1, A2, A3... (parameters related to the steady state of the engine) in the test data is calculated, and the absolute value parameter of the data change corresponding to the calculated data of each test channel parameter is expressed as V A1 、VA2 、V A3 ... indicates that the value of n is configured based on the sampling rate of the turboshaft engine data acquisition system. The value of n should not be less than the number of data points collected by the data acquisition system during one data acquisition cycle. The present invention does not impose any restrictions on the value of n.

[0076] Step S103 : filtering the absolute value of the data change based on a preset data change threshold to obtain a filtered absolute value of the data change.

[0077] In one example, the data change threshold t of each test channel parameter is set A1 , t A2 , t A3 ..., the absolute value parameter V of the data change A1 、V A2 、V A3 ...is filtered, the absolute value of the data change less than the threshold is set to 0, and the absolute value of the data change greater than the threshold is retained. The absolute value parameter of the filtered data change is expressed as V fA1 、V fA2 、V fA3 .... Among them, the absolute value of the data change amount less than the threshold value indicates that the engine is in a stable operating state.

[0078] Step S104 : Based on the sampling rate of the engine data acquisition system, the filtered absolute value of the data variation is processed using a maximum sliding window to obtain a first data set corresponding to each test channel parameter.

[0079] In one example, the maximum sliding window is used to transform the absolute value V of the filtered data. fA1 、V fA2 、V fA3 ...processed to obtain V fsA1 、V fsA2 、V fsA3 ..., the length m of the sliding window is set according to the time the engine needs to maintain stable operation and the sampling rate.

[0080] Step S105 : performing a union of the first data sets to obtain a second data set.

[0081] In one example, a union of VfsA1, VfsA2, VfsA3, ... is obtained, and the obtained data parameter is represented by V to obtain a second data set.

[0082] Step S106: Screen the second data set to determine a state mutation point.

[0083] In the embodiment of the present invention, the state mutation point is a state mutation point where the engine changes from a steady state to a transition state.

[0084] In one example, the condition Vi = 0 and Vi + 1 > 0 is used to determine the state transition point Vi from steady state to transition state, where i represents the test data sequence. The state transition point represents the point at which the engine has been operating in the steady state for the longest time and can be used to determine the optimal steady-state performance point.

[0085] Step S107: determining an initial optimal steady-state performance point based on the sampling rate and the state mutation point.

[0086] In one example, select the irth test data D i-r is the optimal steady-state performance point. Here, r is a configuration parameter used to adjust the state mutation point. Due to the influence of engine conditions and test equipment accuracy, data near the state mutation point from steady state to transition state is often unstable. Based on actual conditions, data approximately 3 seconds before the mutation point can be used as the optimal steady-state performance point. If the data acquisition system sampling rate is 5 Hz, then r = 3 * 5 = 15. The time period before the state mutation point, the data acquisition system sampling rate, and the value of r are not limited in this invention.

[0087] Step S108 , taking the initial optimal steady-state performance point as the starting point, selecting a first number of test data before the initial optimal steady-state performance point in the second data set as a third data set, averaging the third data set to obtain an average steady-state performance point.

[0088] In one example, to avoid excessive random errors caused by a single data point, the average value D of the parameters in the test data range [ira, ir] is calculated. aver Where a can be configured based on actual conditions. For example, if averaging 5 seconds of data is desired and the engine data acquisition system sampling rate is 5 Hz, then a is a = 5 * 5 = 25. The time period before the initial optimal steady-state performance point, the data acquisition system sampling rate, and the value of a are not limited in this invention.

[0089] Step S109: converting the average steady-state performance point according to the standard environmental conditions to obtain steady-state performance point data under the standard environmental conditions.

[0090] In one example, D is adjusted according to environmental conditions (ambient temperature, atmospheric pressure, air humidity, Mach number, etc.). aver Convert and obtain the steady-state performance point data D under standard conditions averst Traverse all test data and obtain all steady-state performance point data.

[0091] In one implementation scenario, Figure 2 FIG. 1 is a flow chart of a method for extracting steady-state performance points from turboshaft engine test data according to an embodiment of the present invention. Figure 2As shown, the method for extracting steady-state performance points from turboshaft engine test data may include the following steps:

[0092] Step 1: Select the relative speed (NGR) and load rod angle (CLP) as the test channel parameters for steady-state performance point calculation (more parameters such as turbine inlet temperature, torque, power, etc. can be selected according to actual conditions, and the calculation method is the same). Figure 3a 1 is a schematic diagram of the data change amount and the absolute value of the data change amount between each data point and the data points 50 apart in an NGRR parameter according to an embodiment of the present invention. Figure 3b FIG. 1 is a schematic diagram of the data change amount and the absolute value of the data change amount between each data point and the data points 50 apart in a CLP parameter according to an embodiment of the present invention. Figure 3a and Figure 3b As shown in the figure, the absolute value of the data change between each data point and the data points 50 apart in the NGRR and CLP parameters in the test data is calculated, and the corresponding absolute value parameter of the calculated data change is expressed by V NGR 、V CLP express.

[0093] Step 2: Set the parameters of each test channel and the data change threshold t at 50 data points. NGR =0.009, t CLP = 0.2 (can be set according to the actual situation of the engine and test equipment, the specific value is not limited in the present invention), the absolute value parameter V NGR 、V CLP The absolute value of the data change that is less than the threshold is set to 0, and the absolute value of the data change that is greater than the threshold retains the original value. Figure 4a 3 is a schematic diagram of the data change between each data point and the data points 50 apart and the absolute value of the filtered data change in an NGRR parameter according to an embodiment of the present invention. Figure 4b FIG. 1 is a schematic diagram of the data change amount between each data point and the data points 50 apart and the absolute value of the filtered data change amount in a CLP parameter according to an embodiment of the present invention. Figure 4a and Figure 4b As shown, the absolute value parameter of the filtered data change is expressed as V fNGR 、V fCLP .

[0094] Step 3: Figure 5a According to an embodiment of the present invention, a method for calculating the absolute value V of the data transformation amount by using a maximum sliding window is used. fNGR Processing to obtain V fsNGR Schematic diagram, Figure 5b According to an embodiment of the present invention, a method for calculating the absolute value V of the data transformation amount by using a maximum sliding window is used. fCLPProcessing to obtain V fsCLP Schematic diagram, such as Figure 5a and Figure 5b As shown, the maximum sliding window is applied to the absolute value V of the filtered data transformation fNGR 、V fCLP Processing to obtain V fsNGR 、V fsCLP The engine needs to maintain stable operation for 120 seconds. The sampling rate of the engine data acquisition system is 5 Hz, and the length of the sliding window is 120*5=600.

[0095] Step 4: Figure 6 FIG. 1 is a schematic diagram of determining a state mutation point according to an embodiment of the present invention. Figure 6 As shown, for V fsNGR 、V fsCLP Find the union, and the obtained data parameters are represented by V, and V i =0 and V i+1 The condition of >0 determines the state mutation point V from the engine steady state to the transition state i , i represents the serial number of the test data.

[0096] Step 5: According to the actual situation, take the data about 3s before the mutation point as the best steady-state performance point. If the sampling rate of the data acquisition system is 5Hz, then r=3*5=15. Select the i-15th test data D i-15 is the optimal steady-state performance point.

[0097] Step 6: To avoid excessive random errors caused by a single data point, average the data 5 seconds before the best performance point, that is, calculate the average value D of the parameters in the test data number range [i-15-25, i-15]. aver .

[0098] Step 7: Adjust D according to environmental conditions (ambient temperature, atmospheric pressure, air humidity and Mach number, etc.) aver Convert and obtain the steady-state performance point data D under standard conditions averst .

[0099] Step 8: Traverse the entire test data and repeat steps 4 to 7 to obtain all steady-state performance point data.

[0100] The method for extracting steady-state performance points of a turboshaft engine provided in this embodiment calculates the data variation of the test data corresponding to each test channel parameter, filters the data variation using the data variation threshold of each test channel parameter, and uses a maximum sliding window to determine the state mutation point from the engine steady state to the transition state. Based on the state mutation point, the selection range of the optimal steady-state performance point is determined to obtain all steady-state performance point data, thereby achieving automated, efficient, fast, and easy-to-configure extraction of the steady-state performance points of the turboshaft engine. Because the process of extracting the steady-state performance points of a turboshaft engine does not involve the configuration of statistical data, this method is more versatile and easier to debug. It can be quickly applied to different engine models and different test bench equipment, reducing the difficulty of engine steady-state performance testing.

[0101] In this embodiment, a method for extracting steady-state performance points of a turboshaft engine is provided, which can be used in the above-mentioned computer device. Figure 7 FIG. 1 is a flow chart of another method for extracting steady-state performance points of a turboshaft engine according to an embodiment of the present invention. Figure 7 As shown, the process includes the following steps:

[0102] Step S701: Determine the test channel parameters of the engine's steady-state test channel and collect test data corresponding to each test channel parameter. Figure 1 Step S101 of the illustrated embodiment will not be described in detail here.

[0103] Step S702: Calculate the absolute value of the data change of each test channel parameter corresponding to each test data. Figure 1 Step S102 of the illustrated embodiment will not be described in detail here.

[0104] Step S703 : filtering the absolute value of the data change based on a preset data change threshold to obtain a filtered absolute value of the data change.

[0105] Specifically, the above step S703 includes:

[0106] Step S7031: determine whether the absolute value of the current data change is less than a preset data change threshold.

[0107] Step S7032: When the absolute value of the current data change is less than the preset data change threshold, the current data change is set to 0.

[0108] Step S7033: When the absolute value of the current data change is not less than the preset data change threshold, the current data change is maintained until all the absolute values ​​of the data change are traversed to obtain the filtered absolute value of the data change.

[0109] In one example, the parameters of each test channel are set to the data change threshold t NGR =0.009, t CLP =0.2 (can be set according to the actual situation of the engine and test equipment), the absolute value parameter V NGR 、V CLP The absolute value of the data change less than the threshold is set to 0, and the absolute value of the data change greater than the threshold is retained. The absolute value parameter of the data change after filtering is expressed as V fNGR 、V fCLP .

[0110] In this method, by setting the data change threshold of each test channel parameter, the absolute value of the data change of each test data point is filtered, so that the physical meaning of the filtered data change is more intuitive and it is easier to configure the extraction of the steady-state performance point of the turboshaft engine.

[0111] Step S704 : Based on the sampling rate of the engine data acquisition system, the filtered absolute value of the data variation is processed using a maximum sliding window to obtain a first data set corresponding to each test channel parameter.

[0112] Specifically, the length of the maximum value sliding window is determined based on the stabilization time for the engine to maintain stable operation and the sampling rate of the engine data acquisition system.

[0113] In one example, a maximum sliding window is applied to the filtered data absolute values ​​of the change amounts VfNGR and VfCLP to obtain VfsNGR and VfsCLP. The engine requires 120 seconds of stable operation. The sampling rate of the engine data acquisition system is 5 Hz, and the sliding window length is 120 * 5 = 600 seconds. The present invention does not impose any restrictions on the required stable operation time of the engine.

[0114] In this way, by setting a maximum sliding window to process the absolute value of the data transformation amount after filtering of each relevant channel parameter, smoothing of the test data is achieved, while ensuring the stable operation time of each test channel parameter.

[0115] Step S705: Calculate the union of the first data sets to obtain the second data set. Figure 1 Step S105 of the illustrated embodiment will not be described in detail here.

[0116] Step S706: Screen the second data set to determine the state mutation point.

[0117] Specifically, the above step S706 includes:

[0118] Step S7061, determining whether the second data at the current moment is equal to 0, and whether the second data at the next moment is greater than 0.

[0119] Step S7062: When the second data at the current moment is equal to 0 and the second data at the next moment is greater than 0, determine that the second data at the current moment is a state mutation point.

[0120] Step S7063: When the second data at the current moment is not equal to 0, or the second data at the next moment is not greater than 0, it is determined that the second data at the current moment is not a state mutation point.

[0121] In one example, for V fsNGR 、V fsCLP Find the union, and the obtained data parameters are represented by V, and V i =0 and V i+1 The condition of >0 determines the state mutation point V from the engine steady state to the transition state i , i represents the serial number of the test data.

[0122] In this method, the state mutation point represents the point at which the engine has been running in the stable state for the longest time, which can be used to determine the selection of the optimal steady-state performance point, making it easier to subsequently use the state mutation point to screen the optimal steady-state performance point.

[0123] Step S707: Determine the initial optimal steady-state performance point based on the sampling rate and the state mutation point. Figure 1 Step S107 of the illustrated embodiment will not be described in detail here.

[0124] Step S708: Taking the initial optimal steady-state performance point as the starting point, select the first number of test data before the initial optimal steady-state performance point from the second data set as the third data set, average the third data set, and obtain the average steady-state performance point. Figure 1 Step S108 of the illustrated embodiment will not be described in detail here.

[0125] Step S709: convert the average steady-state performance point according to the standard environmental conditions to obtain the steady-state performance point data under the standard environmental conditions. Figure 1 Step S109 of the illustrated embodiment will not be described in detail here.

[0126] The method for extracting the steady-state performance points of a turboshaft engine provided in this embodiment filters the absolute value of the data change of each test data point by setting the data change threshold of each test channel parameter, so that the physical meaning of the filtered data change is more intuitive and it is easier to configure the extraction of the steady-state performance points of the turboshaft engine. By setting a maximum sliding window to process the absolute value of the filtered data change of each relevant channel parameter, smoothing of the test data is achieved, while ensuring the stable operation time of each test channel parameter. The state mutation point represents the point at which the engine has been running for the longest time in this stable state, and can be used to determine the selection of the best steady-state performance point, so as to facilitate the subsequent screening of the best steady-state performance point using the state mutation point.

[0127] In this embodiment, a method for extracting steady-state performance points of a turboshaft engine is provided, which can be used in the above-mentioned computer device. Figure 8 FIG. 1 is a flow chart of another method for extracting steady-state performance points of a turboshaft engine according to an embodiment of the present invention. Figure 8 As shown, the process includes the following steps:

[0128] Step S801: Determine the test channel parameters of the engine's steady-state test channel and collect test data corresponding to each test channel parameter. Figure 7 Step S701 of the illustrated embodiment will not be described in detail here.

[0129] Step S802: Calculate the absolute value of the data change of each test channel parameter corresponding to each test data. Figure 7 Step S702 of the illustrated embodiment will not be described in detail here.

[0130] Step S803: Filter the absolute value of the data change based on the preset data change threshold to obtain the filtered absolute value of the data change. Figure 7 Step S703 of the illustrated embodiment will not be described in detail here.

[0131] Step S804: Based on the sampling rate of the engine data acquisition system, the absolute value of the filtered data variation is processed using a maximum sliding window to obtain a first data set corresponding to each test channel parameter. Figure 7 Step S704 of the illustrated embodiment will not be described in detail here.

[0132] Step S805: Calculate the union of the first data sets to obtain the second data set. Figure 7 Step S705 of the illustrated embodiment will not be described in detail here.

[0133] Step S806: Screen the second data set to determine the state mutation point, which is the state mutation point where the engine changes from a steady state to a transition state. Figure 7 Step S706 of the illustrated embodiment will not be described in detail here.

[0134] Step S807: determining an initial optimal steady-state performance point based on the sampling rate and the state mutation point.

[0135] Specifically, the above step S807 includes:

[0136] Step S8071: Determine a first preset period before the state mutation point according to the actual condition of the engine.

[0137] Step S8072: Determine a second quantity based on the sampling rate and the first preset time period.

[0138] Step S8073: Taking the state mutation point as a starting point, a second number of test data before the state mutation point is selected from the second data set as an initial optimal steady-state performance point.

[0139] In one example, based on the actual situation, the data about 3 seconds before the mutation point is taken as the optimal steady-state performance point. If the sampling rate of the data acquisition system is 5Hz, then r = 3*5 = 15. Select the i-15th test data D i-15 is the optimal steady-state performance point.

[0140] In this method, due to the influence of the engine state and the accuracy of the test equipment, the data near the state mutation point from the steady state to the transition state of the engine is often unstable. Therefore, by selecting the data of the first preset time period before the state mutation point as the initial optimal steady-state performance point, the stability of the selection of the initial optimal steady-state performance point is improved, and the data accuracy of the optimal steady-state performance point is ensured.

[0141] Step S808 , taking the initial optimal steady-state performance point as the starting point, selecting a first number of test data before the initial optimal steady-state performance point in the second data set as a third data set, averaging the third data set to obtain an average steady-state performance point.

[0142] Specifically, the first number is determined by: determining a second preset period before the initial optimal steady-state performance point according to the actual condition of the engine; and determining the first number based on the sampling rate and the second preset period.

[0143] In one example, to avoid excessive random errors caused by a single data point, the data 5 seconds before the best performance point is averaged, that is, the average value Daver of the parameters in the test data number range [i-15-25, i-15] is calculated.

[0144] In this method, in order to avoid excessive random errors that may be caused by a single data point, the data within the experimental data sequence number range before the initial optimal steady-state performance point are averaged, which further improves the accuracy and reliability of the steady-state performance point data.

[0145] Step S809: convert the average steady-state performance point according to the standard environmental conditions to obtain the steady-state performance point data under the standard environmental conditions. Figure 7 Step S709 of the illustrated embodiment will not be described in detail here.

[0146] The method for extracting steady-state performance points for a turboshaft engine provided in this embodiment utilizes data from the transition point between steady and transition states, often unstable due to the influence of engine conditions and test equipment accuracy. Therefore, by selecting data from approximately the first preset period before the transition point as the initial optimal steady-state performance point, the stability of the initial optimal steady-state performance point selection is improved, ensuring the accuracy of the optimal steady-state performance point data. To avoid excessive random errors caused by a single data point, data within the experimental data sequence number range before the initial optimal steady-state performance point is averaged, further improving the accuracy and reliability of the steady-state performance point data.

[0147] This embodiment also provides a device for extracting the steady-state performance point of a turboshaft engine. This device is used to implement the above-mentioned embodiments and preferred embodiments, and details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that implements a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, implementation using hardware, or a combination of software and hardware, is also possible and contemplated.

[0148] This embodiment provides a device for extracting steady-state performance points of a turboshaft engine. Figure 9 Shown, including:

[0149] The data acquisition module 901 is used to determine the test channel parameters of the engine's steady-state test channel and collect test data corresponding to each test channel parameter. Figure 1 Step S101 of the illustrated embodiment will not be described in detail here.

[0150] The absolute value calculation module 902 is used to calculate the absolute value of the data change of each test channel parameter corresponding to each test data. Figure 1 Step S102 of the illustrated embodiment will not be described in detail here.

[0151] The data filtering module 903 is used to filter the absolute value of the data change based on the preset data change threshold to obtain the filtered absolute value of the data change. Figure 1Step S103 of the illustrated embodiment will not be described in detail here.

[0152] The sliding processing module 904 is used to process the absolute value of the filtered data change using the maximum sliding window based on the sampling rate of the engine data acquisition system to obtain the first data set corresponding to each test channel parameter. Figure 1 Step S104 of the illustrated embodiment will not be described in detail here.

[0153] The data union module 905 is used to union the first data sets to obtain the second data set. Figure 1 Step S105 of the illustrated embodiment will not be described in detail here.

[0154] The state mutation point determination module 906 is used to screen the second data set and determine the state mutation point, which is the state mutation point where the engine changes from a steady state to a transition state. Figure 1 Step S106 of the illustrated embodiment will not be described in detail here.

[0155] The steady-state performance point determination module 907 is used to determine the initial optimal steady-state performance point based on the sampling rate and the state mutation point. Figure 1 Step S107 of the illustrated embodiment will not be described in detail here.

[0156] The data averaging module 908 is used to take the initial optimal steady-state performance point as the starting point, select the first number of test data before the initial optimal steady-state performance point in the second data set as the third data set, and average the third data set to obtain the average steady-state performance point. Figure 1 Step S108 of the illustrated embodiment will not be described in detail here.

[0157] The data conversion module 909 is used to convert the average steady-state performance point according to the standard environmental conditions to obtain the steady-state performance point data under the standard environmental conditions. Figure 1 Step S109 of the illustrated embodiment will not be described in detail here.

[0158] In some optional implementations, the data filtering module 903 includes:

[0159] The change threshold judgment unit is used to judge whether the absolute value of the current data change is less than a preset data change threshold.

[0160] The change amount setting unit is used to set the current data change amount to 0 when the absolute value of the current data change amount is less than a preset data change amount threshold.

[0161] The absolute value traversal unit is used to maintain the current data change when the absolute value of the current data change is not less than the preset data change threshold, until all the absolute values ​​of the data change are traversed to obtain the filtered absolute value of the data change.

[0162] In some optional implementations, the length of the maximum value sliding window is determined based on a stabilization time for the engine to maintain stable operation and a sampling rate of a data acquisition system of the engine.

[0163] In some optional implementations, the state mutation point determination module 906 includes:

[0164] The second data judging unit is used to judge whether the second data at the current moment is equal to 0, and whether the second data at the next moment is greater than 0.

[0165] The state mutation point determining unit is configured to determine that the second data at the current moment is a state mutation point when the second data at the current moment is equal to 0 and the second data at the next moment is greater than 0.

[0166] The non-state mutation point determining unit is configured to determine that the second data at the current moment is not a state mutation point when the second data at the current moment is not equal to 0 or the second data at the next moment is not greater than 0.

[0167] In some optional implementations, the steady-state performance point determination module 907 includes:

[0168] The first preset period determination unit is used to determine a first preset period before a state mutation point according to an actual condition of the engine.

[0169] The second quantity determining unit is configured to determine the second quantity based on the sampling rate and the first preset time period.

[0170] The initial optimal steady-state performance point determining unit is configured to take the state mutation point as a starting point and select a second number of test data before the state mutation point in the second data set as the initial optimal steady-state performance point.

[0171] In some optional implementations, the data averaging module 908 includes:

[0172] The second preset period determination unit is used to determine a second preset period before the initial optimal steady-state performance point according to the actual condition of the engine.

[0173] The first quantity determining unit is configured to determine a first quantity based on a sampling rate and a second preset time period.

[0174] The further functional description of each of the above modules and units is the same as that of the above corresponding embodiments and will not be repeated here.

[0175] The turboshaft engine steady-state performance point extraction device in this embodiment is presented in the form of a functional unit, where the unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that executes one or more software or fixed programs, and / or other devices that can provide the above functions.

[0176] The embodiment of the present invention also provides a computer device having the above Figure 9 The device for extracting steady-state performance points of a turboshaft engine is shown.

[0177] See also Figure 10 , Figure 10 is a structural diagram of a computer device provided by an optional embodiment of the present invention, such as Figure 10 As shown, the computer device includes: one or more processors 10, memory 20, and interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. Various components utilize different buses to communicate with each other and can be installed on a common mainboard or installed in other ways as needed. The processor can process the instructions executed in the computer device, including instructions stored in the memory or on the memory to display the graphical information of the GUI on an external input / output device (such as, a display device coupled to the interface). In some optional embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories. Equally, multiple computer devices can be connected, and each device provides part of the necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system). Figure 10 A processor 10 is taken as an example.

[0178] The processor 10 may be a central processing unit, a network processor, or a combination thereof. The processor 10 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit, a programmable logic device, or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general purpose array logic, or any combination thereof.

[0179] The memory 20 stores instructions that can be executed by at least one processor 10, so that the at least one processor 10 executes the method shown in the above embodiment.

[0180] The memory 20 may include a program storage area and a data storage area, wherein the program storage area may store an operating system and application programs required for at least one function; the data storage area may store data created based on the use of the computer device, etc. In addition, the memory 20 may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some optional embodiments, the memory 20 may optionally include a memory remotely located relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0181] The memory 20 may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a flash memory, a hard disk or a solid-state drive; the memory 20 may also include a combination of the above types of memory.

[0182] The computer device also includes an input device 30 and an output device 40. The processor 10, the memory 20, the input device 30 and the output device 40 can be connected via a bus or other means. Figure 10 The bus connection is taken as an example.

[0183] The input device 30 can receive input digital or character information and generate key signal input related to user settings and function control of the computer device, such as a touch screen, a keypad, a mouse, a trackpad, a touch pad, an indicator stick, one or more mouse buttons, a trackball, a joystick, etc. The output device 40 can include a display device, an auxiliary lighting device (e.g., an LED), and a tactile feedback device (e.g., a vibration motor). The above-mentioned display device includes but is not limited to a liquid crystal display, a light emitting diode, a display, and a plasma display. In some optional embodiments, the display device can be a touch screen.

[0184] The embodiment of the present invention also provides a computer-readable storage medium. The above-mentioned method according to the embodiment of the present invention can be implemented in hardware, firmware, or implemented as a computer code that can be recorded in a storage medium, or implemented as a computer code that is originally stored in a remote storage medium or a non-temporary machine-readable storage medium and downloaded through a network and will be stored in a local storage medium, so that the method described herein can be stored in such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only storage memory, a random access memory, a flash memory, a hard disk or a solid-state drive, etc.; further, the storage medium can also include a combination of the above-mentioned types of memory. It can be understood that a computer, a processor, a microprocessor controller or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by a computer, a processor or hardware, the method shown in the above embodiment is implemented.

[0185] A portion of the present invention may be applied as a computer program product, such as a computer program instruction, which, when executed by a computer, can call or provide the method and / or technical solution according to the present invention through the operation of the computer. Those skilled in the art should understand that the form in which the computer program instruction exists in a computer-readable medium includes, but is not limited to, a source file, an executable file, an installation package file, etc. Accordingly, the way in which the computer program instruction is executed by the computer includes, but is not limited to: the computer directly executes the instruction, or the computer compiles the instruction and then executes the corresponding compiled program, or the computer reads and executes the instruction, or the computer reads and installs the instruction and then executes the corresponding installed program. Here, the computer-readable medium may be any available computer-readable storage medium or communication medium that can be accessed by the computer.

[0186] Although the embodiments of the present invention have been described with reference to the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present invention. Such modifications and variations are all within the scope defined by the appended claims.

Claims

1. A method for extracting steady-state performance points of a turboshaft engine, characterized in that: The method comprises: Determining test channel parameters of a steady-state test channel of the engine, and collecting test data corresponding to each of the test channel parameters; Calculating the absolute value of the data change of each test channel parameter corresponding to each test data; Based on a preset data change threshold, filtering the absolute value of the data change to obtain a filtered absolute value of the data change; Based on the sampling rate of the data acquisition system of the engine, the absolute value of the filtered data change is processed using a maximum sliding window to obtain a first data set corresponding to each test channel parameter; Calculating a union of the first data sets to obtain a second data set; Screening the second data set to determine a state mutation point, where the state mutation point is a state mutation point at which the engine changes from a steady state to a transition state; Determining an initial optimal steady-state performance point based on the sampling rate and the state mutation point; Taking the initial optimal steady-state performance point as a starting point, selecting a first number of test data before the initial optimal steady-state performance point in the second data set as a third data set, and averaging the third data set to obtain an average steady-state performance point; The average steady-state performance point is converted according to standard environmental conditions to obtain steady-state performance point data under standard environmental conditions.

2. The method according to claim 1, characterized in that The filtering of the absolute value of the data change based on a preset data change threshold to obtain the filtered absolute value of the data change includes: Determine whether the absolute value of the current data change is less than the preset data change threshold; When the absolute value of the current data change is less than the preset data change threshold, the current data change is set to 0; When the absolute value of the current data change is not less than the preset data change threshold, the current data change is maintained until all the absolute values ​​of the data change are traversed to obtain the filtered absolute value of the data change.

3. The method according to claim 1, characterized in that The length of the maximum value sliding window is determined based on a stabilization time for the engine to maintain stable operation and a sampling rate of a data acquisition system of the engine.

4. The method according to claim 1, wherein The screening of the second data set based on the preset conditions to determine the state mutation point includes: Determine whether the second data at the current moment is equal to 0, and whether the second data at the next moment is greater than 0; When the second data at the current moment is equal to 0 and the second data at the next moment is greater than 0, determining the second data at the current moment as the state mutation point; When the second data at the current moment is not equal to 0, or the second data at the next moment is not greater than 0, it is determined that the second data at the current moment is not the state mutation point.

5. The method according to claim 1, wherein The determining of the initial optimal steady-state performance point based on the sampling rate and the state mutation point includes: Determining a first preset time period before the state mutation point according to the actual condition of the engine; determining a second number based on the sampling rate and the first predetermined period; Taking the state mutation point as a starting point, a second number of test data before the state mutation point is selected from the second data set as the initial optimal steady-state performance point.

6. The method according to claim 1, characterized in that The first quantity is determined as follows: determining a second preset period before the initial optimal steady-state performance point based on an actual condition of the engine; The first number is determined based on the sampling rate and the second preset time period.

7. A device for extracting steady-state performance points of a turboshaft engine, characterized in that: The device comprises: A data acquisition module, configured to determine test channel parameters of a steady-state test channel of the engine and to acquire test data corresponding to each of the test channel parameters; a change absolute value calculation module, configured to calculate the absolute value of the data change of each test channel parameter corresponding to each test data; A data filtering module is used to filter the absolute value of the data change based on a preset data change threshold to obtain a filtered absolute value of the data change; a sliding processing module, configured to process the absolute value of the filtered data variation using a maximum sliding window based on a sampling rate of the engine data acquisition system to obtain a first data set corresponding to each of the test channel parameters; a data union module, configured to union the first data sets to obtain a second data set; a state mutation point determination module, configured to screen the second data set and determine a state mutation point, wherein the state mutation point is a state mutation point at which the engine changes from a steady state to a transition state; a steady-state performance point determination module, configured to determine an initial optimal steady-state performance point based on the sampling rate and the state mutation point; a data averaging module, configured to use the initial optimal steady-state performance point as a starting point, select a first number of test data before the initial optimal steady-state performance point from the second data set as a third data set, and average the third data set to obtain an average steady-state performance point; The data conversion module is used to convert the average steady-state performance point according to the standard environmental conditions to obtain the steady-state performance point data under the standard environmental conditions.

8. A computer device, characterized in that: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the method for extracting the steady-state performance point of a turboshaft engine according to any one of claims 1 to 6 by executing the computer instructions.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a computer to execute the method for extracting the steady-state performance point of a turboshaft engine according to any one of claims 1 to 6.

10. A computer program product, characterized in that The method comprises computer instructions for causing a computer to execute the method for extracting the steady-state performance point of a turboshaft engine according to any one of claims 1 to 6.

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