A control method, system, storage medium and electronic device for gear accuracy

Abstract

The present invention discloses a method, a system, a storage medium and an electronic device for controlling gear precision. The method includes: measuring the vibration and noise value of a gearbox and performing Fourier transform to obtain a first amplitude spectrum diagram corresponding to the gearbox; finding the amplitude exceeding the gearbox detection standard curve and the abnormal order to which it belongs from the first amplitude spectrum diagram; determining the gear causing the abnormal order and its tooth surface machining error based on the abnormal order; determining the target machining parameter causing the tooth surface machining error based on the tooth surface machining error; numerically optimizing the target machining parameter and using the gear detection standard curve set for the gear for constraint to obtain the machining parameter standard of the gear; wherein, the machining parameter standard is used to limit the machine tool and its related machining parts to machine the gear, so as to obtain a gear meeting the gear precision requirements.

Description

Technical Field

[0001] The present application relates to the technical field of automotive development, and in particular, to a method, system, storage medium, and electronic device for controlling gear precision. Background Art

[0002] An electric vehicle is a motor vehicle with hybrid drive or full electric drive. Since there is no background noise of an engine to cover it, higher requirements are put forward for NVH (Noise, Vibration, Harshness) in terms of vehicle manufacturing quality.

[0003] As is well known, a gear is a key component belonging to a gearbox. The noise generated during gear meshing is the main noise source of the gearbox and even the electric vehicle. Therefore, studying gear meshing noise is of great significance for improving the vehicle quality of electric vehicles.

[0004] The current detection method generally detects the qualification of gears. For example, the vibration noise value of the gearbox is measured by EOL and recorded, the gears that do not meet the requirements in the gearbox are found, and the vibration noise value of the gearbox is re-measured after replacing the gears that do not meet the requirements until the vibration noise value of the gearbox meets the requirements.

[0005] The above detection method indirectly detects the qualification of gears through EOL measurement. A large number of gear samples need to be made in advance, the parameters of the gear samples are recorded and sequentially put into the gearbox for EOL measurement, and then the qualified gears can be determined from them. This is time-consuming and laborious, and the qualification rate of gears under the NVH index cannot be actively controlled. Summary of the Invention

[0006] The present invention provides a method, system, storage medium, and electronic device for controlling gear precision. Starting from the noise value caused by gears, by establishing a relationship among EOL noise detection, surface precision detection of gears, and control of machining parameters of machine tools, the precision control is improved by modifying the machining parameters of machine tools, so as to solve or partially solve the technical problems of the existing detection method being time-consuming and laborious and unable to actively control the qualification rate of gears under the NVH index, and can actively control the qualification rate of the detected gears under the NVH index.

[0007] To solve the above technical problems, in the first aspect of the present invention, a method for controlling gear precision is disclosed, and the method includes:

[0008] Measuring the vibration noise value of the gearbox and performing Fourier transform to obtain a first amplitude spectrum diagram corresponding to the gearbox;

[0009] Finding the amplitude exceeding the detection standard curve of the gearbox and the abnormal order to which it belongs from the first amplitude spectrum diagram;

[0010] Based on the abnormal order, determine the gear that causes the abnormal order and its tooth surface machining error;

[0011] Based on the tooth surface machining error, determine the target machining parameters that cause the tooth surface machining error;

[0012] Perform numerical optimization on the target machining parameters and use the gear detection standard curve set for the gear for constraint to obtain the machining parameter standard of the gear; wherein, the machining parameter standard is used to limit the machine tool and its related machining parts to machine the gear, so as to obtain a gear that meets the gear accuracy requirements.

[0013] Preferably, the orders in the first spectrogram include integer orders and non-integer orders;

[0014] The determining the gear that causes the abnormal order and its tooth surface machining error based on the abnormal order includes:

[0015] If the abnormal order is a non-integer order, determine the gear that causes the non-integer order and its tooth surface machining error from the mapping relationship between the order and the machining error.

[0016] Preferably, the determining the target machining parameters that cause the tooth surface machining error based on the tooth surface machining error specifically includes:

[0017] Conduct a split-plot experiment based on the tooth surface machining error to determine several machining parameters that cause the tooth surface machining error;

[0018] Determine the preset number of the target machining parameters with the top ranking in terms of the influence on the machining error from the several machining parameters.

[0019] Preferably, the performing numerical optimization on the target machining parameters and using the gear detection standard curve set for the gear for constraint to obtain the machining parameter standard of the gear specifically includes:

[0020] Adjust the parameter values of the target machining parameters and machine a gear sample according to the adjusted parameter values;

[0021] Perform waviness detection on the gear sample to obtain a waviness detection result; wherein, the gear detection standard curve is a waviness standard curve;

[0022] Use the waviness standard curve to constrain the waviness detection result, and inversely adjust the parameter values of the target machining parameters according to the first constraint result until the waviness detection result is within the waviness standard curve, so as to obtain the machining parameter standard.

[0023] Preferably, the performing waviness detection on the gear sample to obtain a waviness detection result specifically includes:

[0024] Detect the waviness of the gear sample to obtain waviness-related parameters;

[0025] Calculate the waviness detection result by using the waviness-related parameters; the waviness detection result includes one or more of: arithmetic mean deviation of profile, root mean square deviation of profile, skewness of profile, and kurtosis of profile.

[0026] Preferably, after adjusting the parameter value of the target machining parameter and machining a gear sample according to the adjusted parameter value, the method further includes:

[0027] Install the gear sample into the gearbox, measure the vibration and noise value of the gearbox by using the production line offline test EOL system and perform Fourier transform to obtain a second frequency spectrum diagram of the gear sample; wherein, the second frequency spectrum diagram includes the amplitude and order of the gear sample; wherein, the gear detection standard curve is an amplitude limit curve;

[0028] Use the amplitude limit curve to constrain the amplitude of the gear sample, and inversely adjust the parameter value of the target machining parameter according to the second constraint result until the amplitude of the gear sample is within the gear detection standard curve, so as to obtain the machining parameter standard.

[0029] Preferably, the tooth surface machining error includes one or more of: surface waviness, pitch error, and tooth surface damage.

[0030] In a second aspect of the present invention, a control system for gear accuracy is disclosed, and the system includes:

[0031] A first measurement module, configured to measure the vibration and noise value of the gearbox and perform Fourier transform to obtain a first frequency spectrum diagram corresponding to the gearbox;

[0032] A search module, configured to search for the amplitude exceeding the gearbox detection standard curve and the abnormal order to which it belongs from the first frequency spectrum diagram;

[0033] A first determination module, configured to determine the gear causing the abnormal order and its tooth surface machining error based on the abnormal order;

[0034] A second determination module, configured to determine the target machining parameter causing the tooth surface machining error based on the tooth surface machining error;

[0035] An optimization module, configured to numerically optimize the target machining parameter and perform constraint by using a gear detection standard curve set for the gear to obtain a machining parameter standard for the gear; wherein, the machining parameter standard is used to limit the machine tool and its related machining parts to machine the gear, so as to obtain a gear meeting the gear accuracy requirements.

[0036] Preferably, the orders in the first frequency spectrum diagram include integer orders and non-integer orders;

[0037] The first determination module is specifically configured to, if the abnormal order is a non-integer order, determine the gear causing the non-integer order and its tooth surface machining error from the mapping relationship between the order and the machining error.

[0038] Preferably, the second determination module is specifically configured to perform a split-plot experiment based on the tooth surface machining error to determine a plurality of machining parameters causing the tooth surface machining error; and determine a preset number of the target machining parameters with the top ranking in terms of the influence of the machining error from the plurality of machining parameters.

[0039] Preferably, the optimization module specifically includes:

[0040] An adjustment module, configured to adjust the parameter values of the target machining parameters and machine a gear sample according to the adjusted parameter values;

[0041] A detection module, configured to perform waviness detection on the gear sample to obtain a waviness detection result; wherein, the gear detection standard curve is a waviness standard curve;

[0042] A first constraint module, configured to use the waviness standard curve to constrain the waviness detection result, and inversely adjust the parameter values of the target machining parameters according to the first constraint result until the waviness detection result is within the waviness standard curve, so as to obtain the machining parameter standard.

[0043] Preferably, the detection module is specifically configured to:

[0044] Detect the waviness of the gear sample to obtain waviness-related parameters;

[0045] Calculate the waviness detection result by using the waviness-related parameters; the waviness detection result includes one or more of: arithmetic mean deviation of profile, root mean square deviation of profile, skewness of profile, and kurtosis of profile.

[0046] Preferably, the system further includes:

[0047] A measurement module, configured to install the gear sample into a gearbox, measure the vibration and noise value of the gearbox by using an end-of-line (EOL) system for offline testing of the production line and perform Fourier transform to obtain a second frequency spectrum diagram of the gear sample; wherein, the second frequency spectrum diagram includes the amplitude and order of the gear sample; wherein, the gear detection standard curve is an amplitude limit curve;

[0048] A second constraint module, configured to constrain the amplitude of the gear sample by using the amplitude limit curve, and inversely adjust the parameter value of the target machining parameter according to the second constraint result until the amplitude of the gear sample is within the gear detection standard curve, so as to obtain the machining parameter standard.

[0049] In a third aspect of the present invention, a computer-readable storage medium is disclosed, on which a computer program is stored, and when the program is executed by a processor, the steps of the above method are implemented.

[0050] In a fourth aspect of the present invention, an electronic device is disclosed, including a memory, a processor, and a computer program stored on the memory and executable on the processor, and when the processor executes the program, the steps of the above method are implemented.

[0051] Through one or more technical solutions of the present invention, the present invention has the following beneficial effects or advantages:

[0052] The present invention discloses a method, a system, a storage medium, and an electronic device for controlling the gear accuracy. In order to actively control the qualified rate of gears under NVH indicators, this solution first measures the vibration and noise value of the gearbox and performs Fourier transform to obtain the first amplitude spectrum diagram corresponding to the gearbox; and finds the amplitude and the abnormal order to which it belongs that exceed the gearbox detection standard curve from the first amplitude spectrum diagram. Since the orders of different gears are different, the gear causing the abnormal order and its tooth surface machining error can be determined based on the abnormal order. Further, the target machining parameter causing the tooth surface machining error is found accordingly. By numerically optimizing the target machining parameter and using the gear detection standard curve set for the gear itself for constraint, the machining parameter standard of the gear can be obtained, which is used to limit the machine tool and its related machining parts to machine the gear, so as to obtain a gear that meets the gear accuracy requirements. It can be seen that this solution starts from the noise value caused by the gear, finds out the tooth surface machining error causing the gear noise and the machine tool machining parameter causing the error, and obtains the manufacturing standard of the gear for the target machining parameter accordingly. This solution establishes a relationship between the EOL noise detection, the surface accuracy detection of the gear, and the control of the machining parameters of the machine tool, and improves the accuracy control by modifying the machining parameters of the machine tool, thereby actively controlling the qualified rate of the detected gears under NVH indicators. In addition, this solution directly modifies and constrains the gear itself by using the gear detection standard curve set for the gear, and can manufacture gears that meet the accuracy requirements.

[0053] The above description is only an overview of the technical solution of the present invention. In order to be able to understand the technical means of the present invention more clearly, it can be implemented according to the content of the specification. And in order to make the above and other purposes, features, and advantages of the present invention more obvious and understandable, the following specific embodiments of the present invention are specifically given. Description of the Drawings

[0054] By reading the following detailed description of the preferred embodiments, various other advantages and benefits will become clear to those of ordinary skill in the art. The drawings are only for the purpose of showing the preferred embodiments and are not considered to be a limitation of the present invention. Moreover, throughout the drawings, the same reference numerals are used to represent the same components.

[0055] In the drawings:

[0056] Figure 1 An implementation flowchart of a method for controlling gear accuracy according to an embodiment of the present invention is shown;

[0057] Figure 2 A comparison schematic diagram of a gearbox detection standard curve and a first spectrogram according to an embodiment of the present invention is shown;

[0058] Figure 3 A schematic diagram of the experimental results of the crack region of surface waviness according to an embodiment of the present invention is shown;

[0059] Figure 4 A schematic diagram of the composition of a control system for gear accuracy according to an embodiment of the present invention is shown. Specific Embodiments

[0060] The exemplary embodiments of the present invention will be described in more detail below with reference to the drawings. Although the exemplary embodiments of the present invention are shown in the drawings, it should be understood that the present invention can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided so that the present invention can be more thoroughly understood and the scope of the present invention can be fully conveyed to those skilled in the art.

[0061] Referring to Figure 1 , an implementation flowchart of a method for controlling gear accuracy according to an embodiment of the present invention is disclosed, including the following steps:

[0062] Step 101, measure the vibration and noise value of the gearbox and perform Fourier transform to obtain the first spectrogram corresponding to the gearbox.

[0063] Generally speaking, a gearbox is loaded with several rotating components, such as bearings, gears, etc. Vibration will be generated when rotating components mesh, and other components in the gearbox transmit the vibration, thus generating vibration noise inside the gearbox. The vibration noise values generated by different rotating components are different. For example, three gears at different positions of the same bearing generate different vibration noise values. For another example, different positions of the same gear also generate different vibration noise values. Since the vibration noise value generated inside the gearbox is a continuous time-domain signal, for the convenience of analysis, the vibration noise value of the gearbox can be measured first by using the end-of-line (EOL) test system on the production line, and then Fourier transform is performed on it. Among them, the EOL system is a commonly used noise measurement system for offline detection such as fault diagnosis and function verification of new energy vehicles. The Fourier algorithm is used to transform the time-domain signal curve generated by the gearbox gears to obtain the first frequency spectrum diagram of the frequency-domain signal. According to the transformation principle of the Fourier algorithm, any continuous time series or signal can be expressed as an infinite superposition of sine wave signals with different frequencies. Therefore, the least squares method can be used to decompose the sine waves of each order in turn and calculate the spectrum. The root mean square of the amplitudes of each order is calculated respectively, so as to obtain the first spectrum image. In the first frequency spectrum diagram, the vertical axis represents the amplitude and the horizontal axis represents the order.

[0064] It should be noted that the time-domain signal curves of the gears in the gearbox can be jointly fitted into the same frequency spectrum image. Of course, the time-domain signal curves of the gears in the gearbox can also be fitted into their respective frequency spectrum images, and can be selected according to the actual situation in actual applications.

[0065] Step 102, find the amplitude exceeding the gearbox detection standard curve and the corresponding abnormal order from the first frequency spectrum diagram.

[0066] In this embodiment, the gearbox detection standard curve is obtained by fitting the tooth surface curves of several qualified gears and is used as the standard for detecting abnormal gear noise in the gearbox. The amplitude and order of the first frequency spectrum diagram correspond to each other. Therefore, if the amplitude exceeds the gearbox detection standard curve, it means that the corresponding order is an abnormal order. See Figure 2 , which is a comparison schematic diagram of the gearbox detection standard curve and the first frequency spectrum diagram. Among them, the gearbox detection standard curve is a relatively smooth curve, and the measured amplitude value in the first frequency spectrum diagram will exceed the gearbox detection standard curve. Then, based on the amplitude value exceeding the gearbox detection standard curve, the corresponding abnormal order can be determined.

[0067] As is well known, components in a rotating state will generate vibration noise with a certain amplitude, which varies with the rotational speed. The vibration noise response of a structure usually appears at multiples or fractions of the rotational speed, that is, at the order. In most cases, the response generated by a gearbox is related to a specific order (including the response generated by the resonance frequency), and corresponding responses will appear at specific orders. Each rotating component (such as gears, shafts, pistons, pumps, etc.) contributes to the total level of vibration noise of the gearbox. Orders are used to analyze the respective contributions of each rotating component to the total level. In this embodiment, the time-series signal curves of the gears in the gearbox are converted into representations using amplitude orders, and the meshing order of the gearbox corresponds to the number of teeth meshing between the gears. Therefore, if the number of teeth of the gears is different, the orders they are in are different, and the amplitudes of the vibration noise they generate are also different. For example, the orders and amplitudes corresponding to 3 gears at different positions of the same bearing are all different. Therefore, based on the order and amplitude, the gear that generates vibration noise can be accurately determined from the 3 gears, and then vibration reduction and noise reduction analysis can be carried out for the gear that generates vibration noise.

[0068] Furthermore, for the same gear, the value of the vibration noise generated during meshing is at an integer order after Fourier transform. However, due to tooth surface defects of the gear, such as surface waviness, pitch error, tooth surface damage, etc., the vibration noise value may be at a non-integer order after Fourier transform. Since the first spectrum diagram contains both integer orders and non-integer orders, after finding the abnormal order, it will be determined whether the abnormal order exceeding the gearbox detection standard curve belongs to an integer order or a non-integer order. If it is a non-integer order, it indicates that the gear has tooth surface defects.

[0069] Step 103: Based on the abnormal order, determine the gear that causes the abnormal order and its tooth surface machining error.

[0070] In this embodiment, if the abnormal order is a non-integer order, the gear that causes the non-integer order and its tooth surface machining error are determined from the mapping relationship between the order and the machining error.

[0071] Specifically, the tooth surface machining error includes one or more of surface waviness, pitch error, and tooth surface damage. Each tooth surface machining error will comprehensively affect the vibration noise of the gear, and the influence of each tooth surface machining error on the noise of the gear can be reflected in the order. Therefore, in this embodiment, the mapping relationship between the gear order and the machining error can be statistically analyzed in advance. Thus, when the detected gear has an abnormal order, one or more gears that cause the non-integer order and their tooth surface machining errors can be analyzed from it.

[0072] Step 104: Based on the tooth surface machining error, determine the target machining parameter that causes the tooth surface machining error.

[0073] In this embodiment, the factors affecting the non-integer order tooth surface machining error of the gear include one or more of surface waviness, pitch error, and tooth surface damage. When specific tooth surface machining errors are obtained, it is necessary to further analyze the influencing factors causing the tooth surface machining errors. During the specific analysis, a split-plot experiment is carried out based on the tooth surface machining error to determine the influencing factors causing the tooth surface machining error. In this embodiment, the tooth surface machining error generally occurs under the action of machining parameters alone or in combination. Therefore, it is necessary to carry out a split-plot experiment on it to determine several machining parameters causing the tooth surface machining error, and then determine a preset number of the target machining parameters with the top influence rankings from the several machining parameters.

[0074] Among them, when carrying out a split-plot experiment based on the tooth surface machining error, several gears are simulated as the first-level experimental units and divided into several groups, and several machining parameters of the machine tool are used as the second-level experimental units. Several groups of gears under the first-level experimental units are respectively combined with one or more second-level experimental units for machining, so as to machine gears with different tooth surface errors for standardized effect analysis, and determine a preset number of target machining parameters with the top influence rankings of the tooth surface machining error from them.

[0075] For the convenience of illustrating and explaining the present invention, the surface waviness in the tooth surface machining error is taken as an example for illustration below.

[0076] If it is determined that the tooth surface machining error of the gear is surface waviness, then a split-plot experiment is carried out for the surface waviness and a tabular conversion effect analysis is carried out. As Figure 3 shown, it is a schematic diagram of the split-plot experiment results of the surface waviness. Since there are periodic regular corrugations on the tooth surface and it is generally caused by vibration, it can be analyzed from Figure 3 that the surface waviness of the gear is caused by resonance with the process system under the combined action of the changes in the grinding parameters and the grinding wheel diameter. Among them, the second feed rate, the interaction between the grinding wheel diameter and the second feed rate, and the interaction among the second feed rate, the grinding speed, and the grinding wheel diameter all have a significant influence on the waviness. It can be directly seen from Figure 3 that the top three machining parameters affecting the surface waviness are: the second feed rate, the grinding speed, and the grinding wheel diameter. Therefore, the above three machining parameters are used as the target machining parameters. That is to say, since the above three machining parameters have the greatest influence on the surface waviness of the gear, in order to improve the gear accuracy, adjustments can be made starting from the above three machining parameters, so as to actively improve the gear accuracy.

[0077] Step 105, numerically optimize the target machining parameters and use the gear detection standard curve set for the gear for constraint to obtain the machining parameter standard of the gear, so as to limit the machine tool and its related machining parts to machine the gear, and thus obtain a gear that meets the gear accuracy requirements.

[0078] In the process of numerically optimizing the target machining parameters, the parameter values of the target machining parameters are adjusted, and a gear sample is machined according to the adjusted parameter values. In order to verify the accuracy of the gear sample, two methods are used for verification in this embodiment. Of course, the two verification methods in this embodiment are only used as examples and do not limit the protection scope of the present invention. In practical applications, other verification methods other than the two verification methods in this embodiment can be used for verification.

[0079] The first verification method is to directly verify the waviness of the gear sample.

[0080] Specifically, in this embodiment, the waviness of the gear sample is detected to obtain a waviness detection result. The waviness detection result is constrained by the waviness standard curve, and the parameter values of the target machining parameters are inversely adjusted according to the first constraint result until the waviness detection result is within the waviness standard curve, so as to obtain the machining parameter standard.

[0081] During the waviness detection process, the waviness of the gear sample is detected to obtain waviness-related parameters. The waviness-related parameters include, but are not limited to: profile peak valley value, profile maximum height, profile unit average line height, profile total height. The waviness detection result is calculated using the waviness-related parameters; the waviness detection result includes: one or more of profile arithmetic mean deviation, profile root mean square deviation, profile skewness, and profile kurtosis.

[0082] Among them, the gear detection standard curve is the waviness standard curve. Specifically, since the waviness detection result has the aforementioned multiple results, different detection results require different standard curves. Therefore, after the detection result is determined, the corresponding standard curve can be obtained according to the detection result, and then the corresponding constraint can be carried out.

[0083] Further, the parameter values of the target machining parameters are inversely adjusted according to the first constraint result until the waviness detection result is within the waviness standard curve, so as to obtain the machining parameter standard. Taking the profile kurtosis curve as an example, the profile kurtosis is constrained by the standard kurtosis curve. The point values within the standard kurtosis curve are considered qualified, and the point values outside the standard kurtosis curve are considered unqualified. For the unqualified kurtosis point values, the point values in the corresponding standard kurtosis curve are used to constrain them, and the parameter values of the second feed rate, grinding speed, and grinding wheel diameter are adjusted with reference to the point values in the corresponding standard kurtosis curve until the standard kurtosis curve is satisfied.

[0084] The second verification method is to load the gear sample into the gearbox for EOL verification.

[0085] In this embodiment, EOL is still used to verify the gear sample. Specifically, the gear sample is installed in the transmission, and the vibration and noise value of the transmission is measured by EOL and Fourier transformed to obtain the second spectrogram of the gear sample. Among them, the amplitude and order of the gear sample are included in the second spectrogram. The second spectrogram in this embodiment can be that the time-domain signal curves of each gear in the transmission can be jointly fitted into the same spectral image. Of course, it can also be a spectral image fitted by the time-domain signal curve of the gear sample alone. At this time, in order to optimize the surface accuracy of the gear, the gear detection standard curve adopted in this embodiment is a self-developed amplitude limit curve, with the ordinate representing the amplitude limit and the abscissa representing the order.

[0086] The amplitude of the gear sample is constrained by using the amplitude limit curve, and the parameter value of the target processing parameter is adjusted inversely according to the second constraint result until the amplitude of the gear sample is within the gear detection standard curve, and the processing parameter standard is obtained. During the constraint process, the point values within the amplitude limit curve are considered qualified, and the point values outside the amplitude limit curve are considered unqualified. If there are point values outside the amplitude limit curve, the corresponding abnormal order is found accordingly, and the parameter values of the second feed rate, grinding speed, and grinding wheel diameter are adjusted accordingly until the amplitude limit curve is satisfied. This solution directly modifies and constrains the gear itself by using the gear detection standard curve set for the gear, and can manufacture gears that meet the accuracy requirements. In practical applications, the self-developed amplitude limit curve can be loaded into the optimizer, and the optimizer is used to inversely adjust the parameter value of the target processing parameter. For example, the parameter values of the target processing parameter determined by the optimizer are as follows: the grinding wheel diameter is ≥225, the grinding speed = 63, the first feed rate = 450 - 550, and the second feed rate = 175 - 185. When the grinding wheel diameter is <225, the grinding speed = 55, the first feed rate = 450 - 550, and the second feed rate = 195 - 240.

[0087] In this solution, starting from the noise value caused by the gear, the tooth surface processing error that causes the gear noise and the machine tool processing parameters that cause the error are found, and the manufacturing standard of the gear for the target processing parameter is obtained. The difference between this solution and the prior art is that the focus of this solution is not to find the defects of the gear, but how to actively improve the gear precision control. Therefore, by establishing the relationship between EOL noise detection, gear surface accuracy detection, and machine tool processing parameter control, starting from the processing parameters of the gear for adjustment, and improving the precision control by modifying the machine tool processing parameters, the qualified rate of the gear under the NVH index can be actively improved.

[0088] Based on the same inventive concept as in the foregoing embodiment, the embodiment of the present invention also discloses a control system for gear precision. Please refer to the followingFigure 4 , the system of this embodiment includes:

[0089] A first measurement module 401, configured to measure the vibration and noise value of the transmission and perform Fourier transform to obtain a first amplitude spectrum diagram corresponding to the transmission;

[0090] A search module 402, configured to search for the amplitude exceeding the transmission detection standard curve and the abnormal order to which it belongs from the first amplitude spectrum diagram;

[0091] A first determination module 403, configured to determine the gear causing the abnormal order and its tooth surface machining error based on the abnormal order;

[0092] A second determination module 404, configured to determine the target machining parameters causing the tooth surface machining error based on the tooth surface machining error;

[0093] An optimization module 405, configured to numerically optimize the target machining parameters and perform constraint using a gear detection standard curve set for the gear to obtain a machining parameter standard for the gear; wherein, the machining parameter standard is used to limit the machine tool and its related machining parts to machine the gear, so as to obtain a gear meeting the gear precision requirements.

[0094] As an optional embodiment, the orders in the first amplitude spectrum diagram include integer orders and non-integer orders;

[0095] The first determination module 403 is specifically configured to, if the abnormal order is a non-integer order, determine the gear causing the non-integer order and its tooth surface machining error from the mapping relationship between the order and the machining error.

[0096] As an optional embodiment, the second determination module 404 is specifically configured to perform a split-plot experiment based on the tooth surface machining error to determine several machining parameters causing the tooth surface machining error; and determine the target machining parameters of a preset quantity with the top ranking in terms of the influence of the machining error from the several machining parameters.

[0097] As an optional embodiment, the optimization module 405 specifically includes:

[0098] An adjustment module, configured to adjust the parameter value of the target machining parameter and machine a gear sample according to the adjusted parameter value;

[0099] A detection module, configured to perform waviness detection on the gear sample to obtain a waviness detection result; wherein, the gear detection standard curve is a waviness standard curve;

[0100] The first constraint module is used to constrain the waviness detection result by using the waviness standard curve, and inversely adjust the parameter value of the target machining parameter according to the first constraint result until the waviness detection result is within the waviness standard curve, so as to obtain the machining parameter standard.

[0101] As an optional embodiment, the detection module is specifically used for:

[0102] Detect the waviness of the gear sample to obtain waviness-related parameters;

[0103] Calculate the waviness detection result by using the waviness-related parameters; the waviness detection result includes one or more of the arithmetic mean deviation of the profile, the root mean square deviation of the profile, the skewness of the profile, and the kurtosis of the profile.

[0104] As an optional embodiment, the system further includes:

[0105] The measurement module is used to load the gear sample into the gearbox, measure the vibration and noise value of the gearbox by using the end-of-line (EOL) system of the production line and perform Fourier transform to obtain the second frequency spectrum diagram of the gear sample; wherein, the second frequency spectrum diagram contains the amplitude and order of the gear sample; wherein, the gear detection standard curve is the amplitude limit curve;

[0106] The second constraint module is used to constrain the amplitude of the gear sample by using the amplitude limit curve, and inversely adjust the parameter value of the target machining parameter according to the second constraint result until the amplitude of the gear sample is within the gear detection standard curve, so as to obtain the machining parameter standard.

[0107] The above is an introduction to the control logic of the control system for gear accuracy. In practical applications, the control system for gear accuracy in this embodiment includes: an EOL system, a computer processing device, and a machine tool parameter control system. Among them, the EOL system is used for noise monitoring, and the computer processing device is used to perform Fourier transform and surface accuracy detection (such as tooth surface machining error analysis, gear machining parameter analysis) on the vibration and noise value of the gearbox detected by the EOL system. The machine tool parameter control system is used to change the machining parameters of the gear, and the three cooperate with each other to complete the accuracy control of gear machining.

[0108] Based on the same inventive concept as in the foregoing embodiments, an embodiment of the present invention also discloses a computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, the steps of any of the foregoing methods are implemented.

[0109] Based on the same inventive concept as in the foregoing embodiments, an embodiment of the present invention further discloses an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the program, the steps of any of the foregoing methods are implemented.

[0110] Through one or more embodiments of the present invention, the present invention has the following beneficial effects or advantages:

[0111] The present invention discloses a method, a system, a storage medium, and an electronic device for controlling the gear accuracy. In order to actively control the qualified rate of gears under NVH indicators, this solution first measures the vibration and noise value of the gearbox and performs Fourier transform to obtain the first amplitude spectrum diagram corresponding to the gearbox; and searches for the amplitude exceeding the gearbox detection standard curve and the abnormal order to which it belongs from the first amplitude spectrum diagram. Since the orders of different gears are different, the gear causing the abnormal order and its tooth surface machining error can be determined based on the abnormal order. Further, the target machining parameters causing the tooth surface machining error are found accordingly. By numerically optimizing the target machining parameters and using the gear detection standard curve set for the gear itself for constraint, the machining parameter standard of the gear can be obtained to be used to limit the machine tool and its related machining parts to machine the gear, so as to obtain a gear meeting the gear accuracy requirements. It can be seen that this solution starts from the noise value caused by the gear, finds out the tooth surface machining error causing the gear noise and the machine tool machining parameters causing the error, and obtains the manufacturing standard of the gear for the target machining parameters accordingly. By establishing a relationship among the EOL noise detection, the surface accuracy detection of the gear, and the control of the machining parameters of the machine tool, and improving the accuracy control by modifying the machining parameters of the machine tool, the qualified rate of the detected gears under NVH indicators is actively controlled. In addition, this solution directly modifies and constrains the gear itself by using the gear detection standard curve set for the gear, and can manufacture gears meeting the accuracy requirements.

[0112] The algorithms and displays provided herein are not inherently related to any particular computer, virtual system, or other device. Various general-purpose systems can also be used in conjunction with the teachings based herein. The structure required to construct such systems will be apparent from the above description. In addition, the present invention is not directed to any particular programming language. It should be understood that the content of the present invention described herein can be implemented using various programming languages, and the description of a particular language above is for the purpose of disclosing the best mode of the present invention.

[0113] In the specification provided herein, a large number of specific details are set forth. However, it can be understood that the embodiments of the present invention can be practiced without these specific details. In some instances, well-known methods, structures, and technologies have not been shown in detail so as not to obscure the understanding of this specification.

[0114] Similarly, it should be understood that, in order to streamline the present invention and assist in understanding one or more of the various inventive aspects, in the foregoing description of the exemplary embodiments of the present invention, the various features of the present invention are sometimes grouped together into a single embodiment, figure, or description thereof. However, the disclosed method should not be construed as reflecting an intention that the claimed invention requires more features than are expressly recited in each claim. Rather, as reflected in the following claims, the inventive aspects lie in less than all of the features of the single embodiments disclosed previously. Thus, the claims following the detailed description are hereby expressly incorporated into the detailed description, with each claim standing on its own as a separate embodiment of the present invention.

[0115] Those skilled in the art can understand that the modules in the devices in the embodiments can be adaptively changed and arranged in one or more devices different from the embodiments. The modules or units or components in the embodiments can be combined into one module or unit or component, and in addition, they can be divided into multiple sub-modules or sub-units or sub-components. Except that at least some of such features and / or processes or units are mutually exclusive, any combination can be used to combine all the features disclosed in this specification (including the accompanying claims, abstract, and drawings) and all the processes or units of any method or device so disclosed. Unless otherwise expressly stated, each feature disclosed in this specification (including the accompanying claims, abstract, and drawings) can be replaced by an alternative feature that provides the same, equivalent, or similar purpose.

[0116] In addition, those skilled in the art can understand that, although some of the embodiments herein include certain features included in other embodiments but not others, the combination of the features of different embodiments means that it is within the scope of the present invention and forms different embodiments. For example, in the following claims, any one of the claimed embodiments can be used in any combination.

[0117] Each component embodiment of the present invention can be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. Those skilled in the art should understand that a microprocessor or a digital signal processor (DSP) can be used in practice to implement some or all of the functions of some or all of the components in the gateway, proxy server, and system according to the embodiments of the present invention. The present invention can also be implemented as a device or apparatus program (e.g., a computer program and a computer program product) for performing part or all of the methods described herein. Such a program for implementing the present invention can be stored on a computer-readable medium, or can be in the form of one or more signals. Such signals can be downloaded from an Internet website, or provided on a carrier signal, or provided in any other form.

[0118] It should be noted that the above embodiments illustrate the present invention rather than limit the present invention, and those skilled in the art can design alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in the claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The present invention can be implemented by means of hardware including several different elements and by means of a suitably programmed computer. In the unit claims listing several devices, several of these devices can be embodied by the same item of hardware. The use of the words first, second, and third, etc. does not denote any order. These words can be interpreted as names.

Claims

1. A method for controlling gear precision, characterized in that The method includes: Measuring the vibration and noise value of the gearbox and performing Fourier transform to obtain the first spectrum diagram corresponding to the gearbox; Searching in the first spectrum diagram for the amplitudes exceeding the gearbox detection standard curve and their abnormal orders; Based on the abnormal order, determining the gear causing the abnormal order and its tooth surface machining error; Based on the tooth surface machining error, determining the target machining parameters causing the tooth surface machining error; Performing numerical optimization on the target machining parameters and using the gear detection standard curve set for the gear for constraint to obtain the machining parameter standard for the gear, specifically including: adjusting the parameter values of the target machining parameters, and machining a gear sample according to the adjusted parameter values; performing waviness detection on the gear sample to obtain a waviness detection result; wherein, the gear detection standard curve is a waviness standard curve; using the waviness standard curve to constrain the waviness detection result, and inversely adjusting the parameter values of the target machining parameters according to the first constraint result until the waviness detection result is within the waviness standard curve, thereby obtaining the machining parameter standard; wherein, the machining parameter standard is used to limit the machine tool and its related machining parts to machine the gear, so as to obtain a gear meeting the gear precision requirements.

2. The method according to claim 1, wherein The orders in the first spectrum diagram include integer orders and non-integer orders; The determining, based on the abnormal order, of the gear causing the abnormal order and its tooth surface machining error includes: If the abnormal order is a non-integer order, determining from the order-machining error mapping relationship the gear causing the non-integer order and its tooth surface machining error.

3. The method according to claim 1, characterized in that, The determining, based on the tooth surface machining error, of the target machining parameters causing the tooth surface machining error specifically includes: Performing a split-plot experiment based on the tooth surface machining error to determine several machining parameters causing the tooth surface machining error; Determining from the several machining parameters the preset number of the target machining parameters with the top ranking in terms of the influence on the machining error.

4. The method according to claim 1, wherein The performing of the waviness detection on the gear sample to obtain a waviness detection result specifically includes: Detecting the waviness of the gear sample to obtain waviness-related parameters; Calculating the waviness detection result by using the waviness-related parameters; the waviness detection result includes one or more of the arithmetic mean deviation of the profile, root mean square deviation of the profile, skewness of the profile, and kurtosis of the profile.

5. The method according to claim 1, characterized in that, After adjusting the parameter values of the target machining parameters and machining a gear sample according to the adjusted parameter values, the method further includes: Installing the gear sample into the gearbox, measuring the vibration and noise value of the gearbox by using the EOL system for off-line testing of the production line and performing Fourier transform to obtain the second spectrum diagram of the gear sample; wherein, the second spectrum diagram contains the amplitude and order of the gear sample; wherein, the gear detection standard curve is an amplitude limit curve. Use the amplitude limit curve to constrain the amplitude of the gear sample, and inversely adjust the parameter value of the target machining parameter according to the second constraint result until the amplitude of the gear sample is within the gear detection standard curve, so as to obtain the machining parameter standard.

6. The method according to any one of claims 1-5, characterized in that, The tooth surface machining error includes one or more of surface waviness, pitch error, and tooth surface damage.

7. A control system for gear accuracy, characterized in that, The system includes: A first measurement module, configured to measure the vibration noise value of the gearbox and perform Fourier transform to obtain a first amplitude spectrum diagram corresponding to the gearbox; A search module, configured to search for the amplitude and the abnormal order to which it belongs that exceed the gearbox detection standard curve from the first amplitude spectrum diagram; A first determination module, configured to determine the gear causing the abnormal order and its tooth surface machining error based on the abnormal order; A second determination module, configured to determine the target machining parameter causing the tooth surface machining error based on the tooth surface machining error; An optimization module, configured to numerically optimize the target machining parameter and use the gear detection standard curve set for the gear for constraint to obtain the machining parameter standard of the gear; wherein, the optimization module specifically includes: an adjustment module, configured to adjust the parameter value of the target machining parameter and machine a gear sample according to the adjusted parameter value; a detection module, configured to perform waviness detection on the gear sample to obtain a waviness detection result; wherein, the gear detection standard curve is a waviness standard curve; a first constraint module, configured to use the waviness standard curve to constrain the waviness detection result, and inversely adjust the parameter value of the target machining parameter according to the first constraint result until the waviness detection result is within the waviness standard curve, so as to obtain the machining parameter standard; the machining parameter standard is used to limit the machine tool and its related machining parts to machine the gear, so as to obtain a gear that meets the gear precision requirements.

8. The control system according to claim 7, characterized in that, The orders in the first amplitude spectrum diagram include integer orders and non-integer orders; The first determination module is specifically configured to, if the abnormal order is a non-integer order, determine the gear causing the non-integer order and its tooth surface machining error from the mapping relationship between the order and the machining error.

9. The control system according to claim 7, characterized in that, The second determination module is specifically configured to perform a split-plot experiment based on the tooth surface machining error to determine several machining parameters causing the tooth surface machining error; and determine the target machining parameters of a preset number with the top ranking in terms of the influence of the machining error from the several machining parameters.

10. The control system according to claim 7, characterized in that, The detection module is specifically configured to: Detect the waviness of the gear sample to obtain waviness-related parameters; Calculate the waviness detection result by using the waviness-related parameters; the waviness detection result includes one or more of the arithmetic mean deviation of the profile, the root mean square deviation of the profile, the skewness of the profile, and the kurtosis of the profile.

11. The control system according to claim 7, wherein The system further includes: A measurement module, configured to load the gear sample into the gearbox, measure the vibration and noise value of the gearbox by using an end-of-line (EOL) test system of the production line and perform Fourier transform to obtain a second frequency spectrum diagram of the gear sample; wherein, the second frequency spectrum diagram includes the amplitude and order of the gear sample; and wherein, the gear detection standard curve is an amplitude limit curve. A second constraint module, configured to constrain the amplitude of the gear sample by using the amplitude limit curve, and inversely adjust the parameter value of the target machining parameter according to the second constraint result until the amplitude of the gear sample is within the gear detection standard curve, so as to obtain the machining parameter standard.

12. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by a processor, the steps of the method according to any one of claims 1-6 are implemented.

13. An electronic device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, When the processor executes the program, the steps of the method according to any one of claims 1-6 are implemented.

Images