Complete machine noise data prediction method and system applied to engineering machinery

Abstract

The invention relates to the technical field of engineering machinery data processing, in particular to a complete machine noise data prediction method and system applied to engineering machinery. The method comprises the following steps: acquiring a noise source sound power level set corresponding to the prototype in a preset noise database; calculating an external initial sound power level of the variant machine according to the noise source sound power level set; obtaining a predicted sound power level correction value corresponding to the prototype in the noise database; and correcting the external initial sound power level according to the predicted sound power level correction value to obtain an external predicted sound power level corresponding to the variant machine. According to the method, scattered parts do not need to be tested one by one to obtain the noise data of the parts, so that the time consumed by noise prediction is shortened, and the overall noise prediction efficiency of the engineering machinery is improved. And the sound absorption and insulation effects of the covering part and the structural part in a complete machine system can be reflected, so that the accuracy of noise data prediction is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of construction machinery data processing, and in particular to a method and system for predicting the overall machine noise data applied to construction machinery. Background Art

[0002] After the test prototype of construction machinery such as loaders is put into the field, it is necessary to test the noise data of the overall machine (such as the sound power level of the external radiation noise, the sound pressure level of the noise beside the driver's ear in the cab, etc.) by means of testing according to the standard of GB / T 25614-2010. If the noise test result meets the standard, no rectification is required; if the noise test result does not meet the standard, a large amount of noise reduction improvement work usually needs to be carried out. In order to reduce the impact of the later noise reduction work on the overall machine R & D progress, the noise data of the overall machine to be developed is usually predicted at the overall machine design stage. At present, for the noise data prediction method of construction machinery, there are both experimental methods, simulation methods, and methods combining the two. The key lies in the construction of the noise database of the pre-components. After the noise data of the components is known, the noise data of the overall machine can be predicted by theoretical calculation or simulation means.

[0003] However, it is found in practice that the acquisition of the noise data of the components depends on the bench test, and there are many components in the construction machinery, which makes the acquisition workload of the component data large and time-consuming, thus affecting the overall noise prediction efficiency; and it is difficult to fully reflect the sound absorption and insulation effects of the covering parts and structural parts in the overall machine system by calculating or simulating the noise data of the scattered components to directly predict the noise data of the overall machine, which easily leads to obvious errors between the predicted data and the actual data.

[0004] Therefore, how to improve the prediction efficiency and prediction accuracy of the overall machine noise data of construction machinery is a technical problem to be solved urgently at present. Summary of the Invention

[0005] The present invention provides a method and system for predicting the overall machine noise data applied to construction machinery, which can improve the prediction efficiency and prediction accuracy of the overall machine noise data of construction machinery.

[0006] In order to solve the above technical problems, in the first aspect of the present invention, a method for predicting the overall machine noise data applied to construction machinery is disclosed. The construction machinery is a variant machine corresponding to a prototype machine, and the prototype machine has multiple different types of noise sources. The method includes:

[0007] Obtaining the set of sound power levels of the noise sources corresponding to the prototype machine in the preset noise database; the set of sound power levels of the noise sources is the set of the measured sound power levels of all the noise sources of the prototype machine;

[0008] Calculate the initial external sound power level of the variant machine according to the set of sound power levels of the noise sources; the initial external sound power level is the external radiation sound power level of the entire variant machine.

[0009] Obtain the predicted sound power level correction value corresponding to the prototype machine in the noise database.

[0010] Correct the initial external sound power level according to the predicted sound power level correction value to obtain the predicted external sound power level corresponding to the variant machine.

[0011] As an alternative implementation, in the first aspect of the present invention, the variant machine has a plurality of noise sources corresponding one by one to the types of noise sources of the prototype machine, and the variant machine can operate under a plurality of preset working condition conditions respectively.

[0012] The calculating the initial external sound power level of the variant machine according to the set of sound power levels of the noise sources includes:

[0013] For any one of the preset working condition conditions, calculate the sound power levels of all the noise sources of the variant machine according to the set of sound power levels of the noise sources, and perform sound power synthesis according to the sound power levels of all the noise sources of the variant machine to obtain the first sound power level corresponding to the variant machine under this preset working condition condition; the first sound power level is the external radiation sound power level of the entire variant machine under this preset working condition condition.

[0014] Perform multi-condition noise synthesis according to the first sound power levels respectively corresponding to the variant machine under all the preset working condition conditions to obtain the initial external sound power level of the variant machine.

[0015] As an alternative implementation, in the first aspect of the present invention, the noise sources of the prototype machine at least include a fan cooling system.

[0016] Before obtaining the set of sound power levels of the noise sources corresponding to the prototype machine in the preset noise database, the method further includes:

[0017] Test the external radiation sound power level of the entire prototype machine under the preset test working condition conditions to obtain the prototype test sound power level corresponding to the prototype machine.

[0018] Measure the near-field noise data of all the noise sources of the prototype machine including the fan cooling system respectively.

[0019] Calculate the measured sound power level of the fan cooling system according to the prototype test sound power level and the near-field noise data of the fan cooling system.

[0020] Calculate the measured sound power level of other noise sources of the prototype machine except the fan cooling system based on the measured sound power level of the fan cooling system and the near-field noise data of other noise sources of the prototype machine except the fan cooling system;

[0021] Calculate the radiated sound power level outside the whole machine of the prototype machine based on the measured sound power levels of all noise sources of the prototype machine to obtain the prototype calculated sound power level;

[0022] Calculate the difference between the prototype calculated sound power level and the prototype measured sound power level to obtain the predicted sound power level correction value corresponding to the prototype machine;

[0023] Integrate the near-field noise data of all noise sources of the prototype machine, the measured sound power levels of all noise sources of the prototype machine, and the predicted sound power level correction value corresponding to the prototype machine to construct a noise database.

[0024] As an alternative implementation manner, in the first aspect of the present invention, the near-field noise data includes a near-field acoustic transfer function and a near-field sound pressure level;

[0025] The separately measuring the near-field noise data of all noise sources of the prototype machine including the fan cooling system includes:

[0026] Measure the near-field acoustic transfer functions corresponding to all noise sources of the prototype machine including the fan cooling system in a state where the prototype machine is not started;

[0027] Measure the near-field sound pressure levels corresponding to all noise sources of the prototype machine including the fan cooling system in a state where the prototype machine is started and operating under the test condition.

[0028] As an alternative implementation manner, in the first aspect of the present invention, the fan cooling system includes at least one heat dissipation fan point source, and each heat dissipation fan point source has a near-field acoustic transfer function and a near-field sound pressure level corresponding to the heat dissipation fan point source;

[0029] The calculating the measured sound power level of the fan cooling system based on the prototype measured sound power level and the near-field noise data of the fan cooling system includes:

[0030] For any one of the heat dissipation fan point sources, calculate the point source sound power level of the heat dissipation fan point source according to the near-field acoustic transfer function and the near-field sound pressure level corresponding to the heat dissipation fan point source;

[0031] Perform sound power synthesis on the point source sound power levels of all the heat dissipation fan point sources to obtain the theoretical sound power level of the fan cooling system;

[0032] Perform noise cancellation correction on the theoretical sound power level of the fan cooling system according to the prototype-tested sound power level to obtain the measured sound power level of the fan cooling system.

[0033] As an alternative implementation, in the first aspect of the present invention, calculating the measured sound power level of other noise sources of the prototype machine except the fan cooling system according to the measured sound power level of the fan cooling system and the near-field noise data of other noise sources of the prototype machine except the fan cooling system includes:

[0034] Calculate the difference between the measured sound power level of the fan cooling system and the theoretical sound power level of the fan cooling system to obtain the correction value of the noise source sound power level;

[0035] For any noise source of the prototype machine except the fan cooling system, calculate the theoretical sound power level of this noise source according to the near-field sound transfer function and near-field sound pressure level of this noise source, and correct the theoretical sound power level of this noise source according to the correction value of the noise source sound power level to obtain the measured sound power level of this noise source.

[0036] As an alternative implementation, in the first aspect of the present invention, the prototype machine can operate under multiple preset working conditions respectively;

[0037] Calculating the out-of-machine radiation sound power level of the whole prototype machine according to the measured sound power levels of all noise sources of the prototype machine to obtain the prototype calculated sound power level includes:

[0038] For any one of the preset working conditions, perform sound power synthesis according to the measured sound power levels of all noise sources of the prototype machine to obtain the second sound power level corresponding to the prototype machine under this preset working condition; the second sound power level is the out-of-machine radiation sound power level of the whole prototype machine under this preset working condition;

[0039] Perform multi-condition noise synthesis according to the second sound power levels respectively corresponding to the prototype machine under all the preset working conditions to obtain the prototype calculated sound power level.

[0040] As an alternative implementation, in the first aspect of the present invention, the method further includes:

[0041] For any noise source of the prototype machine, measure the far-field sound transfer function between this noise source and the cab of the prototype machine in the state where the prototype machine is not started;

[0042] Obtain the near-field sound pressure levels respectively corresponding to all noise sources of the prototype machine in the noise database;

[0043] Predict the sound pressure level of the noise inside the cab of the variant machine based on the far-field acoustic transfer functions and near-field sound pressure levels respectively corresponding to all the noise sources of the prototype machine, and obtain the predicted in-machine sound pressure level corresponding to the variant machine.

[0044] As an alternative implementation, in the first aspect of the present invention, the predicting the sound pressure level of the noise inside the cab of the variant machine based on the far-field acoustic transfer functions and near-field sound pressure levels respectively corresponding to all the noise sources of the prototype machine, and obtaining the predicted in-machine sound pressure level corresponding to the variant machine includes:

[0045] For any noise source of the prototype machine, calculate the product of the far-field acoustic transfer function and the near-field sound pressure level corresponding to this noise source to obtain the single-noise-source sound pressure level corresponding to this noise source; the single-noise-source sound pressure level is the sound pressure level when the noise generated by this noise source propagates to the cab position of the prototype machine;

[0046] Perform sound pressure level synthesis according to the single-noise-source sound pressure levels respectively corresponding to all the noise sources of the prototype machine to obtain the predicted in-machine sound pressure level corresponding to the variant machine.

[0047] The second aspect of the present invention discloses an overall machine noise data prediction system applied to construction machinery. The construction machinery is a variant machine with a corresponding prototype machine, and the prototype machine has multiple different types of noise sources. The system includes:

[0048] A first data acquisition module, configured to acquire the set of noise source sound power levels corresponding to the prototype machine in a preset noise database; the set of noise source sound power levels is the set of measured sound power levels of all the noise sources of the prototype machine;

[0049] A first data calculation module, configured to calculate the initial out-of-machine sound power level of the variant machine according to the set of noise source sound power levels; the initial out-of-machine sound power level is the out-of-machine radiation sound power level of the whole variant machine;

[0050] A second data acquisition module, configured to acquire the predicted sound power level correction value corresponding to the prototype machine in the noise database;

[0051] A sound power level prediction module, configured to correct the initial out-of-machine sound power level according to the predicted sound power level correction value to obtain the predicted out-of-machine sound power level corresponding to the variant machine.

[0052] As an alternative implementation, in the second aspect of the present invention, the variant machine has multiple noise sources that correspond one-to-one to the types of the noise sources of the prototype machine, and the variant machine can operate under multiple preset working conditions respectively;

[0053] The specific manner in which the first data calculation module calculates the initial off-board sound power level of the variant machine according to the set of sound power levels of the noise sources includes:

[0054] For any one of the preset operating condition, calculate the sound power levels of all the noise sources of the variant machine according to the set of sound power levels of the noise sources, and perform sound power synthesis based on the sound power levels of all the noise sources of the variant machine to obtain the first sound power level corresponding to the variant machine under this preset operating condition; the first sound power level is the off-board radiation sound power level of the entire variant machine under this preset operating condition;

[0055] Perform multi-condition noise synthesis based on the first sound power levels respectively corresponding to the variant machine under all the preset operating conditions to obtain the initial off-board sound power level of the variant machine.

[0056] As an optional implementation manner, in the second aspect of the present invention, the noise sources of the prototype machine at least include a fan cooling system;

[0057] The system further includes:

[0058] A prototype machine noise test module, configured to test the off-board radiation sound power level of the entire prototype machine under preset test operating conditions to obtain the prototype test sound power level corresponding to the prototype machine;

[0059] A noise source data measurement module, configured to respectively measure the near-field noise data of all the noise sources of the prototype machine including the fan cooling system;

[0060] A second data calculation module, configured to calculate the measured sound power level of the fan cooling system according to the prototype test sound power level and the near-field noise data of the fan cooling system;

[0061] A third data calculation module, configured to calculate the measured sound power level of the other noise sources of the prototype machine except the fan cooling system according to the measured sound power level of the fan cooling system and the near-field noise data of the other noise sources of the prototype machine except the fan cooling system;

[0062] A prototype machine noise calculation module, configured to calculate the off-board radiation sound power level of the entire prototype machine according to the measured sound power levels of all the noise sources of the prototype machine to obtain a prototype calculation sound power level;

[0063] A correction value calculation module, configured to calculate the difference between the prototype calculation sound power level and the prototype test sound power level to obtain the predicted sound power level correction value corresponding to the prototype machine;

[0064] A database construction module for integrating the near - field noise data of all noise sources of the prototype machine, the measured sound power levels of all noise sources of the prototype machine, and the predicted sound power level correction values corresponding to the prototype machine to construct a noise database.

[0065] As an alternative implementation, in the second aspect of the present invention, the near - field noise data includes near - field acoustic transfer functions and near - field sound pressure levels;

[0066] The specific method by which the noise source data calculation module calculates the near - field noise data of all noise sources of the prototype machine including the fan cooling system respectively includes:

[0067] Measuring the near - field acoustic transfer functions corresponding to all noise sources of the prototype machine including the fan cooling system respectively in a state where the prototype machine is not started;

[0068] Measuring the near - field sound pressure levels corresponding to all noise sources of the prototype machine including the fan cooling system respectively in a state where the prototype machine is started and operating under the test working condition.

[0069] As an alternative implementation, in the second aspect of the present invention, the fan cooling system includes at least one cooling fan point source, and for each cooling fan point source, there is a corresponding near - field acoustic transfer function and near - field sound pressure level;

[0070] The specific method by which the second data calculation module calculates the measured sound power level of the fan cooling system according to the prototype test sound power level and the near - field noise data of the fan cooling system includes:

[0071] For any one of the cooling fan point sources, calculating the point - source sound power level of the cooling fan point source according to the near - field acoustic transfer function and near - field sound pressure level corresponding to the cooling fan point source;

[0072] Performing sound power synthesis on the point - source sound power levels of all the cooling fan point sources to obtain the theoretical sound power level of the fan cooling system;

[0073] Performing noise elimination correction on the theoretical sound power level of the fan cooling system according to the prototype test sound power level to obtain the measured sound power level of the fan cooling system.

[0074] As an alternative implementation, in the second aspect of the present invention, the specific method by which the third data calculation module calculates the measured sound power levels of other noise sources of the prototype machine except the fan cooling system according to the measured sound power level of the fan cooling system and the near - field noise data of other noise sources of the prototype machine except the fan cooling system includes:

[0075] Calculate the difference between the measured sound power level of the fan cooling system and the theoretical sound power level of the fan cooling system to obtain the correction value of the sound power level of the noise source;

[0076] For any noise source of the prototype machine other than the fan cooling system, calculate the theoretical sound power level of the noise source according to the near-field acoustic transfer function and the near-field sound pressure level of the noise source, and correct the theoretical sound power level of the noise source according to the correction value of the sound power level of the noise source to obtain the measured sound power level of the noise source.

[0077] As an optional implementation manner, in the second aspect of the present invention, the prototype machine can operate under multiple preset working conditions respectively;

[0078] The prototype machine noise calculation module calculates the out-of-machine radiation sound power level of the whole prototype machine according to the measured sound power levels of all noise sources of the prototype machine. The specific method for obtaining the prototype calculation sound power level includes:

[0079] For any one of the preset working conditions, perform sound power synthesis according to the measured sound power levels of all noise sources of the prototype machine to obtain the second sound power level corresponding to the prototype machine under this preset working condition; the second sound power level is the out-of-machine radiation sound power level of the whole prototype machine under this preset working condition;

[0080] Perform multi-condition noise synthesis according to the second sound power levels respectively corresponding to the prototype machine under all the preset working conditions to obtain the prototype calculation sound power level.

[0081] As an optional implementation manner, in the second aspect of the present invention, the system further includes:

[0082] The cab noise measurement and calculation module is used to measure the far-field acoustic transfer function between any noise source of the prototype machine and the cab of the prototype machine when the prototype machine is in the unstarted state;

[0083] The third data acquisition module is used to acquire the near-field sound pressure levels respectively corresponding to all noise sources of the prototype machine in the noise database;

[0084] The sound pressure level prediction module is used to predict the sound pressure level of the noise in the cab of the variant machine according to the far-field acoustic transfer functions and the near-field sound pressure levels respectively corresponding to all noise sources of the prototype machine, and obtain the in-machine predicted sound pressure level corresponding to the variant machine.

[0085] As an alternative implementation, in the second aspect of the present invention, the sound pressure level prediction module predicts the sound pressure level of the noise inside the cab of the variant machine according to the far-field acoustic transfer function and the near-field sound pressure level respectively corresponding to all the noise sources of the prototype machine. The specific method for obtaining the predicted in-machine sound pressure level corresponding to the variant machine includes:

[0086] For any noise source of the prototype machine, calculate the product of the far-field acoustic transfer function and the near-field sound pressure level corresponding to this noise source to obtain the single-noise-source sound pressure level corresponding to this noise source; the single-noise-source sound pressure level is the sound pressure level when the noise generated by this noise source propagates to the cab position of the prototype machine;

[0087] Perform sound pressure level synthesis according to the single-noise-source sound pressure levels respectively corresponding to all the noise sources of the prototype machine to obtain the predicted in-machine sound pressure level corresponding to the variant machine.

[0088] The third aspect of the present invention discloses another whole-machine noise data prediction system applied to construction machinery. The system includes:

[0089] A memory storing executable program code;

[0090] A processor coupled to the memory;

[0091] The processor calls the executable program code stored in the memory and executes the whole-machine noise data prediction method applied to construction machinery disclosed in the first aspect of the present invention.

[0092] The fourth aspect of the present invention discloses a computer storage medium. The computer storage medium stores computer instructions, which are used to execute the whole-machine noise data prediction method applied to construction machinery disclosed in the first aspect of the present invention when called by a processor.

[0093] Compared with the prior art, the present invention has the following beneficial effects:

[0094] Obtain the set of noise source sound power levels corresponding to the prototype machine from the preset noise database, and thus calculate the initial out-of-machine sound power level of the variant machine according to the set of noise source sound power levels; then obtain the predicted sound power level correction value corresponding to the prototype machine in the noise database, and correct the initial out-of-machine sound power level according to the predicted sound power level correction value to obtain the predicted sound power level of the variant machine. There is no need to test each of the scattered components one by one to obtain the noise data of the components, thereby reducing the time consumed for noise prediction and improving the efficiency of the whole-machine noise prediction of construction machinery. In addition, by predicting the noise data of the prototype machine and correcting the noise prediction data of the whole variant machine, the sound absorption and insulation effects of the covering parts and structural parts in the whole machine system can be reflected, thereby improving the accuracy of noise data prediction. Description of the Drawings

[0095] To more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0096] Figure 1 is a schematic flow chart of a method for predicting the overall machine noise data applied to construction machinery disclosed by the present invention;

[0097] Figure 2 is a schematic structural diagram of a system for predicting the overall machine noise data applied to construction machinery disclosed by the present invention;

[0098] Figure 3 is a schematic structural diagram of another system for predicting the overall machine noise data applied to construction machinery disclosed by the present invention;

[0099] Figure 4 is a schematic structural diagram of yet another system for predicting the overall machine noise data applied to construction machinery disclosed by the present invention;

[0100] Figure 5 is a schematic structural diagram of yet another system for predicting the overall machine noise data applied to construction machinery disclosed by the present invention. Detailed implementation manners

[0101] In order to enable those skilled in the art to better understand the solutions of the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0102] The terms "first", "second", etc. in the specification and claims of the present invention and the above drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, device, product, or the like that includes a series of steps or units is not limited to the listed steps or units, but may optionally further include steps or units not listed, or may optionally further include other steps or units inherent to these processes, methods, products, or the like.

[0103] Reference to "embodiment" in this text means that the specific features, structures or characteristics described in connection with the embodiments can be included in at least one embodiment of the present invention. The phrase appears at various positions in the specification and does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0104] After a construction machine such as a loader is put into the field for a prototype, it is necessary to test the noise data of the whole machine (such as the sound power level of the external radiation noise, the sound pressure level of the noise beside the driver's ear in the cab, etc.) by testing means according to the standard of GB / T 25614-2010. If the noise test result meets the standard, no rectification is required; if the noise test result does not meet the standard, a large amount of noise reduction improvement work usually needs to be carried out. In order to reduce the impact of the later noise reduction work on the R & D progress of the whole machine, the noise data of the whole machine to be developed is usually predicted at the whole machine design stage. At present, for the noise data prediction method of construction machinery, there are both experimental methods, simulation methods, and methods combining the two. The key lies in the construction of the noise database of the previous components. After the noise data of the components is known, the noise data of the whole machine can be predicted by theoretical calculation or simulation means.

[0105] However, it is found in practice that the acquisition of component noise data depends on bench testing, and there are many components in construction machinery, which makes the acquisition workload of component data large and time-consuming, thus affecting the overall noise prediction efficiency; and it is difficult to fully reflect the sound absorption and insulation effects of the covering parts and structural parts in the whole machine system by calculating or simulating the noise data of the scattered components to directly predict the noise data of the whole machine, which easily leads to obvious errors between the predicted data and the actual data.

[0106] Therefore, how to improve the prediction efficiency and prediction accuracy of the noise data of the whole construction machinery is a technical problem to be solved urgently at present.

[0107] To solve the above technical problems, the present invention discloses a method and system for predicting the noise data of the whole construction machinery, which can improve the prediction efficiency and prediction accuracy of the noise data of the whole construction machinery. The following will be described in detail respectively.

[0108] Embodiment 1

[0109] Please refer to Figure 1 , Figure 1 which is a schematic flow chart of a method for predicting the noise data of the whole construction machinery disclosed by the present invention. Among them, Figure 1The method shown can be applied to the whole machine noise data prediction system, which can predict the noise data of construction machinery. The construction machinery is a variant machine with a corresponding prototype machine, and the prototype machine has multiple different types of noise sources, such as Figure 1 As shown, a whole machine noise data prediction method for construction machinery disclosed in the present invention includes but is not limited to the following operations:

[0110] 101. Obtain the set of noise source sound power levels corresponding to the prototype machine in the preset noise database; the set of noise source sound power levels is the set of measured sound power levels of all noise sources of the prototype machine;

[0111] 102. Calculate the initial outboard sound power level of the variant machine according to the set of noise source sound power levels; the initial outboard sound power level is the outboard radiation sound power level of the whole variant machine;

[0112] 103. Obtain the predicted sound power level correction value corresponding to the prototype machine in the noise database;

[0113] 104. Correct the initial outboard sound power level according to the predicted sound power level correction value to obtain the predicted outboard sound power level corresponding to the variant machine.

[0114] It can be seen that in the embodiment of the present invention, the set of noise source sound power levels corresponding to the prototype machine is obtained from the preset noise database, and thus the initial outboard sound power level of the variant machine is calculated according to the set of noise source sound power levels; then the predicted sound power level correction value corresponding to the prototype machine in the noise database is obtained, and the initial outboard sound power level is corrected according to the predicted sound power level correction value to obtain the predicted sound power level of the variant machine. There is no need to test each of the scattered components one by one to obtain the noise data of the components, thereby reducing the time consumed by noise prediction and improving the efficiency of the whole machine noise prediction of construction machinery. In addition, by predicting the noise data of the prototype machine and correcting the noise prediction data of the whole variant machine, the sound absorption and insulation effects of the covering parts and structural parts in the whole machine system can be reflected, thereby improving the accuracy of noise data prediction.

[0115] In an alternative embodiment, the variant machine has a plurality of noise sources corresponding one-to-one to the types of noise sources of the prototype machine, and the variant machine can operate under a plurality of preset working conditions respectively;

[0116] Calculating the initial outboard sound power level of the variant machine according to the set of noise source sound power levels may include:

[0117] For any preset operating condition, calculate the sound power levels of all noise sources of the variant machine according to the set of sound power levels of the noise sources, and perform sound power synthesis based on the sound power levels of all noise sources of the variant machine to obtain the first sound power level corresponding to the variant machine under this preset operating condition; the first sound power level is the external radiation sound power level of the entire variant machine under this preset operating condition.

[0118] Perform multi-condition noise synthesis based on the first sound power levels respectively corresponding to the variant machine under all preset operating conditions to obtain the initial external sound power level of the variant machine.

[0119] The preset operating condition can be multiple different operating conditions specified in GB / T25614-2010. In the embodiment of the present invention, under any preset operating condition, first calculate the sound power levels of all noise sources of the variant machine according to the sound power levels of each noise source of the prototype machine, and then perform sound power synthesis on the sound power levels of all noise sources of the variant machine to obtain the external radiation sound power level of the entire machine under this operating condition; finally, synthesize the external radiation sound power levels of the variant machine corresponding to each operating condition to obtain the initial external sound power level of the variant machine under the comprehensive condition.

[0120] In an optional embodiment, the noise sources of the prototype machine at least include a fan cooling system.

[0121] Before obtaining the set of sound power levels of the noise sources corresponding to the prototype machine in the preset noise database, a method for predicting the overall machine noise data applied to construction machinery disclosed in the embodiment of the present invention further includes:

[0122] Test the external radiation sound power level of the entire prototype machine under the preset test operating condition to obtain the prototype test sound power level corresponding to the prototype machine.

[0123] Measure the near-field noise data of all noise sources of the prototype machine including the fan cooling system respectively.

[0124] Calculate the measured sound power level of the fan cooling system according to the prototype test sound power level and the near-field noise data of the fan cooling system.

[0125] Calculate the measured sound power level of other noise sources of the prototype machine except the fan cooling system according to the measured sound power level of the fan cooling system and the near-field noise data of other noise sources of the prototype machine except the fan cooling system.

[0126] Calculate the external radiation sound power level of the entire prototype machine according to the measured sound power levels of all noise sources of the prototype machine to obtain the prototype calculated sound power level.

[0127] Calculate the difference between the prototype calculated sound power level and the prototype test sound power level to obtain the predicted sound power level correction value corresponding to the prototype machine.

[0128] Integrate the near - field noise data of all noise sources of the prototype, the measured sound power levels of all noise sources of the prototype, and the corrected values of the predicted sound power levels corresponding to the prototype to construct a noise database.

[0129] In the embodiments of the present invention, in addition to the fan cooling system, other noise sources of the prototype also include the engine, the transmission, the drive axle, the hydraulic pump, the exhaust pipe, etc. When measuring the near - field noise data of all noise sources of the prototype, the noise source data collector is arranged in the near - field range where the distance from the noise source is not greater than 20 cm. Specifically, it can be configured as follows: First, for the fan cooling system, the near - field noise data of multiple areas on the surface of the cooling fan system can be measured, and each area is approximated as a point sound source; Second, for the engine and the transmission, the surfaces of the engine and the transmission are divided into multiple areas, each area is approximated as a point sound source, and the near - field noise data of all areas are measured respectively; Third, for the drive axle, the near - field noise data of the wheel side reducer, the tire grounding position, and the main drive position of the axle need to be measured respectively; Fourth, for the hydraulic pump, due to its small volume, the hydraulic pump can be approximated as a single point sound source to measure the near - field noise data; Fifth, for the exhaust pipe, the pipe orifice of the exhaust pipe is approximated as a single point sound source, and each pipe orifice of the exhaust pipe is measured.

[0130] In an alternative embodiment, the near - field noise data includes the near - field acoustic transfer function and the near - field sound pressure level;

[0131] Measuring the near - field noise data of all noise sources including the fan cooling system of the prototype respectively may include:

[0132] Measuring the near - field acoustic transfer functions corresponding to all noise sources including the fan cooling system of the prototype in the state where the prototype is not started;

[0133] Measuring the near - field sound pressure levels corresponding to all noise sources including the fan cooling system of the prototype in the state where the prototype is started and operating under test conditions.

[0134] In the implementation of the present invention, the relationship between the sound power level of the point sound source, the near - field production function, and the near - field sound pressure level satisfies the formula:

[0135] Lw = 84.5 + Lp - ATF

[0136] Wherein, Lw represents the sound power level of the point sound source, Lp represents the near - field sound pressure level of the point sound source, and ATF represents the near - field acoustic transfer function of the point sound source.

[0137] In an alternative embodiment, the fan cooling system includes at least one cooling fan point sound source, and each cooling fan point sound source has a corresponding near - field acoustic transfer function and near - field sound pressure level;

[0138] Calculating the measured sound power level of the fan heat dissipation system based on the sound power level measured in the prototype test and the near-field noise data of the fan heat dissipation system may include:

[0139] For any heat dissipation fan point source, calculating the point source sound power level of the heat dissipation fan point source according to the near-field acoustic transfer function and near-field sound pressure level corresponding to the heat dissipation fan point source;

[0140] Performing sound power synthesis on the point source sound power levels of all heat dissipation fan point sources to obtain the theoretical sound power level of the fan heat dissipation system;

[0141] Performing noise cancellation correction on the theoretical sound power level of the fan heat dissipation system according to the sound power level measured in the prototype test to obtain the measured sound power level of the fan heat dissipation system.

[0142] In an embodiment of the present invention, it is recorded that the fan heat dissipation system has a total of n heat dissipation fan point sources, and the sound power level of the i-th (i = 1, 2, 3,..., n) heat dissipation fan point source is:

[0143] Lw i = 84.5 + Lp i −ATF i

[0144] wherein, Lp i is the near-field sound pressure level of the i-th heat dissipation fan point source, and ATF i is the near-field acoustic transfer function of the i-th heat dissipation fan point source.

[0145] The expression for calculating the theoretical sound power level of the fan heat dissipation system through sound power synthesis is:

[0146] Lw -fan = 10 × lg(10^(Lw1 / 10) + 10^(Lw2 / 10) + 10^(Lw3 / 10) +... + 10^(Lw n / 10))

[0147] Performing noise cancellation correction on the theoretical sound power level Lw -fan of the fan heat dissipation system according to the sound power level measured in the prototype test to obtain the measured sound power level Lw -test .

[0148] In an optional embodiment, calculating the measured sound power level of other noise sources of the prototype machine except the fan heat dissipation system based on the measured sound power level of the fan heat dissipation system and the near-field noise data of other noise sources of the prototype machine except the fan heat dissipation system may include:

[0149] Calculating the difference between the measured sound power level of the fan heat dissipation system and the theoretical sound power level of the fan heat dissipation system to obtain the noise source sound power level correction value;

[0150] For any noise source of the prototype other than the fan cooling system, calculate the theoretical sound power level of the noise source according to the near-field acoustic transfer function and near-field sound pressure level of the noise source, and correct the theoretical sound power level of the noise source according to the correction value of the noise source sound power level to obtain the measured sound power level of the noise source.

[0151] In the embodiment of the present invention, the expression of the correction value of the noise source sound power level is:

[0152] △Lw = Lw -test -Lw -fan

[0153] where, △Lw represents the correction value of the noise source sound power level, Lw -fan represents the theoretical sound power level of the fan cooling system, Lw -test represents the measured sound power level of the fan cooling system.

[0154] The expression for calculating the measured sound power level of other noise sources of the prototype other than the fan cooling system based on the correction value of the noise source sound power level is:

[0155] Lw' = (84.5 + △Lw) + Lp' - ATF'

[0156] where, Lw' represents the sound power level of other noise sources of the prototype other than the fan cooling system, Lp' represents the near-field sound pressure level of other noise sources of the prototype other than the fan cooling system, and ATF' represents the near-field acoustic transfer function of other noise sources of the prototype other than the fan cooling system.

[0157] In an alternative embodiment, the prototype can operate under multiple preset working conditions respectively;

[0158] Calculate the external radiation sound power level of the whole prototype according to the measured sound power levels of all noise sources of the prototype to obtain the prototype calculated sound power level, including:

[0159] For any preset working condition, perform sound power synthesis according to the measured sound power levels of all noise sources of the prototype to obtain the second sound power level corresponding to the prototype under the preset working condition; the second sound power level is the external radiation sound power level of the whole prototype under the preset working condition;

[0160] Perform multi-condition noise synthesis according to the second sound power levels respectively corresponding to the prototype under all preset working conditions to obtain the prototype calculated sound power level.

[0161] The preset operating conditions can be multiple different operating conditions specified in GB / T25614-2010. In the embodiments of the present invention, under any preset operating condition, the sound power levels of all noise sources of the prototype are synthesized in terms of sound power to obtain the overall machine radiation sound power level under this operating condition; then the overall machine radiation sound power levels corresponding to the prototype under each operating condition are synthesized to obtain the prototype calculation sound power level of the prototype under the comprehensive condition.

[0162] In an alternative embodiment, for the coupling effect of complex noise sources in construction machinery, a frequency-band noise synthesis technology can be introduced to improve the prediction accuracy. Specifically, during the sound power synthesis process, the system divides the spectral characteristics of the noise sources into multiple frequency bands (such as low-frequency band, medium-frequency band, and high-frequency band), and establishes a sound power level synthesis model for each frequency band respectively. For each noise source, its sound power level is decomposed into contribution values for each frequency band and dynamically adjusted through frequency-band weight coefficients. When calculating the initial out-of-machine sound power level of the variant machine, the system first superimposes the sound power levels of the same frequency band of each noise source, and then generates the full-frequency band sound power level through a frequency-band synthesis algorithm. In addition, in view of the differences in sound absorption and insulation characteristics of the covering parts and structural parts in different frequency bands, the system can configure an independent correction coefficient for each frequency band. For example, the sound insulation effect of the cab glass on high-frequency noise is better than that on low-frequency noise, and such characteristics can be accurately reflected in the prediction model through the frequency-band correction coefficient. This implementation method is particularly applicable to construction machinery containing broadband noise sources (such as the combined noise of the hydraulic system and the engine), and can effectively reduce the prediction error caused by the interference effect between frequency bands.

[0163] In an alternative embodiment, a method for predicting the overall machine noise data applied to construction machinery disclosed in the embodiments of the present invention further includes:

[0164] For any noise source of the prototype, measure the far-field sound transfer function between this noise source and the cab of the prototype when the prototype is not started;

[0165] Obtain the near-field sound pressure levels corresponding to all noise sources of the prototype in the noise database;

[0166] Predict the sound pressure level of the noise inside the cab of the variant machine based on the far-field sound transfer functions and near-field sound pressure levels corresponding to all noise sources of the prototype, and obtain the predicted in-machine sound pressure level corresponding to the variant machine.

[0167] It should be noted that the predicted in-machine sound pressure level is the sound pressure level of the noise near the driver's ear inside the cab of the variant machine.

[0168] It can be seen that in the embodiments of the present invention, first, the far-field acoustic transfer function between all noise sources of the prototype machine and the cab of the prototype machine is measured, and then the near-field sound pressure levels of all noise sources of the prototype machine in the noise database are obtained, so as to predict the sound pressure level of the noise in the cab of the variant machine according to the far-field acoustic transfer function and the near-field sound pressure levels of all noise sources of the prototype machine. There is no need to test each of the scattered components one by one to obtain the noise data of the components, thereby reducing the time consumed by noise prediction and improving the efficiency of the whole-machine noise prediction of construction machinery. In addition, by predicting the sound pressure level of the noise in the cab of the variant machine based on the noise data of the prototype machine, the sound absorption and insulation effects of the covering parts and structural parts in the whole machine system can be reflected, thereby improving the accuracy of noise data prediction.

[0169] In an alternative embodiment, predicting the sound pressure level of the noise in the cab of the variant machine according to the far-field acoustic transfer function and the near-field sound pressure levels respectively corresponding to all noise sources of the prototype machine to obtain the predicted in-machine sound pressure level corresponding to the variant machine may include:

[0170] For any noise source of the prototype machine, calculate the product of the far-field acoustic transfer function and the near-field sound pressure level corresponding to the noise source to obtain the single-noise-source sound pressure level corresponding to the noise source; the single-noise-source sound pressure level is the sound pressure level when the noise generated by the noise source propagates to the cab position of the prototype machine;

[0171] Perform sound pressure level synthesis according to the single-noise-source sound pressure levels respectively corresponding to all noise sources of the prototype machine to obtain the predicted in-machine sound pressure level corresponding to the variant machine.

[0172] In the embodiments of the present invention, it is recorded that the prototype machine has a total of m noise sources, then the calculation formula for the single-noise sound pressure level of the jth (j = 0, 1, 2,..., m) prototype machine noise source is:

[0173] Lc j = Lq j ×FTF j

[0174] where, Lc j is the single-noise-source sound pressure level of the jth prototype machine noise source, Lq j is the near-field sound pressure level of the jth prototype machine noise source, and FTF j is the far-field acoustic transfer function of the jth prototype machine noise source.

[0175] The calculation formula for the predicted in-machine sound pressure level corresponding to the variant machine is:

[0176] Lc ear = 10×lg(10^(Lq1 / 10)+10^(Lq2 / 10)+10^(Lq3 / 10)+...+10^(Lq m / 10))

[0177] Among them, Lc ear represents the in - machine predicted sound pressure level of the variant machine.

[0178] In some implementation scenarios, a method for predicting the overall machine noise data of construction machinery disclosed by the present invention may further include a dynamic verification and iterative optimization process for the prediction results of the overall machine noise of the variant machine. Specifically, after calculating the out - of - machine predicted sound power level and the in - machine predicted sound pressure level of the variant machine, the prediction results can be verified based on the test data of the actual trial - produced prototype, and the correction values and acoustic transfer function parameters in the noise database can be dynamically adjusted according to the verification results. By introducing a closed - loop feedback mechanism, the adaptability and long - term accuracy of the noise prediction model can be significantly improved. The specific steps include: First, after the assembly of the trial - produced prototype of the variant machine is completed, measure the out - of - machine radiated sound power level and the in - cabin sound pressure level according to the preset test working conditions to obtain the measured sound power level and the measured sound pressure level; Second, compare the measured data with the predicted data and calculate the prediction error value; If the prediction error exceeds the preset threshold, start the parameter optimization program and perform reverse calibration on the sound power level correction value, near - field acoustic transfer function or far - field acoustic transfer function in the noise database based on the error distribution; Finally, re - import the optimized parameters into the noise database for subsequent noise prediction of the variant machine. This process can be executed periodically to form a data - driven continuous optimization mechanism, which is especially suitable for scenarios where the construction machinery product line is iterated frequently.

[0179] Embodiment 2

[0180] Please refer to Figure 2 , Figure 2 which is a schematic structural diagram of a system for predicting the overall machine noise data of construction machinery disclosed by the present invention. Among them Figure 2 the system shown can be used to execute a method for predicting the overall machine noise data of construction machinery described in Embodiment 1, and this method for predicting the overall machine noise data of construction machinery can predict the noise data of construction machinery. The construction machinery is a variant machine with a corresponding prototype machine, and the prototype machine has multiple different types of noise sources. As Figure 2 shown, a system for predicting the overall machine noise data of construction machinery disclosed by the present invention includes but is not limited to the following modules:

[0181] The first data acquisition module 201 is used to acquire the set of noise source sound power levels corresponding to the prototype machine in the preset noise database; the set of noise source sound power levels is the set of measured sound power levels of all noise sources of the prototype machine;

[0182] The first data calculation module 202 is used to calculate the initial out - of - machine sound power level of the variant machine according to the set of noise source sound power levels; the initial out - of - machine sound power level is the out - of - machine radiated sound power level of the whole variant machine;

[0183] The second data acquisition module 203 is configured to acquire the predicted sound power level correction value corresponding to the prototype machine in the noise database;

[0184] The sound power level prediction module 204 is configured to correct the initial outboard sound power level according to the predicted sound power level correction value to obtain the predicted outboard sound power level corresponding to the variant machine.

[0185] It can be seen that in the embodiment of the present invention, the set of noise source sound power levels corresponding to the prototype machine is acquired from the preset noise database, so as to calculate the initial outboard sound power level of the variant machine according to the set of noise source sound power levels; then the predicted sound power level correction value corresponding to the prototype machine in the noise database is acquired, and the initial outboard sound power level is corrected according to the predicted sound power level correction value to obtain the predicted sound power level of the variant machine. There is no need to test each of the scattered components one by one to obtain the noise data of the components, thereby reducing the time consumed for noise prediction and improving the efficiency of the overall machine noise prediction of construction machinery. In addition, by predicting and correcting the noise prediction data of the entire variant machine through the noise data of the prototype machine, the sound absorption and insulation effects of the covering parts and structural parts in the overall machine system can be reflected, thereby improving the accuracy of noise data prediction.

[0186] In an alternative embodiment, the variant machine has a plurality of noise sources that correspond one-to-one to the types of noise sources of the prototype machine, and the variant machine can operate under a plurality of preset working conditions respectively;

[0187] The specific manner in which the first data calculation module 202 calculates the initial outboard sound power level of the variant machine according to the set of noise source sound power levels includes:

[0188] For any preset working condition, calculate the sound power levels of all the noise sources of the variant machine according to the set of noise source sound power levels, and perform sound power synthesis according to the sound power levels of all the noise sources of the variant machine to obtain the first sound power level corresponding to the variant machine under this preset working condition; the first sound power level is the outboard radiation sound power level of the entire variant machine under this preset working condition;

[0189] Perform multi-condition noise synthesis according to the first sound power levels corresponding to the variant machine under all preset working conditions respectively to obtain the initial outboard sound power level of the variant machine.

[0190] The preset working conditions may be a plurality of different working conditions specified in GB / T25614-2010. In the embodiment of the present invention, under any preset working condition, first calculate the sound power levels of all the noise sources of the variant machine according to the sound power levels of each noise source of the prototype machine, and then perform sound power synthesis on the sound power levels of all the noise sources of the variant machine to obtain the overall machine radiation sound power level under this working condition; finally, synthesize the overall machine radiation sound power levels corresponding to the variant machine under each working condition to obtain the initial outboard sound power level of the variant machine under the comprehensive condition.

[0191] In an alternative embodiment, refer to Figure 3 , Figure 3 which is a schematic structural diagram of another whole-machine noise data prediction system for construction machinery disclosed by the present invention. The noise sources of the prototype machine at least include the fan cooling system;

[0192] As Figure 3 shown, a whole-machine noise data prediction system for construction machinery disclosed by the present invention further includes:

[0193] A prototype machine noise test module 205, configured to test the out-of-machine radiation sound power level of the whole prototype machine under preset test working conditions to obtain the prototype test sound power level corresponding to the prototype machine;

[0194] A noise source data calculation module 206, configured to respectively calculate the near-field noise data of all noise sources of the prototype machine including the fan cooling system;

[0195] A second data calculation module 207, configured to calculate the measured sound power level of the fan cooling system according to the prototype test sound power level and the near-field noise data of the fan cooling system;

[0196] A third data calculation module 208, configured to calculate the measured sound power level of other noise sources of the prototype machine except the fan cooling system according to the measured sound power level of the fan cooling system and the near-field noise data of other noise sources of the prototype machine except the fan cooling system;

[0197] A prototype machine noise calculation module 209, configured to calculate the out-of-machine radiation sound power level of the whole prototype machine according to the measured sound power levels of all noise sources of the prototype machine to obtain the prototype calculation sound power level;

[0198] A correction value calculation module 210, configured to calculate the difference between the prototype calculation sound power level and the prototype test sound power level to obtain the prediction sound power level correction value corresponding to the prototype machine;

[0199] A database construction module 211, configured to integrate the near-field noise data of all noise sources of the prototype machine, the measured sound power levels of all noise sources of the prototype machine, and the prediction sound power level correction value corresponding to the prototype machine to construct a noise database.

[0200] In the embodiments of the present invention, in addition to the fan cooling system, other noise sources of the prototype machine also include the engine, transmission, drive axle, hydraulic pump, exhaust pipe, etc. When measuring the near-field noise data of all noise sources of the prototype machine, the noise source data collector is arranged in the near-field range where the distance from the noise source is not greater than 20 cm. Specifically, it can be configured as follows: First, for the fan cooling system, the near-field noise data of multiple areas on the surface of the cooling fan system can be measured, and each area is approximated as a point sound source; Second, for the engine and transmission, the surfaces of the engine and transmission are divided into multiple areas, and each area is approximated as a point sound source, and the near-field noise data of all areas are measured respectively; Third, for the drive axle, the near-field noise data of the wheel side reducer, the tire grounding position, and the main transmission position of the axle need to be measured respectively; Fourth, for the hydraulic pump, due to its small volume, the hydraulic pump can be approximated as a single point sound source to measure the process noise data; Fifth, for the exhaust pipe, the pipe orifice of the exhaust pipe is approximated as a single point sound source, and each pipe orifice of the exhaust pipe is measured.

[0201] In an alternative embodiment, the near-field noise data includes the near-field acoustic transfer function and the near-field sound pressure level;

[0202] The specific manner in which the noise source data measurement module 206 measures the near-field noise data of all noise sources of the prototype machine including the fan cooling system respectively includes:

[0203] Measure the near-field acoustic transfer function corresponding to each of all noise sources of the prototype machine including the fan cooling system in the state where the prototype machine is not started;

[0204] Measure the near-field sound pressure level corresponding to each of all noise sources of the prototype machine including the fan cooling system in the state where the prototype machine is started and operating under the test working condition.

[0205] In the implementation of the present invention, the relationship between the sound power level of the point sound source and the near-field production function and the near-field sound pressure level satisfies the following formula:

[0206] Lw = 84.5 + Lp - ATF

[0207] Wherein, Lw represents the sound power level of the point sound source, Lp represents the near-field sound pressure level of the point sound source, and ATF represents the near-field acoustic transfer function of the point sound source.

[0208] In an alternative embodiment, the fan cooling system includes at least one cooling fan point sound source, and each cooling fan point sound source has a corresponding near-field acoustic transfer function and near-field sound pressure level;

[0209] The specific manner in which the second data calculation module 207 calculates the measured sound power level of the fan cooling system according to the prototype test sound power level and the near-field noise data of the fan cooling system includes:

[0210] For any point sound source of a cooling fan, calculate the point sound power level of the point sound source of the cooling fan according to the near-field acoustic transfer function and the near-field sound pressure level corresponding to the point sound source of the cooling fan;

[0211] Perform sound power synthesis on the point sound power levels of all point sound sources of the cooling fans to obtain the theoretical sound power level of the fan cooling system;

[0212] Perform noise cancellation correction on the theoretical sound power level of the fan cooling system according to the prototype test sound power level to obtain the measured sound power level of the fan cooling system.

[0213] In the embodiment of the present invention, it is recorded that there are n point sound sources of cooling fans in the fan cooling system, and the sound power level of the i-th (i = 1, 2, 3,..., n) point sound source of the cooling fan is:

[0214] Lw i = 84.5 + Lp i −ATF i

[0215] where Lp i is the near-field sound pressure level of the i-th point sound source of the cooling fan, and ATF i is the near-field acoustic transfer function of the i-th point sound source of the cooling fan.

[0216] The expression for calculating the theoretical sound power level of the fan cooling system by sound power synthesis is:

[0217] Lw -fan = 10×lg(10^(Lw1 / 10) + 10^(Lw2 / 10) + 10^(Lw3 / 10) +... + 10^(Lw n / 10))

[0218] Perform noise cancellation correction on the theoretical sound power level Lw -fan of the fan cooling system according to the prototype test sound power level to obtain the measured sound power level Lw -test .

[0219] In an optional embodiment, the specific manner in which the third data calculation module 208 calculates the measured sound power level of other noise sources of the prototype machine except for the fan cooling system according to the measured sound power level of the fan cooling system and the near-field noise data of other noise sources of the prototype machine except for the fan cooling system includes:

[0220] Calculate the difference between the measured sound power level of the fan cooling system and the theoretical sound power level of the fan cooling system to obtain the noise source sound power level correction value;

[0221] For any noise source of the prototype machine other than the fan cooling system, calculate the theoretical sound power level of the noise source according to the near-field acoustic transfer function and near-field sound pressure level of the noise source, and correct the theoretical sound power level of the noise source according to the correction value of the noise source sound power level to obtain the measured sound power level of the noise source.

[0222] In the embodiment of the present invention, the expression of the correction value of the noise source sound power level is:

[0223] △Lw = Lw -test -Lw -fan

[0224] where, △Lw represents the correction value of the noise source sound power level, Lw -fan represents the theoretical sound power level of the fan cooling system, Lw -test represents the measured sound power level of the fan cooling system.

[0225] The expression for calculating the measured sound power level of other noise sources of the prototype machine other than the fan cooling system based on the correction value of the noise source sound power level is:

[0226] Lw' = (84.5 + △Lw) + Lp' - ATF'

[0227] where, Lw' represents the sound power level of other noise sources of the prototype machine other than the fan cooling system, Lp' represents the near-field sound pressure level of other noise sources of the prototype machine other than the fan cooling system, and ATF' represents the near-field acoustic transfer function of other noise sources of the prototype machine other than the fan cooling system.

[0228] In an optional embodiment, the prototype machine can operate under multiple preset working conditions respectively;

[0229] The prototype machine noise calculation module 209 calculates the external radiation sound power level of the whole prototype machine according to the measured sound power levels of all noise sources of the prototype machine. The specific method for obtaining the prototype calculation sound power level includes:

[0230] For any preset working condition, perform sound power synthesis according to the measured sound power levels of all noise sources of the prototype machine to obtain the second sound power level corresponding to the prototype machine under this preset working condition; the second sound power level is the external radiation sound power level of the whole prototype machine under this preset working condition;

[0231] Perform multi-condition noise synthesis according to the second sound power levels corresponding to the prototype machine under all preset working conditions to obtain the prototype calculation sound power level.

[0232] The preset working condition can be multiple different working conditions specified in GB / T 25614-2010. In the embodiments of the present invention, under any preset working condition, the sound power levels of all noise sources of the prototype are synthesized in terms of sound power to obtain the overall machine radiation sound power level under this working condition; then, the overall machine radiation sound power levels corresponding to the prototype under each working condition are synthesized to obtain the prototype calculation sound power level of the prototype under the comprehensive condition.

[0233] In an alternative embodiment, please refer to Figure 4 , Figure 4 which is a schematic structural diagram of another overall machine noise data prediction system applied to construction machinery disclosed by the present invention. As Figure 4 shown, an overall machine noise data prediction system applied to construction machinery disclosed by the present invention further includes:

[0234] A cab noise measurement module 212, configured to measure the far-field sound transfer function between any noise source of the prototype and the cab of the prototype in the state where the prototype is not started;

[0235] A third data acquisition module 213, configured to acquire the near-field sound pressure levels respectively corresponding to all noise sources of the prototype in the noise database;

[0236] A sound pressure level prediction module 214, configured to predict the sound pressure level of the noise inside the cab of the variant machine according to the far-field sound transfer functions and the near-field sound pressure levels respectively corresponding to all noise sources of the prototype, so as to obtain the in-machine predicted sound pressure level corresponding to the variant machine.

[0237] It should be noted that the in-machine predicted sound pressure level is the sound pressure level of the noise beside the driver's ear inside the cab of the variant machine.

[0238] It can be seen that in the embodiments of the present invention, first, the far-field sound transfer functions between all noise sources of the prototype and the cab of the prototype are measured, and then the near-field sound pressure levels of all noise sources of the prototype in the noise database are acquired, so as to predict the sound pressure level of the noise inside the cab of the variant machine according to the far-field sound transfer functions and the near-field sound pressure levels of all noise sources of the prototype. There is no need to test each of the scattered components one by one to obtain the noise data of the components, thereby reducing the time consumed for noise prediction and improving the efficiency of overall machine noise prediction of construction machinery. In addition, by predicting the sound pressure level of the noise inside the cab of the variant machine as a whole based on the noise data of the prototype, the sound absorption and insulation effects of the covering parts and structural parts in the overall machine system can be reflected, thereby improving the accuracy of noise data prediction.

[0239] In an optional embodiment, a whole-machine noise data prediction system disclosed by the present invention for construction machinery can integrate a spatial sound field reconstruction function to achieve three-dimensional visualization prediction of the whole-machine noise. Specifically, after completing the sound power level prediction, the system constructs a three-dimensional spatial sound field distribution map based on the geometric distribution data of the noise sources (such as the position coordinates of the cooling fan and the installation orientation of the engine) and the sound propagation model. By superimposing the three-dimensional CAD model of the variant machine on the sound field data, the noise radiation intensity of the whole machine in different orientations can be intuitively displayed. For the noise prediction in the cab, the system further combines the acoustic mirror principle and the boundary element algorithm to simulate the multiple reflection and absorption processes of the noise inside the cab, and generates a heat map of the spatial distribution of the sound pressure level. This function not only supports designers to quickly identify the noise hot spots, but also provides data visualization support for the optimization of noise reduction structures (such as the arrangement of sound-absorbing materials and the design of the sound insulation cover openings). During implementation, the system needs to pre-set a standard acoustic transfer function library and be compatible with the data interface of the CAD platform to ensure seamless docking of geometric information and acoustic parameters.

[0240] In an optional embodiment, the sound pressure level prediction module 214 predicts the sound pressure level of the noise inside the cab of the variant machine according to the far-field acoustic transfer function and the near-field sound pressure level respectively corresponding to all the noise sources of the prototype machine. The specific method for obtaining the predicted in-machine sound pressure level corresponding to the variant machine includes:

[0241] For any noise source of the prototype machine, calculate the product of the far-field acoustic transfer function and the near-field sound pressure level corresponding to this noise source to obtain the single-noise-source sound pressure level corresponding to this noise source; the single-noise-source sound pressure level is the sound pressure level when the noise generated by this noise source propagates to the cab position of the prototype machine;

[0242] Perform sound pressure level synthesis according to the single-noise-source sound pressure levels respectively corresponding to all the noise sources of the prototype machine to obtain the predicted in-machine sound pressure level corresponding to the variant machine.

[0243] In the embodiment of the present invention, it is recorded that the prototype machine has a total of m noise sources. Then the calculation formula for the single-noise sound pressure level of the jth (j = 0, 1, 2,..., m) prototype machine noise source is:

[0244] Lc j =Lq j ×FTF j

[0245] Wherein, Lc j is the single-noise sound pressure level of the jth prototype machine noise source, Lq j is the near-field sound pressure level of the jth prototype machine noise source, and FTF j is the far-field acoustic transfer function of the jth prototype machine noise source.

[0246] The calculation formula for the predicted in-machine sound pressure level corresponding to the variant machine is:

[0247] Lc ear = 10 × lg(10^(Lq1 / 10) + 10^(Lq2 / 10) + 10^(Lq3 / 10) +... + 10^(Lq m / 10))

[0248] Wherein, Lc ear represents the predicted sound pressure level inside the variant machine.

[0249] In an optional embodiment, a whole-machine noise data prediction system for construction machinery disclosed in the embodiments of the present invention may adopt a noise source correlation analysis technology based on a knowledge graph. The system constructs a knowledge graph of construction machinery noise, semantically correlates multivariate information such as historical test data, material acoustic properties, and component structure parameters. When predicting a new variant machine, the system automatically retrieves the historical acoustic performance of similar models and similar components in the graph, and optimizes the initial prediction value through analogical reasoning. For example, if a new type of hydraulic pump has the same displacement parameter and housing material as three known pump bodies recorded in the graph, the system will automatically take the weighted average of the noise data of these three pump bodies as the prediction benchmark. This method effectively utilizes the implicit knowledge assets accumulated by the enterprise, especially in the new product development lacking complete prototype data, and can significantly improve the reliability of the prediction results.

[0250] Embodiment III

[0251] Please refer to Figure 5 , Figure 5 which is a schematic structural diagram of another whole-machine noise data prediction system for construction machinery disclosed in the present invention. Wherein Figure 5 the system shown can be used to execute a whole-machine noise data prediction method for construction machinery described in Embodiment I, and this whole-machine noise data prediction method can predict the noise data of construction machinery. As Figure 5 shown, a whole-machine noise data prediction system for construction machinery disclosed in the embodiments of the present invention includes but is not limited to:

[0252] A memory 301 storing executable program code;

[0253] A processor 302 coupled to the memory 301;

[0254] The processor 302 calls the executable program code stored in the memory 301 and executes some or all of the steps in the whole-machine noise data prediction method for construction machinery described in Embodiment I of the present invention.

[0255] Embodiment IV

[0256] An embodiment of the present invention discloses a computer storage medium. The computer storage medium stores computer instructions, which are used to execute some or all of the steps in the whole machine noise data prediction method applied to construction machinery described in Embodiment 1 of the present invention when called by a processor.

[0257] The device embodiments described above are only illustrative. The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical modules. They may be located in one place or distributed to multiple network modules. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. A person of ordinary skill in the art can understand and implement it without creative labor.

[0258] Through the above specific description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, and of course also by hardware. Based on this understanding, the above technical solution, in essence, or the part that contributes to the prior art can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, and the storage medium includes read-only memory (ROM), random access memory (RAM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), one-time programmable read-only memory (OTPROM), electrically-erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc memories, magnetic disk memories, tape memories, or any other computer-readable medium capable of carrying or storing data.

[0259] Finally, it should be noted that: What is disclosed by a whole-machine noise data prediction method and system applied to construction machinery disclosed in the embodiments of the present invention is only the preferred embodiments of the present invention, which are only used to illustrate the technical solutions of the present invention, rather than limiting it; Although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: They can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements on some of the technical features; And these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for predicting the overall machine noise data applied to construction machinery, characterized in that, The construction machinery is a variant machine with a corresponding prototype machine, and the prototype machine has multiple different types of noise sources. The method includes: Obtaining a set of sound power levels of the noise sources corresponding to the prototype machine in a preset noise database; the set of sound power levels of the noise sources is a set of measured sound power levels of all the noise sources of the prototype machine; Calculating the initial off-machine sound power level of the variant machine according to the set of sound power levels of the noise sources; the initial off-machine sound power level is the off-machine radiation sound power level of the whole variant machine; Obtaining a predicted sound power level correction value corresponding to the prototype machine in the noise database; Correcting the initial off-machine sound power level according to the predicted sound power level correction value to obtain the predicted off-machine sound power level corresponding to the variant machine.

2. The whole machine noise data prediction method applied to construction machinery according to claim 1, characterized in that The variant machine has a plurality of noise sources corresponding one-to-one to the types of the noise sources of the prototype machine, and the variant machine can operate under a plurality of preset working condition conditions respectively; The calculating the initial off-machine sound power level of the variant machine according to the set of sound power levels of the noise sources includes: For any one of the preset working condition conditions, calculating the sound power levels of all the noise sources of the variant machine according to the set of sound power levels of the noise sources, and performing sound power synthesis according to the sound power levels of all the noise sources of the variant machine to obtain a first sound power level corresponding to the variant machine under this preset working condition condition; the first sound power level is the off-machine radiation sound power level of the whole variant machine under this preset working condition condition; Performing multi-condition noise synthesis according to the first sound power levels respectively corresponding to the variant machine under all the preset working condition conditions to obtain the initial off-machine sound power level of the variant machine.

3. The method for predicting the overall machine noise data applied to construction machinery according to claim 1, wherein, The noise sources of the prototype machine at least include a fan cooling system; Before obtaining the set of sound power levels of the noise sources corresponding to the prototype machine in the preset noise database, the method further includes: Testing the off-machine radiation sound power level of the whole prototype machine under a preset test working condition condition to obtain a prototype test sound power level corresponding to the prototype machine; Measuring and calculating the near-field noise data of all the noise sources of the prototype machine including the fan cooling system respectively; Calculating the measured sound power level of the fan cooling system according to the prototype test sound power level and the near-field noise data of the fan cooling system; Calculating the measured sound power levels of the other noise sources of the prototype machine except the fan cooling system according to the measured sound power level of the fan cooling system and the near-field noise data of the other noise sources of the prototype machine except the fan cooling system; Calculating the off-machine radiation sound power level of the whole prototype machine according to the measured sound power levels of all the noise sources of the prototype machine to obtain a prototype calculated sound power level; Calculating the difference between the prototype calculated sound power level and the prototype test sound power level to obtain the predicted sound power level correction value corresponding to the prototype machine; Integrating the near-field noise data of all the noise sources of the prototype machine, the measured sound power levels of all the noise sources of the prototype machine and the predicted sound power level correction value corresponding to the prototype machine to construct a noise database.

4. The method for predicting the overall machine noise data applied to construction machinery according to claim 3, wherein, The near-field noise data includes a near-field acoustic transfer function and a near-field sound pressure level; Measuring the near-field noise data of all noise sources including the fan cooling system of the prototype respectively, including: Measuring the near-field acoustic transfer function corresponding to each of all noise sources including the fan cooling system of the prototype when the prototype is in an unstarted state; Measuring the near-field sound pressure level corresponding to each of all noise sources including the fan cooling system of the prototype when the prototype is started and operating under the test working condition.

5. The method for predicting the overall machine noise data applied to construction machinery according to claim 4, wherein The fan cooling system includes at least one heat dissipation fan point source, and each heat dissipation fan point source has a near-field acoustic transfer function and a near-field sound pressure level corresponding to the heat dissipation fan point source; Calculating the measured sound power level of the fan cooling system according to the prototype test sound power level and the near-field noise data of the fan cooling system, including: For any one of the heat dissipation fan point sources, calculating the point source sound power level of the heat dissipation fan point source according to the near-field acoustic transfer function and the near-field sound pressure level corresponding to the heat dissipation fan point source; Performing sound power synthesis on the point source sound power levels of all the heat dissipation fan point sources to obtain the theoretical sound power level of the fan cooling system; Performing noise cancellation correction on the theoretical sound power level of the fan cooling system according to the prototype test sound power level to obtain the measured sound power level of the fan cooling system.

6. The method for predicting the overall machine noise data applied to construction machinery according to claim 5, characterized in that, Calculating the measured sound power level of other noise sources of the prototype except the fan cooling system according to the measured sound power level of the fan cooling system and the near-field noise data of other noise sources of the prototype except the fan cooling system, including: Calculating the difference between the measured sound power level of the fan cooling system and the theoretical sound power level of the fan cooling system to obtain the noise source sound power level correction value; For any noise source of the prototype except the fan cooling system, calculating the theoretical sound power level of the noise source according to the near-field acoustic transfer function and the near-field sound pressure level of the noise source, and correcting the theoretical sound power level of the noise source according to the noise source sound power level correction value to obtain the measured sound power level of the noise source.

7. The method for predicting the overall noise data applied to construction machinery according to claim 3, wherein The prototype can operate under multiple preset working conditions respectively; Calculating the external radiation sound power level of the whole prototype according to the measured sound power levels of all noise sources of the prototype to obtain the prototype calculated sound power level, including: For any one of the preset working conditions, performing sound power synthesis according to the measured sound power levels of all noise sources of the prototype to obtain the second sound power level corresponding to the prototype under the preset working condition; the second sound power level is the external radiation sound power level of the whole prototype under the preset working condition; Performing multi-condition noise synthesis according to the second sound power levels corresponding to the prototype under all the preset working conditions to obtain the prototype calculated sound power level.

8. The method for predicting the overall machine noise data applied to construction machinery according to any one of claims 4 to 6, characterized in that, The method further includes: For any noise source of the prototype, measuring the far-field acoustic transfer function between the noise source and the cab of the prototype when the prototype is in an unstarted state; Obtaining the near-field sound pressure levels corresponding to all noise sources of the prototype in the noise database; Predict the sound pressure level of the noise inside the cab of the variant machine based on the far-field acoustic transfer functions and near-field sound pressure levels respectively corresponding to all the noise sources of the prototype machine, and obtain the predicted in-machine sound pressure level corresponding to the variant machine.

9. The method for predicting the overall machine noise data applied to construction machinery according to claim 8, wherein The predicting the sound pressure level of the noise inside the cab of the variant machine based on the far-field acoustic transfer functions and near-field sound pressure levels respectively corresponding to all the noise sources of the prototype machine, and obtaining the predicted in-machine sound pressure level corresponding to the variant machine includes: For any noise source of the prototype machine, calculate the product of the far-field acoustic transfer function and the near-field sound pressure level corresponding to this noise source to obtain the single-noise-source sound pressure level corresponding to this noise source; the single-noise-source sound pressure level is the sound pressure level when the noise generated by this noise source propagates to the cab position of the prototype machine; Perform sound pressure level synthesis based on the single-noise-source sound pressure levels respectively corresponding to all the noise sources of the prototype machine to obtain the predicted in-machine sound pressure level corresponding to the variant machine.

10. A whole machine noise data prediction system applied to construction machinery, characterized in that, The construction machinery is a variant machine with a corresponding prototype machine, and the prototype machine has multiple different types of noise sources. The system includes: A first data acquisition module, configured to acquire the set of noise source sound power levels corresponding to the prototype machine in a preset noise database; the set of noise source sound power levels is the set of measured sound power levels of all the noise sources of the prototype machine; A first data calculation module, configured to calculate the initial out-of-machine sound power level of the variant machine according to the set of noise source sound power levels; the initial out-of-machine sound power level is the out-of-machine radiation sound power level of the whole variant machine; A second data acquisition module, configured to acquire the predicted sound power level correction value corresponding to the prototype machine in the noise database; A sound power level prediction module, configured to correct the initial out-of-machine sound power level according to the predicted sound power level correction value to obtain the predicted out-of-machine sound power level corresponding to the variant machine.

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