CN112800595A - Method and system for detecting influence of combustion chamber processing parameters on emission based on big data - Google Patents

Method and system for detecting influence of combustion chamber processing parameters on emission based on big data Download PDF

Info

Publication number
CN112800595A
CN112800595A CN202110025980.0A CN202110025980A CN112800595A CN 112800595 A CN112800595 A CN 112800595A CN 202110025980 A CN202110025980 A CN 202110025980A CN 112800595 A CN112800595 A CN 112800595A
Authority
CN
China
Prior art keywords
combustion chamber
processing
parameter
emission
big data
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN202110025980.0A
Other languages
Chinese (zh)
Other versions
CN112800595B (en
Inventor
闫伟
王健
杨晓峰
王辉
李国祥
豆腾尧
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Shandong University
Original Assignee
Shandong University
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Shandong University filed Critical Shandong University
Priority to CN202110025980.0A priority Critical patent/CN112800595B/en
Publication of CN112800595A publication Critical patent/CN112800595A/en
Application granted granted Critical
Publication of CN112800595B publication Critical patent/CN112800595B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00Computer-aided design [CAD]
    • G06F30/20Design optimisation, verification or simulation
    • GPHYSICS
    • G16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16CCOMPUTATIONAL CHEMISTRY; CHEMOINFORMATICS; COMPUTATIONAL MATERIALS SCIENCE
    • G16C20/00Chemoinformatics, i.e. ICT specially adapted for the handling of physicochemical or structural data of chemical particles, elements, compounds or mixtures
    • G16C20/10Analysis or design of chemical reactions, syntheses or processes

Landscapes

  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Chemical & Material Sciences (AREA)
  • Geometry (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Evolutionary Computation (AREA)
  • Computer Hardware Design (AREA)
  • Analytical Chemistry (AREA)
  • Chemical Kinetics & Catalysis (AREA)
  • Crystallography & Structural Chemistry (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Computing Systems (AREA)
  • Combined Controls Of Internal Combustion Engines (AREA)

Abstract

The invention discloses a method and a system for detecting the influence of combustion chamber processing parameters on emission based on big data, wherein the technical scheme is as follows: constructing a diesel engine combustion model, and selecting different piston combustion chamber processing parameters to perform simulation calculation to obtain a simulation result; analyzing the simulation result to obtain the rule of influence of the variation of each parameter on the consistency of the NOx emission; calculating a key parameter processing threshold according to the rule; and acquiring key processing parameter data, and determining a processing parameter distribution range by using a big data tool. The method comprises the steps of firstly constructing a diesel engine combustion model, calculating to obtain influence rules of all parameters on emission, processing collected processing data by combining a big data theory based on the emission rules to obtain a processing parameter tolerance threshold value, and detecting the processing quality of a diesel engine combustion chamber.

Description

Method and system for detecting influence of combustion chamber processing parameters on emission based on big data
Technical Field
The invention relates to the technical field of diesel engines, in particular to a method and a system for detecting influence of combustion chamber processing parameters on emission based on big data.
Background
The piston combustion chamber is an important component of the diesel engine. The piston combustion chamber has a direct influence on the dynamics, economy and emissions of the diesel engine. At present, the emission enters the sixth stage of China, the emission limit value of NOx is greatly reduced, the sensitivity to emission fluctuation is increased, the processing quality needs to be controlled, and the emission consistency is improved, so that the product competitiveness is improved.
The detection of the processing quality of the diesel engine is mainly based on the design requirement, and the tolerance of the processing parameter of the combustion chamber is collected through a tool for measuring the tolerance. Dimensional fluctuations due to tolerances in process parameters may cause the diesel engine to exceed emission limits, and the tolerance ranges conventionally used to test process quality may not meet emission compliance requirements.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide a method and a system for detecting the influence of processing parameters of a combustion chamber on emission based on big data.
In order to achieve the purpose, the invention is realized by the following technical scheme:
in a first aspect, embodiments of the present invention provide a method for detecting emissions affected by combustion chamber processing parameters based on big data, comprising:
constructing a diesel engine combustion model, and selecting different piston combustion chamber processing parameters to perform simulation calculation to obtain a simulation result;
analyzing the simulation result to obtain the rule of influence of the variation of each parameter on the consistency of the NOx emission; calculating a key parameter processing threshold according to the rule;
and acquiring key processing parameter data, and determining a processing parameter distribution range by using a big data tool.
As a further implementation mode, a combustion simulation software is utilized to construct a diesel engine combustion model, an orthogonal test is designed to carry out simulation calculation, and the variation rule of diesel engine emission under each parameter range is obtained.
As a further implementation, the relationship of NOx emissions to key parameters is obtained by applying the simulation results:
Figure BDA0002890250480000021
wherein a represents the throat diameter, b represents the throat diameter, c represents the combustor depth,
Figure BDA0002890250480000022
indicating the amount of NOx emissions.
As a further implementation, the key process parameters include throat diameter, and combustor depth.
As a further implementation, the throat diameter, the diameter of the constriction and the depth of the combustion chamber were analyzed using a big data tool, respectively, yielding: the distribution rule of the diameters of the throats meets the Weber distribution, the distribution rule of the diameters of the contraction positions meets the triangular distribution, and the distribution rule of the depths of the combustion chambers meets the trapezoidal distribution.
As a further implementation mode, the final generation amount of NOx has a quadratic function relation with the throat diameter of the combustion chamber through analysis; within the process parameter tolerances, NOx emissions are positively correlated with combustor depth.
As a further implementation mode, the minimum size of the throat diameter which is larger than the corresponding NOx emission limit value and is smaller than the maximum tolerance required by processing is calculated according to the emission limit value of the diesel engine; the diameter of the contraction part meets the discharge requirement; the depth of the combustion chamber should be greater than the minimum tolerance required for machining and less than the maximum dimension for the NOx emission limit.
In a second aspect, an embodiment of the present invention further provides a system for detecting processing quality of a combustion chamber of a diesel engine based on big data analysis, including:
a combustion model building module configured to: constructing a diesel engine combustion model, and selecting different piston combustion chamber processing parameters to perform simulation calculation to obtain a simulation result;
a machining threshold calculation module configured to: analyzing the simulation result to obtain the rule of influence of the variation of each parameter on the consistency of the NOx emission; calculating a key parameter processing threshold according to the rule;
a distribution threshold calculation module configured to: and acquiring key processing parameter data, and determining a processing parameter distribution range by using a big data tool.
In a third aspect, an embodiment of the present invention further provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor executes the program to implement the method for detecting emissions influenced by the big-data based processing parameters of the combustor.
In a fourth aspect, the embodiment of the present invention further provides a computer readable storage medium, on which a computer program is stored, which when executed by a processor implements the method for detecting emission influenced by big data based combustion chamber processing parameters.
The beneficial effects of the above-mentioned embodiment of the present invention are as follows:
according to one or more embodiments of the invention, a diesel engine combustion model is constructed by using combustion simulation software, the simulation result is subjected to regression analysis to obtain the change rule between the NOx emission and each parameter, and then the threshold value of each processing parameter meeting the requirement of the NOx emission consistency is calculated according to the national standard NOx emission requirement;
according to one or more embodiments of the invention, the diameter of the throat, the diameter of the contraction part and the depth of the combustion chamber are selected as key parameters, and the key parameters are analyzed by using a big data tool to obtain the distribution range of processing parameters; when the diesel engine piston combustion chamber meets the tolerance requirement of the processing parameters, the requirement of NOx emission consistency on the fluctuation of the processing parameters, namely a fluctuation threshold value, is also met, so that the detection accuracy is improved.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, are included to provide a further understanding of the invention, and are incorporated in and constitute a part of this specification, illustrate exemplary embodiments of the invention and together with the description serve to explain the invention and not to limit the invention.
FIG. 1 is a flow diagram in accordance with one or more embodiments of the invention;
FIG. 2 is a plot of a throat diameter distribution profile according to one or more embodiments of the present disclosure;
FIG. 3 is a plot of a diameter distribution at a constriction in accordance with one or more embodiments of the present invention;
FIG. 4 is a graph of combustor depth profiles in accordance with one or more embodiments of the present invention.
Detailed Description
It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the disclosure. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments according to the present application. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, and it should be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof, unless the context clearly indicates otherwise.
The first embodiment is as follows:
the embodiment provides a method for detecting combustion chamber processing parameter influence emission based on big data, which can analyze the influence of diesel engine piston combustion chamber processing parameter variation on the consistency of NOx emission, as shown in FIG. 1, and comprises the following steps:
constructing a diesel engine combustion model, and selecting different piston combustion chamber processing parameters to perform simulation calculation to obtain a simulation result;
analyzing the simulation result to obtain the rule of influence of the variation of each parameter on the consistency of the NOx emission; calculating a key parameter processing threshold according to the rule;
and acquiring key processing parameter data, and determining a processing parameter distribution range by using a big data tool.
Further, firstly, selecting key parameters (throat diameter, diameter of a contraction part and depth of the combustion chamber) in the process of processing the combustion chamber, and constructing a combustion model of the diesel engine by using combustion simulation software; and carrying out simulation calculation to obtain a change rule between the NOx emission and each parameter, and then calculating to obtain the threshold value of each processing parameter meeting the requirement of the NOx emission consistency according to the national standard NOx emission requirement.
In this embodiment, the combustion simulation software may be conversion simulation software; of course, in other embodiments, the combustion simulation software may also be other software capable of modeling the combustion chamber, and may be specifically selected according to actual requirements.
And then, collecting key parameter processing data of the combustion chamber of the diesel engine by using a measuring tool (such as a screw micrometer) for measuring the parameter tolerance of the combustion chamber, and analyzing according to a big data theory to obtain a corresponding distribution rule, thereby calculating the distribution range of each parameter and obtaining the threshold range of the key parameter of the piston combustion chamber of the diesel engine, which meets the national six NOx emission consistency.
Specifically, orthogonal simulation tests are carried out on the diameter of the throat, the diameter of the contraction part and the depth of the combustion chamber, and simulation results are analyzed to obtain the relation between the NOx emission and three key parameters:
Figure BDA0002890250480000051
wherein, the variable a is the diameter of the throat, unit: mm; b is the diameter of the constriction, in units: mm; c combustion chamber depth, unit: mm;
Figure BDA0002890250480000052
NOx emission, unit: and (5) mg.
The diameter of the throat is analyzed by using a big data theory, the obtained distribution is shown in figure 2, the distribution is weber distribution, the shape parameter of the function is 75.025, the proportion parameter is 2599.08, and the weber distribution function formula is as follows:
Figure BDA0002890250480000061
wherein a is the diameter of the throat, unit: mm; f (a) is frequency.
In the processing process, the acquired processing test data are concentrated in a certain range, and the range is the optimal range for processing; if the machining data exceeds the range, the machining data is larger or smaller, and both larger and smaller indicate that the machining quality has a certain problem.
According to an analytical equation, the final generation amount of the NOx in the cylinder and the throat diameter of the combustion chamber have a quadratic function relationship, and the amount of the NOx is reduced along with the increase of the throat diameter in a processing parameter range; in the case of an emission limit specifying a NOx limit of 3.4mg, the throat diameter is calculated to be greater than 74.92 mm. Therefore, when the processing quality is detected, the diameter of the throat is greater than 74.92mm required by the discharge threshold and less than 75.1mm of the maximum required by the processing.
The diameter of the contraction is analyzed by using a big data theory, the distribution is obtained as shown in figure 3, and the quantity of the diameter processing parameters of the contraction at larger and smaller values is basically the same according to the distribution. According to the diameter distribution condition of the contraction part, selecting a triangular distribution function for processing to obtain a distribution formula as follows:
Figure BDA0002890250480000062
wherein b is the diameter of the constriction, unit: mm; f (b) is frequency.
The diameters of the contraction parts are intensively distributed near the standard size, in order to determine the optimal range of the processing parameters, the diameter distribution rule of the contraction parts can be obtained, the diameters of the contraction parts are in the fluctuation range of 64.36mm-61.56mm, the generation amount of NOx is continuously increased, the regression prediction maximum generation amount result of the NOx is in the range of 3.4mg, namely the fluctuation of the NOx along with the diameters of the contraction parts meets the test requirements.
The depth of the combustion chamber is analyzed by utilizing a big data theory, the obtained distribution is shown in figure 4, trapezoidal distribution is selected for processing according to the depth distribution condition of the combustion chamber, and the obtained depth distribution formula of the combustion chamber is as follows:
Figure BDA0002890250480000071
where c is the combustion chamber depth, unit: mm; f (c) is frequency.
The analytical equation can show that the NOx emission is positively correlated with the combustion chamber depth within the tolerance range of the processing parameters, and the combustion chamber depth is calculated to be less than 19.3mm under the condition that the NOx limit specified by the emission limit value is 3.4 mg. The combustor depth should therefore be 19.23mm greater than the minimum required for processing and 19.3mm less than the emission threshold requirement.
And processing the acquired data of the diameter of the throat, the diameter of the contraction part and the depth of the combustion chamber according to an equation and by combining a big data theory. When the processing quality is detected, the diameter of the throat is larger than 74.92mm and smaller than 75.1mm, and the depth of the combustion chamber is larger than 19.23mm and smaller than 19.3 mm.
Example two:
the embodiment provides a diesel engine combustion chamber processing quality detecting system based on big data analysis, includes:
a combustion model building module configured to: constructing a diesel engine combustion model, and selecting different piston combustion chamber processing parameters to perform simulation calculation to obtain a simulation result;
a machining threshold calculation module configured to: analyzing the simulation result to obtain the rule of influence of the variation of each parameter on the consistency of the NOx emission; calculating a key parameter processing threshold according to the rule;
a distribution threshold calculation module configured to: and acquiring key processing parameter data, and determining a processing parameter distribution range by using a big data tool.
Example three:
the embodiment provides an electronic device, which comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the processor executes the program to realize the detection method for the emission influence based on the big data combustion chamber processing parameters.
Example four:
the present embodiments provide a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the described big data based combustor process parameter impact emission detection method.
The steps involved in the second to fourth embodiments correspond to the first embodiment of the method, and the detailed description thereof can be found in the relevant description of the first embodiment. The term "computer-readable storage medium" should be taken to include a single medium or multiple media containing one or more sets of instructions; it should also be understood to include any medium that is capable of storing, encoding or carrying a set of instructions for execution by a processor and that cause the processor to perform any of the methods of the present invention.
Those skilled in the art will appreciate that the modules or steps of the present invention described above can be implemented using general purpose computer means, or alternatively, they can be implemented using program code that is executable by computing means, such that they are stored in memory means for execution by the computing means, or they are separately fabricated into individual integrated circuit modules, or multiple modules or steps of them are fabricated into a single integrated circuit module. The present invention is not limited to any specific combination of hardware and software.
The above description is only a preferred embodiment of the present application and is not intended to limit the present application, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims (10)

1. The method for detecting the influence of the combustion chamber processing parameters on the emission based on the big data is characterized by comprising the following steps:
constructing a diesel engine combustion model, and selecting different piston combustion chamber processing parameters to perform simulation calculation to obtain a simulation result;
analyzing the simulation result to obtain the rule of influence of the variation of each parameter on the consistency of the NOx emission; calculating a key parameter processing threshold according to the rule;
and acquiring key processing parameter data, and determining a processing parameter distribution range by using a big data tool.
2. The method for detecting the influence of the emission of the combustion chamber processing parameters based on the big data as claimed in claim 1, wherein a combustion simulation software is used for constructing a diesel engine combustion model, and an orthogonal test is designed for simulation calculation to obtain the variation rule of the diesel engine emission in each parameter range.
3. The method for detecting the influence emission of the combustion chamber processing parameters based on the big data as claimed in claim 2, wherein the relation between the NOx emission and the key parameters is obtained by the simulation result:
yNOx=28.534-0.0053a2+0.000052abc
wherein a represents the throat diameter, b represents the throat diameter, c represents the combustion chamber depth, yNOxIndicating the amount of NOx emissions.
4. The big-data based detection method of combustor process parameters affecting emissions as claimed in claim 1 wherein said key process parameters include throat diameter, throat diameter and combustor depth.
5. The big-data-based detection method for influence of combustion chamber processing parameters on emissions according to claim 4, wherein the throat diameter, the diameter of the constriction and the depth of the combustion chamber are analyzed by a big-data tool respectively to obtain: the distribution rule of the diameters of the throats meets the Weber distribution, the distribution rule of the diameters of the contraction positions meets the triangular distribution, and the distribution rule of the depths of the combustion chambers meets the trapezoidal distribution.
6. The big data based detection method for influence of combustion chamber processing parameters on emissions as claimed in claim 5, wherein the final amount of NOx generated is a quadratic function of the diameter of the combustion chamber throat; within the process parameter tolerances, NOx emissions are positively correlated with combustor depth.
7. The method for detecting the influence of the emission of the combustion chamber processing parameters based on the big data as claimed in claim 1, wherein the diameter of the throat is calculated according to the emission limit value of the diesel engine, wherein the diameter of the throat is larger than the minimum size corresponding to the emission limit value of NOx and smaller than the maximum tolerance required by processing; the diameter of the contraction part meets the discharge requirement; the depth of the combustion chamber should be greater than the minimum tolerance required for machining and less than the maximum dimension for the NOx emission limit.
8. Diesel engine combustion chamber processing quality detecting system based on big data analysis, its characterized in that includes:
a combustion model building module configured to: constructing a diesel engine combustion model, and selecting different piston combustion chamber processing parameters to perform simulation calculation to obtain a simulation result;
a machining threshold calculation module configured to: analyzing the simulation result to obtain the rule of influence of the variation of each parameter on the consistency of the NOx emission; calculating a key parameter processing threshold according to the rule;
a distribution threshold calculation module configured to: and acquiring key processing parameter data, and determining a processing parameter distribution range by using a big data tool.
9. An electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor when executing the program implements the method for detecting big data based combustor process parameter impact emissions as claimed in any of claims 1-7.
10. A computer-readable storage medium, on which a computer program is stored, which program, when executed by a processor, implements the big data based combustor process parameter impact emissions detection method as claimed in any one of claims 1-7.
CN202110025980.0A 2021-01-08 2021-01-08 Method and system for detecting influence of combustion chamber processing parameters on emission based on big data Active CN112800595B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202110025980.0A CN112800595B (en) 2021-01-08 2021-01-08 Method and system for detecting influence of combustion chamber processing parameters on emission based on big data

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202110025980.0A CN112800595B (en) 2021-01-08 2021-01-08 Method and system for detecting influence of combustion chamber processing parameters on emission based on big data

Publications (2)

Publication Number Publication Date
CN112800595A true CN112800595A (en) 2021-05-14
CN112800595B CN112800595B (en) 2022-04-22

Family

ID=75809494

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202110025980.0A Active CN112800595B (en) 2021-01-08 2021-01-08 Method and system for detecting influence of combustion chamber processing parameters on emission based on big data

Country Status (1)

Country Link
CN (1) CN112800595B (en)

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP2574763A1 (en) * 2011-09-30 2013-04-03 Volvo Car Corporation NOx emission estimation method and arrangement
US20140002809A1 (en) * 2012-06-29 2014-01-02 On-Site Analysis Inc Multifunctional fluid meter and method for measuring coolant, bio-diesel, gas-ethanol and def
CN110414132A (en) * 2019-07-29 2019-11-05 山东大学 A kind of engine intelligent design method and system based on wisdom cloud platform
CN111737842A (en) * 2019-03-19 2020-10-02 新奥数能科技有限公司 Method and device for optimizing emission of nitrogen oxide of combustor

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP2574763A1 (en) * 2011-09-30 2013-04-03 Volvo Car Corporation NOx emission estimation method and arrangement
US20140002809A1 (en) * 2012-06-29 2014-01-02 On-Site Analysis Inc Multifunctional fluid meter and method for measuring coolant, bio-diesel, gas-ethanol and def
CN111737842A (en) * 2019-03-19 2020-10-02 新奥数能科技有限公司 Method and device for optimizing emission of nitrogen oxide of combustor
CN110414132A (en) * 2019-07-29 2019-11-05 山东大学 A kind of engine intelligent design method and system based on wisdom cloud platform

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
刘胜吉等: "单缸柴油机排放性能的生产一致性控制", 《扬州大学学报(自然科学版)》 *
黄加亮等: "燃油喷射系统优化对柴油机性能的影响及喷油参数再优化", 《大连海事大学学报》 *

Also Published As

Publication number Publication date
CN112800595B (en) 2022-04-22

Similar Documents

Publication Publication Date Title
DE102007051784B4 (en) Knock detection device for an internal combustion engine
CN103853899A (en) Fatigue life calculation method for shaft parts
CN113159162A (en) Fault diagnosis method and system based on information fusion and grey correlation
WO2022213603A1 (en) Method, apparatus, and device for verifying compression ratio of engine, and storage medium
CN112417764A (en) K nearest neighbor regression prediction method for boiler special equipment steam flow prediction
CN111881564A (en) Method for predicting amplitude-variable fatigue life of mechanical structure
CN117877619B (en) Method and system for improving flame retardance of high-dispersity cement dispersant
CN112800595B (en) Method and system for detecting influence of combustion chamber processing parameters on emission based on big data
Jones et al. Control-oriented knock simulation
CN114186806A (en) Carbon emission influence factor analysis method and system based on single-layer LMDI
CN105893686A (en) Designing and manufacturing method for accurately controlling consistency of compression ratio
JP2004068729A (en) Adapting method for engine control parameter and its system
CN115408927B (en) Data processing method and device for predicting rock mass parameters
CN113933297B (en) Tunnel surrounding rock grading method and device, electronic equipment and medium
CN115993808A (en) System and method for diagnosing energy consumption of gas steam boiler
CN111929720B (en) Neutron detector performance detection method, device, system and computer equipment
CN113623069A (en) Engine EMS knock recognition effect evaluation method and device, electronic equipment and storage medium
CN113807677A (en) Method, device and equipment for determining oil field energy consumption index and storage medium
CN107145694B (en) RBF neural network-based continuous rotation detonation combustor pressure increase ratio prediction method
CN112329108A (en) Optimized anti-floating checking calculation method and system for subway station
CN111553072B (en) Method and device for determining equipment characteristic curve
CN114091540B (en) Method for constructing cold test intelligent detection model of diesel engine, detection method and system
JP2020139897A (en) Knocking level evaluation method
CN105868456B (en) Aircraft constrained optimization method based on filter technology and subdivision rectangle algorithm
Ulmer et al. Improving the Calibration Process of Internal Combustion Engines by Using an Innovative Multidimensional Optimization Algorithm

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant