CN114810448B - Method for online analysis of fuel gas injection process time of direct injection engine in high-pressure natural cylinder based on wavelet transformation - Google Patents
Method for online analysis of fuel gas injection process time of direct injection engine in high-pressure natural cylinder based on wavelet transformation Download PDFInfo
- Publication number
- CN114810448B CN114810448B CN202210380960.XA CN202210380960A CN114810448B CN 114810448 B CN114810448 B CN 114810448B CN 202210380960 A CN202210380960 A CN 202210380960A CN 114810448 B CN114810448 B CN 114810448B
- Authority
- CN
- China
- Prior art keywords
- time
- gas
- pressure
- pressure signal
- injection process
- 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.)
- Active
Links
Images
Classifications
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F02—COMBUSTION ENGINES; HOT-GAS OR COMBUSTION-PRODUCT ENGINE PLANTS
- F02M—SUPPLYING COMBUSTION ENGINES IN GENERAL WITH COMBUSTIBLE MIXTURES OR CONSTITUENTS THEREOF
- F02M65/00—Testing fuel-injection apparatus, e.g. testing injection timing ; Cleaning of fuel-injection apparatus
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T10/00—Road transport of goods or passengers
- Y02T10/10—Internal combustion engine [ICE] based vehicles
- Y02T10/30—Use of alternative fuels, e.g. biofuels
Landscapes
- Engineering & Computer Science (AREA)
- Chemical & Material Sciences (AREA)
- Combustion & Propulsion (AREA)
- Mechanical Engineering (AREA)
- General Engineering & Computer Science (AREA)
- Combined Controls Of Internal Combustion Engines (AREA)
Abstract
The invention discloses a wavelet transformation-based online analysis method for the gas injection process time of a direct injection engine in a high-pressure natural cylinder. Step 1: installing and debugging equipment, wherein an inlet pressure sensor is arranged at the gas inlet of the natural gas HPDI injector, and meanwhile, a pressure sensor is arranged at the gas hole of the injector; step 2: performing wavelet transform-based processing on pressure signals acquired by the pressure sensor installed in the step 1; step 3: performing a time feature recognition algorithm based on the pressure signal processed based on the wavelet transformation in the step 2; step 4: and (3) comparing and analyzing the time characteristics obtained by the time characteristic identification in the step (3) with the air injection rules measured by the offline experiments, so as to realize the time online analysis of the gas injection process of the direct injection engine in the high-pressure natural cylinder. The method is used for solving the problem that the time characteristics of the existing natural gas injection process are not observable; and the on-line analysis of the time characteristics of the gas injection process is realized.
Description
Technical Field
The invention belongs to the field of power energy sources; in particular to a method for analyzing the time of the gas injection process of a direct injection engine in a high-pressure natural cylinder on line based on wavelet transformation.
Background
In recent years, with the release of national emission regulations, the shortage of traditional fuel resources is faced with various problems in the internal combustion engine industry. Natural gas fuel is considered as a very promising alternative energy source with the advantages of low exhaust pollution, high octane number, high antiknock, abundant reserves and renewable. According to statistical data, it has been shown that natural gas fuels have been used in industry for years and compared to conventional diesel engines. Natural gas engines typically have low carbon emissions. However, the traditional premixed combustion natural gas engine has the problems that the engine charge coefficient is reduced and the efficiency is reduced due to factors such as the knock limit, the pre-combustion and the like, and the high-pressure natural gas in-cylinder direct injection (HPDI) technology directly injects natural gas into a cylinder, so that good air-fuel ratio is ensured, the charging efficiency is improved, the combustion is promoted, and the premixed combustion natural gas engine has good application prospect.
The injector is the most important part of the natural in-cylinder direct injection technology as an actuator of the fuel supply system. The variation of the injection characteristics of the injectors is quite complex due to the complex aero-hydro-electric structure inside the injectors, which is a difficult problem for the development of HPDI technology when the injection characteristics of the HPDI injectors are not directly observable during actual operation.
Because the injector injection characteristics can not be directly observed in the actual running process, the control of the HPDI electric control injector adopts open loop control, and the injection strategies of different working conditions of the engine are difficult to realize by realizing the calibrated MAP. Therefore, it is necessary to provide an online test method capable of realizing online feedback to the injector and further realizing closed-loop control of the injection quantity, and simultaneously providing real-time monitoring, fault early warning and residual life prediction of the injector according to the operation state of the injector.
Disclosure of Invention
The invention provides a wavelet transformation-based online analysis method for the time of a fuel gas injection process of a direct injection engine in a high-pressure natural cylinder, which is used for solving the problem that the time characteristic of the existing natural gas injection process is not observable; by analyzing the time-frequency characteristic of the inlet pressure signal, the recognition of the injector time characteristic is realized on the wavelet change of the inlet pressure signal and the signal after the dimension reduction processing, and the on-line analysis of the gas injection process time characteristic is realized.
The invention is realized by the following technical scheme:
a method for online analysis of fuel gas injection process time of a direct injection engine in a high-pressure natural cylinder based on wavelet transformation comprises the following steps:
step 1: installing and debugging equipment, wherein an inlet pressure sensor is arranged at the gas inlet of the natural gas HPDI injector 1, and meanwhile, a pressure sensor is arranged at the gas hole of the injector;
step 2: performing wavelet transform-based processing on pressure signals acquired by the pressure sensor installed in the step 1;
step 3: performing a time feature recognition algorithm based on the pressure signal processed based on the wavelet transformation in the step 2;
step 4: and (3) comparing and analyzing the time characteristics obtained by the time characteristic identification in the step (3) with the air injection rules measured by the offline experiments, so as to realize the time online analysis of the gas injection process of the direct injection engine in the high-pressure natural cylinder.
The method for analyzing the time of the fuel gas injection process of the direct injection engine in the high-pressure natural cylinder on line based on wavelet transformation comprises the following steps of 1, installing equipment, wherein the equipment comprises a natural gas HPDI injector 1, PXI2, an upper computer 3, a pressure control device 4, a pressure sensor 5, a gas source 6, a gas rail 7, a gas compressor 8 and an amplifier module 9.
The natural gas HPDI injector 1 is respectively connected with PXI2 and a pressure sensor 5, the pressure sensor 5 is connected with an upper computer 3 through an amplifier module 9, the PXI2 is connected with the upper computer 3, the pressure sensor 5 is connected with a gas compressor 8 through a gas rail 7, the gas compressor 8 is connected with a gas source 6, and the gas rail 7 is connected with a pressure control device 4.
The method for analyzing the time of the fuel gas injection process of the direct injection engine in the high-pressure natural cylinder on line based on wavelet transformation comprises the following steps of 1, installing equipment, wherein the equipment comprises a natural gas HPDI injector 1, PXI2, an upper computer 3, a pressure control device 4, a pressure sensor 5, a gas source 6, a gas rail 7, a gas compressor 8 and an amplifier module 9.
The gas source 6 is pressurized by the compressor 8 and then is sprayed by the natural gas HPDI sprayer 1 through the gas rail 7 and the pressure sensor 5;
the signal of the pressure sensor 5 is amplified by a charge amplifier 9; collecting the inlet pressure signal through a data collecting module in the upper computer; the collected inlet pressure signals are stored in an upper computer;
the inlet pressure sensor 5 of the natural gas HPDI injector 1 transmits signals to PXI2, and the PXI2 transmits processed signals to the upper computer 3;
the air pressure of the air rail 7 is monitored by the pressure control device 4;
the pressure control device 4 transmits a signal to the upper computer 3.
On-line analysis method for fuel gas injection process time of direct injection engine in high-pressure natural cylinder based on wavelet transformation, wherein a force sensor is arranged at an air hole of a natural gas HPDI injector 1 and is injectedDefinition of the time characteristics of the process, the starting moment t of air injection 0 Full-open time t of needle valve 1 Time t when needle valve starts to seat 2 Jet end time t 3 。
The step 2 is to conduct wavelet transformation-based processing on pressure signals, namely, to derive inlet pressure signals, to analyze the correlation between the variation rate of the derived inlet pressure signals and the jet law, to obtain a time-varying signal, and to divide the time-domain into three stages of ascending, stable and descending, to extract the stable stages, wherein the wavelet transformation of the signal is defined as:
wherein a is a telescoping factor; τ is a translation factor; p (t) is the inlet pressure signal; psi is a window function; t is time;
extracting time domain features and wavelet domain features from the change rate of the inlet pressure signal of the segmented stationary segment; in order to adapt to the computing power of the electronic control unit of the engine, the feature dimension reduction processing is needed, and the time domain feature is saved so as to facilitate the subsequent time feature recognition.
An online analysis method for the fuel gas injection process time of a direct injection engine in a high-pressure natural cylinder based on wavelet transformation, wherein the feature dimension reduction processing adopts a main component analysis method for dimension reduction processing, specifically,
normalization of data:
the new coordinate system is { w 1 ，w 2 ，…,w n -w is i Is standard orthogonal base, m is dimension of dimension reduction, x i For sample data, mean (x i ) For the mean of the group, std (x i ) Is the standard deviation;
sample data x i The projection in the low dimensional space coordinate system satisfies:
wherein z is ij Is x i Coordinates of the j-th dimension in a dimension-reduced coordinate system;
according to the recent reconfigurability, the original sample points satisfy based on the distance between the reconstructed sample points:
in which W is T XX T W is the sample variance, I is the identity matrix, W is { W 1 ，w 2 ，…,w n }，tr(W T XX T W) is a matrix trace;
using lagrange multipliers for equation (4):
XX T W＝γW (5)
for covariance matrix XX T All the characteristic values are obtained, and the obtained characteristic values are expressed as gamma in sequence 1 ≥γ 2 ≥···≥γ m The eigenvectors corresponding to the first m eigenvalues are solutions required by principal component analysis, as shown in formula (6):
W * ＝(w 1 ,w 2 ,···w m ) (6)
wherein W is * The solution that is sought for the principal component analysis.
In the injection process of the natural gas injector, the change rate of the inlet pressure signal is divided into three stages, namely an ascending stage, a stable stage and a descending stage; wherein the three phases are defined as falling (t 0 -t 1 ) Ascending (t) 2 -t 3 ) The method is stable, and after the change rate of the inlet pressure signal is subjected to dimension reduction treatment, the time domain characteristics of the inlet pressure signal are still reserved and can be used for identifying the time characteristicsIn the process.
A time online analysis method for a fuel gas injection process of a direct injection engine in a high-pressure natural cylinder based on wavelet transformation is provided, wherein the time characteristic recognition algorithm in the step 3 is specifically that the first break point of the change rate of an inlet pressure signal after wavelet transformation and dimension reduction processing is t 1 Forward searching to reach the stationary phase point t 0 The method comprises the steps of carrying out a first treatment on the surface of the The second point of interruption is t 2 Retrieving backward the plateau as t 3 If there is only one break point, let t be 1 And t 2 Temporally coincident, it is therefore determined that the needle begins to seat without opening during the injection, and is always in motion during the entire injection.
A method for online analysis of fuel gas injection process time of a direct injection engine in a high-pressure natural cylinder based on wavelet transformation comprises the following steps:
step S1: collecting a natural gas HPDI injector 1 inlet pressure signal;
step S2: deriving the pressure signal of the step S1;
step S3: performing wavelet change on the derivative pressure signal in the step S2;
step S4: performing dimension reduction treatment on the pressure signal subjected to wavelet change in the step S3;
step S5: the change rate of the inlet pressure signal of the pressure signal subjected to the dimension reduction processing in the step S4 is divided into a first break point t 1 And a second break point t 2 ；
Step S6: based on the first break point t of step S5 1 Forward searching to reach the stationary phase point t 0 ；
Step S7: based on the second break point t of step S5 2 Retrieving backward the plateau as t 3 ；
Step S8: judging the first break point t of step S5 1 And a second break point t 2 Whether or not they are equal; if equal description t 1 And t 2 Overlapping in time domain, and starting to seat when the needle valve is not opened in the injection process; if not equal to indicate t 1 And t 2 Is not coincident in time domain and is sprayedThe needle valve is opened during the process.
The beneficial effects of the invention are as follows:
the invention ensures the structural integrity of the natural gas engine.
The invention has real-time performance.
The invention has the advantages of no need of changing the structure of the device, good economy and long service life.
The invention has rapid signal processing speed and high precision.
Drawings
FIG. 1 is a schematic diagram of an experimental set-up of the present invention.
Fig. 2 is a schematic diagram of a time characteristic definition curve of the present invention.
Fig. 3 is a flow chart of the method of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
A method for online analysis of fuel gas injection process time of a direct injection engine in a high-pressure natural cylinder based on wavelet transformation comprises the following steps:
step 1: installing and debugging equipment, wherein an inlet pressure sensor is arranged at the gas inlet of the natural gas HPDI injector 1, and meanwhile, a pressure sensor is arranged at the gas hole of the injector;
step 2: performing wavelet transform-based processing on pressure signals acquired by the pressure sensor installed in the step 1;
step 3: performing a time feature recognition algorithm based on the pressure signal processed based on the wavelet transformation in the step 2;
step 4: and (3) comparing and analyzing the time characteristics obtained by the time characteristic identification in the step (3) with the air injection rules measured by the offline experiments, so as to realize the time online analysis of the gas injection process of the direct injection engine in the high-pressure natural cylinder.
The method for analyzing the time of the fuel gas injection process of the direct injection engine in the high-pressure natural cylinder on line based on wavelet transformation comprises the following steps of 1, installing equipment, wherein the equipment comprises a natural gas HPDI injector 1, PXI2, an upper computer 3, a pressure control device 4, a pressure sensor 5, a gas source 6, a gas rail 7, a gas compressor 8 and an amplifier module 9.
The natural gas HPDI injector 1 is respectively connected with PXI2 and a pressure sensor 5, the pressure sensor 5 is connected with an upper computer 3 through an amplifier module 9, the PXI2 is connected with the upper computer 3, the pressure sensor 5 is connected with a gas compressor 8 through a gas rail 7, the gas compressor 8 is connected with a gas source 6, and the gas rail 7 is connected with a pressure control device 4.
The method for analyzing the time of the fuel gas injection process of the direct injection engine in the high-pressure natural cylinder on line based on wavelet transformation comprises the following steps that 1, equipment is installed, and specifically comprises a natural gas HPDI injector 1, PXI2, an upper computer 3, a pressure control device 4, a pressure sensor 5, a gas source 6, a gas rail 7 and a gas compressor 8;
the gas source 6 is pressurized by the compressor 8 and then is sprayed by the natural gas HPDI sprayer 1 through the gas rail 7 and the pressure sensor 5;
the signal of the pressure sensor 5 is amplified by a charge amplifier 9; collecting the inlet pressure signal through a data collecting module in the upper computer; the collected inlet pressure signals are stored in an upper computer;
the inlet pressure sensor 5 of the natural gas HPDI injector 1 transmits signals to PXI2, and the PXI2 transmits processed signals to the upper computer 3;
the air pressure of the air rail 7 is monitored by the pressure control device 4;
the pressure control device 4 transmits a signal to the upper computer 3.
A method for analyzing the time of the fuel injection process of a direct injection engine in a high-pressure natural cylinder on line based on wavelet transformation is characterized in that a force sensor is arranged at the air hole of a natural gas HPDI injector 1 and is used for measuring the momentum at the outlet of the spray hole so as to be communicated with the air holeObtaining a jet rule by a momentum method; as shown in fig. 1; defining the time characteristics of the injection process and the injection starting time t 0 Full-open time t of needle valve 1 Time t when needle valve starts to seat 2 Jet end time t 3 . As shown in fig. 2.
The step 2 is to process the pressure signal based on wavelet transformation, namely, only according to the injector inlet pressure signal, the corresponding relation with the injector time characteristic cannot be found, so that the inlet pressure signal is derived, the correlation between the change rate of the derived inlet pressure signal and the air injection rule is analyzed, the change rate of the inlet pressure signal is obtained as a time-varying signal, and the time-varying signal is divided into three stages of ascending, stable and descending in the time domain, the stable stage is extracted, and the time domain division of the change rate of the inlet pressure signal is realized;
the wavelet transform of a signal is defined as:
wherein a is a scaling factor (scale parameter); τ is a translation factor (position parameter); p (t) is the inlet pressure signal; psi is a window function; t is time;
the method comprises the steps of carrying out effective feature extraction on the change rate of an inlet pressure signal of a segmented stationary segment, and mainly extracting time domain features and wavelet domain features; in order to adapt to the computing power of the electronic control unit of the engine, the feature dimension reduction processing is needed, and the time domain feature is saved so as to facilitate the subsequent time feature recognition.
An online analysis method for the fuel gas injection process time of a direct injection engine in a high-pressure natural cylinder based on wavelet transformation, wherein the feature dimension reduction processing adopts a main component analysis method for dimension reduction processing, specifically,
normalization of data:
the new coordinate system is { w 1 ，w 2 ，…,w n -w is i Is standard orthogonal base, m is dimension of dimension reduction, x i For sample data, mean (x i ) For the mean of the group, std (x i ) Is the standard deviation;
sample data x i The projection in the low dimensional space coordinate system satisfies:
wherein z is ij Is x i Coordinates of the j-th dimension in a dimension-reduced coordinate system;
according to the recent reconfigurability, the original sample points satisfy based on the distance between the reconstructed sample points:
in which W is T XX T W is the sample variance, I is the identity matrix, W is { W 1 ，w 2 ，…,w n }，tr(W T XX T W) is a matrix trace;
using lagrange multipliers for equation (4):
XX T W＝γW (5)
for covariance matrix XX T All the characteristic values are obtained, and the obtained characteristic values are expressed as gamma in sequence 1 ≥γ 2 ≥···≥γ m The eigenvectors corresponding to the first m eigenvalues are solutions required by principal component analysis, as shown in formula (6):
W * ＝(w 1 ,w 2 ,···w m ) (6)
wherein W is * The solution that is sought for the principal component analysis.
After the main analysis and analysis of the signals are carried out, the main information of the data is enhanced, the characteristics are better embodied, and the subsequent time characteristic recognition process is easier to realize.
In the injection process of the natural gas injector, the change rate of the inlet pressure signal is divided into three stages, namely an ascending stage, a stable stage and a descending stage. Wherein the three phases are defined as falling (t 0 -t 1 ) Ascending (t) 2 -t 3 ) And the time domain characteristics of the inlet pressure signal are still reserved after the change rate of the inlet pressure signal is subjected to dimension reduction treatment, and the time domain characteristics can be used in the time characteristic identification process.
A time online analysis method for a fuel gas injection process of a direct injection engine in a high-pressure natural cylinder based on wavelet transformation is provided, wherein the time characteristic recognition algorithm in the step 3 is specifically that the first break point of the change rate of an inlet pressure signal after wavelet transformation and dimension reduction processing is t 1 Forward searching to reach the stationary phase point t 0 The method comprises the steps of carrying out a first treatment on the surface of the The second point of interruption is t 2 Retrieving backward the plateau as t 3 If there is only one break point, let t be 1 And t 2 Temporally coincident, it is therefore determined that the needle begins to seat without opening during the injection, and is always in motion during the entire injection. The algorithm flow is shown in fig. 3;
a method for online analysis of fuel gas injection process time of a direct injection engine in a high-pressure natural cylinder based on wavelet transformation comprises the following steps:
step S1: collecting a natural gas HPDI injector 1 inlet pressure signal;
step S2: deriving the pressure signal of the step S1;
step S3: performing wavelet change on the derivative pressure signal in the step S2;
step S4: performing dimension reduction treatment on the pressure signal subjected to wavelet change in the step S3;
step S5: the change rate of the inlet pressure signal of the pressure signal subjected to the dimension reduction processing in the step S4 is divided into a first break point t 1 And a second break point t 2 ；
Step S6: based on the first break of step S5Point t 1 Forward searching to reach the stationary phase point t 0 ；
Step S7: based on the second break point t of step S5 2 Retrieving backward the plateau as t 3 ；
Step S8: judging the first break point t of step S5 1 And a second break point t 2 Whether or not they are equal; if equal description t 1 And t 2 Overlapping in time domain, and starting to seat when the needle valve is not opened in the injection process; if not equal to indicate t 1 And t 2 Temporally misaligned and the needle valve opened during injection.
The inlet pressure sensor of fig. 1 is installed at the inlet of the injector in a clamping manner, and signals are collected through a data collection module.
The inlet pressure derivative signal is subjected to wavelet transformation and dimension reduction processing, and the time characteristic is identified through the method of fig. 3.
And (3) performing comparison analysis on the gas injection law graph measured under the same line with the identified time characteristics, so as to realize the time on-line analysis of the gas injection process of the direct injection engine in the high-pressure natural cylinder based on wavelet transformation.
Claims (5)
1. The online analysis method for the fuel gas injection process time of the direct injection engine in the high-pressure natural cylinder based on wavelet transformation is characterized by comprising the following steps of:
step 1: installing and debugging equipment, wherein an inlet pressure sensor (5) is installed at the gas inlet of the natural gas HPDI injector (1), and meanwhile, a force sensor is installed at the gas hole of the injector;
step 2: processing the pressure signal acquired by the pressure sensor (5) at the gas inlet installed in the step 1 based on wavelet transformation;
step 3: performing a time feature recognition algorithm based on the pressure signal processed based on the wavelet transformation in the step 2;
step 4: comparing and analyzing the time characteristics obtained by the time characteristic identification in the step 3 with the air injection rules measured by the offline experiments, so as to realize the online analysis of the gas injection process time of the direct injection engine in the high-pressure natural cylinder;
the step 2 of wavelet transformation-based processing of the pressure signal is specifically to derive an inlet pressure signal, analyze the correlation between the variation rate of the derived inlet pressure signal and the jet rule to obtain a time-varying signal, divide the time-domain into three stages of ascending, stabilizing and descending, extract the stabilizing stage,
the wavelet transform of a signal is defined as:
wherein a is a telescoping factor; τ is a translation factor; p (t) is the inlet pressure signal; psi is a window function; t is time;
extracting time domain features and wavelet domain features from the change rate of the inlet pressure signal of the segmented stationary segment; in order to adapt to the computing power of an electronic control unit of the engine, the feature dimension reduction is processed by adopting a method of principal component analysis, and the time domain features are saved so as to facilitate the subsequent time feature recognition;
in the injection process of the natural gas injector, the change rate of the inlet pressure signal is divided into three stages, namely an ascending stage, a stable stage and a descending stage; wherein the three phases are defined as falling (t 0 -t 1 ) Ascending (t) 2 -t 3 ) The method is stable, and after the dimension reduction treatment is carried out on the change rate of the inlet pressure signal, the time domain characteristics of the inlet pressure signal are still reserved and are used in the time characteristic identification process;
the time characteristic recognition algorithm in the step 3 is specifically that the first break point of the change rate of the inlet pressure signal after wavelet transformation and dimension reduction processing is t 1 Forward searching to reach the stationary phase point t 0 The method comprises the steps of carrying out a first treatment on the surface of the The second point of interruption is t 2 Retrieving backward the plateau as t 3 If there is only one break point, let t be 1 And t 2 The time domain coincides, so that the condition is determined that the needle valve starts to seat when the needle valve is not opened in the injection process, and the needle valve is always in a motion state in the whole injection process;
the feature dimension reduction processing adopts a main component analysis method to reduce dimension, specifically,
normalization of data:
the new coordinate system is { w 1 ，w 2 ，…,w n -w is i Is standard orthogonal base, m is dimension of dimension reduction, x i For sample data, mean (x i ) For the mean of the group, std (x i ) Is the standard deviation;
sample data x i The projection in the low dimensional space coordinate system satisfies:
wherein z is ij Is x i Coordinates of the j-th dimension in a dimension-reduced coordinate system;
according to the recent reconfigurability, the original sample points satisfy based on the distance between the reconstructed sample points:
in which W is T XX T W is the sample variance, I is the identity matrix, W is { W 1 ，w 2 ，…,w n }，tr(W T XX T W) is a matrix trace;
using lagrange multipliers for equation (4):
XX T W＝γW (5)
for covariance matrix XX T All the characteristic values are obtained, and the obtained characteristic values are expressed as gamma in sequence 1 ≥γ 2 ≥···≥γ m The eigenvectors corresponding to the first m eigenvalues are solutions required by principal component analysis, as shown in formula (6):
W * ＝(w 1 ,w 2 ,···w m ) (6)
wherein W is * The solution that is sought for the principal component analysis.
2. The method for on-line analysis of the gas injection process time of the direct injection engine in the high-pressure natural cylinder based on wavelet transformation according to claim 1 is characterized in that the equipment installed in the step 1 comprises a natural gas HPDI injector (1), a PXI (2), an upper computer (3), a pressure control device (4), a pressure sensor (5), a gas source (6), a gas rail (7), a gas compressor (8) and an amplifier module (9);
the natural gas HPDI ejector (1) is connected with PXI (2) and pressure sensor (5) respectively, pressure sensor (5) are connected with host computer (3) through amplifier module (9), PXI (2) are connected with host computer (3), pressure sensor (5) are connected with air compressor (8) through air rail (7), air compressor (8) are connected with air supply (6), air rail (7) are connected with pressure control device (4).
3. The method for on-line analysis of the gas injection process time of the direct injection engine in the high-pressure natural cylinder based on wavelet transformation according to claim 1 is characterized in that the equipment installed in the step 1 comprises a natural gas HPDI injector (1), a PXI (2), an upper computer (3), a pressure control device (4), a pressure sensor (5), a gas source (6), a gas rail (7) and a gas compressor (8);
the gas source (6) is pressurized by the gas compressor (8) and then is ejected by the natural gas HPDI ejector (1) through the gas rail (7) and the pressure sensor (5);
the signal of the pressure sensor (5) is amplified by a charge amplifier (9); collecting the inlet pressure signal through a data collecting module in the upper computer; the collected inlet pressure signals are stored in an upper computer;
an inlet pressure sensor (5) of the natural gas HPDI injector (1) transmits signals to the PXI (2), and the PXI (2) transmits processed signals to an upper computer (3);
the air pressure of the air rail (7) is monitored by a pressure control device (4);
the pressure control device (4) transmits signals to the upper computer (3).
4. A method for on-line analysis of the fuel gas injection process time of a direct injection engine in a high pressure natural cylinder based on wavelet transformation according to claim 1 or 3, characterized in that a force sensor is installed at the air hole of the natural gas HPDI injector (1), the injection process time characteristics are defined, and the injection starting time t 0 Full-open time t of needle valve 1 Time t when needle valve starts to seat 2 Jet end time t 3 。
5. The method for online analysis of the fuel gas injection process time of the direct injection engine in the high-pressure natural cylinder based on wavelet transformation according to claim 1, wherein the online analysis method comprises the following steps:
step S1: collecting an inlet pressure signal of a natural gas HPDI injector (1);
step S2: deriving the pressure signal of the step S1;
step S3: performing wavelet change on the derivative pressure signal in the step S2;
step S4: performing dimension reduction treatment on the pressure signal subjected to wavelet change in the step S3;
step S5: the change rate of the inlet pressure signal of the pressure signal subjected to the dimension reduction processing in the step S4 is divided into a first break point t 1 And a second break point t 2 ；
Step S6: based on the first break point t of step S5 1 Forward searching to reach the stationary phase point t 0 ；
Step S7: based on the second break point t of step S5 2 Retrieving backward the plateau as t 3 ；
Step S8: judging the first break point t of step S5 1 And a second break point t 2 Whether or not they are equal; if equal description t 1 And t 2 Overlapping in time domain, and starting to seat when the needle valve is not opened in the injection process; if not equal to indicate t 1 And t 2 Misalignment in time domain, needle valve opened during injectionAnd (5) starting.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210380960.XA CN114810448B (en) | 2022-04-12 | 2022-04-12 | Method for online analysis of fuel gas injection process time of direct injection engine in high-pressure natural cylinder based on wavelet transformation |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210380960.XA CN114810448B (en) | 2022-04-12 | 2022-04-12 | Method for online analysis of fuel gas injection process time of direct injection engine in high-pressure natural cylinder based on wavelet transformation |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN114810448A CN114810448A (en) | 2022-07-29 |
| CN114810448B true CN114810448B (en) | 2023-06-13 |
Family
ID=82533994
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210380960.XA Active CN114810448B (en) | 2022-04-12 | 2022-04-12 | Method for online analysis of fuel gas injection process time of direct injection engine in high-pressure natural cylinder based on wavelet transformation |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114810448B (en) |
Family Cites Families (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US9435310B2 (en) * | 2013-03-07 | 2016-09-06 | Cummins Inc. | Hydraulic start-of-injection detecting system and method |
| CN110500217B (en) * | 2019-07-23 | 2021-07-27 | 南京航空航天大学 | Diesel engine common rail system oil pump fault detection method based on measurable data characteristics |
| CN111520267A (en) * | 2019-12-30 | 2020-08-11 | 哈尔滨工程大学 | Common rail fuel injector fault diagnosis method based on FOA-VMD and HDE |
| CN112761843A (en) * | 2021-02-18 | 2021-05-07 | 哈尔滨工程大学 | Common rail oil injector fault diagnosis method |
-
2022
- 2022-04-12 CN CN202210380960.XA patent/CN114810448B/en active Active
Also Published As
| Publication number | Publication date |
|---|---|
| CN114810448A (en) | 2022-07-29 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN105003372B (en) | A kind of distributive value method for diagnosing faults based on the observation of rail pressure waveform feature parameter | |
| Bodisco et al. | Inter-cycle variability of in-cylinder pressure parameters in an ethanol fumigated common rail diesel engine | |
| CN104919298B (en) | Explosive motor based on exhaust manifold pressure misfires detection | |
| CN105003373B (en) | A kind of injection timing method for diagnosing faults based on the observation of rail pressure waveform feature parameter | |
| Shen et al. | Gaussian mixture model clustering-based knock threshold learning in automotive engines | |
| CN109187038B (en) | A method of emulation obtains boat diesel engine fault data | |
| Tamura et al. | Misfire detection on internal combustion engines using exhaust gas temperature with low sampling rate | |
| Hellring et al. | Spark advance control using the ion current and neural soft sensors | |
| Gu et al. | Misfire fault diagnosis method for diesel engine based on MEMD and dispersion entropy | |
| CN114810448B (en) | Method for online analysis of fuel gas injection process time of direct injection engine in high-pressure natural cylinder based on wavelet transformation | |
| Ofner et al. | Knock detection in combustion engine time series using a theory-guided 1-D convolutional neural network approach | |
| CN110259616B (en) | Diesel engine common rail system fuel injector fault detection method based on measurable data characteristics | |
| Ke et al. | Multiscale bidirectional diversity entropy for diesel injector fault-type diagnosis and fault degree diagnosis | |
| Wang et al. | Misfire and knock detection based on the ion current inside a passive pre-chamber of gasoline engine | |
| CN102644514B (en) | Diagnosis method for drift failure of rail pressure sensor in common rail system | |
| Wang et al. | Effect of port gas injection on the combustion instabilities in a spark-ignition lean-burn natural gas engine | |
| CN105606367A (en) | Misfire detection self-adaptive determination method and device under stable condition of engine | |
| CN113062811B (en) | Method for identifying key time characteristics of oil injection process according to frequency spectrum characteristics of pressure signal at inlet of oil injector | |
| Singh et al. | An Evaluation of Knock Determination Techniques for Diesel-Natural Gas Dual Fuel Engines | |
| CN114722334B (en) | STFT-based online identification method for gas injection time characteristics of high-pressure natural gas direct injection engine | |
| CN106884729B (en) | The method of detonation signal detection based on the separation of compression pressure change rate | |
| He et al. | Multi-scale dynamics for a lean-burn spark ignition natural gas engine under low load conditions | |
| Hosseini et al. | Knock probability determination employing convolutional neural network and IGTD algorithm | |
| Yang et al. | Nonlinear dynamics of cycle-to-cycle variations in a lean-burn natural gas engine with a non-uniform pre-mixture | |
| Wei et al. | Study on Online Identification Method of Injection Time Characteristics for the High Pressure Diesel-Natural Gas Co-direct Injection Engine |
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 |