CN115112772A - Urea-SCR system Urea crystallization diagnosis method based on vibration signal attenuation pattern recognition - Google Patents
Urea-SCR system Urea crystallization diagnosis method based on vibration signal attenuation pattern recognition Download PDFInfo
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- 238000002425 crystallisation Methods 0.000 title claims abstract description 141
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- XSQUKJJJFZCRTK-UHFFFAOYSA-N Urea Chemical compound NC(N)=O XSQUKJJJFZCRTK-UHFFFAOYSA-N 0.000 title claims abstract description 84
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Abstract
The invention belongs to the technical field of motor vehicle emission control, and particularly relates to a Urea crystallization diagnosis method of a Urea-SCR system based on vibration signal attenuation mode identification. According to the method, the target crystallization site is determined, and the positions of the signal generator and the signal collector are reasonably arranged, so that the influence of urea crystallization on the vibration response characteristic of the system can be fully reflected. The target crystallization site and the crystallization risk limit value are obtained based on a real urea crystallization test of a target engine-aftertreatment system, and have good crystallization risk correlation. The target crystallization site and the crystallization risk limit value obtained based on the test can be used for all vehicle types equipped with the urea injection-mixing system, and the method has good universality.
Description
Technical Field
The invention belongs to the technical field of motor vehicle emission control, and particularly relates to a Urea crystallization diagnosis method of a Urea-SCR system based on vibration signal attenuation mode identification.
Background
The exhaust gas of the engine contains harmful substances (NOx for short) such as nitrogen oxides, and the main components of the harmful substances are NO and NO 2 . NOx is N in the air drawn into the cylinder by the engine 2 And O 2 Reaction products at elevated temperatures. Engine emission regulations limit the amount of NOx emissions and specify limits of varying degrees.
Urea selective catalytic reduction technology (Urea-SCR technology for short) for controlling NO by engine x The main technologies for emissions, the most common forms of which are: the urea aqueous solution is used for decomposing to generate ammonia gas, and the ammonia gas and NO are generated under the action of an SCR (selective catalytic reduction) catalyst x The selective catalytic reduction reaction is carried out to generate nitrogen and water which are then discharged into the atmosphere, and different urea amounts are sprayed into the exhaust gas of the diesel engine to carry out NO treatment x The discharge amount of the fuel is effectively controlled.
Fig. 1 is a schematic structural diagram of a conventional Urea-SCR system, Urea crystals (also called Urea deposits) are a common problem in the practical application process of the Urea-SCR system, and accumulation of the Urea crystals can cause exhaust back pressure to rise, so that the working efficiency of a catalyst is reduced, the economical efficiency and the emission characteristic of an engine are poor, and in severe cases, an exhaust pipe can even be blocked, so that the engine cannot normally work.
No corresponding sensor or detection device on the current vehicle can detect the occurrence of urea crystallization, the problem of urea crystallization is usually discovered only after the urea crystallization degree seriously affects the dynamic property or emission property of the vehicle, and the engine runs for a long time under the condition of poor economy and emission property.
Disclosure of Invention
In order to solve the problems, after urea crystallization occurs in the post-treatment system, the urea crystallization is identified and quantitative evaluation indexes are given by comparing the vibration signal attenuation modes in the normal state of the system, so that accurate diagnosis of the urea crystallization risk is realized. Therefore, a Urea crystallization diagnosis method of the Urea-SCR system based on vibration signal attenuation pattern recognition is provided. The technical scheme of the diagnosis method comprises the following steps
Step (1) will identify the crystalline high incidence region of the targeted SCR system. Specifically, a urea crystallization risk test of a rack is carried out on a target engine-post-treatment system, a urea crystallization generation condition is artificially manufactured to confirm a crystallization high-incidence area of the target post-treatment system, and the crystallization high-incidence area is defined as a target crystallization site (generally located at the boundary of a mixer, and an included angle area between the wall surface of an exhaust pipe and the mixer);
step (2) sending out vibration excitation for diagnosis purpose through a specific device. The device is called a signal generator in the embodiment of the invention, can knock the pipe wall or the metal surface of the mixer according to a certain frequency to force the pipe wall or the metal surface of the mixer to generate regular and controllable forced vibration, and the knocking frequency is generated according to the diagnosis requirement and can be flexibly set according to the hardware characteristic of a system and different diagnosis and test requirements. The tapping portion of the signal generator requires continuous physical contact with the target crystallization site to facilitate continuous propagation of the vibrations in the same solid medium. Preferably, it is arranged at the wall of the exhaust duct closest to the target crystallization site.
And (3) acquiring the signal characteristics of the vibration excitation passing through the target crystallization area through a signal collector. The signal collector needs to be arranged on an extension line of the signal generator and the target crystallization site to collect the direct attenuation characteristic of the vibration excitation signal after passing through the target crystallization site.
And (4) acquiring the vibration signal attenuation characteristics of the system without urea crystallization under different temperature conditions under the state without urea injection. When no urea crystal exists, the vibration generated by the signal generator is mainly transmitted in the sheet metal structure, the vibration excitation response characteristic at the signal collector is mainly determined by the physical properties of the material such as thickness, rigidity and temperature and the like in the transmission path region from the signal generator to the signal collector and the contact relation such as welding, constraint and the like, for the similar post-processing systems, the material thickness and rigidity parameters are basically consistent with the contact relation such as welding, constraint and the like, so the temperature is the main actual variable influencing the signal transmission characteristic, and the vibration signal attenuation characteristic of the system without the urea crystal under different temperature conditions needs to be acquired as the basic reference characteristic data of crystal judgment.
And (5) artificially manufacturing urea crystals by excessively spraying urea, and acquiring vibration signal attenuation characteristics of the system when urea crystals with different degrees exist under different temperature conditions. The urea crystallization process of the SCR system occurs in a non-high pressure condition, so that the formed deposit crystal is disordered and loose in structure, and when the urea crystal is vibrated, the urea crystal is easy to deform, even collapse and break so as to absorb part of vibration energy, therefore, when the urea crystal exists on the surface of a target crystallization site, because some parts in the transmission path region from the signal generator to the signal collector are covered by the urea crystal, the attenuation degree of the vibration signal generated by forced generation is increased compared with the non-urea crystal covering state, and the signal attenuation mode is obviously changed. Since the newly generated crystal density does not generally vary significantly within a single driving cycle, the attenuation of the vibration signal is determined primarily by the quality of the crystal in the vibration transmission path. Meanwhile, the temperature also affects the signal transmission characteristics in this state, so that the vibration signal attenuation characteristics under different temperature conditions and different crystallization degrees need to be collected as the reference for crystallization degree judgment.
And (6) taking the amplitude change characteristic and 10% amplitude arrival time as main diagnostic basis. And analyzing the acquired signals by the signal acquisition device, and identifying the current vibration signal attenuation mode. Since the single-vibration signal attenuation is not obvious, the single-vibration signal attenuation result is influenced by the deviation of production consistency and the structural, size or shape change caused in the using process, and therefore, the specific diagnosis conclusion is not confirmed only by the single-vibration signal attenuation degree. When the vibration excitation of the signal generator is stopped, the vibration will repeatedly 'ring' in the transmission path, and will be weakened each time, and when some part in the transmission path area is covered by urea crystal, the damping effect of urea will be acted at each 'ring', resulting in the total time and the 'ring' times for the vibration amplitude at the signal collector to be reduced to 10% of the excitation amplitude. Whether the target crystallization site is in a crystalline state or not can be screened more precisely based on the 10% amplitude arrival time.
Step (7) parameterization setting of the diagnosis model,
the initial SCR upstream temperature (T) was recorded 30s after engine shut down with urea injection shut down to ensure no urea crystallization in the system SCR ) And ambient temperature (T) Env ) Setting different frequencies (f) for the signal generator Tx ) Sum amplitude (A) Tx ) The excitation signal can be triggered to obtain the main frequency (f) of the response through the No. 1 signal collector Rx_Norm ) Sum amplitude (A) Rx_Norm ) The characteristic value, and the duration (T) of the vibration amplitude reduced to 10% of the excitation amplitude is recorded Norm )，
Inputting: [ T ] sCR ，f Tx ，A Tx ]
An intermediate layer: implicit to
And (3) outputting: [ f ] of Rx_Norm ，A Rx_Norm ，T Norm ]
Establishing a mapping relation from an input matrix to an output matrix in a normal state, and carrying out test on different T values through acquired test data SCR ，f Tx ，A Tx Training the neural network under the input condition to stably calculate and test the output f Rx_Norm ，A Rx_Norm ，T Norm Consistent results.
Artificially obtaining urea crystals with different degrees (slight: C; more: B; serious: A) at target crystallization sites by increasing the injection quantity, and calculating f by training a mature neural network model Rx_Norm ，A Rx_Norm ，T Norm The signal of No. 1 signal collector department under the different degree urea crystallization state is measured respectively through the experiment to the serious degree crystallization is for example, and corresponding signal is: main frequency of response (f) Rx_Dep_A ) Sum amplitude (A) Rx_Dep_A ) The characteristic value, and the duration (T) of the vibration amplitude reduced to 10% of the excitation amplitude is recorded Dep_A )。
Respectively comparing:
[f Rx_Norm ，A Rx_Norm ，T Norm ]and [ f Rx_Dep_A ，A Rx_Dep_A ，T Dep_A ]
[f Rx_Norm ，A Rx_Norm ，T Norm ]And [ f Rx_Dep_B ，A Rx_Dep_B ，T Dep_B ]
[f Rx_Norm ，A Rx_Norm ，T Norm ]And [ f Rx_Dep_C ，A Rx_Dep_C ，T Dep_C ]
Obtaining a corresponding crystallization degree judgment coefficient matrix
[f A ，A A ，T A ]，[f B ，A B ，T B ]，[f C ，A C ，T C ]
Determining the crystallization diagnostic function f (f, A, T), and obtaining f (f) respectively A ，A A ，T A ) Corresponding high crystallization risk limit C A ，f(f B ，A B ，T B ) Corresponding moderate crystallization risk limit C B And f (f) c ，A C ，T C ) Corresponding Low crystallization Risk Limit C C In which C is A ＜C B ＜C C 。
And (8) obtaining the actual response main frequency and amplitude (and the duration of reducing the vibration amplitude to 10% of the excitation amplitude) through the signal collector, calculating a corresponding crystallization risk coefficient by using a crystallization diagnosis function, and comparing the crystallization risk coefficient with each risk limit value obtained in the step (7) to obtain a crystallization risk conclusion.
Actual response dominant frequency (f) obtained by signal collector in on-line diagnosis process Rx_Online ) Sum amplitude (A) Rx_Online ) And duration (T) of vibration amplitude reduction to 10% of excitation amplitude Online ) And calculating the corresponding crystallization risk coefficient C by using the crystallization diagnosis function f (f, A, T) Online 。
The crystallization risk factor and C A 、C B 、C C Respectively compare if C Online ＜C A Then the system is considered to have a serious crystallization risk; if C is present A ＜C Online ＜C B Then the system is considered to have a moderate risk of crystallization; if C is present B ＜C Online ＜C C Then the system is considered to have low crystallization risk; if C is present C ＜C Online The system is considered to be free of crystallization risk.
The invention provides a method for identifying Urea crystallization state of a Urea-SCR system based on contact type vibration signals. Based on the vibration excitation response test result carried out under the condition of urea crystallization or no urea crystallization, the deeply trained neural network model can obtain the vibration signal attenuation modes of the exhaust aftertreatment system under the normal state, the low crystallization risk state, the medium crystallization risk state and the serious crystallization risk state according to the signal generation characteristics under the current pre-and post-treatment temperature states. The crystallization risk grade corresponding to the vibration signal attenuation mode in the current state can be obtained by acquiring the amplitude change characteristic and the 10% amplitude arrival time on line and comparing the modes, and the fault diagnosis result is stored in the nonvolatile memory, so that a vehicle user can know the Urea crystallization state of the current post-processing system before the next driving starts, the vehicle user can actively adopt corresponding driving means to eliminate Urea crystallization conveniently, and the normal service capacity of the Urea-SCR system is improved.
The target crystallization site and the crystallization risk limit value are obtained based on a real urea crystallization test of a target engine-aftertreatment system, and have good crystallization risk correlation. The target crystallization site and the crystallization risk limit value obtained based on the test can be used for all vehicle types equipped with the urea injection-mixing system, and the method has good universality.
Drawings
FIG. 1 is a schematic structural diagram of a prior Urea-SCR system;
FIG. 2 is a schematic diagram of the configuration of a vibration signal attenuation pattern recognition system;
FIG. 3 is a flow chart of a method for implementing urea crystallization diagnosis based on a vibration signal attenuation pattern;
FIG. 4 is a schematic diagram of identifying urea crystals based on vibration signal attenuation characteristics;
FIG. 5 is a diagram of a vibration responsive neural network model.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The vibration signal attenuation pattern recognition system designed in this embodiment is configured as shown in fig. 2, and the flow chart of the specific diagnosis method is shown in fig. 3:
step (1) will identify the crystalline high incidence zone of the targeted SCR system. Specifically, a urea crystallization risk test of a rack is carried out on a target engine-post-treatment system, a urea crystallization generation condition is artificially manufactured to confirm a crystallization high-incidence area of the target post-treatment system, and the crystallization high-incidence area is defined as a target crystallization site (generally located at the boundary of a mixer, and an included angle area between the wall surface of an exhaust pipe and the mixer);
step (2) sending out vibration excitation for diagnosis purpose through a specific device. The device is called a signal generator in the embodiment of the invention, can knock the pipe wall or the metal surface of the mixer according to a certain frequency to force the pipe wall or the metal surface of the mixer to generate regular and controllable forced vibration, and the knocking frequency is generated according to the diagnosis requirement and can be flexibly set according to the hardware characteristic of a system and different diagnosis and test requirements. The tapping portion of the signal generator requires continuous physical contact with the target crystallization site to facilitate continuous propagation of the vibrations in the same solid medium. Preferably, it is arranged at the wall of the exhaust duct closest to the target crystallization site.
And (3) acquiring the characteristics of the signal after the vibration excitation passes through the target crystallization area through a signal collector. The signal collector needs to be arranged on an extension line of the signal generator and the target crystallization site to collect the direct attenuation characteristic of the vibration excitation signal after passing through the target crystallization site.
And (4) acquiring the vibration signal attenuation characteristics of the system without urea crystals under different temperature conditions in the state without spraying urea. When no urea crystal exists, the vibration generated by the signal generator is mainly transmitted in the sheet metal structure, the vibration excitation response characteristic at the signal collector is mainly determined by the physical properties of the material such as thickness, rigidity and temperature and the like in the transmission path region from the signal generator to the signal collector and the contact relation such as welding, constraint and the like, for the similar post-processing systems, the material thickness and rigidity parameters are basically consistent with the contact relation such as welding, constraint and the like, so the temperature is the main actual variable influencing the signal transmission characteristic, and the vibration signal attenuation characteristic of the system without the urea crystal under different temperature conditions needs to be acquired as the basic reference characteristic data of crystal judgment.
And (5) artificially manufacturing urea crystals by excessively spraying urea, and acquiring vibration signal attenuation characteristics of the system when urea crystals with different degrees exist under different temperature conditions. The urea crystallization process of the SCR system occurs in a non-high pressure condition, so that the formed deposit crystal is disordered and loose in structure, and when the urea crystal is vibrated, the urea crystal is easy to deform, even collapse and break so as to absorb part of vibration energy, therefore, when the urea crystal exists on the surface of a target crystallization site, because some parts in the transmission path region from the signal generator to the signal collector are covered by the urea crystal, the attenuation degree of the vibration signal generated by forced generation is increased compared with the non-urea crystal covering state, and the signal attenuation mode is obviously changed. Since the newly generated crystal density does not generally vary significantly within a single driving cycle, the attenuation of the vibration signal is determined primarily by the quality of the crystal in the vibration transmission path. Meanwhile, the temperature also affects the signal transmission characteristics in this state, so that the vibration signal attenuation characteristics under different temperature conditions and different crystallization degrees need to be collected as the reference for crystallization degree judgment.
And (6) taking the amplitude change characteristic and the 10% amplitude arrival time as main diagnostic bases. And analyzing the acquired signals by the signal acquisition device, and identifying the current vibration signal attenuation mode. Since the attenuation of the single vibration signal is not obvious, the deviation of production consistency and the change of structure, size or shape caused in the using process can influence the attenuation result of the single vibration signal, and therefore, the specific diagnosis conclusion is not only confirmed by the attenuation degree of the single vibration signal. When the vibration excitation of the signal generator is stopped, the vibration will repeatedly 'ring' in the transmission path, and will be weakened each time, and when some part in the transmission path area is covered by urea crystal, the damping effect of urea will be acted at each 'ring', resulting in the total time and the 'ring' times for the vibration amplitude at the signal collector to be reduced to 10% of the excitation amplitude. Whether the target crystallization site is in a crystalline state or not can be screened more precisely based on the 10% amplitude arrival time.
Step (7) parameterization setting of the diagnosis model,
the initial SCR upstream temperature (T) was recorded 30s after engine shut down with urea injection shut down to ensure no urea crystallization in the system SCR ) And ambient temperature (T) Env ) Setting different frequencies (f) for the signal generator Tx ) Sum amplitude (A) Tx ) The excitation signal can be triggered to obtain the main frequency (f) of the response through the No. 1 signal collector Rx_Norm ) Sum amplitude (A) Rx_Norm ) The characteristic value, and the duration (T) of the vibration amplitude reduced to 10% of the excitation amplitude is recorded Norm )，
Inputting: [ T ] sCR ，f Tx ，A Tx ]
An intermediate layer: implicit to
And (3) outputting: [ f ] Rx_Norm ，A Rx_Norm ，T Norm ]
Establishing a mapping relation from an input matrix to an output matrix in a normal state, and carrying out test on different T values through acquired test data SCR ，f Tx ，A Tx Training the neural network under the input condition to stably calculate and obtain the output f of the test Rx_Norm ，A Rx_Norm ，T Norm Consistent results.
Artificially obtaining urea crystals with different degrees (slight: C; more: B; serious: A) at target crystallization sites by increasing the injection quantity, and calculating f by training a mature neural network model Rx_Norm ，A Rx_Norm ，T Norm The signal of No. 1 signal collector department under the different degree urea crystallization state is measured respectively through the experiment, and to regard the degree of severity crystallization as an example, the corresponding signal is: response main frequency (f) Rx_Dep_A ) Sum amplitude (A) Rx_Dep_A ) The characteristic value, and the duration (T) of the vibration amplitude reduced to 10% of the excitation amplitude is recorded Dep_A ). The structural diagram of the vibration-related neural network model is shown in fig. 5:
and (3) respectively comparing:
[f Rx_Norm ，A Rx_Norm ，T Norm ]and [ f Rx_Dep_A ，A Rx_Dep_A ，T Dep_A ]
[f Rx_Norm ，A Rx_Norm ，T Norm ]And [ f Rx_Dep_B ，A Rx_Dep_B ，T Dep_B ]
[f Rx_Norm ，A Rx_Norm ，T Norm ]And [ f Rx_Dep_C ，A Rx_Dep_C ，T Dep_C ]
Obtaining a corresponding crystallization degree judgment coefficient matrix
[f A ，A A ，T A ]，[f B ，A B ，T B ]，[f C ，A C ，T C ]
Determining the crystallization diagnostic function f (f, A, T), and obtaining f (f) respectively A ，A A ，T A ) Corresponding high crystallization risk limit C A ，f(f B ，A B ，T B ) Corresponding moderate crystallization risk limit C B And f (f) C ，A C ，T C ) Corresponding Low crystallization Risk Limit C C In which C is A ＜C B ＜C C 。
And (8) obtaining the actual response main frequency and amplitude (and the duration of reducing the vibration amplitude to 10% of the excitation amplitude) through the signal collector, calculating a corresponding crystallization risk coefficient by using a crystallization diagnosis function, and comparing the crystallization risk coefficient with each risk limit value obtained in the step (7) to obtain a crystallization risk conclusion.
Actual response dominant frequency (f) obtained by signal collector in on-line diagnosis process Rx_Online ) Sum amplitude (A) Rx_Online ) And duration (T) of vibration amplitude reduction to 10% of excitation amplitude Online ) And calculating the corresponding crystallization risk coefficient C by using the crystallization diagnosis function f (f, A, T) Online . A schematic diagram for identifying urea crystals based on vibration signal attenuation characteristics is shown in fig. 4.
The crystallization risk factor and C A 、C B 、C C Respectively compare if C Online ＜C A Then the system is considered to have a serious crystallization risk; if C is present A ＜C Online ＜C B Then the system is considered to have a moderate risk of crystallization; if C is present B ＜C Online ＜C C Then the system is considered to have low crystallization risk; if C is C ＜C Online The system is considered to be free of crystallization risk.
Although the preferred embodiments of the present patent have been described in detail, the present patent is not limited to the above embodiments, and various changes can be made without departing from the spirit of the present patent within the knowledge of those skilled in the art.
Claims (7)
1. A Urea crystallization diagnosis method of a Urea-SCR system based on vibration signal attenuation pattern recognition is characterized by comprising the following steps: the method comprises the following steps:
step (1) confirming a crystallization high-incidence area of a target SCR system;
step (2) sending out vibration excitation for diagnosis purpose through a signal generating device;
step (3) acquiring signal characteristics of the vibration excitation passing through a target crystallization area through a signal collector;
step (4) collecting vibration signal attenuation characteristics of a system without urea crystallization under different temperature conditions under the state without urea injection;
artificially manufacturing urea crystals by excessively spraying urea, and acquiring vibration signal attenuation characteristics of the system in the presence of urea crystals of different degrees under different temperature conditions;
step (6) using the amplitude change characteristic and 10% amplitude arrival time as main diagnosis basis, analyzing the acquired signals by the signal acquisition device, and identifying the current vibration signal attenuation mode;
step (7) carrying out parametric setting on the diagnosis model to obtain a high crystallization risk limit value, a medium crystallization risk limit value and a low crystallization risk limit value;
and (8) online diagnosis and judgment, namely obtaining the actual response main frequency and amplitude (and the duration of reducing the vibration amplitude to 10% of the excitation amplitude) through the signal collector, calculating a corresponding crystallization risk coefficient by using a crystallization diagnosis function, and comparing the crystallization risk coefficient with each risk limit value obtained in the step (7) to obtain a crystallization risk conclusion.
2. The diagnostic method of claim 1, wherein: the step (1) is specifically as follows: the urea crystallization risk test of the bench is carried out on the target engine-post treatment system, and the high crystallization area of the target post treatment system is confirmed by artificially manufacturing urea crystallization generation conditions and is defined as a target crystallization site.
3. The diagnostic method of claim 1, wherein: the signal generating device in the step (2) knocks the pipe wall or the metal surface of the mixer according to a certain frequency to force the pipe wall or the metal surface of the mixer to generate regular and controllable forced vibration; the knocking frequency is generated according to the diagnosis requirement and can be flexibly set according to the hardware characteristic of the system and different diagnosis and test requirements; the tapping portion of the signal generating device requires continuous physical contact with the target crystallization site to facilitate continuous propagation of the vibrations in the same solid medium.
4. The diagnostic method of claim 3, wherein: the knocking part of the signal generating device is arranged on the wall of the exhaust pipe closest to the target crystallization site.
5. The diagnostic method of claim 1, wherein: the signal collector needs to be arranged on an extension line of the signal generator and the target crystallization site to collect the direct attenuation characteristic of the vibration excitation signal after passing through the target crystallization site.
6. The diagnostic method of claim 1, wherein: the step (7) is specifically as follows:
(71) the initial SCR upstream temperature (T) was recorded 30s after engine shut down with urea injection shut down to ensure no urea crystallization in the system SCR ) And ambient temperature (T) Env ) Setting different frequencies (f) for the signal generator Tx ) Sum amplitude (A) Tx ) The excitation signal can be triggered to obtain the main frequency (f) of the response through the No. 1 signal collector Rx_Norm ) Sum amplitude (A) Rx_Norm ) The characteristic value, and the duration (T) of the vibration amplitude reduced to 10% of the excitation amplitude is recorded Norm ) Inputting: [ T ] SCR ，f Tx ，A Tx ]And an intermediate layer: implicit, output: [ f ] of Rx_Norm ，A Rx_Norm ，T Norm ]；
(72) Establishing a mapping relation from an input matrix to an output matrix in a normal state, and carrying out test on different T values through acquired test data SCR ，f Tx ，A Tx Training the neural network under the input condition to stably calculate and test the output f Rx_Norm ，A Rx_Norm ，T Norm Consistent results;
(73) artificially obtaining urea crystals with different degrees at target crystallization sites by increasing injection quantity, and calculating f by training a mature neural network model Rx_Norm ，A Rx_Norm ，T Norm The signal of No. 1 signal collector department under the different degree urea crystallization state is measured respectively through the experiment to the serious degree crystallization is for example, and corresponding signal is: sound boxDominant frequency (f) Rx_Dep_A ) Sum amplitude (A) Rx_Dep_A ) The characteristic value, and the duration (T) of the vibration amplitude reduced to 10% of the excitation amplitude is recorded Dep_A )；
(74) And (3) respectively comparing:
[f Rx_Norm ，A Rx_Norm ，T Norm ]and [ f Rx_Dep_A ，A Rx_Dep_A ，T Dep_A ]
[f Rx_Norm ，A Rx_Norm ，T Norm ]And [ f Rx_Dep_B ，A Rx_Dep_B ，T Dep_B ]
[f Rx_Norm ，A Rx_Norm ，T Norm ]And [ f Rx_Dep_C ，A Rx_Dep_C ，T Dep_C ]
Obtaining a corresponding crystallization degree judgment coefficient matrix
[f A ，A A ，T A ]，[f B ，A B ，T B ]，[f C ，A C ，T C ]；
(75) Determining the crystallization diagnostic function f (f, A, T), and obtaining f (f) respectively A ，A A ，T A ) Corresponding high crystallization risk limit C A ，f(f B ，A B ，T B ) Corresponding moderate crystallization risk limit C B And f (f) C ，A C ，T C ) Corresponding Low crystallization Risk Limit C C In which C is A ＜C B ＜C C 。
7. The diagnostic method of claim 6, wherein: the step (8) is specifically as follows: actual response dominant frequency (f) obtained by signal collector in on-line diagnosis process Rx_Online ) Sum amplitude (A) Rx_Online ) And duration (T) of vibration amplitude reduction to 10% of excitation amplitude Online ) And calculating the corresponding crystallization risk coefficient C by using the crystallization diagnosis function f (f, A, T) Online (ii) a The crystallization risk factor and C A 、C B 、C C Respectively compare if C Online ＜C A Then the system is considered to be severeThe risk of crystallization; if C is present A ＜C Online ＜C B Then the system is considered to have a moderate risk of crystallization; if C is present B ＜C Online ＜C C If so, the system is considered to have low crystallization risk; if C is present C ＜C Online The system is considered to be free of crystallization risk.
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Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CA649225A (en) * | 1962-09-25 | H. Cook Lucien | Urea crystallization | |
| WO2014146552A1 (en) * | 2013-03-19 | 2014-09-25 | 北京银河之舟环保科技有限公司 | Doppler ultrasonic pickup analyzing and processing method and device |
| CN104956217A (en) * | 2012-12-14 | 2015-09-30 | 大陆汽车有限责任公司 | Method for measuring ultrasonically the fill level of a liquid |
| CN109411027A (en) * | 2018-12-19 | 2019-03-01 | 东风商用车有限公司 | Urea-SCR control parameter offline calibration system and calibration method |
| CN109538943A (en) * | 2018-12-18 | 2019-03-29 | 天津科技大学 | Pipeline scale detection and recognition methods based on supersonic guide-wave |
| CA3139576A1 (en) * | 2018-03-29 | 2019-10-03 | Emissol Llc | Methods and devices for controlling urea mixers to reduce nox emission from combustion engines |
| CN111794837A (en) * | 2020-07-06 | 2020-10-20 | 无锡沃尔福汽车技术有限公司 | Urea injection control system and method |
| CN112879136A (en) * | 2021-01-28 | 2021-06-01 | 天津市津聿动力科技有限公司 | Method and device for evaluating urea crystallization risk based on transient working condition |
| CN113250800A (en) * | 2021-07-06 | 2021-08-13 | 南昌碳印环保科技有限公司 | Active control method for Urea crystallization risk of Urea-SCR system |
| CN113356988A (en) * | 2021-07-06 | 2021-09-07 | 南昌碳印环保科技有限公司 | Online diagnosis method for Urea crystallization risk of Urea-SCR system |
| CN113358363A (en) * | 2021-07-06 | 2021-09-07 | 南昌碳印环保科技有限公司 | Method for identifying Urea crystallization critical state of Urea-SCR system |
| CN113866263A (en) * | 2021-09-26 | 2021-12-31 | 哈勃智能传感(深圳)有限公司 | Urea solution concentration measuring method based on ultrasonic measuring device |
-
2022
- 2022-07-13 CN CN202210828721.6A patent/CN115112772A/en active Pending
Patent Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CA649225A (en) * | 1962-09-25 | H. Cook Lucien | Urea crystallization | |
| CN104956217A (en) * | 2012-12-14 | 2015-09-30 | 大陆汽车有限责任公司 | Method for measuring ultrasonically the fill level of a liquid |
| WO2014146552A1 (en) * | 2013-03-19 | 2014-09-25 | 北京银河之舟环保科技有限公司 | Doppler ultrasonic pickup analyzing and processing method and device |
| CA3139576A1 (en) * | 2018-03-29 | 2019-10-03 | Emissol Llc | Methods and devices for controlling urea mixers to reduce nox emission from combustion engines |
| CN109538943A (en) * | 2018-12-18 | 2019-03-29 | 天津科技大学 | Pipeline scale detection and recognition methods based on supersonic guide-wave |
| CN109411027A (en) * | 2018-12-19 | 2019-03-01 | 东风商用车有限公司 | Urea-SCR control parameter offline calibration system and calibration method |
| CN111794837A (en) * | 2020-07-06 | 2020-10-20 | 无锡沃尔福汽车技术有限公司 | Urea injection control system and method |
| CN112879136A (en) * | 2021-01-28 | 2021-06-01 | 天津市津聿动力科技有限公司 | Method and device for evaluating urea crystallization risk based on transient working condition |
| CN113250800A (en) * | 2021-07-06 | 2021-08-13 | 南昌碳印环保科技有限公司 | Active control method for Urea crystallization risk of Urea-SCR system |
| CN113356988A (en) * | 2021-07-06 | 2021-09-07 | 南昌碳印环保科技有限公司 | Online diagnosis method for Urea crystallization risk of Urea-SCR system |
| CN113358363A (en) * | 2021-07-06 | 2021-09-07 | 南昌碳印环保科技有限公司 | Method for identifying Urea crystallization critical state of Urea-SCR system |
| CN113866263A (en) * | 2021-09-26 | 2021-12-31 | 哈勃智能传感(深圳)有限公司 | Urea solution concentration measuring method based on ultrasonic measuring device |
Non-Patent Citations (3)
| Title |
|---|
| PÄR L.T. GABRIELSSON: "Urea-SCR in Automotive Applications", 《TOPICS IN CATALYSIS>, vol. 28, no. 1, 30 April 2004 (2004-04-30), pages 177 - 184, XP019292050 * |
| 钟秋月: "柴油机SCR系统尿素结晶试验研究", 《测试与试验》, no. 22, 30 November 2018 (2018-11-30), pages 119 - 121 * |
| 陈雷: "满足过IV排放的柴油机后处理控制器的仿真与试验研究", 《中国优秀硕士学位论文全文数据库 工程科技II辑》, no. 4, 15 April 2013 (2013-04-15), pages 035 - 129 * |
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