CN111444574A - Sensor layout optimization method based on dynamic analysis - Google Patents
Sensor layout optimization method based on dynamic analysis Download PDFInfo
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- CN111444574A CN111444574A CN202010216825.2A CN202010216825A CN111444574A CN 111444574 A CN111444574 A CN 111444574A CN 202010216825 A CN202010216825 A CN 202010216825A CN 111444574 A CN111444574 A CN 111444574A
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Abstract
The invention discloses a sensor layout optimization method based on dynamic analysis. The invention establishes a train dynamic model aiming at a target train, establishes a virtual sensor in the train dynamic model and sets an operation condition, and the sensor layout optimization method of the wheel-rail dynamic monitoring system analyzes the corresponding states of different measuring points of the train under the condition of abnormal wheel-rail states by a dynamic simulation analysis method, compares the sensitivities of virtual sensor signals to the abnormal wheel-rail states and further selects an optimal layout scheme of the sensors. The method has the main advantages of low cost, high timeliness, multiple considered working conditions and easiness in application.
Description
Technical Field
The invention relates to a railway transportation safety monitoring technology, in particular to a sensor layout optimization method based on dynamic analysis.
Background
The dynamic state of the wheel track in the running process of the train directly determines the running safety and the quality of the train. In order to ensure the running safety of trains, more and more rail trains are provided with running gear health monitoring systems, and faults of wheel sets and steel rails are diagnosed in time by processing train responses in the running process of the trains. The layout scheme of the sensors is one of important factors for determining the performance of the running gear health monitoring system. In actual operation, train vibration is complex, the most effective installation position and monitoring direction are selected from massive train component vibration information, and the analysis efficiency can be improved while the system performance is improved.
Therefore, establishing an effective sensor layout optimization method becomes an urgent need in the design process of the health monitoring system of the walking part.
Disclosure of Invention
The present invention provides a sensor layout optimization method based on kinetic analysis that solves the above mentioned problems.
The invention is realized by the following technical scheme:
a sensor layout optimization method based on dynamic analysis comprises the following steps:
step 1: in the step, firstly, parameters of a researched object vehicle are determined, wherein the parameters comprise inertial parameters (mass, inertia and the like), suspension parameters (rigidity, damping and the like), geometric parameters (part spacing, appearance size and the like), wheel track parameters (tread model, steel rail type and the like). Then, the vehicle dynamics model can be established in two ways: the first way is to do the programmed calculation by building the equations of the vehicle dynamics:
m, C, K are respectively a vehicle system mass, damping and rigidity matrix, z is a vehicle displacement matrix, and f is wheel-rail excitation.
The second method is that the vehicle dynamics analysis software (e.g., SIMPACK, Gensys, Adams, etc.) which is already mature at present can be used;
reasonably setting operation conditions of simulation analysis according to specific operation characteristics of the researched vehicle, wherein the operation conditions comprise vehicle operation speed, line condition, rail irregularity grade, simulation time and the like;
setting fault wheel-rail fault working conditions such as tread scratch, wheel pair polygon, derailment and the like according to the specific running characteristics of the researched vehicle;
step 2: starting simulation, and acquiring signals acquired by a virtual sensor in the simulation process;
and step 3: according to the signals collected by the virtual sensors, positioning the time period when the wheel rail vibration is abnormal, and positioning the signals of each sensor;
and 4, step 4: determining evaluation indexes of the sensors according to signals of the sensors, calculating the abnormal time periods of the wheel rail vibration according to the evaluation indexes of the sensors, and performing sensitivity analysis on the arrangement schemes of the sensors by comparing the results of the evaluation indexes of the sensors in the abnormal time periods of the wheel rail vibration in the simulation process;
and 5: and generating optimized layout schemes of the sensors according to the sensitivity analysis results of the layout schemes of the sensors, and resetting the sensors according to the optimized layout schemes of the sensors.
Further, in step 1, a plurality of virtual sensors are arranged on the train body, the frame and the axial direction of the target train in the train dynamics model, a pair of axial sensors are arranged on each axle, an axle left side sensor a L1 and an axle right side sensor AR1 are respectively arranged on each frame, two pairs of frame sensors are arranged on each frame, a front bogie left side sensor B L1, a front bogie right side sensor BR1, a rear bogie left side sensor B L2 and a rear bogie right side sensor BR2 are respectively arranged on each train body, two pairs of train body sensors are arranged on each train body, a train body front right side sensor CR1, a train body front left side sensor C L1, a train body rear right side sensor CR2 and a train body rear side sensor C L2 are respectively arranged on each train body, information such as vibration acceleration, displacement, corner, spring force, wheel rail force and the like is obtained according to the vibration transmission relationship of the train system, and the sampling frequency, data acquisition time and the like of the virtual sensors can be set;
the virtual sensors are used for acquiring the vibration acceleration of the test point in the longitudinal direction, the transverse direction and the vertical direction in 3 directions and acquiring signals acquired by the vibration acceleration position sensors of the test point in the longitudinal direction, the transverse direction and the vertical direction in 3 directions.
And further, selecting sensor evaluation indexes, calculating the evaluation indexes of the vibration signals of the wheel rail in the abnormal time period, wherein the sensor evaluation indexes comprise time domain analysis indexes and frequency domain analysis indexes, the time domain analysis indexes comprise root mean square values and maximum values, the frequency domain analysis indexes comprise characteristic frequencies and amplitude values, and analyzing the arrangement scheme of each sensor to carry out sensitivity analysis by comparing the sensor evaluation indexes of the time period when the wheel rail is in the abnormal vibration state in the train simulation process.
Further, when the root mean square value is selected as the evaluation index of the sensor, the sensitivity of each sensor to faults is evaluated by adopting the root mean square value: and calculating to obtain the root mean square value of the acceleration collected by the axle box, the framework and the vehicle body virtual sensor, and comparing the root mean square calculated values of the axle box, the framework and the vehicle body virtual acceleration sensor to obtain the optimized layout scheme of each sensor.
Further, the train dynamics model is realized according to SIMPACK multi-body dynamics software, the train dynamics model is a composite model and comprises a rigid body model which reserves 6 degrees of freedom of key train components based on a vehicle dynamics theory, and the key train components comprise a train body, a framework, wheel pairs and axle boxes and further comprise a rigid-flexible coupling model which reserves the elasticity of a roadbed structure.
Further, according to the running condition of the target train, the signal collecting direction, the signal type and the sampling frequency of the virtual sensor are set in the train dynamics model.
Further, the operation condition setting comprises train traction state setting, vehicle operation speed setting, line setting and track irregularity grade setting in the train dynamics model according to the operation condition of the target train.
The monitoring system comprises a monitoring system applying the sensor layout optimization method based on the dynamic analysis, and adjusts the sensor layout scheme of the monitoring system according to each optimized sensor layout scheme and based on the robustness requirement of the sensor.
The invention has the following advantages and beneficial effects:
according to the sensor layout optimization method for the dynamic wheel track monitoring system, provided by the invention, the corresponding states of different measuring points of a train under the condition of the abnormal wheel track state are analyzed by a dynamic simulation analysis method, and the sensitivity of a virtual sensor signal to the abnormal wheel track state is compared, so that the optimal layout scheme of the sensors is selected. The method has the main advantages of low cost, high timeliness, multiple considered working conditions and easiness in application.
Drawings
The accompanying drawings, which are included to provide a further understanding of the embodiments of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the principles of the invention. In the drawings:
FIG. 1 is a logic flow diagram of the present invention.
Fig. 2 is a schematic diagram of a train dynamics model according to the present invention.
Fig. 3 is a schematic diagram of the track fault setup of the present invention.
FIG. 4 shows the vibration acceleration signals of the derailment process collected by the virtual sensor of the axle between 6.0s and 6.2s according to the simulation result of the invention.
FIG. 5 shows the vibration acceleration signals of the derailment process collected by the frame and the vehicle body virtual sensor in the range of 6.0 s-6.2 s according to the simulation result of the invention.
Fig. 6 is a root mean square calculated value evaluation index diagram of an axle box virtual acceleration sensor according to a simulation result of the present invention.
FIG. 7 is a root mean square calculated value evaluation index diagram of the virtual acceleration sensor constructed by the simulation result of the present invention.
FIG. 8 is a root mean square calculated value evaluation index diagram of the virtual acceleration sensor of the vehicle body according to the simulation result of the present invention.
Detailed Description
Before any embodiments of the invention are explained in detail, it is to be understood that the invention is not limited in its application to the details of construction and the arrangements of components set forth in the following description or illustrated in the drawings. The invention is capable of other embodiments and of being practiced or of being carried out in various ways. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any inventive changes, are within the scope of the present invention.
Example 1
A sensor layout optimization method based on kinetic analysis is shown in FIG. 1, and comprises the following steps:
Reasonably setting operation conditions of simulation analysis according to specific operation characteristics of the researched vehicle, wherein the operation conditions comprise vehicle operation speed, line condition, rail irregularity grade, simulation time and the like;
setting fault wheel-rail fault working conditions such as tread scratch, wheel pair polygon, derailment and the like according to the specific running characteristics of the researched vehicle;
according to design requirements, virtual sensors are respectively established on an axle box, a framework and a vehicle body, the naming rule of the sensors is that 1 letter represents a sensor installation part, wherein A is an axle box (Axlebox), B is a framework (Bogie), C is a vehicle body (Carbody), 2 letter represents the installation position of the sensor on the part, L is the left side (L eft) of the traveling direction of a train, R is the Right side (Right) of the traveling direction of the train, 3 rd digit represents the front and rear positions, as shown in FIG. 2, a plurality of virtual sensors are arranged on the vehicle body, the framework and the axial direction of a target train in a train dynamic model, a pair of axial sensors are arranged on each axle, an axle left side sensor A L and an axle Right side sensor AR1 are respectively arranged on each framework, two pairs of framework sensors are arranged on each framework, a front Bogie left side sensor B L, a front Bogie Right side sensor BR1, a rear Bogie left side sensor B L and a rear Bogie Right side sensor BR 4 are respectively arranged on each framework, two pairs of virtual sensors are arranged on each framework, a front Bogie left side sensor B735 and a rear Bogie left side sensor B732 and a rear Bogie left side sensor CR2 and a rear Bogie sensor are respectively arranged to acquire virtual sensor CR2 and a virtual sensor CR2 which can acquire the virtual sensor of the vibration frequency of the front wheel displacement sensor and the like according to the.
Setting the simulation analysis line condition, wherein the simulation line is a straight line working condition, setting the track gauge to be a standard track gauge mode (1.435m), setting the track irregularity grade to be an American grade 5 spectrum (AAR5), setting the train running speed to be 60km/h and setting the simulation time to be 30 s.
The method is characterized in that a wheel rail abnormal working condition, namely 'the train derails due to rail expansion', is arranged. The track expansion line is shown in fig. 3, wherein 200m before the line is a normal straight line, the track gauge is 1.435m, the track expansion section is 200 m-300 m (a is 100m), and the track expansion width is 1.635m (b is 1.635 m).
Step 2: starting simulation, after calculation is finished, obtaining vibration information collected by the virtual sensor in the whole simulation process: and each measuring point acquires vibration acceleration in 3 directions of longitudinal direction, transverse direction and vertical direction. Acquiring signals acquired by a virtual sensor in a simulation process;
and step 3: according to the signals collected by the virtual sensors, positioning the time period when the wheel rail vibration is abnormal, and positioning the signals of each sensor;
and 4, step 4: determining evaluation indexes of the sensors according to signals of the sensors, calculating the abnormal time periods of the wheel rail vibration according to the evaluation indexes of the sensors, and performing sensitivity analysis on the arrangement schemes of the sensors by comparing the results of the evaluation indexes of the sensors in the abnormal time periods of the wheel rail vibration in the simulation process;
and 5: and generating optimized layout schemes of the sensors according to the sensitivity analysis results of the layout schemes of the sensors, and resetting the sensors according to the optimized layout schemes of the sensors.
The virtual sensors are used for acquiring the vibration acceleration of the test point in the longitudinal direction, the transverse direction and the vertical direction in 3 directions and acquiring signals acquired by the vibration acceleration position sensors of the test point in the longitudinal direction, the transverse direction and the vertical direction in 3 directions.
And further, selecting sensor evaluation indexes, calculating the evaluation indexes of the vibration signals of the wheel rail in the abnormal time period, wherein the sensor evaluation indexes comprise time domain analysis indexes and frequency domain analysis indexes, the time domain analysis indexes comprise root mean square values and maximum values, the frequency domain analysis indexes comprise characteristic frequencies and amplitude values, and analyzing the arrangement scheme of each sensor to carry out sensitivity analysis by comparing the sensor evaluation indexes of the time period when the wheel rail is in the abnormal vibration state in the train simulation process.
Further, when the root mean square value is selected as the evaluation index of the sensor, the sensitivity of each sensor to faults is evaluated by adopting the root mean square value: and calculating to obtain the root mean square value of the acceleration collected by the axle box, the framework and the vehicle body virtual sensor, and comparing the root mean square calculated values of the axle box, the framework and the vehicle body virtual acceleration sensor to obtain the optimized layout scheme of each sensor. On the basis of the previous embodiment, the train dynamics model is realized according to SIMPACK multi-body dynamics software, the train dynamics model is a composite model and comprises a rigid body model which reserves 6 degrees of freedom of key train components based on a vehicle dynamics theory, the key train components comprise a train body, a framework, wheel pairs and axle boxes, and the rigid-flexible coupling model reserves the elasticity of a roadbed structure.
On the basis of the last embodiment, the signal acquisition direction, the signal type and the sampling frequency of the virtual sensor are set in the train dynamics model according to the running condition of the target train.
On the basis of the last embodiment, the operation condition setting comprises train traction state setting, vehicle operation speed setting, line setting and track irregularity grade setting in the train dynamics model according to the operation condition of the target train.
The monitoring system comprises a monitoring system applying the sensor layout optimization method based on the dynamic analysis, and adjusts the sensor layout scheme of the monitoring system according to each optimized sensor layout scheme and based on the robustness requirement of the sensor.
Fig. 3 shows the movement of the front bogie and the left/right wheels of the 1-axle during the operation of the train. Under the running state of the train on a normal line, the wheel-rail contact is symmetrical; when the track expands, the symmetrical contact of the wheel pair begins to change; when the track expansion fault develops, the left wheel of the shaft 1 is separated from the steel rail, and the right wheel still runs on the steel rail at the moment, but the contact point is close to the outer edge of the tread; when the track expansion fault develops to a certain degree, the wheels on the two sides of the shaft 1 are all separated from the steel rail. The derailment fault of the 1-axle wheel pair mainly occurs between 6.0s and 6.2s of simulation analysis, and in the time period, all vibration conditions collected by each virtual sensor exceed normal operation conditions. FIG. 4 shows the vibration acceleration signals of the derailment process collected by the virtual sensor of the axle between 6.0s and 6.2s according to the simulation result of the invention. FIG. 5 shows the vibration acceleration signals of the derailment process collected by the frame and the vehicle body virtual sensor in the range of 6.0 s-6.2 s according to the simulation result of the invention.
The Root Mean Square (RMS) value is used to evaluate how sensitive each sensor is to faults. Fig. 6-8 show the root mean square calculated values of the axle box, the frame, and the vehicle body virtual acceleration sensor between 6.0s and 6.2s, respectively. Through comparative analysis, the following results are found: the axle box sensor has the highest sensitivity to the abnormal motion state of the wheel rail caused by rail expansion, the framework sensor is the next to the framework sensor, and the vehicle body sensor is the lowest. For the axle box and the frame sensor, the vertical vibration signal is higher than the vertical and horizontal vibration signals for the abnormal motion state of the wheel rail caused by rail expansion; for the vehicle body sensor, the longitudinal vibration signal is higher than the transverse and vertical directions for the abnormal motion state of the wheel rail caused by rail expansion.
The sensor of the monitoring system is mounted on the framework and only monitors the vertical vibration of the framework, and the requirements on the robustness of the sensor are high, the vibration magnitude of a signal acquired by a vehicle body sensor is low, and the excitation of the axle box sensor close to a wheel rail is comprehensively considered.
The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are merely exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (7)
1. The sensor layout optimization method based on the dynamic analysis is characterized by comprising the following steps of:
step 1: establishing a train dynamic model aiming at a target train, establishing a virtual sensor in the train dynamic model, and setting an operation condition;
step 2: starting simulation, and acquiring signals acquired by a virtual sensor in the simulation process;
and step 3: according to the signals collected by the virtual sensors, positioning the time period when the wheel rail vibration is abnormal, and positioning the signals of each sensor;
and 4, step 4: determining evaluation indexes of the sensors according to signals of the sensors, calculating the abnormal time periods of the wheel rail vibration according to the evaluation indexes of the sensors, and performing sensitivity analysis on the arrangement schemes of the sensors by comparing the results of the evaluation indexes of the sensors in the abnormal time periods of the wheel rail vibration in the simulation process;
and 5: and generating optimized layout schemes of the sensors according to the sensitivity analysis results of the layout schemes of the sensors, and resetting the sensors according to the optimized layout schemes of the sensors.
2. The dynamics analysis-based sensor layout optimization method according to claim 1, wherein step 1, a plurality of virtual sensors are arranged in a train dynamics model for the body, the architecture and the axial direction of a target train, a pair of axial sensors are arranged for each axle, namely, an axle left sensor a L1, an axle right sensor AR1, two pairs of architecture sensors are arranged for each architecture, namely, a front bogie left sensor B L1, a front bogie right sensor BR1, a rear bogie left sensor B L2 and a rear bogie right sensor BR2, and two pairs of body sensors are arranged for each train body, namely, a body front right sensor CR1, a body front left sensor C L1, a body rear right sensor CR2 and a body rear left sensor C L2;
the virtual sensors are used for acquiring the vibration acceleration of the test point in the longitudinal direction, the transverse direction and the vertical direction in 3 directions and acquiring signals acquired by the vibration acceleration position sensors of the test point in the longitudinal direction, the transverse direction and the vertical direction in 3 directions.
3. The sensor layout optimization method based on dynamics analysis according to claim 2, characterized in that sensor evaluation indexes are selected, evaluation index calculation is performed on vibration signals of wheel rail abnormal time periods, the sensor evaluation indexes comprise time domain analysis indexes and frequency domain analysis indexes, the time domain analysis indexes comprise root mean square values and maximum values, the frequency domain analysis indexes comprise characteristic frequencies and amplitude values, and sensitivity analysis is performed by analyzing each sensor layout scheme by comparing the sensor evaluation indexes of the time periods when the wheel rail is in abnormal vibration states in a train simulation process.
4. The method according to claim 3, wherein when the RMS value is selected as the evaluation index of the sensor, the RMS value is used to evaluate the sensitivity of each sensor to faults: and calculating to obtain the root mean square value of the acceleration collected by the axle box, the framework and the vehicle body virtual sensor, and comparing the root mean square calculated values of the axle box, the framework and the vehicle body virtual acceleration sensor to obtain the optimized layout scheme of each sensor.
5. The method of claim 1, wherein the train dynamics model is implemented according to SIMPACK multi-body dynamics software, and comprises a rigid body model which sets key train components to 6 degrees of freedom based on a vehicle dynamics theory, wherein the key train components comprise a train body, a framework, wheel pairs, axle boxes, and a rigid-flexible coupling model which retains elasticity of a roadbed structure.
6. The dynamics analysis-based sensor layout optimization method according to claim 1, characterized in that the signal acquisition direction, signal type and sampling frequency of a virtual sensor are set in the train dynamics model according to the running condition of a target train.
7. The dynamics analysis-based sensor layout optimization method of claim 1, wherein the operation condition settings include a train traction state setting, a vehicle operation speed setting, a line setting, and a track irregularity level setting in the train dynamics model according to an operation situation of a target train.
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