CN115544852B - Digital human model evaluation method based on motion trail - Google Patents
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Abstract
The invention relates to the field of data processing, and discloses a digital human model evaluation method based on a motion trail. Comprising the following steps: acquiring a first kinematic curve of each part of the digital human body model under a target working condition based on an automobile collision constraint system simulation model with the digital human body model; determining the sub-errors of each part under different dimensions according to the first kinematic curve of each part of the digital human model and the second kinematic curve of each part of the standard model under the target working condition; determining a total error according to the sub-errors; determining an overall error based on the total error; and determining whether the digital human body model meets the simulation and digital detection requirements of the target working condition based on the overall error. According to the method for calculating the comprehensive error by comparing the tracks, the digital human body model which accords with the real human body motion data is screened to perform automobile collision safety simulation and digital detection, so that the detection cost is reduced, and meanwhile, the accuracy of automobile safety performance detection is improved.
Description
Technical Field
The invention relates to the field of data processing, in particular to a digital human model evaluation method based on a motion trail.
Background
In recent years, the active and passive safety performance of the automobile is continuously improved, and the automobile safety is gradually developed to the direction of digitalization and intelligence. With the continuous development of automobile simulation technology, automobile collision simulation can accurately predict the damage degree of passengers in the collision process, the deformation of a vehicle body structure and the like, wherein the damage prediction of the passengers needs to be simulated by a digital human body model. For the digital human body model, the digital human body model is required to be consistent with the real human body data and the test damage result of the physical dummy, and data support is required to be provided for vehicle type development in the aspects of the posture and the movement of the dummy.
In the collision process of the automobile, the movement track and the gesture of the passenger have great influence on the collision damage of the human body. Therefore, part of the working conditions in the automobile safety evaluation procedure are gradually added into the evaluation of the movement track of the passengers on the basis of the collision biological injury, so as to predict and analyze the serious injury caused by the collision in the aspect of kinematics. For example, proper determination of the lateral and forward motion trajectories of the head is critical in studies to reduce head injury. The collision damage assessment is carried out by using a digital human model, and the method is based on the same motion trail as the test result. Some digital mannequins are not accurate enough in kinematic simulation, and the motion simulation degree and applicability of different digital mannequins need to be evaluated before testing. At present, related research results are available for the damage biological simulation degree of the digital human body model, but related research is still lacking for the evaluation of the motion trail of the digital human body model.
In view of this, the present invention has been made.
Disclosure of Invention
In order to solve the technical problems, the invention provides a digital human body model evaluation method based on a motion trail, which can perform standardized evaluation on the applicability of the existing digital human body model aiming at an automobile safety digital test scene, and screen the digital human body model which accords with real human body motion data to perform automobile collision safety simulation and digital detection by a method of comparing the trail to calculate the comprehensive error, thereby reducing the detection cost and improving the accuracy of automobile safety performance detection.
The embodiment of the invention provides a digital human model evaluation method based on a motion trail, which comprises the following steps:
acquiring a first kinematic curve of each part of a digital human body model under a target working condition based on an automobile collision constraint system simulation model with the digital human body model, wherein the target working condition is associated with the automobile collision constraint system simulation model, and the automobile collision constraint system simulation models under different working conditions are different;
determining the sub-errors of each part under different dimensions according to the first kinematic curve of each part of the digital human model and the second kinematic curve of each part of the standard model under the target working condition;
determining the total error corresponding to a part according to the sub-errors of the part in different dimensions;
determining an overall error based on the total error corresponding to each part and the weight corresponding to each part;
and determining whether the digital human model meets simulation and digital detection requirements of the target working condition based on the integral error.
The embodiment of the invention has the following technical effects:
the method can be used for carrying out standardized evaluation on the applicability of the existing digital human body model aiming at the safety digital test scene of the automobile, screening the digital human body model which accords with the real human body motion data to carry out automobile collision safety simulation and digital detection by a method of comparing the track to calculate the comprehensive error, reducing the detection cost and improving the accuracy of automobile safety performance detection.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are needed in the description of the embodiments or the prior art will be briefly described, and it is obvious that the drawings in the description below are some embodiments of the present invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic flow chart of a digital human model evaluation method based on a motion trail according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described below. It will be apparent that the described embodiments are only some, but not all, embodiments of the invention. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the invention, are within the scope of the invention.
The embodiment of the invention provides a digital human model evaluation method based on a motion trail, which refers to a flow diagram of the digital human model evaluation method based on the motion trail shown in fig. 1, and comprises the following steps:
s110, acquiring a first kinematic curve of each part of a digital human body model under a target working condition based on an automobile collision constraint system simulation model with the digital human body model, wherein the target working condition is associated with the automobile collision constraint system simulation model, and the automobile collision constraint system simulation models under different working conditions are different.
The automobile collision constraint system simulation model with the digital human body model comprises the following components: a body structural component model (e.g., a foot pedal model, an instrument panel model), a digital mannequin, and a restraint system component model in direct contact with the digital mannequin (e.g., including, but not limited to, a seat belt model, an airbag model, a seat model, a steering column model).
The method for acquiring the first kinematic curve of each part of the digital human body model under the target working condition based on the simulation model of the automobile collision constraint system with the digital human body model comprises the following steps:
running the simulation model of the automobile collision constraint system with the digital human body model to obtain a display image;
extracting a first kinematic curve of each part of the digital human model by using Hyperworks software based on the display image;
when the automobile collision constraint system simulation model with the digital human body model is operated, the automobile collision constraint system simulation model with the digital human body model has the same initial speed and deceleration waveform as the physical test.
The target condition may be a standard collision condition or a collision condition in the NCAP.
The digital mannequin should be placed with reference to the vehicle design points and vehicle structure, the symmetry plane of the digital mannequin should coincide with the middle plane of the seat plumb, and be exposed to the vertical acceleration field that constitutes the gravity load, without artificial connection or restraint of all limbs. Model constraints, model contacts, model initial velocity and deceleration waveforms are input. The static and dynamic friction coefficients between the vehicle model and the digital phantom, and between the seat belt and the digital phantom were set to 0.3. The model overall initial velocity and deceleration waveform should be consistent with the crash condition physical test.
And establishing a computing environment of a finite element model of the constraint system, and outputting model computing results with a time interval of 0.1ms, including but not limited to animation and damage results, and simultaneously outputting contact force and hourglass energy, contact energy and internal energy of the whole model. The model should meet the condition that no penetration of the contact surface occurs in the animation, the contact force between the digital human model and the vehicle is zero at the beginning, and the total energy is kept unchanged within the tolerance range of 15%; sandglass energy < = 10% of total energy; the contact energy at the start of the simulation < = 1% of the total energy.
Taking a first kinematic curve for extracting the mass center of the head in a certain collision working condition as an example, using measurement commands in Hyperview software to extract the x-direction displacement and the y-direction displacement of the mass center of the head, and drawing the first kinematic curve in the xy plane, namely the motion trail curve of the verification model. The motion trail curve of the standard model can adopt currently known real human body data or extract the motion trail of the head centroid mark according to Marker tracking commands in the Hyperworks-MediaView according to the standard dummy physical test video, namely the motion trail curve (namely the second kinematic curve) of the standard model.
S120, determining the sub-errors of each part under different dimensions according to the first kinematic curve of each part of the digital human body model and the second kinematic curve of each part of the standard model under the target working condition.
S130, determining the total error corresponding to the part according to the sub-errors of the part in the different dimensions.
For example, the same location includes sub-errors in 4 dimensions, then the total error for that location is the sum or weighted sum of the sub-errors in 4 dimensions.
Illustratively, the first kinematic curve, assuming the one part is the headThe line is the kinematic curve of the head, and the sub-errors of 4 dimensions of the head are respectively track errors by determining the sub-errors based on the first kinematic curve of the head of the digital human body model and the second kinematic curve of the head of the standard model under the target working conditionE t Error in shapeE q、 Error of transverse axisE p And error of longitudinal axisE r Total error of headECan be expressed as:
wherein ,
the weights occupied by the 4 dimensions are respectively.
And S140, determining the overall error based on the total error corresponding to each part and the weight corresponding to each part.
For example, the overall error may be expressed as:
wherein ,E j indicating the total error corresponding to the jth site,w j the weight corresponding to the jth site is represented, and ω represents the total number of sites.
S150, determining whether the digital human model meets simulation and digital detection requirements of the target working condition based on the integral error.
For example, if the overall error is less than a threshold, it is determined that the digital phantom meets the simulation and digital detection requirements of the target operating condition, in other words, the digital phantom may be used for collision simulation and digital detection under the target operating condition.
Specifically, the second kinematic curve of a part of the standard model can be expressed in the xy plane as: l (t) = (x (t), y (t)), x (t), y (t) are the horizontal and vertical coordinates of the second kinematic curve at the time t, for example, taking a certain position as a head as an example, x (t), and y (t) are the coordinates of the centroid of the head at the time t in the x direction and the y direction, respectively.
The first kinematic curve of the head of the verification model (i.e. the digital manikin to be evaluated) can be expressed in the xy-plane as: l ' (t) = (x ' (t), y ' (t)), x ' (t), y ' (t) are the abscissa of the first kinematic curve of the verification model head at time t, respectively.
Based on the above definition, the orbit error Et is calculated:
at the same time t, the absolute distance of the first kinematic curve of the verification model head from the second kinematic curve of the standard model head can be expressed as:
in consideration of the cumulative effect of the errors, the present embodiment uses the real-time distance between the second kinematic curve L (t) of the standard model head and the origin as the reference of the evaluation score. At time t, the distance between the second kinematic curve L (t) of the standard model head and the origin is d (t):
based on the above, the track error of the headE t The determination is based on the following relation:
wherein ,E t Representing the orbit error of the part, N represents the discrete data points included in the second kinematic curve of the part under the target working condition, E t (t) a track error quantization index value indicating that the first kinematic curve corresponding to the one part and the second kinematic curve corresponding to the one part at the time t;
E t (t) is determined based on the following relationship:
For shape errors: by comparing the trend changes of the two curves in each time step, the difference in the shapes of the two curves can be reflected, and taking any time point t as an example, the motion track of the point in the delta t time is as follows:
the error epsilon (t) of the first and second kinematic curves at time t can be expressed as:
the arc length S (t) of the second kinematic curve in the Δt time is
The arc length S' (t) of the first kinematic curve over Δt time is:
to sum up, shape errorsE q The determination is based on the following relation:
Eq(t) a shape error quantization index value representing a first kinematic curve corresponding to the head at time t and a second kinematic curve corresponding to the head;
Eq(t) is determined based on the following relationship:
in general terms, the sub-errors in the different dimensions include track errors;
correspondingly, the determining the sub-errors of each part under different dimensions according to the first kinematic curve of each part of the digital human model and the second kinematic curve of each part of the standard model under the target working condition comprises the following steps:
determining the orbit error of a part of the digital human body model according to a first kinematic curve of the part and a second kinematic curve of the part of the standard model under the target working conditionE t ；
Wherein the track error of the partE t The determination is based on the following relation:
wherein ,E t representing the orbit error of the part, N represents the discrete data points included in the second kinematic curve of the part under the target working condition, E t (t) a track error quantization index value indicating that the first kinematic curve corresponding to the one part and the second kinematic curve corresponding to the one part at the time t;
E t (t) is determined based on the following relationship:
wherein e (t) represents the absolute distance between the first kinematic curve corresponding to the part and the second kinematic curve corresponding to the part at the time of t, and the calculation formula of e (t) is as follows
Wherein x (t) represents an abscissa of the second kinematic curve corresponding to the one part at the time t, y (t) represents an ordinate of the second kinematic curve corresponding to the one part at the time t, x '(t) represents an abscissa of the first kinematic curve corresponding to the one part at the time t, and y' (t) represents an ordinate of the first kinematic curve corresponding to the one part at the time t;
δ 1 （t）=1%*d（t），δ 2 (t) =50% d (t), d (t) represents the distance between the second kinematic curve corresponding to the one part at the time t and the origin, and the calculation formula of d (t) is as follows
。
Further, the sub-errors in the different dimensions further include shape errors;
correspondingly, the determining the sub-errors of each part under different dimensions according to the first kinematic curve of each part of the digital human model and the second kinematic curve of each part of the standard model under the target working condition further comprises:
determining shape error of a part of the digital human body model according to a first kinematic curve of the part and a second kinematic curve of the part of the standard model under the target working conditionE q ；
Wherein the shape error of the partE q The determination is based on the following relation:
wherein ,E q representing the shape error of the one part,Eq(t) a shape error quantization index value indicating that the first kinematic curve corresponding to the one portion and the second kinematic curve corresponding to the one portion at the time t;
Eq(t) is determined based on the following relationship:
wherein ,εq (t) represents the relative error, ε, of the first kinematic curve corresponding to the one part and the second kinematic curve corresponding to the one part at time t q The formula of (t) is
S (t) represents the arc length of the second kinematic curve corresponding to the part within the time delta t, and the calculation formula of S (t) is
X (t) represents the abscissa of the second kinematic curve corresponding to the one part at the time t, y (t) represents the ordinate of the second kinematic curve corresponding to the one part at the time t, x (t+Δt) represents the abscissa of the second kinematic curve corresponding to the one part at the time (t+Δt), and y (t+Δt) represents the ordinate of the second kinematic curve corresponding to the one part at the time (t+Δt);
s '(t) represents the arc length of the first kinematic curve corresponding to the part in the Δt time, and the calculation formula of S' (t) is as follows:
epsilon (t) represents the absolute error of a first kinematic curve corresponding to the part at the moment t and a second kinematic curve corresponding to the part, and the calculation formula of epsilon (t) is as follows:
wherein x '(t) represents the abscissa of the first kinematic curve corresponding to the one part at the time t, y' (t) represents the ordinate of the first kinematic curve corresponding to the one part at the time t, x '(t+Δt) represents the abscissa of the first kinematic curve corresponding to the one part at the time (t+Δt), and y' (t+Δt) represents the ordinate of the first kinematic curve corresponding to the one part at the time (t+Δt).
Further, the sub-errors in different dimensions further include a horizontal axis error;
correspondingly, the determining the sub-errors of each part under different dimensions according to the first kinematic curve of each part of the digital human model and the second kinematic curve of each part of the standard model under the target working condition further comprises:
determining a horizontal axis error of a part of the digital human body model according to a first kinematic curve of the part and a second kinematic curve of the part of the standard model under the target working conditionE p ；
Wherein the cross-axis error of the one partE p The determination is based on the following relation:
wherein, intercepting a curve section of the second kinematic curve and the first kinematic curve in the same time period, and the starting point moment of the intercepted curve section is marked as t s The end point time is marked as t e The number of discrete data points included in the intercepted curve segment is M, the first kinematic curve corresponding to the part is translated along the time axis, the translation amount is M data points, and the upper limit of M is
，0<β<After 0.5 translation, the number of data points of the overlapping part of the first kinematic curve and the second kinematic curve corresponding to the part in the intercepted curve segment is n=M- |m|, i is used for marking specific data points, M 0 The translation amount corresponding to the maximum correlation value K (m) is represented, and the calculation formula of the correlation value K (m) is as follows:
wherein ,Kx (m) represents the post-translational stageA value of the cross-axis correlation between one kinematic curve and the second kinematic curve in the x-direction, K y (m) represents a value of a cross-axis correlation between the first kinematic curve and the second kinematic curve in the y-direction after the translation;
when-the Chinese medicine
) When m is more than or equal to 0, K x The formula of (m) is:
when m is more than 0 and less than or equal to
) When K is x The formula of (m) is:
when-the Chinese medicine
) When m is more than or equal to 0, K y The formula of (m) is:
when m is more than 0 and less than or equal to
) When K is y The formula of (m) is:
wherein ,
meaning that β, M is rounded down to the nearest integer, x e (t) represents the horizontal axis sitting at time t after the second kinematic curve corresponding to the one part is normalizedMark, y e (t) represents the vertical axis coordinate at the time t after the second kinematic curve corresponding to the part is normalized, x e 't' represents the horizontal axis coordinate at time t after the first kinematic curve corresponding to the one part is normalized, y e 't' represents the vertical axis coordinate at time t after the first kinematic curve corresponding to the one part is normalized; x is x e （t）、y e （t）、x e ' (t) and y e The expression of' (t) is:
x e （t s +i and Deltat represent the second kinematic curve corresponding to the one part normalized to (t) s The abscissa of time +i × Δt), y e （t s +i and Deltat represent the second kinematic curve corresponding to the one part normalized to (t) s Vertical axis coordinates, x, at time +i × Δt) e '（t s +i and Deltat represent the first kinematic curve corresponding to the one part normalized to the first one s The abscissa of time +i × Δt), y e '（t s +i and Deltat represent the first kinematic curve corresponding to the one part normalized to the first one s Vertical axis coordinates at +i+Δt); x is x e '（t s ++ (i-m) and Deltat) represent the first kinematic curve corresponding to the one part, normalized at (t) s The abscissa of time + (i-m),. DELTA.t), y e '（t s ++ (i-m) and Deltat) represent the first kinematic curve corresponding to the one part, normalized at (t) s The vertical axis coordinates at time + (i-m),. DELTA.t); x is x e （t s ++ (i+m) and Δt represent that the second kinematic curve corresponding to the one part is normalized at (t) s The abscissa of time + (i+m),. DELTA.t), y e （t s ++ (i+m) and Δt represent that the second kinematic curve corresponding to the one part is normalized at (t) s The vertical axis coordinates at time + (i+m),. DELTA.t).
Further, the sub-errors in the different dimensions further include a vertical axis error;
correspondingly, the determining the sub-errors of each part under different dimensions according to the first kinematic curve of each part of the digital human model and the second kinematic curve of each part of the standard model under the target working condition comprises the following steps:
determining a longitudinal axis error of a part of the digital human body model according to a first kinematic curve of the part and a second kinematic curve of the part of the standard model under the target working conditionE r ；
Wherein the longitudinal axis error of the partE r The determination is based on the following relation:
E r =U x ﹒U y
wherein ,U x Representing the vertical axis coordinate error fraction in the x direction between the translated first and second kinematic curves, U y Representing a vertical axis coordinate error fraction in the y-direction between the translated first and second kinematic curves; u (U) x and U y The determination is based on the following expressions:
wherein ,u x representing the value of the vertical axis correlation between the first kinematic curve and the second kinematic curve in the x direction after translation,u y representing the value of the correlation between the vertical axis of the translated first and second kinematic curves in the y-direction,u x andu y the determination is based on the following expressions:
the digital human body model evaluation method based on the motion trail can perform standardized evaluation on the applicability of the existing digital human body model aiming at the automobile safety digital test scene, and the digital human body model conforming to the real human body motion data is screened to perform automobile collision safety simulation and digital detection by comparing the method of calculating the comprehensive error of the trail, so that the detection cost is reduced, and meanwhile, the accuracy of automobile safety performance detection is improved.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of the present application. As used in this specification, the terms "a," "an," "the," and/or "the" are not intended to be limiting, but rather are to be construed as covering the singular and the plural, unless the context clearly dictates otherwise. The terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method or apparatus comprising such elements.
It should also be noted that the positional or positional relationship indicated by the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc. are based on the positional or positional relationship shown in the drawings, are merely for convenience of describing the present invention and simplifying the description, and do not indicate or imply that the apparatus or element in question must have a specific orientation, be constructed and operated in a specific orientation, and thus should not be construed as limiting the present invention. Unless specifically stated or limited otherwise, the terms "mounted," "connected," and the like are to be construed broadly and may be, for example, fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; can be directly connected or indirectly connected through an intermediate medium, and can be communication between two elements. The specific meaning of the above terms in the present invention will be understood in specific cases by those of ordinary skill in the art.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the essence of the corresponding technical solutions from the technical solutions of the embodiments of the present invention.
Claims (7)
1. A digital manikin evaluation method based on a motion trail, comprising the steps of:
acquiring a first kinematic curve of each part of a digital human body model under a target working condition based on an automobile collision constraint system simulation model with the digital human body model, wherein the target working condition is associated with the automobile collision constraint system simulation model, and the automobile collision constraint system simulation models under different working conditions are different;
determining the sub-errors of each part under different dimensions according to the first kinematic curve of each part of the digital human model and the second kinematic curve of each part of the standard model under the target working condition;
determining the total error corresponding to a part according to the sub-errors of the part in different dimensions;
determining an overall error based on the total error corresponding to each part and the weight corresponding to each part;
determining whether the digital human model meets simulation and digital detection requirements of the target working condition based on the overall error;
the sub-errors in the different dimensions include track errors;
correspondingly, the determining the sub-errors of each part under different dimensions according to the first kinematic curve of each part of the digital human model and the second kinematic curve of each part of the standard model under the target working condition comprises the following steps:
based on a first kinematic curve of a portion of the digital manikin and the portion of the standard model at the target workerDetermining the orbit error of the part according to a second kinematic curve under the conditionE t ；
Wherein the track error of the partE t The determination is based on the following relation:
wherein ,Et Representing the track error of the one part,Nrepresenting the discrete data points included in the second kinematic curve of the part under the target working condition, E t (t) a track error quantization index value indicating that the first kinematic curve corresponding to the one part and the second kinematic curve corresponding to the one part at the time t;
E t (t) is determined based on the following relationship:
wherein e (t) represents the absolute distance between the first kinematic curve corresponding to the part and the second kinematic curve corresponding to the part at the time of t, and the calculation formula of e (t) is as follows
Wherein x (t) represents an abscissa of the second kinematic curve corresponding to the one part at the time t, y (t) represents an ordinate of the second kinematic curve corresponding to the one part at the time t, x '(t) represents an abscissa of the first kinematic curve corresponding to the one part at the time t, and y' (t) represents an ordinate of the first kinematic curve corresponding to the one part at the time t;
δ 1 （t）=1%×d（t），δ 2 (t) =50% ×d (t), d (t) represents the distance between the origin and the second kinematic curve corresponding to the one part at the time t, and the calculation formula of d (t) is
；
The sub-errors in the different dimensions also include shape errors;
correspondingly, the determining the sub-errors of each part under different dimensions according to the first kinematic curve of each part of the digital human model and the second kinematic curve of each part of the standard model under the target working condition further comprises:
determining shape error of a part of the digital human body model according to a first kinematic curve of the part and a second kinematic curve of the part of the standard model under the target working conditionE q ；
Wherein the shape error of the partE q The determination is based on the following relation:
wherein ,E q representing the shape error of the one part,E q (t) a shape error quantization index value indicating that the first kinematic curve corresponding to the one portion and the second kinematic curve corresponding to the one portion at the time t;
E q (t) is determined based on the following relationship:
wherein ,εq (t) represents the relative error, ε, of the first kinematic curve corresponding to the one part and the second kinematic curve corresponding to the one part at time t q The formula of (t) is:
s (t) represents the arc length of the second kinematic curve corresponding to the part within the time delta t, and the calculation formula of S (t) is +.>
x (t) represents the abscissa of the second kinematic curve corresponding to the one part at the time t, y (t) represents the ordinate of the second kinematic curve corresponding to the one part at the time t, x (t+Δt) represents the abscissa of the second kinematic curve corresponding to the one part at the time (t+Δt), and y (t+Δt) represents the ordinate of the second kinematic curve corresponding to the one part at the time (t+Δt);
s '(t) represents the arc length of the first kinematic curve corresponding to the part in the Δt time, and the calculation formula of S' (t) is as follows:
epsilon (t) represents the absolute error of a first kinematic curve corresponding to the part at the moment t and a second kinematic curve corresponding to the part, and the calculation formula of epsilon (t) is as follows:
wherein x '(t) represents the abscissa of the first kinematic curve corresponding to the one part at the time t, y' (t) represents the ordinate of the first kinematic curve corresponding to the one part at the time t, x '(t+Δt) represents the abscissa of the first kinematic curve corresponding to the one part at the time (t+Δt), and y' (t+Δt) represents the ordinate of the first kinematic curve corresponding to the one part at the time (t+Δt).
2. The method of claim 1, wherein the sub-errors in the different dimensions further comprise a horizontal axis error;
correspondingly, the determining the sub-errors of each part under different dimensions according to the first kinematic curve of each part of the digital human model and the second kinematic curve of each part of the standard model under the target working condition further comprises:
determining a horizontal axis error of a part of the digital human body model according to a first kinematic curve of the part and a second kinematic curve of the part of the standard model under the target working conditionE p ；
Wherein the cross-axis error of the one partE p The determination is based on the following relation:
wherein, intercepting a curve section of the second kinematic curve and the first kinematic curve in the same time period, and the starting point moment of the intercepted curve section is marked as t s The end point time is marked as t e The number of discrete data points included in the intercepted curve segment is M, the first kinematic curve corresponding to the part is translated along the time axis, the translation amount is M data points, and the upper limit of M is
，0<β<0.5, after translation, the number of data points of the overlapping part of the first kinematic curve and the second kinematic curve corresponding to the part in the intercepted curve segment is n=M- |m|, i is used for marking specific data points, M 0 The translation amount corresponding to the maximum correlation value K (m) is represented, and the calculation formula of the correlation value K (m) is as follows:
wherein ,Kx (m) represents the value of the cross-axis correlation in the x-direction between the translated first and second kinematic curves, K y (m) represents a value of a cross-axis correlation between the first kinematic curve and the second kinematic curve in the y-direction after the translation;
when-the Chinese medicine
）≤When m is less than or equal to 0, K x The formula of (m) is:
when-the Chinese medicine
) When m is more than or equal to 0, K y The formula of (m) is:
when m is more than 0 and less than or equal to
) When K is y The formula of (m) is:
wherein ,
meaning that β, M is rounded down to the nearest integer, x e (t) represents the horizontal axis coordinate at the time t after the second kinematic curve corresponding to the one part is normalized, y e (t) represents the vertical axis coordinate at the time t after the second kinematic curve corresponding to the part is normalized, x e 't' represents the horizontal axis coordinate at time t after the first kinematic curve corresponding to the one part is normalized, y e 't' represents the vertical axis coordinate at time t after the first kinematic curve corresponding to the one part is normalized; x is x e （t）、y e （t）、x e ' (t) and y e The expression of' (t) is: />
x e （t s +i and Deltat represent the second kinematic curve corresponding to the one part normalized to (t) s The abscissa of time +i × Δt), y e （t s +i and Deltat represent the second kinematic curve corresponding to the one part normalized to (t) s Vertical axis coordinates, x, at time +i × Δt) e '（t s +i and Deltat represent the first kinematic curve corresponding to the one part normalized to the first one s The abscissa of time +i × Δt), y e '（t s +i and Deltat represent the first kinematic curve corresponding to the one part normalized to the first one s Vertical axis coordinates at +i+Δt); x is x e '（t s ++ (i-m) and Deltat) represent the first kinematic curve corresponding to the one part, normalized at (t) s The abscissa of time + (i-m),. DELTA.t), y e '（t s ++ (i-m) and Deltat) represent the first kinematic curve corresponding to the one part, normalized at (t) s The vertical axis coordinates at time + (i-m),. DELTA.t); x is x e （t s ++ (i+m) and Δt represent that the second kinematic curve corresponding to the one part is normalized at (t) s The abscissa of time + (i+m),. DELTA.t), y e （t s ++ (i+m) and Δt represent that the second kinematic curve corresponding to the one part is normalized at (t) s The vertical axis coordinates at time + (i+m),. DELTA.t).
3. The method of claim 2, wherein the sub-errors in the different dimensions further comprise a vertical axis error;
correspondingly, the determining the sub-errors of each part under different dimensions according to the first kinematic curve of each part of the digital human model and the second kinematic curve of each part of the standard model under the target working condition comprises the following steps:
determining a longitudinal axis error of a part of the digital human body model according to a first kinematic curve of the part and a second kinematic curve of the part of the standard model under the target working conditionE r ；
Wherein the longitudinal axis error of the partE r The determination is based on the following relation:
E r =U x ﹒U y
wherein ,Ux Representing the vertical axis coordinate error fraction in the x direction between the translated first and second kinematic curves, U y Representing a vertical axis coordinate error fraction in the y-direction between the translated first and second kinematic curves; u (U) x and Uy The determination is based on the following expressions:
wherein ,u x representing the value of the vertical axis correlation between the first kinematic curve and the second kinematic curve in the x direction after translation,u y representing the value of the correlation between the vertical axis of the translated first and second kinematic curves in the y-direction,u x andu y the determination is based on the following expressions:
4. the method of claim 1, wherein the vehicle collision restraint system simulation model with digital mannequin includes: a body structural component model, a digital manikin, and a restraint system component model in direct contact with the digital manikin.
5. The method of claim 4, wherein the obtaining a first kinematic curve for each part of the digital phantom under the target condition based on the simulation model of the collision constraint system of the vehicle with the digital phantom comprises:
running the simulation model of the automobile collision constraint system with the digital human body model to obtain a display image;
extracting a first kinematic curve of each part of the digital human model by using Hyperworks software based on the display image;
when the automobile collision constraint system simulation model with the digital human body model is operated, the automobile collision constraint system simulation model with the digital human body model has the same initial speed and deceleration waveform as the physical test.
6. The method of claim 1, wherein the sub-errors in the different dimensions include orbit errors, shape errors, transverse axis errors, and longitudinal axis errors; the determining the total error corresponding to the part according to the sub-errors of the part in the different dimensions comprises the following steps:
determining the total error corresponding to the one part based on the following formula:
wherein ,Erepresenting the total error corresponding to the part E t Representing the track error of the one part,E q representing the shape error of the one part,E p representing the horizontal axis error of the one part,E r representing the error of the vertical axis of the one part,
and weights corresponding to the orbit error, the shape error, the horizontal axis error and the vertical axis error are respectively represented.
7. The method of claim 1, wherein determining the overall error based on the total error for each location and the weight for each location, respectively, comprises:
determining the overall error based on the following equation:
wherein ,E sum representing the said overall error as a function of the error,E j indicating the total error corresponding to the jth site,w j the weight corresponding to the j-th part is represented, and omega represents the total number of the parts;
determining whether the digital human model meets simulation and digital detection requirements of the target working condition based on the overall error comprises the following steps: and if the integral error is smaller than a threshold value, determining that the digital human model meets the simulation and digital detection requirements of the target working condition.
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