A method for analyzing vehicle load based on vibration data

Abstract

The application relates to the technical field of vehicle load analysis, and particularly discloses a method for analyzing vehicle load based on vibration data, which comprises the following steps: step S1: vibration monitoring points are arranged on a vehicle, vibration amplitudes at each moment during driving are collected in real time, and time-domain vibration signals are generated; step S2: a current driving section and a time window are determined, vibration signals of historical vehicles on the section are aggregated, common characteristics are extracted through derivative analysis and sub-interval similarity matching, and a section road surface vibration signal is constructed; and step S3: road surface noise is removed from the current vehicle signal to obtain an inherent vibration signal, the inherent frequency is extracted through FFT transformation, and the vehicle weight is calculated in combination with a spring stiffness coefficient; the application separates road surface noise dynamically through historical data, and realizes high-precision and non-contact load monitoring.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of vehicle load analysis, and particularly relates to a method for analyzing vehicle load based on vibration data. BACKGROUND

[0002] Vehicle load refers to the maximum weight that a vehicle can carry under the premise of ensuring safe driving. From the perspective of traffic administration, different vehicle models and axle numbers correspond to different load standards. From the perspective of a driving license, the load standard marked on the driving license is the standard, that is, the vehicle load tonnage specified on the factory certificate of conformity.

[0003] In today's transportation industry, there is a prominent and urgent problem in existing technology, that is, the phenomenon of truck overloading is becoming more and more serious and has become an industry problem that cannot be ignored. With the continuous growth of logistics transportation demand and the intensification of market competition, some truck drivers and operating enterprises often choose to overload trucks in order to pursue higher economic benefits, which brings many safety hazards and negative effects to the entire industry.

[0004] In actual operation, if the vehicle is within the three-year warranty period, but the vehicle is damaged due to overloading, such cases occur from time to time. In this case, the vehicle manufacturer faces a huge evidence dilemma. Since the damage of the vehicle may be caused by multiple factors, and overloading is only one possible cause, it is not easy to accurately determine that there is a direct causal relationship between vehicle damage and overloading. Moreover, in complex practical application scenarios, it is even more difficult to obtain complete and effective evidence to support the claims of the vehicle manufacturer. This not only brings economic losses to the vehicle manufacturer, but also affects the reputation and market image of the enterprise.

[0005] The existing technology for measuring the total weight of a vehicle mainly realizes it by installing a strain gauge sensor on the vehicle shock absorber. However, this method has many drawbacks in practice. From the perspective of installation, the operation process is relatively complex and tedious. Since the structure of the vehicle shock absorber system is relatively complex, professional technicians need to perform accurate operations to ensure that the installation position of the sensor is accurate and that the sensor perfectly fits the shock absorber system. This not only puts high requirements on the professional level of technicians, but also increases the time cost and labor cost of installation.

[0006] In addition, the strain gauge sensor in this installation mode is also prone to damage. Vehicles will face various complex road conditions and environmental conditions during driving, such as bumps, vibrations, high temperatures, humidity, etc. These factors can affect the strain gauge sensor installed on the shock absorber to varying degrees, causing the performance of the sensor to decline or even fail. Once the sensor is damaged, the total weight of the vehicle cannot be accurately measured, thereby affecting the reliability and stability of the entire system. Moreover, replacing the damaged sensor also requires a certain amount of time and cost, further increasing the use cost and maintenance difficulty. SUMMARY

[0007] The purpose of the present application is to provide a method for analyzing vehicle load based on vibration data, which solves the above technical problems.

[0008] The purpose of the present application can be achieved by the following technical solutions:

[0009] A method for analyzing vehicle load based on vibration data, comprising the following steps:

[0010] Step S1: setting a vibration monitoring point on the vehicle, the vibration monitoring point is used to obtain the vibration data of the vehicle in real time, the vibration data is the vibration amplitude of the vehicle at each time during driving; according to the vibration data, the vibration signal of the vehicle during driving is generated;

[0011] Step S2: obtaining the driving section of the vehicle during driving, and setting a time interval, obtaining all historical vehicles passing through the driving section in the last time interval, and obtaining the historical vibration signal of all historical vehicles in the last time interval, obtaining the road vibration signal of the driving section according to the historical vibration signal of all historical vehicles;

[0012] Step S3: purifying the vibration signal of the vehicle according to the road vibration signal to obtain the inherent vibration signal of the vehicle; performing Fourier transform on the inherent vibration signal to obtain the inherent frequency domain signal, and obtaining the period of the inherent vibration signal according to the inherent frequency domain signal; obtaining the stiffness coefficient of the shock absorbing device of the vehicle, and obtaining the estimated weight of the vehicle according to the period and the stiffness coefficient.

[0013] As a further scheme of the present application: the vibration data acquisition process comprises:

[0014] The vibration monitoring point is based on a displacement sensor, which monitors the displacement change of the center point of the vehicle body in the up-down direction at each time; if the center point of the vehicle body is displaced upward by a distance d, the vibration amplitude at this time is recorded as d; if the center point of the vehicle body is displaced downward by a distance d, the vibration amplitude at this time is recorded as -d.

[0015] As a further aspect of the present invention: the process of setting the time interval includes:

[0016] Obtain the minimum speed limit v and the length L of the road segment, and obtain the travel time time = L / v; obtain the current time t. now And obtain the time before the current time, denoted as t. time Then the time interval [t] is obtained. time , t now ].

[0017] As a further aspect of the present invention: the process of obtaining the road surface vibration signal includes:

[0018] The points corresponding to each moment on the historical vibration signal are recorded as reference points. The slope of the tangent line of the historical vibration signal at each reference point is obtained to obtain the derivative curve of the historical vibration signal. The range of the horizontal coordinate of the derivative curve is obtained and divided into several sub-intervals. All curve segments of the derivative curve on the sub-intervals are obtained, and the average segment is obtained based on all curve segments. The similarity between each curve segment on the sub-interval and the average segment is obtained, and the curve segments with similarity exceeding a preset similarity threshold are selected and recorded as class segments. If the number of class segments exceeds the number threshold, the sub-interval is recorded as a common sub-interval.

[0019] Obtain curve segments of all historical vibration signals on the common sub-interval, denoted as signal segments, and obtain the average segment of all signal segments on the common sub-interval, denoted as average signal segments; obtain the road vibration signal based on the average signal segments on each common sub-interval.

[0020] As a further aspect of the present invention: the process of obtaining the road vibration signal further includes:

[0021] If there are no common segments in the sub-interval, then the vibration amplitude corresponding to all horizontal coordinates in the sub-interval is recorded as 0.

[0022] As a further aspect of the present invention: the process of obtaining the similarity includes:

[0023] Let the average segment be denoted as P(t), where t is the horizontal axis, and the curve segment be denoted as Q(t). Then the similarity... , where [t0, t1] represents the range of the horizontal coordinates of the sub-interval.

[0024] As a further aspect of the present invention: the purification process includes:

[0025] The vibration amplitude of the vibration signal at each moment is obtained to obtain the amplitude set {F1, F2, ..., F...} n}, where Fn This represents the vibration amplitude at the nth moment of the vibration signal; and the vibration amplitude of the road surface vibration signal at each moment is obtained to obtain the road surface amplitude set {f1, f2, ..., f...}. n}, where f n Let Fn represent the vibration amplitude at the nth moment of the road vibration signal, where n is the total number of moments. Subtracting each element in the road vibration amplitude set from the amplitude set yields the inherent amplitude set {F1-f1, F2-f2, ..., Fn}. n -f n The inherent vibration signal is generated based on the inherent amplitude set.

[0026] As a further aspect of the present invention: the process of obtaining the estimated weight of the vehicle includes obtaining the estimated weight of the vehicle based on the period T and the stiffness coefficient k. .

[0027] The beneficial effects of this invention are:

[0028] This invention provides a method for analyzing vehicle load based on vibration data. Its core innovation lies in achieving non-contact, high-precision load measurement by separating road vibration noise and extracting the vehicle's natural vibration frequencies. Traditional methods require installing strain gauge sensors on shock absorbers, which is complex and prone to damage. This invention, however, only requires placing vibration sensors (such as displacement sensors) on the vehicle body, making installation simple, low-cost, and highly reliable. By monitoring load in real time, it can provide automakers with objective data on whether vehicles are overloaded, solving the problem of liability determination when damage is caused by overloading. By constructing road surface vibration signals from historical vehicle vibration data and removing this noise from current vehicle signals, the accuracy of natural frequency extraction is significantly improved. Data acquisition is dynamically adjusted based on time intervals and road segment speed limits. The window (time interval) ensures that the analyzed data matches the current road conditions; Fourier transform (FFT) is performed on the natural vibration signal to directly extract the period T related to vehicle weight, and then the mass is calculated by formula. The algorithm is efficient and computationally inefficient; through derivative curve analysis, sub-interval similarity, and common segment screening, the road vibration characteristics are accurately separated; it is applicable to scenarios such as logistics fleets and traffic enforcement, helping to prevent safety hazards caused by overloading. Long-term monitoring of load changes can help determine the aging or failure of the shock absorption system; in summary, this invention solves the problems of complex installation, easy damage, and low accuracy of traditional strain gauge methods by denoising vibration signals and inverting vehicle weight from natural frequencies. It has both technical feasibility and commercial promotion value, and is especially suitable for the fields of modern intelligent transportation and vehicle safety management. Attached Figure Description

[0029] The invention will now be further described with reference to the accompanying drawings.

[0030] Figure 1is a flowchart of a method for analyzing vehicle load based on vibration data. DETAILED DESCRIPTION

[0031] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work fall within the scope of protection of the present application.

[0032] Please refer to Figure 1 The present application is a method for analyzing vehicle load based on vibration data, which comprises the following steps:

[0033] Step S1: setting a vibration monitoring point on the vehicle, the vibration monitoring point is used to acquire vibration data of the vehicle in real time, the vibration data is the vibration amplitude of the vehicle at each time during driving; according to the vibration data, a vibration signal of the vehicle during driving is generated;

[0034] As a preferred embodiment of the present application, the vibration data acquisition process comprises:

[0035] The vibration monitoring point is based on a displacement sensor, which monitors the displacement change of the vehicle body center point in the up-down direction at each time; if the vehicle body center point is displaced by a distance d upwards, the vibration amplitude at this time is recorded as d; if the vehicle body center point is displaced by a distance d downwards, the vibration amplitude at this time is recorded as -d;

[0036] As a preferred embodiment of the present application, the vibration signal acquisition process comprises:

[0037] Each time is numbered, the number is taken as the horizontal coordinate, and the vibration amplitude is taken as the vertical coordinate to establish a coordinate system; each numbered time and its corresponding vibration amplitude are converted into the coordinate point of the corresponding position on the coordinate system, and each coordinate point is connected by a smooth curve to obtain the vibration signal;

[0038] It can be understood that the displacement sensor is installed at the key position of the vehicle (such as the center of the vehicle body) to monitor the displacement change of the vehicle in the vertical direction (up and down) in real time; the displacement sensor records the instantaneous displacement amount of the vehicle body (such as +d for upward displacement and -d for downward displacement), forming a continuous vibration amplitude sequence; the vibration amplitudes at each time are integrated in time sequence to construct a time-domain vibration signal (the horizontal coordinate is time and the vertical coordinate is amplitude), reflecting the comprehensive vibration state of the vehicle during driving;

[0039] It should be noted that the vehicle's shock absorbers use a set of springs or leaf springs. When the vehicle is driving, uneven road surfaces will cause the vehicle to vibrate, and the vehicle's shock absorbers will then work. During this process, the vibration of the vehicle will be combined with the parameters of the vehicle's shock absorbers and the inherent vibration amplitude caused by the vehicle's weight.

[0040] Step S2: Obtain the road segment in which the vehicle travels during its journey, and set a time interval. Obtain all historical vehicles that have passed through the road segment in the previous time interval, and obtain the historical vibration signals of all historical vehicles in the previous time interval. Based on the historical vibration signals of all historical vehicles, obtain the road surface vibration signal of the road segment.

[0041] In a preferred embodiment of the present invention, the process of setting the time interval includes:

[0042] Obtain the minimum speed limit v and the length L of the road segment, and obtain the travel time time = L / v; obtain the current time t. now And obtain the time before the current time, denoted as t. time Then the time interval [t] is obtained. time , t now ];

[0043] In a preferred embodiment of the present invention, the process of obtaining the road vibration signal includes:

[0044] The points corresponding to each moment on the historical vibration signal are recorded as reference points. The slope of the tangent line of the historical vibration signal at each reference point is obtained to obtain the derivative curve of the historical vibration signal. The range of the horizontal coordinate of the derivative curve is obtained and divided into several sub-intervals. All curve segments of the derivative curve on the sub-intervals are obtained, and the average segment is obtained based on all curve segments. The similarity between each curve segment on the sub-interval and the average segment is obtained, and the curve segments with similarity exceeding a preset similarity threshold are selected and recorded as class segments. If the number of class segments exceeds the number threshold, the sub-interval is recorded as a common sub-interval.

[0045] Obtain curve segments of all historical vibration signals on the common sub-interval, denoted as signal segments, and obtain the average segment of all signal segments on the common sub-interval, denoted as average signal segment; obtain the road vibration signal based on the average signal segment on each common sub-interval;

[0046] The process of obtaining the road surface vibration signal also includes:

[0047] If there is no common segment in the sub-interval, then the vibration amplitude corresponding to all horizontal coordinates in the sub-interval is recorded as 0;

[0048] It should be noted that the tangent slope (first derivative) of each time point of the vibration signal of each historical vehicle is calculated to generate a derivative curve, which can highlight the rate of change characteristics of the signal and filter out constant amplitude interference; for example: road bumps can cause the amplitude of the vibration signal to change suddenly, and the derivative curve will present obvious peaks at this point; the abscissa (time axis) of the derivative curve is divided into several subintervals, in each subinterval, the derivative curve segments of all vehicles in the subinterval are counted, and the average is taken as the reference mode; similar curve segments (similar segments) are screened out through mean square error algorithm; if the proportion of similar segments exceeds the threshold, it is considered that there is a common vibration mode (i.e. common vibration caused by road) in the subinterval; for the period marked as a common subinterval, the corresponding segment of the original vibration signal is extracted and averaged to synthesize the road vibration signal; if there is no common mode in a subinterval (such as few vehicles or complex road conditions), it is directly set to zero to avoid introducing invalid noise; through the common feature extraction of multi-vehicle data, the vibration caused by the road (common mode) and the vibration of the vehicle itself (random difference) are distinguished;

[0049] The similarity obtaining process comprises:

[0050] The average segment is denoted as P(t), t is the abscissa, and the curve segment is denoted as Q(t), and the similarity is Where [t0, t1] represents the abscissa range of the subinterval.

[0051] As a preferred embodiment of the present application, the process of obtaining the road vibration signal according to the average signal segment in each common subinterval further comprises:

[0052] If there are two consecutive subintervals, denoted as [t0, t1] and [t1, t2], and the average signal segments corresponding to [t0, t1] and [t1, t2] are denoted as G(t) and G'(t) respectively; if G(t1)≠G'(t1), the vibration amplitude at t1 is recorded as [G(t1)+G'(t1)] / 2;

[0053] It is worth noting that at the junction point t1 of adjacent subintervals, if G(t1)≠G'(t1), it indicates that the signal has a discontinuous jump (which may be caused by data segmentation or noise mutation); at this time, the arithmetic mean of the two is taken to smoothly connect the two segments and eliminate the jump point; the essence is to perform linear interpolation on the boundary points of the segmented signal to ensure that the generated road vibration signal is continuous in time domain and avoid introducing false high-frequency components (such as step noise) due to segmentation processing; ensure that the finally synthesized road vibration signal is a continuous curve, which is more in line with the physical characteristics of the real road vibration;

[0054] It can be understood that according to the position and time interval of the section where the current vehicle travels (such as through GPS positioning and section speed limit calculation time window), the vibration data of all historical vehicles on the same section in the near future (such as the previous 30 minutes) is screened out;

[0055] For example: if the length of the section L=10km, the minimum speed limit v=60km / h, then the time interval is [current time-10 minutes, current time];

[0056] It can be understood that the vibration signals of the historical vehicles are aligned by time, and the common characteristics are extracted; through derivative analysis (calculating the slope of the tangent line) and sub-interval similarity matching (such as mean square error), the vibration mode common to all vehicles is screened out, and is regarded as the vibration noise caused by the road surface; the average value of the screened common vibration segment is taken to obtain the road surface vibration signal (i.e. noise template) of the section;

[0057] It should be noted that the vibration noise benchmark of the current road surface is constructed through historical data, which provides a basis for eliminating random road vibration in the subsequent step (step S3), and ensures that only the inherent vibration of the vehicle is retained; the vibration characteristics of different sections (such as asphalt road, gravel road) or different times (such as potholes after rain) of the same section are different, this method can update the noise model in real time and improve the adaptability; avoid the influence of single vehicle signal by instantaneous bumps (such as passing through the deceleration belt), reduce the misjudgment probability through multi-vehicle data statistics;

[0058] Step S3: according to the road surface vibration signal, the vibration signal of the vehicle is purified to obtain the inherent vibration signal of the vehicle; the inherent frequency domain signal is obtained by Fourier transform on the inherent vibration signal, and the period of the inherent vibration signal is obtained according to the inherent frequency domain signal; the stiffness coefficient of the shock absorbing device of the vehicle is obtained, and the estimated weight of the vehicle is obtained according to the period and the stiffness coefficient;

[0059] As a preferred embodiment of the present application, the purification process includes:

[0060] The vibration amplitude of the vibration signal at each time is obtained to obtain the amplitude set {F1, F2,..., Fn}, wherein Fn represents the vibration amplitude corresponding to the nth time on the vibration signal; and the vibration amplitude of the road surface vibration signal at each time is obtained to obtain the road surface amplitude set {f1, f2,..., fn}, wherein fn represents the vibration amplitude corresponding to the nth time on the road surface vibration signal, and n is the total number of times; the elements in the amplitude set and the road surface amplitude set are subtracted to obtain the inherent amplitude set {F1-f1, F2-f2,..., Fn-fn}; n n n n n n ​​​​​} generating an inherent vibration signal according to the inherent amplitude set;

[0061] As a preferred embodiment of the present application, the process of obtaining the estimated weight of the vehicle comprises obtaining the estimated weight of the vehicle according to the period T and the stiffness coefficient k ;

[0062] It should be noted that the shock absorbing device of the vehicle is usually a spring, and the stiffness coefficient of the spring is calculated according to the vibration period formula of the spring , wherein T represents the vibration period, i.e. the time required for the oscillator to complete one complete vibration, in seconds (s), m represents the mass of the oscillator, i.e. the mass of the ball, in kilograms (kg), and the stiffness coefficient k reflects the ability of the spring to resist stretching or compression;

[0063] It can be understood that the road surface vibration signal (noise reference) generated in step S2 is subtracted from the original vibration signal to obtain an inherent vibration signal that only reflects the characteristics of the vehicle itself; the mathematical expression is: inherent amplitude = original amplitude - road noise amplitude; and the time-domain inherent vibration signal is converted into a frequency domain to identify the main frequency point (i.e. the inherent frequency) of the energy set; by eliminating road noise, it is ensured that the inherent frequency only reflects the mass of the vehicle, avoiding errors caused by road conditions interference.

[0064] The above has described one embodiment of the present application in detail, but the above description is only a preferred embodiment of the present application and cannot be considered as limiting the scope of the present application. Any equivalent changes and improvements made according to the scope of the present application should still be within the scope of the present application.

Claims

1. A method of analyzing a load of a vehicle based on vibration data, characterized by, The method comprises the following steps: Step S1: setting a vibration monitoring point on the vehicle, the vibration monitoring point being used to acquire vibration data of the vehicle in real time, the vibration data being a vibration amplitude of the vehicle at each time during driving; and generating a vibration signal of the vehicle during driving according to the vibration data; Step S2: acquiring a driving section of the vehicle during driving, setting a time interval, acquiring all historical vehicles passing through the driving section in a previous time interval, and acquiring historical vibration signals of all the historical vehicles in the previous time interval; and obtaining a road surface vibration signal of the driving section according to the historical vibration signals of all the historical vehicles; Step S3: purifying the vibration signal of the vehicle according to the road surface vibration signal to obtain an inherent vibration signal of the vehicle; performing Fourier transform on the inherent vibration signal to obtain an inherent frequency domain signal, and obtaining a period of the inherent vibration signal according to the inherent frequency domain signal; acquiring a stiffness coefficient of a shock absorption device of the vehicle, and obtaining an estimated weight of the vehicle according to the period and the stiffness coefficient; In step S3, the purifying process comprises: The vibration amplitude of the vibration signal at each moment is obtained to obtain the amplitude set {F1, F2, ..., F...} n }, where F n This represents the vibration amplitude at the nth moment of the vibration signal; and the vibration amplitude of the road surface vibration signal at each moment is obtained to obtain the road surface amplitude set {f1, f2, ..., f...}. n }, where f n Let Fn represent the vibration amplitude corresponding to the nth time point in the road vibration signal, where n is the total number of time points. Subtracting each element in the road vibration amplitude set from the amplitude set yields the inherent amplitude set {F1-f1, F2-f2, ..., Fn}. n -f n The inherent vibration signal is generated based on the inherent amplitude set.

2. The method of claim 1, wherein, In step S1, the acquiring process of the vibration data comprises: The vibration monitoring point is based on a displacement sensor that monitors displacement changes of a center point of a vehicle body of the vehicle in a vertical direction at each time; if the center point of the vehicle body is displaced by a distance d upwards, the vibration amplitude at this time is recorded as d; if the center point of the vehicle body is displaced by a distance d downwards, the vibration amplitude at this time is recorded as -d.

3. The method of claim 1, wherein, In step S2, the setting process of the time interval comprises: Obtain the minimum speed limit v and the length of the driving section L of the driving section, obtain the driving time time=L / v; obtain the current time t now , and obtain the time before the current time time, denoted as t time , then the time interval [t time , t now ] is obtained.

4. The method of claim 1, wherein, In step S2, the obtaining process of the road surface vibration signal comprises: Each point on the historical vibration signal at each time is recorded as a reference point, a tangent slope of the historical vibration signal at each reference point is acquired to obtain a derivative curve of the historical vibration signal; a horizontal coordinate range of the derivative curve is acquired, and the horizontal coordinate range is divided into a plurality of subintervals; curve segments of all the derivative curves on the subintervals are acquired, and an average segment is obtained according to all the curve segments; a similarity between each curve segment and the average segment on the subintervals is acquired, and a curve segment with a similarity exceeding a preset similarity threshold is selected and recorded as a similar segment; if the number of the similar segments exceeds a number threshold, the subinterval is recorded as a common subinterval; Curve segments of all the historical vibration signals on the common subintervals are recorded as signal segments, and an average segment of all the signal segments on the common subintervals is recorded as an average signal segment; a road surface vibration signal is obtained according to the average signal segments on each common subinterval.

5. The method of claim 4, wherein the method further comprises: In step S2, the obtaining process of the road surface vibration signal further comprises: If there is no common segment on the subinterval, the vibration amplitude corresponding to all the horizontal coordinates on the subinterval is recorded as 0.

6. The method of claim 4, wherein the method further comprises: In step S2, the obtaining process of the similarity comprises: Let the average segment be denoted P(t), t being the abscissa, and the curve segment be denoted Q(t), then the similarity where [t0, t1] denotes the abscissa range of the subinterval.

7. The method of claim 1, wherein the method further comprises: In step S3, the process of obtaining the estimated weight of the vehicle comprises obtaining the estimated weight of the vehicle according to the period T and the stiffness coefficient k .

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