Method for analyzing vehicle load based on vibration data

Abstract

The invention 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 of: S1, setting vibration monitoring points on a vehicle, acquiring vibration amplitudes at all moments during driving in real time, and generating time domain vibration signals; s2, determining a current driving road section and a time window, aggregating vibration signals of historical vehicles on the road section, extracting public features through derivative analysis and sub-interval similarity matching, and constructing road section pavement vibration signals; s3, road noise is removed from the current vehicle signal, a natural vibration signal is obtained, natural frequency is extracted through FFT transformation, and the vehicle weight is calculated in combination with a spring stiffness coefficient; according to the invention, road noise is dynamically separated through historical data, and high-precision and non-contact load monitoring is realized.

Description

Technical Field

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

[0002] Vehicle load refers to the maximum weight that a vehicle can carry while ensuring safe driving; from the perspective of traffic road administration, different vehicle types and axle numbers correspond to different load standards; from the perspective of the vehicle license, the load standard marked on the vehicle license shall prevail, that is, the vehicle load tonnage specified on the factory certificate of conformity.

[0003] In today's transportation industry, there is a relatively prominent and urgent problem in the existing technologies, that is, the phenomenon of overloaded trucks is becoming increasingly serious and has already 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 potential safety hazards and negative impacts to the entire industry.

[0004] In the actual operation process, if the vehicle is within the three guarantees period and the vehicle is damaged due to overloading, such situations occur frequently. In this case, vehicle manufacturers face a huge burden of proof. Since the vehicle damage may be caused by the combined action of multiple factors, and overloading is only one of the possible reasons, it is not easy to accurately define the direct causal relationship between vehicle damage and overloading. Moreover, in complex actual application scenarios, it is even more difficult to obtain complete and effective evidence to support the claims of vehicle manufacturers. This not only brings economic losses to vehicle manufacturers, but also affects the reputation and market image of the enterprise.

[0005] The existing technologies for measuring the total weight of a vehicle mainly achieve this by installing strain gauge sensors on the vehicle shock absorbers. However, this method has exposed many drawbacks in practice. From the perspective of installation, its operation process is relatively complex and cumbersome. Due to the relatively complex structure of the vehicle shock absorber system, installing strain gauge sensors requires professional technicians to perform precise operations to ensure that the installation position of the sensor is accurate and can be perfectly adapted to the shock absorber system. This not only places high requirements on the professional level of technicians, but also increases the installation time cost and labor cost.

[0006] In addition, the strain gauge sensors installed in this way are also prone to damage. When the vehicle is in motion, it will face various complex road conditions and environmental conditions, such as bumps, vibrations, high temperatures, humidity, etc. These factors may all have varying degrees of impact on the strain gauge sensors installed on the shock absorbers, resulting in a decline in the performance of the sensors or even their failure. Once the sensor is damaged, it is impossible to accurately measure the total weight of the vehicle, thus 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 usage cost and maintenance difficulty. Summary of the Invention

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

[0008] The purpose of the present invention can be achieved through the following technical solutions: A method for analyzing vehicle load based on vibration data includes the following steps: Step S1: Set vibration monitoring points on the vehicle. The vibration monitoring points are used to obtain the vibration data of the vehicle in real time. The vibration data is the vibration amplitude at each moment during the vehicle's driving process. According to the vibration data, generate a vibration signal of the vehicle during the driving process. Step S2: Obtain the driving section of the vehicle during the driving process, set a time interval, obtain all historical vehicles that passed through the driving section in the previous time interval, and obtain the historical vibration signals of all historical vehicles in the previous time interval. According to the historical vibration signals of all historical vehicles, obtain the road surface vibration signal of the driving section. Step S3: According to the road surface vibration signal, perform purification processing on the vibration signal of the vehicle to obtain the inherent vibration signal of the vehicle. Perform Fourier transform on the inherent vibration signal to obtain the inherent frequency domain signal, and obtain the period of the inherent vibration signal according to the inherent frequency domain signal. Obtain the stiffness coefficient of the shock absorber device of the vehicle, and obtain the estimated weight of the vehicle according to the period and the stiffness coefficient.

[0009] As a further solution of the present invention: The process of obtaining the vibration data includes: The vibration monitoring points are based on displacement sensors. The displacement sensors monitor the displacement changes of the center point of the vehicle body in the up and down directions at each moment. If the center point of the vehicle body moves upward by a distance d, record the vibration amplitude at this time as d. If the center point of the vehicle body moves downward by a distance d, record the vibration amplitude at this time as -d.

[0010] As a further solution of the present invention: The process of setting the time interval includes: Obtain the minimum speed limit v and the road section length L of the driving section, and obtain the driving time time = L / v; obtain the current moment t now , and obtain the time moment of time before the current moment, denoted as t time , then the time interval [t time , t now is obtained.

[0011] As a further solution of the present invention: the obtaining process of the road surface vibration signal includes: Mark the points corresponding to each moment on the historical vibration signal as reference points, obtain the tangent slope of the historical vibration signal at each reference point, and obtain the derivative curve of the historical vibration signal; obtain the abscissa range of the derivative curve, and divide the abscissa range into several sub-intervals; obtain the curve segments of all derivative curves on the sub-intervals, and obtain the average segment according to all curve segments; obtain the similarity between each curve segment and the average segment on the sub-interval, and select the curve segments whose similarity exceeds the preset similarity threshold, denoted as class segments; if the number of class segments exceeds the number threshold, then mark the sub-interval as a common sub-interval; Obtain the 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 the average signal segment; obtain the road surface vibration signal according to the average signal segments on each common sub-interval.

[0012] As a further solution of the present invention: the obtaining process of the road surface vibration signal further includes: If there is no common segment on the sub-interval, then mark the vibration amplitudes corresponding to all abscissas on the sub-interval as 0.

[0013] As a further solution of the present invention: the obtaining process of the similarity includes: Denote the average segment as P(t), where t is the abscissa, and denote the curve segment as Q(t), then the similarity , where [t0, t1] represents the abscissa range of the sub-interval.

[0014] As a further solution of the present invention: the process of purification treatment includes: Obtain the vibration amplitudes of the vibration signal at each moment, and obtain the amplitude set {F1, F2,..., F n}, where F n represents the vibration amplitude corresponding to the nth moment on the vibration signal; and obtain the vibration amplitudes of the road surface vibration signal at each moment, and obtain the road surface amplitude set {f1, f2,..., f n}, where f nrepresents the vibration amplitude corresponding to the nth moment on the road surface vibration signal, where n is the total number of moments; subtract each element in the amplitude set from the corresponding element in the road surface amplitude set to obtain the natural amplitude set {F1 - f1, F2 - f2,..., F n - f n}, and generate a natural vibration signal according to the natural amplitude set.

[0015] As a further solution of the present invention: the process of obtaining the estimated weight of the vehicle includes obtaining the estimated weight of the vehicle according to the period T and the stiffness coefficient k .

[0016] Advantages of the present invention: The present invention provides a method for analyzing vehicle load based on vibration data. The core innovation lies in realizing non-contact and high-precision load measurement by separating road surface vibration noise and extracting the natural vibration frequency of the vehicle; traditional methods require installing strain gauge sensors on shock absorbers, which are complex to operate and easily damaged; while the present invention only needs to arrange vibration sensors (such as displacement sensors) on the vehicle body, with simple installation, low cost and high reliability; by real-time monitoring of the load, it can provide objective data on whether the vehicle is overloaded for vehicle manufacturers, and solve the problem of responsibility definition when damage is caused by overloading; construct the road surface vibration signal of the road section through historical vehicle vibration data, and eliminate this noise from the current vehicle signal, significantly improving the accuracy of natural frequency extraction; dynamically adjust the data acquisition window (time interval) based on the time interval and road section speed limit to ensure that the analyzed data matches the current road surface conditions; perform Fourier transform (FFT) on the natural vibration signal, directly extract the period T related to the vehicle weight, and then calculate the mass through the formula, with efficient algorithm and small calculation amount; accurately separate the road surface vibration characteristics through derivative curve analysis, sub-interval similarity and common segment screening; applicable to scenarios such as logistics fleets and traffic law enforcement, helping to prevent safety hazards caused by overloading, and long-term monitoring of load changes can assist in judging the aging or failure of the shock absorption system; in summary, the present invention uses vibration signal denoising and natural frequency inversion to calculate the vehicle weight, solves the problems of complex installation, easy damage and low accuracy of traditional strain gauge methods, has both technical feasibility and commercial promotion value, and is especially suitable for modern intelligent transportation and vehicle safety management fields. Description of the Drawings

[0017] The following further describes the present invention with reference to the drawings.

[0018] Figure 1 is a schematic flow chart of a method for analyzing vehicle load based on vibration data according to the present invention. Detailed Embodiments

[0019] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0020] Please refer to Figure 1 As shown, the present invention is a method for analyzing vehicle load based on vibration data, including the following steps: Step S1: Set vibration monitoring points on the vehicle. The vibration monitoring points are used to obtain the vibration data of the vehicle in real time. The vibration data is the vibration amplitude at each moment during the driving process of the vehicle; according to the vibration data, generate a vibration signal of the vehicle during the driving process. As a preferred embodiment of the present invention, the process of obtaining the vibration data includes: The vibration monitoring points are based on displacement sensors. The displacement sensors monitor the displacement changes of the center point of the vehicle body in the up and down directions at each moment; if the center point of the vehicle body moves upward by a distance d, the vibration amplitude at this time is recorded as d; if the center point of the vehicle body moves downward by a distance d, the vibration amplitude at this time is recorded as -d. As a preferred embodiment of the present invention, the process of obtaining the vibration signal includes: Number each moment. Take the number as the abscissa and the vibration amplitude as the ordinate to establish a coordinate system; convert the moment number and its corresponding vibration amplitude of each number into coordinate points at corresponding positions on the coordinate system, and connect the coordinate points with a smooth curve to obtain a vibration signal. It can be understood that displacement sensors are installed at key positions of the vehicle (such as the center of the vehicle body) to monitor the displacement changes of the vehicle in the vertical direction (up and down) in real time; the displacement sensors record the instantaneous displacement of the vehicle body (such as +d for upward displacement and -d for downward displacement), forming a continuous vibration amplitude sequence; integrate the vibration amplitudes at each moment in time sequence to construct a time-domain vibration signal (the abscissa is time and the ordinate is amplitude), reflecting the comprehensive vibration state of the vehicle during driving. It should be noted that a set of springs or leaf spring shock absorbers are used for vehicle shock absorption. When the vehicle is driving, the uneven road surface will cause the vehicle to vibrate, and at this time, the vehicle shock absorption device will participate in the work; during this process, the parameters of the vehicle shock absorption device and the natural vibration amplitude generated by the vehicle weight will be superimposed on the vibration of the vehicle. Step S2: Obtain the driving section of the vehicle during driving, set a time interval, obtain all historical vehicles passing through the driving section in the previous time interval, obtain the historical vibration signals of all historical vehicles in the previous time interval, and obtain the road surface vibration signal of the driving section according to the historical vibration signals of all historical vehicles; In a preferred embodiment of the present invention, the process of setting the time interval includes: Obtain the minimum speed limit v and the section length L of the driving section, and obtain the driving time time = L / v; obtain the current moment t now , and obtain the time time before the current moment, denoted as t time , then the time interval [t time , t now is obtained; In a preferred embodiment of the present invention, the process of obtaining the road surface vibration signal includes: Denote the points corresponding to each moment on the historical vibration signal as reference points, obtain the tangent slopes of the historical vibration signal at each reference point to obtain the derivative curve of the historical vibration signal; obtain the abscissa range of the derivative curve, and divide the abscissa range into several sub-intervals; obtain the curve segments of all derivative curves on the sub-intervals, and obtain the average segment according to all curve segments; obtain the similarity between each curve segment and the average segment on the sub-interval, and select the curve segments whose similarity exceeds the preset similarity threshold, denoted as class segments; if the number of class segments exceeds the number threshold, then denote the sub-interval as a common sub-interval; Obtain the 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 the average signal segment; obtain the road surface vibration signal according to the average signal segments on each common sub-interval; The process of obtaining the road surface vibration signal further includes: If there is no common segment on the sub-interval, then denote the vibration amplitudes corresponding to all abscissas on the sub-interval as 0; It should be noted that the tangent slope (first derivative) at each time point is calculated for the vibration signal of each historical vehicle to generate a derivative curve. The derivative curve can highlight the change rate characteristics of the signal and filter out the constant amplitude interference. For example, road bumps will cause sudden changes in the amplitude of the vibration signal, and obvious peaks will appear in the derivative curve at this point. The abscissa (time axis) of the derivative curve is divided into several sub-intervals. In each sub-interval, the derivative curve segments of all vehicles in this sub-interval are statistically analyzed, and the mean value is taken as the reference pattern. Through algorithms such as mean square error, curve segments (similar segments) similar to the average segment are screened. If the proportion of the similar segments exceeds the threshold, it is considered that there is a common vibration pattern in this sub-interval (i.e., the common vibration caused by the road surface). For the time period marked as the common sub-interval, the corresponding segments of the original vibration signal are extracted and averaged to synthesize the road surface vibration signal. If there is no common pattern in a certain sub-interval (such as few vehicles or complex road conditions), it is directly set to zero to avoid introducing invalid noise. Through the extraction of the common characteristics of multi-vehicle data, the vibration caused by the road surface (common pattern) is distinguished from the vibration of the vehicle itself (random difference). The process of obtaining the similarity includes: Denote the average segment as P(t), where t is the abscissa, and denote the curve segment as Q(t), then the similarity , where [t0, t1] represents the abscissa range of the sub-interval; As a preferred embodiment of the present invention, the process of obtaining the road surface vibration signal based on the average signal segments on each common sub-interval further includes: If there are two consecutive sub-intervals, denoted as [t0, t1] and [t1, t2] respectively, 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), then the vibration amplitude at t1 is denoted as [G(t1) + G'(t1)] / 2; It should be noted that at the intersection point t1 of adjacent sub-intervals, if G(t1) ≠ G'(t1), it means that there is a discontinuous jump in the signal (possibly caused by data segmentation or noise mutation); at this time, by taking the arithmetic mean of the two, the two segments are smoothly connected to eliminate the jump point; essentially, linear interpolation is performed on the boundary points of the segmented signal to ensure that the generated road surface vibration signal is continuous in the time domain and avoid introducing false high-frequency components (such as step noise) due to segmentation processing; ensure that the finally synthesized road surface vibration signal is a continuous curve, which is more in line with the physical characteristics of the real road surface vibration; It can be understood that according to the road section position and time interval of the current vehicle's travel (such as calculating the time window through GPS positioning and road section speed limit), the vibration data of all historical vehicles on the same road section in the recent period (such as the previous 30 minutes) are screened; For example: If the road section length L = 10 km and the minimum speed limit v = 60 km / h, the time interval is [current time - 10 minutes, current time]; It can be understood that the vibration signals of historical vehicles are aligned in time to extract common features; through derivative analysis (calculating the tangent slope) and sub-interval similarity matching (such as mean square error), the vibration modes common to all vehicles are screened out and regarded as the vibration noise caused by the road surface; the average value of the screened common vibration segments is taken to obtain the road surface vibration signal (i.e., the noise template) of this road section; It should be noted that by constructing the vibration noise benchmark of the current road surface through historical data, it provides a basis for eliminating random road surface vibrations in the subsequent steps (step S3), ensuring that only the inherent vibrations of the vehicle itself are retained; the vibration characteristics of different road sections (such as asphalt roads, gravel roads) or the same road section at different times (such as potholes after rain) are different, and this method can update the noise model in real time to improve adaptability; it avoids the influence of the instantaneous bumps (such as passing over a speed bump) on the signal of a single vehicle, and reduces the misjudgment probability through multi-vehicle data statistics; Step S3: According to the road surface vibration signal, purify the vibration signal of the vehicle to obtain the inherent vibration signal of the vehicle; perform Fourier transform on the inherent vibration signal to obtain the inherent frequency domain signal, and obtain the period of the inherent vibration signal according to the inherent frequency domain signal; obtain the stiffness coefficient of the shock absorber device of the vehicle, and obtain the estimated weight of the vehicle according to the period and the stiffness coefficient; As a preferred embodiment of the present invention, the process of the purification process includes: Obtain the vibration amplitude at each moment of the vibration signal to obtain an amplitude set {F1, F2,..., F n}, where F n represents the vibration amplitude corresponding to the nth moment on the vibration signal; and obtain the vibration amplitude at each moment of the road surface vibration signal to obtain a road surface amplitude set {f1, f2,..., f n}, where f n represents the vibration amplitude corresponding to the nth moment on the road surface vibration signal, and n is the total number of moments; subtract each element in the amplitude set from the corresponding element in the road surface amplitude set to obtain an inherent amplitude set {F1 - f1, F2 - f2,..., F n - f n}, and generate an inherent vibration signal according to the inherent amplitude set; As a preferred embodiment of the present invention, the process of obtaining the estimated weight of the vehicle includes obtaining the estimated weight of the vehicle according to the period T and the stiffness coefficient k ; It should be noted that the shock absorber device of the vehicle is usually a spring. According to the stiffness coefficient of the spring and according to the vibration period calculation formula of the spring , where T represents the vibration period, that is, the time required for the oscillator to complete one full vibration, with the unit of seconds (s), m represents the mass of the oscillator, that is, the mass of the small ball, with the unit of kilograms (kg), and the spring constant k reflects the ability of the spring to resist stretching or compression; It can be understood that subtracting the road surface vibration signal (noise reference) generated in step S2 from the original vibration signal gives the inherent vibration signal that only reflects the vehicle's own characteristics; mathematical expression: inherent amplitude = original amplitude - road surface noise amplitude; and converting the inherent vibration signal in the time domain to the frequency domain to identify the main frequency point (i.e., the natural frequency) where the energy is concentrated; by removing the road surface noise, it is ensured that the natural frequency only reflects the vehicle mass and avoids errors caused by road condition interference.

[0021] The above has described a specific embodiment of the present invention in detail, but the content described is only a preferred embodiment of the present invention and cannot be considered as limiting the scope of implementation of the present invention. Any equivalent changes and improvements made within the scope of the application of the present invention shall still fall within the scope covered by the patent of the present invention.

Claims

1. A method for analyzing vehicle load based on vibration data, characterized in that, Including the following steps: Step S1: Set vibration monitoring points on the vehicle. The vibration monitoring points are used to obtain the vibration data of the vehicle in real time. The vibration data is the vibration amplitude at each moment during the driving process of the vehicle. Generate a vibration signal of the vehicle during the driving process according to the vibration data; Step S2: Obtain the driving section of the vehicle during the driving process, set a time interval, obtain all historical vehicles passing through the driving section in the previous time interval, and obtain the historical vibration signals of all historical vehicles in the previous time interval. Obtain the road surface vibration signal of the driving section according to the historical vibration signals of all historical vehicles; Step S3: Purify the vibration signal of the vehicle according to the road surface vibration signal to obtain the inherent vibration signal of the vehicle. Perform Fourier transform on the inherent vibration signal to obtain the inherent frequency domain signal, and obtain the period of the inherent vibration signal according to the inherent frequency domain signal. Obtain the stiffness coefficient of the shock absorber device of the vehicle, and obtain the estimated weight of the vehicle according to the period and the stiffness coefficient.

2. The method for analyzing vehicle load based on vibration data according to claim 1, wherein In step S1, the process of obtaining the vibration data includes: The vibration monitoring points are based on displacement sensors. The displacement sensors monitor the displacement changes of the center point of the vehicle body in the up and down directions at each moment. If the center point of the vehicle body moves upward by a distance d, record the vibration amplitude at this time as d. If the center point of the vehicle body moves downward by a distance d, record the vibration amplitude at this time as -d.

3. The method for analyzing the vehicle load based on vibration data according to claim 1, wherein, In step S2, the process of setting the time interval includes: Obtain the minimum speed limit v and the section length L of the driving section, and obtain the driving time time = L / v; obtain the current moment t now , and obtain the time moment time before the current moment, denoted as t time , then the time interval [t time , t now is obtained.

4. A method for analyzing vehicle load based on vibration data according to claim 1, characterized in that, In step S2, the process of obtaining the road surface vibration signal includes: Record the points corresponding to each moment on the historical vibration signal as reference points, obtain the tangent slope of the historical vibration signal at each reference point to obtain the derivative curve of the historical vibration signal; obtain the abscissa range of the derivative curve, and divide the abscissa range into several sub-intervals; obtain all the curve segments of the derivative curve on the sub-interval, and obtain the average segment according to all the curve segments; obtain the similarity between each curve segment and the average segment on the sub-interval, select the curve segments whose similarity exceeds the preset similarity threshold, and record them as class segments; if the number of class segments exceeds the number threshold, record the sub-interval as a common sub-interval; Obtain all the curve segments of the historical vibration signals on the common sub-interval, record them as signal segments, and obtain the average segment of all the signal segments on the common sub-interval, record it as the average signal segment; obtain the road surface vibration signal according to the average signal segments on each common sub-interval.

5. A method for analyzing vehicle load based on vibration data according to claim 4, characterized in that, In step S2, the process of obtaining the road surface vibration signal further includes: If there is no common segment on the sub-interval, record the vibration amplitude corresponding to all abscissas on the sub-interval as 0.

6. The method for analyzing the vehicle load based on vibration data according to claim 4, wherein, In step S2, the process of obtaining the similarity includes: Denote the average segment as P(t), where t is the abscissa, and denote the curve segment as Q(t). Then the similarity , where [t0, t1] represents the abscissa range of the sub-interval.

7. A method for analyzing vehicle load based on vibration data according to claim 1, characterized in that In step S3, the process of purification processing includes: Obtain the vibration amplitudes of the vibration signal at each moment to get an amplitude set {F1, F2,..., F n}, where F n represents the vibration amplitude corresponding to the nth moment on the vibration signal; and obtain the vibration amplitudes of the road surface vibration signal at each moment to get a road surface amplitude set {f1, f2,..., f n}, where f n represents the vibration amplitude corresponding to the nth moment on the road surface vibration signal, and n is the total number of moments; subtract the elements in the amplitude set and the road surface amplitude set correspondingly to get an inherent amplitude set {F1 - f1, F2 - f2,..., F n - f n}, and generate an inherent vibration signal according to the inherent amplitude set.

8. A method for analyzing vehicle load based on vibration data according to claim 1, characterized in that In step S3, the process of obtaining the estimated weight of the vehicle includes obtaining the estimated weight of the vehicle according to the period T and the stiffness coefficient k .

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