A method for identifying the time period when a rail transit train passes through a vibration detection section

Abstract

The present invention provides a method for identifying the time period when a rail transit train passes through a vibration detection section. The method is based on vehicle-induced vibration acceleration time history data obtained through field testing. The time history curves of the Z vibration level corresponding to the induced vibration time history data are calculated using weighting factors W and Wk. The two curves are subtracted to obtain a difference curve. Finally, the first-order derivative of the difference curve is obtained by taking the first-order derivative curve. The first-order derivative curve has an upward convex peak and a downward concave trough. The time corresponding to the peak is the time when the leading train passes through the detection section, and the time corresponding to the trough is the time when the trailing train passes through the detection section. The method for identifying the time period when a rail transit train passes through a vibration detection section of the present invention has a clear, concise, and simple calculation process, and the analysis results are accurate, reliable, and highly operational.

Description

Technical Field

[0001] The present invention belongs to the technical field of rail transit vibration signal recognition, and in particular relates to a method for identifying a time period during which a rail transit train passes through a vibration detection section. Background Art

[0002] While rail transit construction can significantly alleviate urban traffic pressure, it also inevitably presents numerous associated challenges, including the environmental impact of vehicle-induced vibration (VIV). Train-induced vibrations can impact residents' lives and work, the use of precision equipment, and the lifespan of building structures. Accurately assessing the environmental impact of VIV is crucial in both rail transit construction and operation, directly impacting the selection of vibration and noise reduction measures and the upgrading and retrofitting of operating lines. Consequently, a significant number of VIV testing tests are required in rail transit.

[0003] Conducting vehicle-induced vibration testing on operating lines collects extensive trackside and ground vibration time history data during vehicle passage periods. Obtaining vibration impact evaluation metrics requires post-processing of this data. This post-processing method relies on current vibration evaluation standards. The accuracy of these evaluation metrics, calculated using the evaluation metric calculation methods specified in these standards, is influenced by multiple factors, including the time it takes for the lead and trailing trains to pass through the test section (hereinafter collectively referred to as the "lead and trailing train transit time"). Current Chinese standards do not clearly define the criteria for determining this "lead and trailing train transit time." This determination is primarily influenced by the subjective nature of the data analyst, and different judgments are bound to differ, leading to varying evaluation metric calculations. Therefore, accurate determination of this "lead and trailing train transit time" is essential to derive accurate vibration environmental impact evaluation metrics.

[0004] Existing invention patent CN 107563403 B discloses a method for identifying the operating conditions of high-speed trains. It uses variational mode decomposition and fuzzy entropy to decompose the monitoring data, and uses MultiView K-means as a clusterer for identification. Invention patent CN 114997231 A discloses a method for quickly identifying the environmental vibration response induced by subway trains. It uses the average value of the square of the weighted acceleration of the operation as the judgment threshold, and judges whether the vibration source is a subway train based on the judgment threshold; invention patent CN109583323 B discloses a method for identifying subway vibration signals based on door control loop units. It uses a network model to perform dimensionality reduction processing on sample data and construct a subway vibration signal identification model. However, in the detection and evaluation analysis of the impact of rail transit vehicle-induced vibration environment, the above patents still lack an accurate judgment method for the moment when the head and tail cars pass through the detection section. Summary of the Invention

[0005] In response to the current problem that there is still a lack of accurate judgment methods when rail transit trains pass through vibration detection sections, the present invention provides a method for identifying the time period when rail transit trains pass through vibration detection sections, which can effectively eliminate the influence of the lack of judgment rules and subjective judgment factors in rail transit vehicle-induced vibration analysis, and ensure the accuracy of vehicle-induced vibration environmental impact assessment.

[0006] The present invention is achieved through the following technical solutions:

[0007] A method for identifying a time period during which a rail transit train passes through a vibration detection section comprises the following steps:

[0008] (1) The acceleration time history data of the train-induced vibration is collected by the vibration acceleration sensor and data acquisition instrument arranged on the track site. a (t);

[0009] (2) Calculate the time history curve VLz of the Z vibration level corresponding to the acceleration time history data a(t) by using the W weighting factor w (t): The continuously collected acceleration time history data a (t) is divided into several 1s segments, and the data of each segment is analyzed by 1 / 3 times to obtain the t of each segment. i The corresponding plumb bob Z vibration level VLz i ; Complete the calculation of the Z-level of the plumb bob corresponding to the acceleration time history data of all sections, and obtain the data VLz of the Z-level of the plumb bob changing with time during the entire measurement period w (t);

[0010] (3) Calculate the time history curve VLz of the Z vibration level corresponding to the acceleration time history data a(t) caused by the train vibration using the Wk weighting factor wk (t), the specific method is the same as step (2);

[0011] (4) Use VLz wk (t) minus VLz w (t) a curve is obtained and recorded as VLz0(t);

[0012] (5) Find the first-order derivative of VLz0(t). Since VLz wk (t) and VLz w The difference in (t) shows a change characteristic from small to large, almost constant, and from large to small during the train passing period. Therefore, the first-order derivative of VLz0(t) has an upward convex peak and a downward concave trough. The moment corresponding to the peak is the moment when the front of the train passes the detection section, and the moment corresponding to the trough is the moment when the rear of the train passes the detection section.

[0013] Preferably, the t iThe plumb Z vibration level VLz corresponding to the segment data i The calculation method is as follows:

[0014] A1: Vibration time history data a (t) Perform Fourier transform to find the vibration components in the frequency band corresponding to each center frequency. Perform inverse Fourier transform on the vibration components found, and then calculate the effective value of acceleration a corresponding to each center frequency according to the following formula: w :

[0015] ;

[0016] Where: a 1 (t) is the acceleration data within the frequency band corresponding to a certain center frequency; T = 1s;

[0017] A2: The calculation formula for the j-th center frequency crossover level VALj is as follows:

[0018] ;

[0019] A3: The calculation formula for the Z vibration level VLz is as follows:

[0020] ;

[0021] Where: Wj is the W weighting factor corresponding to the j-th center frequency when calculating VLzw(t), and Wj is the Wk weighting factor corresponding to the j-th center frequency when calculating VLzwk(t).

[0022] Preferably, the W weighting factor is recommended by standard ISO 2631-1985.

[0023] Preferably, the Wk weighting factor is recommended by standard ISO2631-1997.

[0024] Preferably, the 1 / 3 fold analysis in step (2) adopts the calculation method recommended by standard GB10071.

[0025] The present invention is based on the vehicle-induced vibration acceleration time history data obtained from field tests a(t), the W weighting factor recommended by ISO2631-1985 is used to calculate the time history curve VLz(t) of the Z vibration level corresponding to the vehicle-induced vibration time history data, which is recorded as VLzw(t). The Wk weighting factor recommended by ISO2631-1997 is used to calculate the time history curve VLz(t) of the Z vibration level corresponding to the vehicle-induced vibration time history data, which is recorded as VLzwk(t), where t represents time. Then VLzw(t) and VLzwk(t) are plotted on the same graph. Subtracting VLzw(t) from VLzwk(t) can produce a curve, which is denoted as VLz0(t). VLz0(t)=VLzwk(t)-VLzw(t). The first-order derivative of VLz0(t) is obtained. Since the difference between VLzwk(t) and VLzw(t) changes from small to large → almost constant → from large to small during the train passing period, the first-order derivative of VLz0(t) has an upward convex peak and a downward concave trough. The moment corresponding to the peak is the moment when the first train passes the detection section, and the moment corresponding to the trough is the moment when the last train passes the detection section.

[0026] The beneficial effects of the present invention are as follows:

[0027] The present invention's method for identifying the time period during which a rail transit train passes through a vibration detection section features a clear, concise, and simple calculation process, resulting in accurate and reliable analysis results and strong operability. This method can save significant manpower and material resources, improving efficiency. It can also effectively eliminate the influence of missing judgment rules and subjective judgment factors in rail transit vehicle-induced vibration analysis, ensuring the accuracy of vehicle-induced vibration environmental impact assessments. Furthermore, the present invention is applicable not only to urban rail transit but also to high-speed rail, intercity rail, and urban rail transit. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 This is the technical roadmap of the present invention.

[0029] Figure 2 The acceleration time history data in the embodiment a (t)Fig.

[0030] Figure 3 The time course data in the embodiment a (t) The time history curve VLz corresponding to the Z vibration level w (t)Fig.

[0031] Figure 4 VLz(t) and VLz in the embodiment wk (t) curve.

[0032] Figure 5 It is the VLz0(t) curve diagram in the embodiment.

[0033] Figure 6This is the first-order derivative curve of VLz0(t). DETAILED DESCRIPTION

[0034] The present invention will be further described below with reference to the accompanying drawings. Example

[0035] A method for identifying the time period when a rail transit train passes through a vibration detection section, the technical route is as follows Figure 1 As shown, the specific steps include:

[0036] (1) The acceleration time history data of the train-induced vibration is collected by the vibration acceleration sensor and data acquisition instrument arranged on the track site. a (t), such as Figure 2 shown.

[0037] (2) Calculate acceleration time history data using the W weighting factor recommended by ISO2631-1985 a (t) The time history curve VLz corresponding to the Z vibration level w (t), the specific steps are as follows:

[0038] The continuously collected acceleration time history data a (t) is divided into several 1s segments, and the calculation method recommended by GB10071 is used to perform 1 / 3 fold analysis on the data of each segment to obtain the t of each segment. i The corresponding plumb bob Z vibration level VLz i ; Complete the calculation of the Z-level of the plumb bob corresponding to the acceleration time history data of all sections, and obtain the data VLz of the Z-level of the plumb bob changing with time during the entire measurement period w (t), such as Figure 3 As shown;

[0039] Specifically, the t i The plumb Z vibration level VLz corresponding to the segment data i The calculation method is as follows:

[0040] A1: Vibration time history data a (t) Perform Fourier transform to find the vibration components in the frequency band corresponding to each center frequency. Perform inverse Fourier transform on the vibration components found, and then calculate the effective value of acceleration a corresponding to each center frequency according to the following formula: w :

[0041]

[0042] Where: a 1 (t) is the acceleration data within the frequency band corresponding to a certain center frequency; T = 1s;

[0043] A2: The calculation formula for the j-th center frequency crossover level VALj is as follows:

[0044]

[0045] A3: The calculation formula for the Z vibration level VLz is as follows:

[0046]

[0047] Where: Wj is the W weighting factor corresponding to the j-th center frequency when calculating VLzw(t), and Wj is the Wk weighting factor corresponding to the j-th center frequency when calculating VLzwk(t).

[0048] (3) Calculate the time history curve VLz of the Z vibration level corresponding to the vibration time history data a(t) using the Wk weighting factor recommended by ISO2631-1997 wk (t), the specific method is the same as step (2), and VLz w (t) and VLz wk (t) Draw in the same figure, such as Figure 4 shown.

[0049] (4) Then use VLz wk (t) minus VLz w (t) to obtain a curve, which is recorded as VLz0(t), such as Figure 5 shown.

[0050] (5) Take the first-order derivative of VLz0(t) and we get Figure 6 The first derivative curve of VLz0(t) is shown in the figure. wk (t) and VLz w The difference between (t) Figure 5 ) shows a change characteristic from small to large → almost constant → from large to small during the train passing period, so the first-order derivative of VLz0(t) has an upward convex peak and a downward concave trough (see Figure 6 ), the moment corresponding to the wave crest is the moment when the front of the vehicle passes through the detection section, and the moment corresponding to the wave trough is the moment when the rear of the vehicle passes through the detection section.

[0051] The above embodiments are merely exemplary embodiments of the present invention and are not intended to limit the scope of the present invention. The scope of protection of the present invention is defined by the claims. Persons skilled in the art may make various modifications or equivalent substitutions to the present invention within the spirit and scope of protection of the present invention, and such modifications or equivalent substitutions shall also be deemed to fall within the scope of protection of the present invention.

Claims

1. A method for identifying a time period during which a rail transit train passes through a vibration detection section, characterized in that: The following steps are involved: (1) The acceleration time history data a(t) of the train-induced vibration is collected by using the vibration acceleration sensors and data acquisition instruments arranged on the track site; (2) Calculate the time history curve VLz of the Z vibration level corresponding to the acceleration time history data a(t) by using the W weighting factor w (t): Divide the continuously collected acceleration time history data a(t) into several segments with a duration of 1s, and perform 1 / 3 fold analysis on the data of each segment to obtain the t of each segment. i The corresponding plumb bob Z vibration level VLz i ; Complete the calculation of the Z-level of the plumb bob corresponding to the acceleration time history data of all sections, and obtain the data VLz of the Z-level of the plumb bob changing with time during the entire measurement period w (t); (3) Calculate the time history curve VLz of the Z vibration level corresponding to the acceleration time history data a(t) caused by the train vibration using the Wk weighting factor wk (t), the specific method is the same as step (2); (4) Use VLz wk (t) minus VLz w (t) a curve is obtained and recorded as VLz0(t); (5) Calculate the first-order derivative of VLz0(t), since VLz wk (t) and VLz w The difference in (t) shows a change characteristic from small to large, almost constant, and from large to small during the train passing period. Therefore, the first-order derivative of VLz0(t) has an upward convex peak and a downward concave trough. The moment corresponding to the peak is the moment when the front of the train passes the detection section, and the moment corresponding to the trough is the moment when the rear of the train passes the detection section.

2. The method for identifying a period of time during which a rail transit train passes through a vibration detection section according to claim 1, characterized in that: No. t i The plumb bob Z vibration level VLz corresponding to the segment data i The calculation method is as follows: A1: Perform Fourier transform on the acceleration time history data a(t) to find the vibration components within the frequency band corresponding to each center frequency. Perform inverse Fourier transform on the vibration components found, and then calculate the acceleration effective value a corresponding to each center frequency according to the following formula: w : Where: a1(t) is the acceleration data whose frequency is within the frequency band corresponding to a certain center frequency; T = 1s; A2: The calculation formula for the j-th center frequency crossover level VALj is as follows: A3: The calculation formula for the Z vibration level VLz is as follows: Where: Wj is the W weighting factor corresponding to the j-th center frequency when calculating VLzw(t), and Wj is the Wk weighting factor corresponding to the j-th center frequency when calculating VLzwk(t).

3. The method for identifying a period of time during which a rail transit train passes through a vibration detection section according to claim 1, characterized in that: The W weighting factor is recommended by the standard ISO 2631-1985.

4. The method for identifying a period of time during which a rail transit train passes through a vibration detection section according to claim 1, wherein: The Wk weighting factor is recommended by the standard ISO2631-1997.

5. The method for identifying a period of time during which a rail transit train passes through a vibration detection section according to claim 1, characterized in that: Step (2) performs 1 / 3 fold analysis using the calculation method recommended by standard GB10071.

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