JP6884343B2 - Derailment sign detection system, control device, derailment sign detection method, and derailment sign detection program - Google Patents

Description

The present invention relates to a derailment sign detection system, a control device, a derailment sign detection method, and a derailment sign detection program.

As a conventional technique for detecting a sign of derailment of a railway train, the techniques described in Patent Document 1 and Patent Document 2 by the present inventors are known.

In the technique of Patent Document 1, the pitch angular velocity and roll angular velocity of a running bogie are detected by a sensor attached to the bogie frame, and the detected bogie pitch angular velocity or bogie pitch angular velocity detection value becomes larger than a preset threshold value. It is determined that the derailment is a sign on the condition that the detected bogie roll angular velocity or the integrated value of the bogie roll angular velocity becomes larger than the preset threshold value.

Further, in the technique of Patent Document 2, the detected roll angular velocity of the trolley is stored in a storage device, a moving average is calculated based on the history of the roll angular velocity, and a predicted value of the roll angular velocity is calculated from the moving average. .. Then, when the detected pitch angular velocity of the bogie and the predicted value of the roll angular velocity after a predetermined time each exceed a predetermined threshold value, it is determined as a sign of derailment of the train.

Japanese Patent No. 5468016 Japanese Unexamined Patent Publication No. 2014-231308

By using the prior arts of Patent Documents 1 and 2, it is possible to detect a sign of derailment of a train, but these prior arts may not always exhibit sufficient performance depending on the conditions. For example, when parameters such as threshold values determined based on data measured on a test track are applied to a train traveling on an actual business line, disturbances generated in pitch angular velocity and roll angular velocity at rail joints and the like are generated. Due to the influence of the significant value due to the above, false detection of derailment sign may occur. Further, since the threshold value used for detecting the derailment sign greatly depends on the traveling speed, it is difficult to determine an appropriate threshold value, and erroneous detection tends to occur particularly in the low speed range.

In addition, it is conceivable to adopt various methods for analysis of pitch angular velocity, roll angular velocity, etc., but when detecting a train derailment sign, it is detected within 0.2 seconds after the sign occurs. Since there is a restriction that it is difficult to avoid derailment unless measures are taken immediately, only methods that can be analyzed in near real time can be adopted.

The present invention has been made in view of the above circumstances, and an object of the present invention is a derailment sign detection system, a control device, a derailment sign detection method, and a derailment sign detection capable of improving the detection accuracy of a derailment sign of a train. To provide a program.

In order to achieve the above-mentioned object, the derailment sign detection system, the control device, the derailment sign detection method, and the derailment sign detection program according to the present invention are characterized by the following (1) to (5).
(1) A detector provided on the train to detect the pitch angular velocity and roll angular velocity of the running train, and
The wavelet coefficient of the pitch angular velocity is calculated as the first wavelet coefficient, the wavelet coefficient of the roll angular velocity is calculated as the second wavelet coefficient, and the calculated first wavelet coefficient and the second wavelet coefficient are calculated. When the coefficients exceed the predetermined coefficients, the control device that determines the derailment sign of the train and
When the control device determines that it is a derailment sign, an output unit that notifies the derailment sign to the outside and
Equipped with a,
The control device calculates the first wavelet coefficient and the second wavelet coefficient only in the range of 0.5 to 100 Hz, which is a low frequency region.
Derailment sign detection system.

According to the derailment sign detection system having the configuration of (1) above, it is possible to improve the detection accuracy of the derailment sign of the train. That is, by comparing the first wavelet coefficient and the second wavelet coefficient obtained by wavelet analysis of each of the detected values of the pitch angular velocity and the roll angular velocity with the threshold value, and determining the detection value, at a place such as a rail seam at low speed. False positives due to the effects of disturbances that occur can be reduced.

Further, according to the derailment sign detection system having the above configuration (1 ), it is possible to further improve the detection accuracy of the derailment sign of the train. That is, when the wheel flange of the train rides on the rail and leads to derailment, it has been confirmed that high output with low frequency exists in both pitch angular velocity and roll angular velocity, so it is calculated within the range of low frequency region. By using the first wavelet coefficient and the second wavelet coefficient, the accuracy of detecting the derailment sign is improved.

( 2 ) The control device calculates a moving average of at least the roll angular velocity based on the history of detected values, predicts a change in the roll angular velocity from the moving average, and calculates the predicted value of the roll angular velocity. The derailment sign of the train is determined based on the first wavelet coefficient and the second wavelet coefficient.
The derailment sign detection system according to (1) above.

According to the derailment sign detection system having the configuration of (2 ) above, the condition of combining the predicted value of the roll angular velocity, the calculated first wavelet coefficient, and the previous two wavelet coefficients can be determined, so that the detection accuracy of the derailment sign can be determined. Can be further improved.

( 3 ) Based on the pitch angle speed and roll angle speed of the running train provided in the train and detected by a predetermined detection unit, the wavelet coefficient of the pitch angle speed is calculated as the first wavelet coefficient, and the roll angle speed is calculated. The wavelet coefficient is calculated as the second wavelet coefficient, and when the calculated first wavelet coefficient and the second wavelet coefficient each exceed the predetermined threshold values, it is determined as a derailment sign of the train and a derailment sign. If it is determined, the derailment sign detection is notified to the outside,
The first wavelet coefficient and the second wavelet coefficient are calculated only within the range of 0.5 to 100 Hz, which is a low frequency region.
Control device.

According to the control device having the configuration of (3 ) above, it is possible to improve the detection accuracy of the derailment sign of the train as in the derailment sign detection system of (1) above.

( 4 ) Enter the detected values of the pitch angular velocity and roll angular velocity of the running train.
The wavelet coefficient of the pitch angular velocity is calculated as the first wavelet coefficient, and the wavelet coefficient is calculated.
The wavelet coefficient of the roll angular velocity is calculated as the second wavelet coefficient, and the wavelet coefficient is calculated.
Comparing each of the calculated first wavelet coefficient and the second wavelet coefficient with a predetermined threshold value,
When the first wavelet coefficient and the second wavelet coefficient exceed the threshold value, it is determined that the train is a derailment sign, and the derailment sign detection is notified to the outside.
The first wavelet coefficient and the second wavelet coefficient are calculated only within the range of 0.5 to 100 Hz, which is a low frequency region.
Derailment sign detection method.

According to the derailment sign detection method having the configuration of the above ( 4 ), it is possible to improve the detection accuracy of the derailment sign of the train as in the derailment sign detection system of the above (1).

( 5 ) A step of inputting the detected values of the pitch angular velocity and the roll angular velocity of the running train, and
The step of calculating the wavelet coefficient of the pitch angular velocity as the first wavelet coefficient, and
The step of calculating the wavelet coefficient of the roll angular velocity as the second wavelet coefficient, and
A step of comparing each of the calculated first wavelet coefficient and the second wavelet coefficient with a predetermined threshold value.
When the first wavelet coefficient and the second wavelet coefficient exceed the threshold value, it is determined that the train is a derailment sign, and the derailment sign detection is notified to the outside.
Let the computer perform the process including
The first wavelet coefficient and the second wavelet coefficient are calculated only within the range of 0.5 to 100 Hz, which is a low frequency region.
Derailment sign detection program.

By executing the derailment sign detection program having the configuration of (5 ) above on a predetermined computer, it is possible to improve the detection accuracy of the derailment sign detection system of the train as in the derailment sign detection system of (1) above.

According to the derailment sign detection system, the control device, the derailment sign detection method, and the derailment sign detection program of the present invention, it is possible to improve the detection accuracy of the derailment sign detection of the train. That is, when the wheel flange of the train rides on the rail and leads to derailment, it has been confirmed that high output with low frequency exists in both pitch angular velocity and roll angular velocity, so it is calculated within the range of low frequency region. By using the first wavelet coefficient and the second wavelet coefficient, the accuracy of detecting the derailment sign is improved.

The present invention has been briefly described above. Further, the details of the present invention will be further clarified by reading through the embodiments described below (hereinafter referred to as "embodiments") with reference to the accompanying drawings. ..

FIG. 1 is a side view showing a configuration example of a train equipped with the derailment sign detection system according to the embodiment of the present invention. FIG. 2 is a plan view showing a bogie frame of a bogie of a train. FIG. 3 is a side view showing a bogie frame of a bogie of a train. FIG. 4 is a block diagram showing a configuration example of a derailment sign detection system. FIG. 5 is a block diagram showing a configuration example of the frequency domain derailment sign detection unit. FIG. 6 is a block diagram showing input / output and determination conditions in the time domain derailment sign detection unit. FIG. 7 is a waveform diagram showing examples of input signals and various wavelets in wavelet analysis. FIG. 8 is a waveform diagram showing a waveform of a Morley wavelet used as a mother wavelet. 9 (a), 9 (b), 9 (c), 9 (d), 9 (e), 9 (f), 9 (g), and 9 (h) are shown. It is a time chart which shows the time transition of the wavelet coefficient of the roll angular velocity and the pitch angular velocity in each of eight kinds of test data obtained by the experiment using the test trajectory. 10 (a) and 10 (b) are three-dimensional graphs showing the distribution state of wavelet coefficients with respect to a set of test data obtained in an experiment using a test trajectory, and FIG. 10 (a) is a roll angular velocity. , FIG. 10B shows the pitch angular velocities, respectively. 11 (a) and 11 (b) are time charts showing the time transition of the wavelet coefficient based on a set of test data obtained in the experiment using the test trajectory, and FIG. 11 (a) is the roll angular velocity. , FIG. 11B shows the pitch angular velocities, respectively.

Specific embodiments of the present invention will be described below with reference to the respective figures.

<Train configuration example>
FIG. 1 shows a configuration example of the train 20 equipped with the derailment sign detection system according to the embodiment of the present invention. FIG. 2 shows a state in which the bogie frame 25 of the bogie 22 of the train 20 is viewed from above. Further, FIG. 3 shows a state in which the bogie frame 25 is viewed from the side surface.

The derailment sign detection system 50 of the present invention is used in a state of being mounted on a train 20 having a configuration as shown in FIG. Although the train 20 shown in FIG. 1 is a two-car train, it can also be used for a train 20 having one or three or more cars.

As shown in FIG. 1, each vehicle body 21 of the train 20 is connected to a lower portion thereof and includes a plurality of bogies 22 that support the vehicle body 21. In the example of FIG. 1, two bogies 22 are provided in front of and behind each vehicle body 21. Each carriage 22 includes a bogie frame 25 as shown in FIGS. 2 and 3.

The bogie frame 25 is provided with an axle 23 so as to straddle the bogie frame 25, and wheels 24 in contact with the rail are connected to both ends of the axle 23. Further, as shown in FIGS. 2 and 3, the angular velocity sensor 35 is arranged near the center of the bogie frame 25 in the front-rear direction and on the left side in the width direction of the train 20. The bogie 22 is also provided with a speed sensor 34 (see FIG. 4) that detects the traveling speed of the train 20.

The angular velocity sensor 35 detects the pitch angular velocity and the roll angular velocity. In this embodiment, an angular velocity sensor 35 configured as a microgyroscope having a tuning fork type vibrator is used. The pitch angular velocity is the angular velocity of rotation (or inclination) about the pitch direction, that is, the width direction of the train 20, and the roll angular velocity is the rotational (or inclination) about the roll direction, that is, the front-rear direction of the train 20. Angular velocity.

<Configuration example of derailment sign detection system 50>
FIG. 4 is a configuration example of the derailment sign detection system 50.

The derailment sign detection system 50 shown in FIG. 4 is prepared for each of the bogies 22 of the train 20 shown in FIG. 1, for example, and the control unit 51 of each derailment sign detection system 50 is installed on the vehicle body 21. The electric signals of the angular velocity sensor 35 and the speed sensor 34 mounted on each carriage 22 are input to the control unit 51 of each derailment sign detection system 50. Of course, it is also possible to centrally control a plurality of bogies 22 of a plurality of vehicle bodies 21 by one control unit 51.

The control unit 51 is a computer, and is provided with hardware having sufficient performance so that the calculation process can be completed in a short time. Further, it is provided with control software for realizing each function corresponding to the frequency domain derailment sign detection unit 10, the time domain derailment sign detection unit 30, and the final determination unit 40. A plurality of independent computers may be provided inside the control unit 51.

The derailment sign detection system 50 shown in FIG. 4 is equipped with two types of derailment sign detection algorithms in order to detect the derailment sign of the train 20 and prevent derailment. One derailment sign detection algorithm is incorporated in the frequency domain derailment sign detection unit 10, and the other derailment sign detection algorithm is incorporated in the time domain derailment sign detection unit 30.

Although the details will be described later, the derailment sign detection algorithm incorporated in the frequency domain derailment sign detection unit 10 inputs the pitch angular velocity θ (t) and the roll angular velocity φ (t) output by the angular velocity sensor 35, and these are input. Wavelet analysis is applied to each of the signals of, and the wavelet coefficient is calculated for each signal. In addition, "t" represents time. Then, the presence or absence of a sign of derailment is identified by comparing each of the wavelet coefficient of the pitch angular velocity and the wavelet coefficient of the roll angular velocity, which change with time series, with a predetermined threshold value. Actually, when the wavelet coefficient of the pitch angular velocity exceeds the threshold value and at the same time the wavelet coefficient of the roll angular velocity exceeds the threshold value, it is detected as a sign of derailment.

On the other hand, the derailment sign detection algorithm incorporated in the time domain derailment sign detection unit 30 is basically the same as the algorithm disclosed in Patent Document 2. That is, the pitch angular velocity θ (t) output by the angular velocity sensor 35, the roll angular velocity φ (t), and the traveling speed V (t) output by the speed sensor 34 are input and processed, respectively. Then, the change in roll angular velocity is predicted based on the calculation of the moving average. Further, the pitch angular velocity and the threshold value are compared, and the predicted value of the roll angular velocity and the threshold value are compared, and the derailment sign is detected based on the result. For each threshold value used by the time domain derailment sign detection unit 30, an appropriate value is adopted according to the traveling speed V (t).

Basically, sufficient performance for derailment sign detection can be obtained only by the frequency domain derailment sign detection unit 10 incorporating the newly developed derailment sign detection algorithm. However, the algorithm of the frequency domain derailment sign detection unit 10 and the algorithm of the time domain derailment sign detection unit 30 have different advantages and disadvantages. Therefore, it is possible to avoid derailment more effectively by properly using the two types of derailment sign detection algorithms.

Therefore, the final determination unit 40 inputs the derailment sign determination output 17 output by the frequency domain derailment sign detection unit 10 and the derailment sign determination output 18 output by the time domain derailment sign detection unit 30, and is based on these signals. And implement optimal train control.

A train brake device 38 and a train watering device 39 are connected to the output of the final determination unit 40. That is, derailment can be prevented by applying braking with the brake device 38 when a sign of derailment is detected. The watering device 39 is a device that sprinkles water on the contact portion between the rail and the wheel flange. That is, when the wheel flange is in a state of riding on the rail as a sign of derailment, water is sprinkled on the contact portion to reduce the friction coefficient. As a result, the wheel flange on the rail can be returned to the normal position, and derailment can be prevented. In the present embodiment, the case where the derailment sign detection system 50 includes the watering device 39 is described as an example, but this is an example, and the derailment is performed in place of the watering device 39 or in addition to the watering device 39. It may be provided with another device to prevent it.

As a typical control example of the final determination unit 40, when the derailment sign determination output 17 output by the frequency domain derailment sign detection unit 10 recognizes the derailment sign, the final determination unit 40 controls the train brake device 38. And control to apply the brake. Further, when the derailment sign determination output 18 output by the time domain derailment sign detection unit 30 recognizes the derailment sign, the final determination unit 40 controls the watering device 39 of the train to sprinkle water and reduce the friction coefficient.

When a sign of derailment is detected, an alarm may be output or a pseudo voice signal or the like may be used to notify that the vehicle is dangerous. However, in reality, derailment cannot be avoided unless watering and brake control are performed within 0.2 seconds after the derailment sign is detected. Therefore, it is desirable that the final determination unit 40 automatically controls watering and braking.

<Frequency domain derailment sign detection unit 10>
FIG. 5 shows a configuration example of the frequency domain derailment sign detection unit 10. The frequency domain derailment sign detection unit 10 shown in FIG. 5 includes two wavelet transform processing units 11 and 12 and a derailment sign determination unit 13.

The wavelet transform processing unit 11 repeatedly samples and inputs a signal of pitch angular velocity θ (t) output by the angular velocity sensor 35 at a constant cycle (for example, 1/200 [second]), and wavelet transform processing is performed on this signal. To carry out. The wavelet coefficient 14 of the pitch angular velocity is obtained as a time-series signal at the output of the wavelet transform processing unit 11. The wavelet transform will be described later.

Further, the wavelet transform processing unit 12 repeatedly samples and inputs a signal of roll angular velocity φ (t) output by the angular velocity sensor 35 at a constant period (for example, 1/200 [second]), and wavelet to this signal. Perform the conversion process. The wavelet coefficient 15 of the roll angular velocity is obtained as a time-series signal at the output of the wavelet transform processing unit 12.

According to the results of various experiments, it was found that there is a high output of low frequency in both the roll angular velocity and the pitch angular velocity when the wheel flange climbing derailment of the train occurs. Therefore, in order to effectively detect the sign of derailment, each of the wavelet transform processing units 11 and 12 is limited to a predetermined low frequency range, for example, 0.5 to 100 [Hz]. To calculate the wavelet coefficient.

The derailment sign determination unit 13 is based on the wavelet coefficient 14 of the pitch angular velocity output by the wavelet transform processing unit 11, the wavelet coefficient 15 of the roll angular velocity output by the wavelet transform processing unit 12, and the wavelet coefficient threshold value 16. Judgment is carried out. Regarding the threshold value 16 of the wavelet coefficient, independent threshold values may be assigned to both the wavelet coefficient 14 of the pitch angular velocity and the wavelet coefficient 15 of the roll angular velocity, but a common threshold value is used for both. Further, in the present embodiment, the threshold value 16 of the wavelet coefficient is a predetermined constant and does not change. However, in some cases, the value of the wavelet coefficient threshold value 16 may be adjusted so as to change slightly depending on, for example, the traveling speed of the train.

When the derailment sign determination unit 13 detects a state in which the value of the wavelet coefficient 14 of the pitch angular velocity exceeds the threshold value 16 and at the same time the value of the wavelet coefficient 15 of the roll angular velocity exceeds the threshold value 16, the derailment sign determination output 17 outputs the derailment sign determination output 17. Outputs a signal indicating detection.

<Time domain derailment sign detection unit 30>
FIG. 6 shows the input / output and determination conditions in the time domain derailment sign detection unit 30.

As shown in FIGS. 6 and 4, signals of pitch angular velocity θ (t), roll angular velocity φ (t), and traveling velocity V (t) are input to the input of the time domain derailment sign detection unit 30. Further, as a parameter used by the time domain derailment sign detection unit 30 in control, as shown in FIG. 6, there are a pitch angular velocity threshold value, a roll angular velocity moving average predicted value threshold value, a detection time, an inclination measurement time, and a predicted time. Here, each value of the pitch angular velocity threshold value and the roll angular velocity moving average predicted value threshold value changes so as to use the optimum value for the traveling velocity V (t).

As shown in the block of the time domain derailment sign detection unit 30 in FIG. 6, the time domain derailment sign detection unit 30 determines the detection of the derailment sign by comparing three conditions, and outputs the result as a warning. To do. The three conditions to be compared are as follows, and are determined by the logical product of these.

(1) The pitch angular velocity θ (t) is equal to or higher than the pitch angular velocity threshold value (speed-dependent).
(2) The moving average value Φ of the roll angular velocity φ (t) is equal to or higher than the threshold value (speed dependent).
(3) The predicted value Φp based on the moving average of the roll angular velocity φ (t) is equal to or higher than the threshold value (speed dependence).
Since the content of the process in the time domain derailment sign detection unit 30 is the same as that of the prior art disclosed in Patent Document 2, detailed description thereof will be omitted.

<Explanation of wavelet transform>
The input signal in the wavelet analysis and each waveform of various wavelets are shown in FIG. The waveform of the Morley wavelet used as the mother wavelet is shown in FIG. However, various waveforms can be used for the mother wavelet according to the analysis target.

In addition, Fourier analysis is generally used as a method for performing frequency analysis of signals. However, when the Fourier transform is performed, the information about time is lost, so that the necessary information cannot be obtained in the application for detecting a sudden change such as a sign of derailment of a train. Further, in the case of short-time Fourier analysis using a humming window, it is difficult to capture a low frequency in a short time, so that a derailment sign cannot be detected within 0.2 seconds, for example.

Wavelets are temporary waves, and wavelet analysis is a method of expressing arbitrary time series data as the sum of wavelets. For example, as shown in FIG. 7, when the wave W1 is input as an arbitrary input signal, it is decomposed into various wavelets, and the wave W1 is divided into, for example, the sum of the wavelets W2, W3, W4, W5, and W6. Can be expressed.

The wavelet transform includes a continuous wavelet transform (CWT) and a discrete wavelet transform (DWT). In the continuous wavelet transform, the mother wavelet is used, and the moved / enlarged / reduced copy and the wave of the input signal are compared with respect to this mother wavelet. In the continuous wavelet transform, the inner product is used to measure the similarity between the signal and the analytic function. Various shapes can be used for the mother wavelet. If the wavelet is a complex value, the CWT is a complex value function of scale and position, and if the signal is a real value, the CWT is a real value function of scale and position. The continuous wavelet transform can be expressed by the following equation.

但し、
Ｃ（ａ，ｂ；ｆ（ｔ），Ψ（ｔ））：ウェーブレット係数（ＣＷＴ係数）
ａ：スケールパラメータ
ｂ：位置パラメータ
ｆ（ｔ）：入力信号（原信号）
Ψ（ｔ）：マザーウェーブレット
ｔ：時間

However,
C (a, b; f (t), Ψ (t)): Wavelet coefficient (CWT coefficient)
a: Scale parameter b: Position parameter f (t): Input signal (original signal)
Ψ (t): Mother wavelet t: Time

That is, the wavelet coefficient is obtained by intermittent changes of the scale parameter (a) and the position parameter (b) based on the mother wavelet Ψ (t) and the input signal f (t). Multiplying each coefficient by the appropriate scaled and moved wavelets (eg, W2 to W6 shown in FIG. 7) yields the constituent wavelets of the original signal.

In the wavelet transform processing units 11 and 12 of the present embodiment, the waveform of the Morley wavelet shown in FIG. 8 is adopted as the mother wavelet Ψ (t) of the wavelet transform. Morley wavelets are available in real and complex versions. The real value version of the Morley wavelet is expressed by the following equation. Constants are used for normalization and reconstruction.

The continuous wavelet transform (CWT) of the first equation (1) can be rewritten as the following equation by using the inverse Fourier transform. This also allows the continuous wavelet transform to be interpreted as frequency-based filtering of the signal.

Equation (3) above indicates that the spread of the wavelet over time causes the contraction of its support in the frequency domain. The center frequency moves toward lower frequencies due to the spread. In the wavelet transform, the expansion of wavelet motion is defined as the conservation of energy. To conserve energy during contraction, frequency support requires an increase in peak energy levels. The quality factor (also sometimes called the filter factor) is the ratio of peak energy to bandwidth. Therefore, the wavelet is sometimes called a constant Q filter. This is because the contraction and expansion of the wavelet frequency support results in a proportional increase or decrease in peak energy. This is an important characteristic of wavelets that are useful in detecting signs of train derailment.

The above equation (3) basically defines CWT as the inverse Fourier transform of the product of the Fourier transforms. This means that the CWT can be calculated using the inverse Fourier transform.
There is an efficient algorithm for the calculation of the discrete Fourier transform. Therefore, in order to enable the adoption of an efficient algorithm in CWT, the concept of CWT is applied to the Fourier region, and the calculation formula of CWT is constructed.

上記第（５）式は、畳み込みとしてＣＷＴを明示的に表現している。 The above equation (4) can be rewritten in the form of the following equation.

The above equation (5) explicitly expresses CWT as a convolution.

When executing a discrete version of CWT, the input sequence is represented as an N-length vector (x [n]). The discrete version of the CWT convolution is expressed by:

In order to obtain the CWT in the form of the above equation (6), it is necessary to calculate the convolution of each value of the shifted parameter (b) and repeat this process for each scale (a). However, when the two series extend in a ring shape and are divided into periods up to the length N, the ring-shaped convolution can be expressed by the following equation (7) as the product of the discrete Fourier transform. CWT is the inverse Fourier transform of the product.

By expressing the CWT as an inverse Fourier transform as described above, it becomes possible to carry out the calculation of the CWT by adopting the fast Fourier algorithm. As a result, the calculation efficiency can be significantly improved and the calculation cost of convolution can be reduced.

Using the method as described above, the wavelet transform processing units 11 and 12 shown in FIG. 5 perform the wavelet transform calculation process, respectively. The wavelet transform processing unit 11 processes the pitch angular velocity θ (t) to calculate the wavelet coefficient 14 of the pitch angular velocity. Further, the wavelet transform processing unit 12 processes the roll angular velocity φ (t) to calculate the wavelet coefficient 15 of the roll angular velocity. The calculated pitch angular velocity wavelet coefficient 14 and the roll angular velocity wavelet coefficient 15 are both time-series signals that change.

<Explanation of experimental data>
Parameters such as various threshold values are appropriately determined in advance so that each of the frequency domain derailment sign detection unit 10 and the time domain derailment sign detection unit 30 of the derailment sign detection system 50 shown in FIG. 4 can correctly detect the train derailment sign detection unit 30. There is a need to. Therefore, an experiment was conducted and the data of the result was used to adjust the derailment sign detection system 50.

On the test track of the Chiba Laboratory of the University of Tokyo, a flange climbing derailment test was conducted at various running speeds using a full-scale trolley. In this test, various measures were taken so that the derailment test could be performed safely. Further, similarly to the train 20 shown in FIG. 1, the angular velocity sensor 35, the speed sensor 34, and other sensors were mounted on the bogie and the test was carried out. That is, time-series data including the pitch angular velocity θ (t), the roll angular velocity φ (t), and the traveling velocity V (t) in the trolley were measured and recorded using a data logger.

As a result of this experiment, "Test 1", "Test 2", "Test 3", "Test 4", "Test 5", "Test 6", "Test 7", and "Test 7" shown in Table 1 below. Eight sets of data from "Test 8" were extracted and each data was analyzed.

The time transitions of the wavelet coefficients of the roll angular velocity (Roll) and the pitch angular velocity (Pitch) in each of the eight types of test data obtained in the experiment using the test trajectory are shown in FIGS. 9 (a), 9 (b), and 9. (C), FIG. 9 (d), FIG. 9 (e), FIG. 9 (f), FIG. 9 (g), and FIG. 9 (h), respectively. In FIGS. 9 (a) to 9 (h), the horizontal axis represents time (seconds) and the vertical axis represents the value of the wavelet coefficient.

In FIGS. 9 (a) to 9 (h), the portion surrounded by a square represents a portion where a derailment or a sign thereof has occurred. That is, when the wheel flange of the bogie rides on the rail, both the wavelet coefficient of the roll angular velocity (Roll) and the wavelet coefficient of the pitch angular velocity (Pitch) increase at the same time. That is, in a situation where derailment or a sign thereof occurs, both the wavelet coefficient of the roll angular velocity (Roll) and the wavelet coefficient of the pitch angular velocity (Pitch) are increased to a predetermined value or more.

Further, as shown in Table 1, in "Test 1" to "Test 8", the traveling speeds immediately before the start of riding on the wheel flanges are different, but each of FIGS. 9 (a) to 9 (h). There is no significant difference in the magnitude of the wavelet coefficient at the location where the derailment sign occurs.

Therefore, in the present embodiment, a constant constant independent of the traveling speed is given as the threshold value 16 of the wavelet coefficient given to the derailment sign determination unit 13 of the frequency domain derailment sign detection unit 10. Specifically, in the same environment as the data of FIGS. 9 (a) to 9 (h), it is assumed that a value of about “0.08” is assigned as the threshold value 16 of the wavelet coefficient. Therefore, when the derailment sign determination unit 13 shown in FIG. 5 detects that the wavelet coefficient 14 of the pitch angular velocity exceeds "0.08" and at the same time the wavelet coefficient 15 of the roll angular velocity exceeds "0.08". In addition, it is judged that there is a sign of derailment.

3D graphs showing the distribution of wavelet coefficients in the time axis direction and the frequency axis direction for a set of test data obtained in an experiment using a test trajectory are shown in FIGS. 10 (a) and 10 (b). FIG. 10A shows the roll angular velocity, and FIG. 10B shows the pitch angular velocity.

In addition, the time transition of the wavelet coefficient based on a set of test data obtained in the experiment using the test trajectory is shown in FIGS. 11 (a) and 11 (b). FIG. 11A shows the roll angular velocity, and FIG. 11B shows the pitch angular velocity.

In the derailment sign detection algorithm adopted by the frequency domain derailment sign detection unit 10, the time transition of the power spectral density of the pitch angular velocity and the roll angular velocity in the low frequency region (for example, 0.5 to 100 [Hz]) is monitored. Can be done. That is, the sign of derailment is detected by monitoring the changes as shown in the graphs of FIGS. 10 (a) and 10 (b).

By analyzing the obtained experimental data, the frequency components of the pitch angular velocity and the roll angular velocity distinguish between the normal running state of the bogie (including the disturbance generated at the rail seam, etc.) and the wheel flange riding derailment state. It turned out to be very effective above. Further, by adopting the wavelet analysis of the pitch angular velocity and the roll angular velocity, the time transition of the frequency component can be monitored in real time, so that it can be detected within 0.2 seconds after the occurrence of the derailment sign.

Further, as in the derailment sign detection system 50 shown in FIG. 4, the derailment sign detection unit 10 and the time domain derailment sign detection unit 30 are adopted and two types of derailment sign detection algorithms are used in combination to derail. The accuracy of predictive detection can be further improved, and effective derailment prevention control becomes possible. For example, in the case of the derailment sign detection algorithm of the time domain derailment sign detection unit 30 alone, erroneous detection of the derailment sign may occur due to the influence of a large value due to the disturbance generated at the rail joint. However, by combining an algorithm that employs wavelet analysis, it is possible to suppress the occurrence of false positives.

The functions of each part of the derailment sign detection system 50 can be realized as a dedicated control device mounted on a train, or can be realized by incorporating it as an application program in a general-purpose device such as a personal computer.

Here, the features of the derailment sign detection system, the control device, the derailment sign detection method, and the embodiment of the derailment sign detection program according to the present invention described above are briefly summarized below [1] to [6], respectively.
[1] A detection unit (angular velocity sensor 35) provided on the train to detect the pitch angular velocity and the roll angular velocity of the running train.
The wavelet coefficient of the pitch angular velocity is calculated as the first wavelet coefficient, the wavelet coefficient of the roll angular velocity is calculated as the second wavelet coefficient, and the calculated first wavelet coefficient and the second wavelet coefficient are calculated. When each exceeds the predetermined threshold, the control device (frequency region derailment sign detection unit 10) that determines the derailment sign of the train, and
When the control device determines that it is a derailment sign, an output unit (final determination unit 40) that notifies the derailment sign to the outside,
Derailment sign detection system (50).

[2] The control device (wavelet transform processing units 11 and 12) calculates the first wavelet coefficient and the second wavelet coefficient only within the range of the low frequency region.
The derailment sign detection system according to the above [1].

[3] The control device (control unit 51) calculates a moving average of at least the roll angular velocity based on the history of detected values, predicts a change in the roll angular velocity from the moving average, and predicts the roll angular velocity. Based on the calculated first wavelet coefficient and the second wavelet coefficient, the derailment sign of the train is determined.
The derailment sign detection system according to the above [1] or [2].

[4] Based on the pitch angle speed and roll angle speed of the running train provided in the train and detected by a predetermined detection unit, the wavelet coefficient of the pitch angle speed is calculated as the first wavelet coefficient, and the roll angle speed is calculated. The wavelet coefficient is calculated as the second wavelet coefficient, and when the calculated first wavelet coefficient and the second wavelet coefficient each exceed the predetermined threshold values, it is determined as a derailment sign of the train and a derailment sign. When it is determined, the control device (frequency region derailment sign detection unit 10) notifies the outside of the derailment sign detection.

[5] Enter the detected values of the pitch angular velocity and roll angular velocity of the running train.
The wavelet coefficient of the pitch angular velocity is calculated as the first wavelet coefficient (corresponding to the function of the wavelet transform processing unit 11).
The wavelet coefficient of the roll angular velocity is calculated as the second wavelet coefficient (corresponding to the function of the wavelet transform processing unit 12).
The calculated first wavelet coefficient and the second wavelet coefficient are each compared with a predetermined threshold value (corresponding to the function of the derailment sign determination unit 13).
When the first wavelet coefficient and the second wavelet coefficient exceed the threshold value, it is determined that the train is a derailment sign, and the derailment sign detection is notified to the outside (corresponding to the function of the final determination unit 40). ,
Derailment sign detection method.

[6] A step of inputting the detected values of the pitch angular velocity and the roll angular velocity of the running train, and
A step of calculating the wavelet coefficient of the pitch angular velocity as the first wavelet coefficient (corresponding to the function of the wavelet transform processing unit 11) and
The step of calculating the wavelet coefficient of the roll angular velocity as the second wavelet coefficient (corresponding to the function of the wavelet transform processing unit 12) and
A step of comparing each of the calculated first wavelet coefficient and the second wavelet coefficient with a predetermined threshold value (corresponding to the function of the derailment sign determination unit 13).
When the first wavelet coefficient and the second wavelet coefficient exceed the threshold value, it is determined that the train is a derailment sign, and the step of notifying the outside of the derailment sign detection (corresponding to the function of the final determination unit 40). )When,
A derailment sign detection program that causes a computer to perform processing including.

10 Frequency domain derailment sign detection unit 11, 12 Wavelet transform processing unit 13 Derailment sign judgment unit 14 Pitch angular velocity wavelet coefficient 15 Roll angular velocity wavelet coefficient 16 Wavelet coefficient threshold 17, 18 Derailment sign judgment output 20 Train 21 Body 22 trolley 23 Axle 24 Wheels 25 Bogey frame 30 time domain derailment sign detection unit 31, 32 Train control signal 34 Speed sensor 35 Angle speed sensor 38 Train brake device 39 Train sprinkler 40 Final judgment unit 50 Derailment sign detection system 51 Control unit

Claims (5)

A detector installed on the train that detects the pitch angular velocity and roll angular velocity of the running train,
The wavelet coefficient of the pitch angular velocity is calculated as the first wavelet coefficient, the wavelet coefficient of the roll angular velocity is calculated as the second wavelet coefficient, and the calculated first wavelet coefficient and the second wavelet coefficient are calculated. When the coefficients exceed the predetermined coefficients, the control device that determines the derailment sign of the train and
When the control device determines that it is a derailment sign, an output unit that notifies the derailment sign to the outside and
Equipped with a,
The control device calculates the first wavelet coefficient and the second wavelet coefficient only in the range of 0.5 to 100 Hz, which is a low frequency region.
Derailment sign detection system. The control device calculates a moving average of at least the roll angular velocity based on the history of detected values, predicts a change in the roll angular velocity from the moving average, and uses the predicted value of the roll angular velocity and the calculated first one. The derailment sign of the train is determined based on the wavelet coefficient of the above and the second wavelet coefficient of the above.
The derailment sign detection system according to claim 1. Based on the pitch angle speed and roll angle speed of the running train provided in the train and detected by a predetermined detection unit, the wavelet coefficient of the pitch angle speed is calculated as the first wavelet coefficient, and the wavelet coefficient of the roll angle speed is calculated. When the first wavelet coefficient calculated as the second wavelet coefficient and the calculated second wavelet coefficient exceed the predetermined threshold values, it is determined as a derailment sign of the train and determined as a derailment sign. In that case, the derailment sign detection is notified to the outside,
The first wavelet coefficient and the second wavelet coefficient are calculated only within the range of 0.5 to 100 Hz, which is a low frequency region.
Control device. Enter the detected values of the pitch angular velocity and roll angular velocity of the running train,
The wavelet coefficient of the pitch angular velocity is calculated as the first wavelet coefficient, and the wavelet coefficient is calculated.
The wavelet coefficient of the roll angular velocity is calculated as the second wavelet coefficient, and the wavelet coefficient is calculated.
Comparing each of the calculated first wavelet coefficient and the second wavelet coefficient with a predetermined threshold value,
When the first wavelet coefficient and the second wavelet coefficient exceed the threshold value, it is determined that the train is a derailment sign, and the derailment sign detection is notified to the outside.
The first wavelet coefficient and the second wavelet coefficient are calculated only within the range of 0.5 to 100 Hz, which is a low frequency region.
Derailment sign detection method. Steps to input the detected values of pitch angular velocity and roll angular velocity of the running train,
The step of calculating the wavelet coefficient of the pitch angular velocity as the first wavelet coefficient, and
The step of calculating the wavelet coefficient of the roll angular velocity as the second wavelet coefficient, and
A step of comparing each of the calculated first wavelet coefficient and the second wavelet coefficient with a predetermined threshold value.
When the first wavelet coefficient and the second wavelet coefficient exceed the threshold value, it is determined that the train is a derailment sign, and the derailment sign detection is notified to the outside.
Let the computer perform the process including
The first wavelet coefficient and the second wavelet coefficient are calculated only within the range of 0.5 to 100 Hz, which is a low frequency region.
Derailment sign detection program.

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