Derailment sign detection system, control device, derailment sign detection method, and derailment sign detection program
阅读说明:本技术 脱轨预兆检测系统、控制装置、脱轨预兆检测方法以及脱轨预兆检测程序 (Derailment sign detection system, control device, derailment sign detection method, and derailment sign detection program ) 是由 须田义大 林世彬 兰德尔·德温·雷迪 影山真佐富 古贺进一郎 久保光太 川锅哲也 角田 于 2018-06-01 设计创作,主要内容包括:针对从搭载于转向架的角速度传感器(35)输出的俯仰角速度θ(t)、横滚角速度<Image he="65" wi="134" file="DDA0002306073330000011.GIF" imgContent="drawing" imgFormat="GIF" orientation="portrait" inline="no"></Image>分别应用小波分析,算出俯仰角速度的小波系数(14)和横滚角速度的小波系数(15)。将以时间序列变化的2个小波系数(14、15)分别与小波系数的阈值(16)进行比较,在两者超过阈值时检测到脱轨预兆。例如利用针对0.5~100Hz的低频率区域算出的小波系数。将频率区域与时间区域的2种脱轨预兆检测算法组合以提高脱轨预兆检测精度。通过采用小波分析,从而能够进行频率区域的实时处理,实现脱轨预防。(For the pitch angle velocity theta (t) and roll angle velocity outputted from an angular velocity sensor (35) mounted on a bogie Wavelet analysis is applied to calculate a wavelet coefficient (14) of pitch angle velocity and a wavelet coefficient (15) of roll angle velocity. 2 wavelet coefficients (14, 15) varying in time series are respectively compared with a threshold value (16) of wavelet coefficients, and a sign of derailment is detected when both exceed the threshold value. For example, wavelet coefficients calculated for a low frequency region of 0.5 to 100Hz are used. Dividing frequency region and time regionThe 2 derailment precursor detection algorithms of the domain are combined to improve the derailment precursor detection accuracy. By adopting wavelet analysis, real-time processing of a frequency region can be performed, and derailment prevention is realized.)
The derailment sign detection system of kinds, comprising:
a detection unit that is provided to a train and detects a pitch angle rate and a roll angle rate of the running train;
a controller that calculates a wavelet coefficient of the pitch angle velocity as a 1 st wavelet coefficient and a wavelet coefficient of the roll angle velocity as a 2 nd wavelet coefficient, and determines a sign of derailment of the train when the calculated 1 st wavelet coefficient and the calculated 2 nd wavelet coefficient each exceed a predetermined threshold value; and
an output unit that notifies the outside of the sign of derailment when the control device determines that the sign of derailment is present.
2. The derailment precursor detection system of claim 1,
the control means is limited to calculating the 1 st wavelet coefficient and the 2 nd wavelet coefficient only in a range of a low frequency region.
3. The derailment precursor detection system of claim 1 or 2,
the control device calculates a moving average value based on a history of detection values at least for the roll angular velocity, predicts a change in the roll angular velocity from the moving average value, and determines a sign of derailment of the train based on the predicted value of the roll angular velocity and the calculated 1 st wavelet coefficient and the 2 nd wavelet coefficient.
A control device of , wherein,
the control device is installed in a train, calculates a wavelet coefficient of a pitch angle rate as a 1 st wavelet coefficient and a wavelet coefficient of a roll angle rate as a 2 nd wavelet coefficient based on a pitch angle rate and a roll angle rate of a running train detected by a predetermined detection unit, determines a sign of derailment of the train when the calculated 1 st wavelet coefficient and the calculated 2 nd wavelet coefficient each exceed a predetermined threshold, and notifies detection of the sign of derailment to the outside when the calculated sign of derailment is determined.
5, derailment warning sign detection method, characterized in that,
inputting detection values of a pitch angle speed and a roll angle speed of a running train;
calculating a wavelet coefficient of the pitch angle velocity as a 1 st wavelet coefficient;
calculating a wavelet coefficient of the roll angular velocity as a 2 nd wavelet coefficient;
comparing the calculated 1 st wavelet coefficient and the 2 nd wavelet coefficient with a predetermined threshold value respectively; and
and when the 1 st wavelet coefficient and the 2 nd wavelet coefficient exceed the threshold, determining that the train is in derailment sign, and notifying the detection of the derailment sign to the outside.
A derailment precursor detection program of , which causes a computer to execute a process including the steps of:
inputting detection values of a pitch angle velocity and a roll angle velocity of a running train;
calculating a wavelet coefficient of the pitch angle velocity as a 1 st wavelet coefficient;
calculating a wavelet coefficient of the roll angular velocity as a 2 nd wavelet coefficient;
comparing the calculated 1 st wavelet coefficient and the 2 nd wavelet coefficient with a predetermined threshold value; and
and a step of determining a sign of derailment of the train when the 1 st wavelet coefficient and the 2 nd wavelet coefficient exceed the threshold, and notifying detection of the sign of derailment to the outside.
Technical Field
The present invention relates to a derailment sign detection system, a control device, a derailment sign detection method, and a derailment sign detection program.
Background
As a prior art for detecting a sign of derailment of a railway train, technologies described in
In the technique of
In the technique of patent document 2, the detected roll angular velocity of the bogie is stored in the storage device, a moving average value is calculated from the history of the roll angular velocity, and a predicted value of the roll angular velocity is calculated from the moving average value. Then, when the predicted values of the detected pitch angle velocity and roll angle velocity of the bogie after a predetermined time each exceed a predetermined threshold value, it is determined as a sign of derailment of the train.
Disclosure of Invention
Technical problem to be solved by the invention
Although the prior art of
Although various methods can be adopted for analysis of the pitch angle velocity, the roll angle velocity, and the like, when a sign of derailment of the train is detected, if the sign is not detected within 0.2 seconds from the occurrence of the sign and a countermeasure is taken immediately, it is difficult to avoid the limitation of derailment, and therefore, a method other than real-time analysis cannot be basically adopted.
The present invention has been made in view of the above circumstances, and an object thereof is to provide a derailment sign detection system, a control device, a derailment sign detection method, and a derailment sign detection program that can improve the detection accuracy of a derailment sign of a train.
Means for solving the problems
In order to achieve the above 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 (6).
(1) A derailment sign detection system, comprising:
a detection unit that is provided to a train and detects a pitch angle velocity and a roll angle velocity of the running train;
a controller that calculates a wavelet coefficient of the pitch angle velocity as a 1 st wavelet coefficient and a wavelet coefficient of the roll angle velocity as a 2 nd wavelet coefficient, and determines a sign of derailment of the train when the calculated 1 st wavelet coefficient and the calculated 2 nd wavelet coefficient each exceed a predetermined threshold value; and
an output unit that notifies the outside of the sign of derailment when the control device determines that the sign of derailment is present.
According to the derailment sign detection system having the configuration of the above (1), the detection accuracy of the derailment sign of the train can be improved. That is, by comparing the 1 st wavelet coefficient and the 2 nd wavelet coefficient obtained by wavelet analysis of the detected values of the pitch angle velocity and the roll angle velocity with the threshold value and performing determination, it is possible to reduce erroneous detection due to the influence of disturbance occurring at a portion such as a track joint at low speed.
(2) The derailment sign detection system according to (1) above, wherein the control device calculates the 1 st wavelet coefficient and the 2 nd wavelet coefficient only in a range of a low frequency region.
According to the derailment sign detection system having the configuration of the above (2), since it is possible to improve the detection accuracy of the derailment sign of the train by steps, that is, since it is confirmed that there is a high output of a low frequency in both the pitch angle velocity and the roll angle velocity when the wheel edge of the train gets over the track until the derailment, the detection accuracy of the derailment sign is improved by using the 1 st wavelet coefficient and the 2 nd wavelet coefficient calculated in the range of the low frequency region.
(3) The derailment sign detection system according to the above (1) or (2), wherein the control device calculates a moving average value based on a history of detection values at least for the roll angular velocity, predicts a change in the roll angular velocity from the moving average value, and determines the derailment sign of the train based on the predicted value of the roll angular velocity and the calculated 1 st wavelet coefficient and 2 nd wavelet coefficient.
According to the derailment sign detection system having the configuration of (3) above, it is possible to determine the condition in which the predicted value of the roll angular velocity, the calculated 1 st wavelet coefficient, and the first 2 wavelet coefficient are combined, and it is possible to further improve the detection accuracy of the derailment sign.
(4) A control device installed in a train, wherein a wavelet coefficient of a pitch angle rate is calculated as a 1 st wavelet coefficient and a wavelet coefficient of a roll angle rate is calculated as a 2 nd wavelet coefficient based on a pitch angle rate and a roll angle rate of a running train detected by a predetermined detection unit, and when the calculated 1 st wavelet coefficient and the calculated 2 nd wavelet coefficient each exceed a predetermined threshold value, a sign of derailment of the train is determined, and when a sign of derailment is determined, detection of the sign of derailment is notified to the outside.
According to the control device having the configuration of the above (4), the detection accuracy of the sign of derailment of the train can be improved in the same manner as the sign of derailment detection system of the above (1).
(5) method for detecting derailment sign, wherein,
inputting detection values of a pitch angle speed and a roll angle speed of a running train;
calculating a wavelet coefficient of the pitch angle velocity as a 1 st wavelet coefficient;
calculating a wavelet coefficient of the roll angular velocity as a 2 nd wavelet coefficient;
comparing the calculated 1 st wavelet coefficient and the 2 nd wavelet coefficient with a predetermined threshold value respectively;
and when the 1 st wavelet coefficient and the 2 nd wavelet coefficient exceed the threshold, determining that the train is in derailment sign, and notifying the detection of the derailment sign to the outside.
According to the derailment precursor detection method having the configuration of (5), the accuracy of detecting the derailment precursor of the train can be improved as in the derailment precursor detection system of (1).
(6) derailment sign detection programs, wherein a computer is caused to execute a process including the steps of inputting detected values of a pitch angle velocity and a roll angle velocity of a running train;
calculating a wavelet coefficient of the pitch angle velocity as a 1 st wavelet coefficient;
calculating a wavelet coefficient of the roll angular velocity as a 2 nd wavelet coefficient;
comparing the calculated 1 st wavelet coefficient and the 2 nd wavelet coefficient with a predetermined threshold value; and
and a step of determining a sign of derailment of the train when the 1 st wavelet coefficient and the 2 nd wavelet coefficient exceed the threshold, and notifying detection of the sign of derailment to the outside.
By executing the derailment precursor detection program having the configuration of (6) above with a predetermined computer, the accuracy of detecting the derailment precursor of the train can be improved as in the derailment precursor detection system of (1) above.
Effects of the invention
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, the detection accuracy of the derailment sign of the train can be improved. That is, since it is confirmed that there is a high output with a low frequency for both the pitch angle velocity and the roll angle velocity when the wheel edge of the train gets over the track until derailment, the detection accuracy of the derailment sign is improved by using the 1 st wavelet coefficient and the 2 nd wavelet coefficient calculated in the range of the low frequency region.
The present invention has been described above in a concise manner, and further, details of the present invention should be further clarified by reading modes for carrying out the invention (hereinafter, referred to as "embodiments") described below with reference to the drawings.
Drawings
Fig. 1 is a side view showing a configuration example of a train on which a derailment sign detection system according to an embodiment of the present invention is mounted.
Fig. 2 is a plan view showing a bogie frame of a bogie of the train.
Fig. 3 is a side view of a bogie frame showing a bogie of the train.
Fig. 4 is a block diagram showing a configuration example of the 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 conditions of input/output and determination in the time zone derailment sign detection unit.
Fig. 7 is a waveform diagram showing an example of an input signal and various wavelets in wavelet analysis.
Fig. 8 is a waveform diagram showing the waveform of a Morlet wavelet used as a mother wavelet.
Fig. 9 (a), 9 (b), 9 (c), 9 (d), 9 (e), 9 (f), 9 (g), and 9 (h) are time charts showing the time courses of wavelet coefficients of roll and pitch velocities obtained in the experiment using the test trajectory for each of the 8 types of test data.
Fig. 10 (a) and 10 (b) are three-dimensional graphs showing the distribution state of wavelet coefficients according to 1 set of test data obtained in an experiment using a test trajectory, fig. 10 (a) shows roll angular velocity, and fig. 10 (b) shows pitch angular velocity.
Fig. 11 (a) and 11 (b) are time charts showing the time transition of wavelet coefficients based on 1 set of test data obtained in an experiment using a test trajectory, fig. 11 (a) shows roll angular velocity, and fig. 11 (b) shows pitch angular velocity.
Description of the symbols
10: frequency region derailment sign detection unit
11. 12: wavelet transform processing unit
13: derailment sign determination unit
14: wavelet coefficient of pitch angle velocity
15: wavelet coefficient of roll angular velocity
16: threshold of wavelet coefficient
17. 18: derailment warning sign determination output
20: train with movable track
21: vehicle body
22: steering frame
23: axle shaft
24: wheel of vehicle
25: steering frame
30: time zone derailment sign detection unit
31. 32: train control signal
34: speed sensor
35: angular velocity sensor
38: brake device for train
39: train sprinkler
40: final determination unit
50: derailment warning sign detection system
51: control unit
Detailed Description
Specific embodiments according to the present invention will be described below with reference to the drawings.
< example of train construction >
Fig. 1 shows a configuration example of a
The sign-off-
As shown in fig. 1, each vehicle body 21 of the
The
The
< example of configuration of derailment
Fig. 4 shows an example of the structure of the derailment
For example, the derailment
The
The derailment
As will be described in detail later, in the derailment sign detection algorithm built in the frequency range derailment
On the other hand, , the derailment sign detection algorithm built in the time zone derailment
Basically, sufficient performance can be obtained for the derailment precursor detection only by the newly developed frequency-region derailment
Then, the
The
As a typical control example of the
Further, when a sign of derailment is detected, an alarm may be output, a danger may be notified using an analog voice signal, or the like. However, in practice, if the control of the sprinkler and the brake is not performed within 0.2 seconds from the detection of the sign of derailment, the derailment cannot be avoided. Therefore, it is preferable that the
< frequency region derailment
Fig. 5 shows a configuration example of the frequency domain derailment
The wavelet
In addition, the wavelet
From the results of various experiments, it is found that when the edge of the wheel of the train moves up the track and derailment occurs, both the roll angle velocity and the pitch angle velocity have high outputs with low frequencies. In order to effectively detect the sign of derailment, the wavelet
The derailment
When the value of the wavelet coefficient 14 of the pitch angle velocity exceeds the threshold value 16 and the value of the
< time zone derailment
Fig. 6 shows conditions of input/output and determination in the time zone derailment
As shown in fig. 6 and 4, the time zone derailment
As shown in a block of the time zone derailment
(1) The pitch angle rate θ (t) is equal to or higher than a threshold value (speed dependence) of the pitch angle rate.
(2) Roll angular velocity
Is equal to or higher than the threshold value (speed-dependent).(3) Based on roll angular velocity
The predicted value Φ p of the moving average value of (2) is equal to or greater than the threshold value (speed dependence).The contents of the processing in the time zone derailment
< description of wavelet transform >
Fig. 7 shows respective waveforms of an input signal and various wavelets in wavelet analysis. In addition, fig. 8 shows the waveform of a Morlet wavelet used as a mother wavelet. However, the mother wavelet can use various waveforms according to the analysis object.
However, when fourier transform is performed, information related to time is lost, and therefore, necessary information cannot be obtained in an application for detecting a sudden change such as a sign of derailment of a train.
Wavelets are temporary waves, and wavelet analysis is a method of expressing arbitrary time-series data as a sum of wavelets. For example, as shown in fig. 7, when a wave W1 is input as an arbitrary input signal, the wave W1 can be decomposed into various wavelets, and for example, the wave W1 can be expressed as the sum of wavelets W2, W3, W4, W5, and W6.
Among the wavelet transforms there are Continuous Wavelet Transforms (CWT) and Discrete Wavelet Transforms (DWT). In the continuous wavelet transform, a mother wavelet is used, and a copy function obtained by shifting, enlarging, or reducing the mother wavelet is compared with a wave of an input signal. In the continuous wavelet transform, the determination of the approximation of the signal to the analysis function uses the inner product. A variety of shapes can be used in the mother wavelet. When the wavelet is complex, the CWT becomes a complex function of scale and position, and when the signal is real, the CWT becomes a real function of scale and position. The continuous wavelet transform can be represented as follows.
[ mathematical formula 1]
Wherein the content of the first and second substances,
c (a, b; f (t), Ψ (t)): wavelet coefficient (CWT coefficient)
a: dimension parameter
b: location parameter
f (t): input signal (original signal)
Ψ (t): mother wavelet
t: time of day
In other words, wavelet coefficients are obtained based on the mother wavelet Ψ (t) and the input signal f (t) according to the discontinuous changes of the scale parameter (a) and the position parameter (b). When each coefficient is multiplied by a wavelet (for example, W2 to W6 shown in fig. 7) obtained by appropriate enlargement/reduction and movement, a constituent wavelet of the original signal is generated.
In the wavelet
[ mathematical formula 2]
The Continuous Wavelet Transform (CWT) of the above formula (1) can be rewritten into the following formula using an inverse fourier transform. Thereby, the continuous wavelet transform can also be interpreted as a filtering based on the frequency of the signal.
[ mathematical formula 3]
The above expression (3) indicates that the expansion of the wavelet after the elapse of time causes the contraction of the support thereof in the frequency domain. The center frequency shifts to a low frequency direction due to the spread. In wavelet transform, the expansion of wavelet action is defined as the conservation of energy. Frequency support requires an increase in the peak energy level in order to conserve energy during contraction. The quality coefficient (or sometimes also referred to as a filter coefficient) is the ratio of the peak energy to the bandwidth. Thus, wavelets are sometimes referred to as constant Q filters. The contraction and expansion of the frequency support of the wavelet is due to an increase or decrease proportional to the peak energy. This is an important characteristic of wavelets that have utility in detecting signs of derailment in a train.
The above expression (3) basically defines CWT as an inverse fourier transform of a product of fourier transform. This means that the CWT can be calculated using an inverse fourier transform.
Efficient algorithms exist for the computation of the discrete fourier transform. Therefore, since an efficient algorithm of the CWT can be adopted, the calculation formula of the CWT can be constructed by applying the viewpoint of the CWT to the fourier region.
[ mathematical formula 4]
The above formula (4) can be rewritten into the following formula.
[ math figure 5]
The above expression (5) explicitly expresses the CWT in the form of a convolution.
In the case of a discrete form of CWT, the input sequence is represented as an N-length vector (x [ N ]). The discrete form of the convolution of the CWT is expressed as the following equation.
[ mathematical formula 6]
In order to obtain the CWT in the form of the above equation (6), it is necessary to calculate the product of each value of the parameter (b) of the migration, and this procedure is repeated for each scale (a). However, when the 2 sequences are extended in a circular shape and are phased to the length N, the circular product is expressed as a product of discrete fourier transform in the following expression (7). CWT is the inverse fourier transform of the product.
[ mathematical formula 7 ]
By representing the CWT in the form of an inverse fourier transform as described above, the computation of the CWT can be performed using a high-speed fourier algorithm. Therefore, the calculation efficiency can be greatly improved, and the calculation cost of the product can be reduced.
Using the above-described technique, each of the wavelet
< description of Experimental data >
It is necessary to appropriately determine various parameters such as thresholds in advance so that the frequency-area derailment-
On a test track of a thousand leaf laboratory of tokyo university, a derailment test in which the edge of a wheel goes over the track was performed for various running speeds using a real-world large bogie. In this test, various efforts and time are required to perform the derailment test safely. In addition, similarly to the
As a result of this experiment, 8 sets of data, i.e., "
[ TABLE 1]
Test number
Speed just before the edge of the wheel starts to cross the track [ km/h ]]
11.85
Test 2
8.11
Test 3
5.31
Test 4
11.85
7.54
Test 6
5.27
Test 7
7.5
Test 8
3.51
Fig. 9 (a), 9 (b), 9 (c), 9 (d), 9 (e), 9 (f), 9 (g), and 9 (h) show the wavelet coefficients of the Roll rate (Roll) and the Pitch rate (Pitch) of each of 8 types of test data obtained in the experiment using the test trajectory. In fig. 9 (a) to 9 (h), the horizontal axis of each image represents time (seconds), and the vertical axis represents the value of the wavelet coefficient.
In fig. 9 (a) to 9 (h), the parts surrounded by the boxes indicate the parts where derailment or the sign thereof occurs, that is, when the wheel edge of the bogie goes over the track, the values of both the wavelet coefficient of the Roll angular velocity (Roll) and the wavelet coefficient of the Pitch angular velocity (Pitch) become large at the same time.
As shown in table 1, the traveling speeds immediately before the wheel edge moves on the track are different from each other in "
Therefore, in the present embodiment, a fixed constant independent of the running speed is given as the threshold value 16 of the wavelet coefficient supplied to the derailment
Fig. 10 (a) and 10 (b) show three-dimensional images showing the distribution states of wavelet coefficients in the time axis direction and the frequency axis direction of 1 set of test data obtained in an experiment using a test track. Fig. 10 (a) shows roll angular velocity, and fig. 10 (b) shows pitch angular velocity.
Fig. 11 (a) and 11 (b) show the time transition of wavelet coefficients based on 1 set of test data obtained in an experiment using a test trajectory. Fig. 11 (a) shows a roll angular velocity, and fig. 11 (b) shows a pitch angular velocity.
In the derailment sign detection algorithm employed by the frequency region derailment
As is clear from analysis of the obtained experimental data, the frequency components of the pitch angle velocity and the roll angle velocity are very effective in distinguishing between a normal running state of the bogie (including disturbances occurring at a track joint or the like) and a derailment state of the track over the edge of the wheel. Further, by using wavelet analysis of the pitch angle velocity and the roll angle velocity, the temporal change of the frequency components can be monitored in real time, and therefore, the sign of derailment can be detected within 0.2 seconds from the occurrence of the sign of derailment.
Further, as shown in the derailment
The functions of each part of the derailment
Features of the embodiments of the derailment precursor detection system, the control device, the derailment precursor detection method, and the derailment precursor detection program according to the present invention are briefly summarized in the following [1] to [6], respectively.
[1] A derailment sign detection system (50) comprising:
a detection unit (angular velocity sensor 35) that is provided in the train and detects the pitch angle velocity and the roll angle velocity of the running train;
a control device (frequency range derailment sign detection means 10) that calculates a wavelet coefficient of the pitch angle velocity as a 1 st wavelet coefficient and a wavelet coefficient of the roll angle velocity as a 2 nd wavelet coefficient, and determines a derailment sign of the train when the calculated 1 st wavelet coefficient and the calculated 2 nd wavelet coefficient each exceed a predetermined threshold value;
and an output unit (final determination unit 40) that notifies the outside of the sign of derailment when the control device determines that the sign of derailment is present.
[2] The derailment sign detection system according to [1] above, wherein the control device (wavelet
[3] The derailment sign detection system according to [1] or [2] above, wherein the control device (control unit 51) calculates a moving average value based on a history of detection values at least for the roll angular velocity, predicts a change in the roll angular velocity from the moving average value, and determines the derailment sign of the train based on the predicted value of the roll angular velocity and the calculated 1 st wavelet coefficient and 2 nd wavelet coefficient.
[4] A control device (a frequency range sign derailment detection means 10) provided in a train, wherein a wavelet coefficient of a pitch angle rate is calculated as a 1 st wavelet coefficient and a wavelet coefficient of a roll angle rate is calculated as a 2 nd wavelet coefficient based on a pitch angle rate and a roll angle rate of a running train detected by a predetermined detection unit, and when the calculated 1 st wavelet coefficient and the calculated 2 nd wavelet coefficient each exceed a predetermined threshold value, the control device determines that the train is a sign derailed, and when the control device determines that the train is a sign derailed, the control device notifies the outside of the sign derailment detection.
[5] method for detecting derailment sign, wherein,
inputting detection values of a pitch angle speed and a roll angle speed of a running train;
calculating a wavelet coefficient of the pitch angle rate as a 1 st wavelet coefficient (corresponding to a function of the wavelet transform processing unit 11);
a wavelet coefficient for calculating the roll angular velocity as a 2 nd wavelet coefficient (corresponding to the function of the wavelet transform processing unit 12);
comparing the calculated 1 st wavelet coefficient and the calculated 2 nd wavelet coefficient with a predetermined threshold value (corresponding to the function of the derailment sign determination unit 13);
when the 1 st wavelet coefficient and the 2 nd wavelet coefficient exceed the threshold, it is determined that the train has a sign of derailment, and a sign of derailment detection is notified to the outside (corresponding to the function of the final determination unit 40).
[6] derailment sign detection program, wherein the program causes a computer to execute a process comprising the steps of:
inputting detection values of a pitch angle velocity and a roll angle velocity of a running train;
a step of calculating a wavelet coefficient of the pitch angle rate as a 1 st wavelet coefficient (corresponding to a function of the wavelet transform processing unit 11);
a step of calculating a wavelet coefficient of the roll angular velocity as a 2 nd wavelet coefficient (a function equivalent to the function of the wavelet transform processing unit 12);
a step of comparing the calculated 1 st wavelet coefficient and the calculated 2 nd wavelet coefficient with a predetermined threshold value (corresponding to a function of the derailment sign determination unit 13); and
and a step (corresponding to the function of the final determination unit 40) of determining a sign of derailment of the train when the 1 st wavelet coefficient and the 2 nd wavelet coefficient exceed the threshold, and notifying the outside of detection of the sign of derailment.
While the present invention has been described in detail and with reference to specific embodiments thereof, it will be apparent to one skilled in the art that various changes and modifications can be made therein without departing from the spirit and scope thereof.
The present application is based on the japanese patent application filed on 6/2/2017 (japanese patent application 2017-110259), the contents of which are incorporated herein by reference.
According to the present invention, it is possible to reduce false detection due to the influence of disturbance occurring at a position such as a track joint at a low speed in the detection of a sign of derailment. The present invention having this effect is useful for a derailment sign detection system, a control device, a derailment sign detection method, and a derailment sign detection program that can improve the accuracy of detecting a derailment sign of a train.
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