CN115031784A - Flexible sensing array for bogie structure/environment synchronous monitoring and decoupling method - Google Patents
Flexible sensing array for bogie structure/environment synchronous monitoring and decoupling method Download PDFInfo
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Abstract
The invention belongs to the technical field of intelligent monitoring of rail transit vehicles, and mainly relates to a flexible multi-mode sensing device and a signal decoupling method for online measurement of the wind speed and the structural vibration of a bogie. The flexible multi-mode sensing device comprises a hot mold sensing module for measuring the air flow speed on the surface of the bogie and a piezoelectric module for measuring vibration, the flexibility characteristic can ensure that the flexible multi-mode sensing device is tightly and seamlessly attached to the surface of a curved surface framework of the bogie, the surface flow field distribution of the bogie is not influenced, the surface air pressure and the structural vibration of the bogie influence the piezoelectric sensing module, the thermal film sensor is insensitive to vibration, a decoupling method of the air pressure and the structural vibration of the bogie based on empirical mode decomposition is provided, the decoupling of the air pressure and the structural vibration signal of the bogie is realized, and the intelligent monitoring level of the structural health of the bogie is improved.
Description
Technical Field
The invention belongs to the technical field of intelligent monitoring of rail transit vehicles, and mainly relates to a flexible multi-modal sensing device and a signal decoupling method for online measurement of the wind speed and the structural vibration of a bogie.
Background
The bogie is a key device for ensuring the stable and safe operation of the train. In the running process of the train, the bogie plays roles of carrying the weight of the train, buffering and damping in the running process of the train, guiding in the running of the train and braking. Along with the continuous improvement of railway transportation volume, the running speed of trains is continuously increased, the influence of wind on a bogie cannot be ignored easily, the counter-vibration force generated by the collision of a high-speed rolling wheel pair and a track and transmitted to the bogie is increased, the loss of the bogie is increased, the performance requirement of the bogie is higher, and the running safety of the bogie is directly influenced.
In the process of high-speed running of a train, a bogie is mainly influenced by a strong wind environment and wheel pair-track collision. The wind environment in the cavity of the bogie is complex and changeable, is related to the environment in the cavity and the running speed of the train, and the vibration force change of the wind environment to the bogie can be obtained through the change of the wind speed. People of Shijiazhuang railway university such as Shichangxin and Hu army sea invent a novel wind speed and direction sensor (CN207649678U) which is applied to a universal swing rod and a rotating frame. When wind blows towards the wind speed and direction sensor, the universal swing rod of the sensor can swing towards the wind, the swing direction of the universal swing rod is the wind direction, and the swing angle of the universal swing rod along the wind translates the wind speed. But the bogie surface air current is complicated and changeable and irregular, and has high requirement on detection sensitivity, the situation that the universal swing rod has not been swung, and the wind speed has changed can appear, and the universal swing rod has a complicated and heavy structure, is difficult to attach to the bogie surface, and can also influence the distribution of the bogie surface flow field. A piezoelectric vibration sensor (CN113884174A) of a compression type sensitive element is invented in Tianzhong mountain, Yilin and the like, the compression type piezoelectric vibration sensor integrates the compression type piezoelectric sensitive element and a conditioning circuit (amplifying and processing signals), an inner shell and an aviation plug are required to be installed when the sensor is installed on an object to be measured for use, but due to the fact that an outer shell exists and needs to be connected with the object to be measured through a threaded hole, the sensor has the characteristics of being complex in installation process and too heavy in device, and meanwhile, the distribution of a flow field on the surface of a bogie can be influenced. The detection system of the traditional bogie usually collects various types of data of the bogie by installing various types of sensors, and has the defects of excessive quantity, low integration, easiness in interference, complex installation, high cost and the like.
The flexible multi-mode sensing device adopts the hot film type sensor in the aspect of measuring wind speed, and adopts the piezoelectric film sensor in the aspect of measuring vibration, so that the installation process of the sensor is simplified, the mutual interference among the sensors is reduced, and the anti-interference capability is improved. The flexible multi-mode sensor device has the characteristics of softness, thinness and thinness, can be closely attached to a complex structure of a bogie, does not affect the functional characteristics and the surface flow field distribution of the bogie, collects the wind speed information on the surface of the bogie and the vibration information received by the bogie, and improves the accuracy of collecting the air flow and the structural vibration signals on the surface of the bogie by the flexible multi-mode sensor device due to the conformal surface mounting performance. A decoupling method of surface airflow and structural vibration based on multi-parameter information of the bogie is provided, and fine sensing and health monitoring of the bogie are achieved.
Disclosure of Invention
A first object of the present invention is to provide a flexible multi-modal sensing device for bogie-facing surface airflow velocity monitoring in synchrony with structural vibrations, the device comprises a hot mold sensing module for measuring the air velocity on the surface of the bogie and a piezoelectric module for measuring vibration, wherein the hot mold sensing module comprises a wind speed thermosensitive unit and two heating resistor units applied to the thermosensitive unit, so that the measurement of the wind speed and the structural vibration of the bogie is realized, all functional units are integrated on the same flexible substrate and are conformally arranged on the surface of the curved surface framework of the H-shaped bogie, the flexibility characteristic of the flexible sensor can ensure that the flexible sensor is tightly attached to the surface of the curved surface framework of the bogie in a seamless manner without influencing the surface flow field distribution of the bogie, the wind speed and vibration force voltage change signals of the bogie are collected in real time, and the relation between the real-time wind speed and the output signals of the hot mold sensor can be calculated; the mapping relation between the piezoelectric output voltage and the structural vibration is calibrated, so that real-time monitoring of multiple parameters of the bogie is realized, and synchronous monitoring of the structural vibration of the bogie and an environmental signal is the most effective and direct method for ensuring the running safety of a train, and has an important promoting effect on the running safety monitoring and intelligent operation and maintenance of the train.
The second purpose of the invention is to provide a decoupling method of the surface wind pressure and the structural vibration of the bogie based on flexible multi-modal sensing data, wherein the wind pressure directly influences the surface flow field distribution of the bogie and simultaneously influences the structural vibration of the bogie; the structural vibration signal of a bogie can be influenced by the counterforce of wheel rail vibration, the surface flow field information of the bogie can be collected by a hot mold sensor in a flexible multi-mode sensing array, the vibration signal of the bogie structure caused by the coupling of wind pressure and wheel rail vibration can be collected by a piezoelectric sensor in the flexible multi-mode sensing array, the characteristic that the hot mold sensor is only sensitive to air flow is utilized, the influence of the wheel rail vibration counterforce on the hot mold sensor can be ignored, a decoupling method of bogie wind pressure and structural vibration based on empirical mode decomposition is provided, the influence rule of wind pressure environment and bogie structural vibration on the structural health and safe driving of the bogie is evaluated, the vibration signal x (t) recorded by the sensor and the wind speed signal y (t), and the proposed decoupling algorithm of the bogie structure and the environment sensing mainly comprises the following steps: IMF component calculation, empirical mode decomposition, autocorrelation and covariance coefficient calculation, and the method comprises the following specific steps:
(1) the sensor acquires an original signal x (t) and makes h 0 ＝x(t)、g 0 (t)＝y(t)；
(2) Obtain the original signal h k (t) And g 0 (t) an extreme point;
(3) the spline curves are connected to obtain upper and lower envelope lines e xmax (t)、e xmin (t) and e ymax (t)、e ymin (t)；
(4) Summing the envelopes and taking the average to obtain:
the median function of x (t):
median function of y (t):
(5) subtracting m from h (t) x (t) subtracting m from g (t) y (t)：
h k (t)＝h k-1 (t)-m x(k-1) (t)
g k (t)＝g k-1 (t)-m y(k-1) (t)
(6) Judgment h k (t) and g k (t) whether the IMF condition is satisfied:
h satisfying IMF condition k (t) obtaining IMF components: imf x(i) (t)＝h k (t)；
H not satisfying IMF condition k (t) repeating the operations 2, 3, 4, 5 and 6;
g satisfying IMF condition k (t) obtaining IMF components: imf y(i) (t)＝g k (t)；
G not satisfying IMF condition k (t) repeating the operations 2, 3, 4, 5 and 6;
(7) imf obtained by continuously subtracting Shifting algorithm from original signal k (t) component:
vibration signal x (t) decomposition:
u x(0) (t)＝x(t)、u x(i) (t)＝u x(i-1) (t)-Imf x(i) (t)；
the wind speed signal y (t) is decomposed:
u y(0) (t)＝y(t)、u y(i) (t)＝u y(i-1) (t)-Imf y(i) (t)；
(8) judging u after decomposition of the vibration signal x (t) x(i) (t) if there are more than two poles, if yes, repeating steps 1, 2, 3, 4, 5, 6, 7 and 8, wherein h is the IMF component not obtained for the first time in step 1 0 (t)＝u x(i) (t) if satisfied, ending EMD decomposition;
judging u after the decomposition of the wind speed signal y (t) y(i) (t) if there are more than two poles, if yes, repeating steps 1, 2, 3, 4, 5, 6, 7 and 8, wherein h is the IMF component not obtained for the first time in step 1 0 (t)＝u y(i) (t), if satisfied, ending EMD decomposition;
(9) after EMD decomposition is finished, obtaining a formula of original signal decomposition:
vibration signal x (t) residual component: r is x (t)＝u x(i) (t)；
Vibration signal x (t) decomposition:
wind speed signal y (t) residual component: r is y (t)＝u y(i) (t)；
The wind speed signal y (t) is decomposed:
(10) calculating the autocorrelation function of vibration signal x (t) and Imf x (i) (t) autocorrelation function of the component:
the autocorrelation function of the wind speed signal y (t) and its Imf are obtained y(i) (t) autocorrelation function of the component:
(11) solving the cross-correlation coefficient of the vibration signal x (t) and the wind speed signal y (t):
imf setting ρ as a filtered vibration signal x (t) x(i) (t) a threshold value;
(12) imf for solving vibration signal x (t) x(i) (t) cross-correlation coefficient of component and wind speed signal y (t):
(13) filtering out Imf where ρ (j) is less than ρ x(i) (t) component, discarding components having ρ (j) greater than ρ Imf x(i) (t) component, since ρ is a coefficient relating the vibration signal x (t) to the wind speed signal y (t), and ρ (j) is Imfx of the vibration signal x (t) (i) (t) a coefficient of the degree to which the component is correlated with the wind speed signal y (t):
when rho (j) > rho, the influence of the wind speed signal y (t) on the vibration signal x (t) in the frequency band is large;
when rho (j) < rho, the influence of the wind speed signal y (t) on the vibration signal x (t) in the frequency band is small;
rejection of wind speed signals y (t) with a large effect on IMF IMF x(i) (t) the component has the purpose of infinitely reducing the influence of wind speed on the vibration, thereby obtaining a vibration signal with almost no influence of wind speed;
(14) imf obtained by filtering x(i) And (t) reconstructing the signal to obtain a decoupled vibration signal X (t).
Furthermore, the flexible multi-mode sensing device for measuring the wind speed and the structural vibration of the bogie has the advantages of being soft and small in film thickness, and comprising 2 vibration force piezoelectric units, one wind speed heat-sensitive unit and two heating resistor units, all the units are integrated on one flexible substrate, the flexible sensing device can be attached to a curved surface structure of the bogie in a conformal mode, the air flow field of the surface structure of the bogie is not affected, sensing detection of the bogie in a complex fluid environment is facilitated, accuracy and precision of fluid detection are improved, and meanwhile sensitivity and precision of vibration monitoring of the bogie are improved due to the conformal attachment.
Furthermore, the flexible multi-modal sensing device comprises 12 sensors of different types, which are respectively arranged on the curved surface of the H-shaped framework of the bogie, each single arm is divided into three sections, the sensors are uniformly distributed in pairs, the temperature sensing unit and the heating resistor unit construct a constant temperature difference mode control circuit containing a Wheatstone bridge, and a voltage signal only influenced by wind speed is output due to the convection heat loss principle and the heat sensitive characteristic of the resistor of the temperature sensing unit; the two vibration sensing units can output a voltage signal influenced by vibration due to the pressure-sensitive characteristic of the two vibration sensing units, the output vibration voltage signal is mainly influenced by wind pressure and wheel rail counter-vibration force, and the two voltage signals are both irregular non-stationary signals. In the sensing device, a wind speed signal is output by a hot film type sensor, and the output signal is slightly influenced by the vibration of a bogie structure due to the detection principle of the hot film type sensor, so the signal is mainly directly determined by the surface air speed of the bogie, but a vibration voltage signal detected by the sensor is influenced by two factors of air flow, pressure and wheel rail vibration and counter-vibration force, so the influence degree of the wind pressure and the wheel rail vibration and counter-vibration force on the vibration of the bogie structure can be decoupled by utilizing the corresponding relation of the hot film sensor and the surface air speed (pressure) of the bogie, and the technical support is provided for the environment-structure vibration integrated monitoring of the bogie.
Further, the invention is a flexible multi-mode sensing device for measuring the wind speed and the vibration force of a bogie, wherein the wind speed detection sensing unit comprises 1 wind speed thermosensitive unit and two heating resistor units thereof. The total size of the film sensor device is 300mm x 60mm, the thickness is 250nm, the thermosensitive unit is positioned at the position where the length of the film is 150mm and the width is 30mm, and the thermosensitive unit is placedThe direction is vertical to the width of the whole film, and the heating resistance unit is arranged in parallel at the position 10mm above and below the wind speed heat-sensitive unit. The thermosensitive unit adopts a platinum resistor as a thermosensitive material, and the Temperature Coefficient of Resistance (TCR) of the thermosensitive unit is 1.75 x 10 3 ppm/DEG C. Resistivity (resistivity) of 2.01 x 10 5 Omega cm, heating resistance unit is 200 omega.
Further, the invention is a flexible multi-modal sensing device for measuring the wind speed and the vibration force of a bogie, wherein the vibration sensing unit comprises 2 vibration force pressure-sensitive units. The two pressure-sensitive units are respectively arranged at the positions of the two width sides, close to the inner 50mm, and the two length sides, close to the inner 30mm of the film sensor, and the distance between the two units is 200 mm. The pressure-sensitive units are all made of PVDF piezoelectric films, the size of each PVDF piezoelectric film is 20mm x 15mm, the thickness of each PVDF piezoelectric film is 0.24mm, and the piezoelectric constant d is 33 24 +/-1 pC/N and an elastic modulus Ep of 1.2 x 10 3 MPa, resistivity of 10 13 Ω·cm。
Further, the bogie environment and structure vibration decoupling method carries out Empirical Mode Decomposition (EMD) on voltage signals output by a thermal film and a piezoelectric sensor, then calculates an IMF component obtained by respective decomposition of multiple sensing signals and an autocorrelation function and a correlation coefficient of an original acquired signal, obtains the correlation coefficient of each IMF through a wind speed signal, sets a threshold value on each IMF component of a composite vibration signal, obtains an effective IMF component of the vibration signal through filtering, reconstructs the IMF component, obtains the influence degree of wind pressure and wheel rail anti-vibration force on a bogie structure vibration signal, realizes the solution of the surface wind pressure of the bogie and the structure vibration signal, and provides support for accurate sensing and safety evaluation of the state information of the bogie.
Furthermore, the thermal film sensor in the flexible multi-mode sensing device for environment and structure vibration of the bogie is used for sensing airflow information on the surface of the bogie, the airflow directly acts on the surface of the bogie and a cavity, the thermistor of the thermal film sensor loses a part of heat due to convection, so that the Temperature of the resistor is reduced, the resistance value is changed, the bridge on a Constant Temperature difference control Circuit (CTD) is unbalanced, and a voltage U which changes along with the wind speed is output, and the output voltage is outputU not only has some relation with wind speed, but also feeds back to a heating resistor to control heating power so as to ensure the temperature Tr of the thermosensitive unit and the ambient temperature T 0 Constant temperature difference of (1), i.e. Δ T ═ T r -T 0 . After the CTD circuit ensures that the delta T is constant, the power P of the thermosensitive sensing unit and the wind speed V are in a single-value relation, and the formula is as follows:
C 1 and C 2 Is constant and V is the fluid velocity T r Is the temperature, T, of the heat-sensitive cell 0 Is the ambient temperature. The constant delta T temperature difference is determined by setting a difference between the thermistor on the bridge and the initial thermistor pair, and the calculation formula is as follows:
ΔR m ＝αR m ·ΔT
α is the temperature coefficient of the heat-sensitive cell, R m Is a thermistor, Δ R m Is the difference between the thermal cell and its bridge resistance calculated by setting Δ T. Furthermore, a piezoelectric film sensor in the flexible multi-mode sensing device for environment and structure vibration of the bogie is influenced by wind pressure generated by a flow field on the surface of the bogie and wheel rail back vibration force, at the moment, an induced voltage generated by the piezoelectric film due to piezoelectric effect is amplified by a conditioning circuit to output a voltage U, the output voltage U is directly related to the composite vibration force collected by the bogie, and the output voltage U and the composite vibration force meet the linear relation, and the formula is as follows:
P＝C·U
u is the voltage generated by the piezoelectric effect of the piezoelectric unit and amplified and output by the conditioning circuit, P is the vibration force received by the bogie, and C is the proportional coefficient of the vibration force and the output voltage calculated by multiple groups of experimental data.
Furthermore, the environment and structure vibration information of the bogie synchronously acquired by the thermal film and the piezoelectricity of the flexible multi-mode sensing device solves the problem of strong coupling between environment and structure vibration signals, the accurate sensing and safety monitoring of the bogie are realized by the environment-structure integrated detection capability, the current monitoring device and method can also be expanded to the monitoring of the bogie by wheel rail vibration, have significance on the health monitoring of the bogie, a wheel rail system and a track, and can comprehensively improve the intelligent monitoring level of the bogie.
In summary, the invention provides a flexible multi-modal sensing device and a signal decoupling method for synchronously monitoring the surface wind pressure and the structural vibration of the bogie. The device mainly adopts two sensors, namely a PVDF piezoelectric film sensor and a platinum resistance type thermosensitive unit sensor, realizes the on-line monitoring of the vibration force and the wind speed of the bogie in the running process of the train, and reduces the potential safety hazard in the running process of the train. The vibration force monitoring is based on the piezoelectric effect principle of the piezoelectric film, and the wind speed measurement is based on the resistance heat sensitivity characteristic of the thermosensitive unit under the condition of heat loss. The decoupling method for detecting the output vibration signal on the bogie utilizes the characteristic that the wind speed signal and the vibration signal are influenced by the wind environment at the same moment, and certain similarity necessarily exists in the change of the two signals to decouple the signal of the wheel-rail counter-vibration force in the output vibration signal. The decoupling of the wind speed vibration and the wheel rail anti-vibration force is realized by using the method of EMD decomposition and calculation of the autocorrelation function and the correlation coefficient, a single signal of the vibration force transmission bogie of wheel rail collision is obtained, the influence of wheel rail motion on the bogie loss is estimated through the signal, the abnormal state of a certain section of track in the train running process is judged through the abnormal signal section of the signal, and the railway maintenance personnel are reminded of performing abnormal investigation on the abnormal section of track in time, so that the potential safety hazard of train running is reduced.
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Fig. 1a is a 3D effect diagram of the flexible multi-modal sensor device attached to the two arms of the bogie. FIG. 1b is a diagram showing the effect of physical quantities of pressure of a bogie in a complex wind environment and vibration force fed back to the bogie when a wheel set collides with a rail during the operation of a train. FIG. 1c is a block diagram of a flexible multi-modal sensing device, comprising: 2 vibration force pressure-sensitive units, a platinum resistance type wind speed heat-sensitive unit and two heat-sensitive unit heating units. FIG. 1d is a schematic diagram of the piezoelectric effect of PVDF piezoelectric film. Fig. 1e is a schematic diagram of the temperature change and thus the resistance change of the thermosensitive unit due to heat loss in a wind convection environment.
FIG. 2 is a schematic diagram of a Wheatstone bridge combined with a wind speed thermosensitive unit for measuring wind speed and a control circuit for ensuring constant temperature difference.
Fig. 3 is a block diagram of the overall system flow using a flexible multimodal sensing apparatus.
FIG. 4 is a scene diagram of an overall system for monitoring wind speed and vibration force on line by applying the flexible multi-modal sensing device to a bogie.
Fig. 5 is a block flow diagram of the EMD method to decompose the signal and calculate the IMF component autocorrelation function and correlation coefficients.
FIG. 6 is a block diagram of a vibration detection calibration process.
FIG. 7 is a block diagram of a wind speed detection calibration process.
Fig. 8 is a flow chart of the flexible multi-modal sensing device applied to real-time detection on a train bogie.
FIG. 9 is a flow chart of the decoupling of the output signals of the flexible multi-modal sensing apparatus.
Fig. 10 is bogie structural vibration state data.
Fig. 11 shows a modal decomposition result (IMF component) of a bogie vibration signal based on an empirical mode method (EMD).
The symbols in the drawings mean:
1, a bogie; 2-a flexible multi-modal sensing device; 3-a ZigBee node; 4-a multi-channel charge amplifier; 5-a data collector; 6-an upper computer; 7- (B-S mode) browser; 21-a pressure sensitive unit; 22-a heating resistance unit; 23-a thermosensitive unit; 211. 212, 213, 214, 221, 222, 223, 224, 231, 232-metal leads.
Detailed Description
In order to make the technical solution and the solution of the present invention more clear, the following drawings are explained in further detail. The techniques and methods described herein are not limited to the present invention, but rather, specific embodiments are described to meet the teachings of the present invention.
The flexible multi-mode sensing device comprises a thermal film and a piezoelectric sensing function, and is characterized in that a thermal film and a piezoelectric sensing function are included, referring to figure 1a, in the operation process, the flow field and the structural vibration information on the surface of a bogie are acquired in real timeFurthermore, the problem that the vibration force generated by the collision of the wheel and the rail on the bogie and transmitted to the bogie is coupled with the vibration force generated by the wind in the cavity of the bogie and is difficult to decouple is solved, as shown in fig. 1: the bogie bears two forces in the running process of the train, namely wind vibration force P Wind power Let one be the wheel-rail collision vibration force P Rail The two forces are random forces acting on the bogie, and have uncertain directions and uncertain magnitudes. In order to collect the irregular force signals, the flexible multi-mode sensing devices are attached to the two arms of the bogie, as shown in fig. 1a, 6 flexible multi-mode sensing devices are arranged at each single arm of the bogie, 12 flexible multi-mode sensing devices are arranged in total, and the flexible multi-mode sensing devices are arranged side by side in pairs and are respectively attached to the bent positions of the two arms of the bogie (8 flexible multi-mode sensing devices are attached to the 4 bent positions of the two arms) and the middle sections of the two arms of the bogie are also attached to the 4 flexible multi-mode sensing devices respectively.
FIG. 1c illustrates the composition of a flexible multi-modal sensing device having a film substrate 300mm long by 60mm wide, consisting of 1 platinum resistance thermistor unit, 2 heater resistor units, and 2 PVDF film pressure sensitive units. The platinum resistance type thermosensitive unit is located at the position where the film is 150mm long and 30mm wide, the placing direction is perpendicular to the width of the whole film, and the heating resistance unit is placed at the position 10mm above and below the wind speed thermosensitive unit in parallel. The specific parameters of the platinum resistance type thermosensitive unit are as follows: TCR 1.75 x 10 3 ppm/DEG C, resistivity of 2.01 x 10 5 Omega cm. The heating resistance unit is 200 omega, the two heating units are connected in parallel, and the parallel resistance is 100 omega.
The PVDF film pressure-sensitive unit is 20mm long, 15mm wide and 0.24mm thick, and is positioned at the position where the two widths of the film sensor are close to the inner 50mm and the two lengths of the film sensor are close to the inner 30mm, and the distance between the two units is 200 mm. The concrete parameters are as follows: piezoelectric constant d 33 24 +/-1 pC/N and an elastic modulus Ep of 1.2 x 10 3 MPa, resistivity of 10 13 Ω·cm。
The principle that the output voltage of the pressure-sensitive unit reflects the sensed vibration force is shown in fig. 1d, when the piezoelectric film is subjected to a pressure P, the positive and negative charges in the piezoelectric film move to two stages, so that a voltage is generated and output, and the magnitude and the speed of the generated voltage are positively correlated with the magnitude of the pressure P. Heat sensitive cell detectorPrinciple of principle As shown in FIG. 1e, the heat-sensitive unit will lose a heat quantity Q under convection in working condition loss And thus the temperature of the temperature sensitive unit changes at, the resistance of the temperature sensitive unit also changes at due to the resistance heat sensitive characteristic of the temperature sensitive unit, thereby causing a change in the output voltage based on the wheatstone bridge.
The wind speed detection of the heat sensitive unit and the heating resistor unit is also based on a Wheatstone bridge and a feedback control circuit, as shown in FIG. 2, 2 constant value resistors R and R r A Wheatstone bridge circuit is formed by the platinum thermistor, and the voltage output between the two bridges is fed back to the two parallel heating resistors P h A feedback control circuit is constructed. Wherein the wheatstone bridge functions to relate wind speed to output voltage. The principle of the method is that the heat lost by the thermistor is changed due to the change of the wind speed, so that the resistance is changed, the change of the intermediate potential of two bridges of a Wheatstone bridge circuit is broken, the output voltage is changed, and the change of the wind speed directly influences the change of the output voltage. The feedback circuit has the function of ensuring the temperature of the thermistor and the temperature of the sensor to be constant. Based on the King formula, the flow velocity of the fluid and the current passing through the thermistor are in a single-value function relation under the condition that the temperature difference between the environment temperature and the thermistor is constant. Therefore, in order to achieve a constant temperature difference, the initial parameters of Rr and Rm are first set to Rr ═ Rm +/Δ Rm (Δ Rm)>0, Rm increases with a positive coefficient), so in the initial situation, Vout outputs a positive voltage to heat Rm and increase it to equal Rr, i.e. a constant heating power is supplied to Rh, Vout outputs a constant value, which ensures that the power of heating resistor Rh is constant to keep the temperature of Rm constant, and the circuit reaches a dynamic equilibrium state.
In order to realize the on-line detection of the bogie in the running process of a train, a thermal film sensor (a thermal sensitive unit) and a vibration sensor (a pressure sensitive unit) are integrated on a flexible multi-mode sensing device, and a detection system is built, firstly, the thermal film sensor outputs a voltage signal influenced by wind speed through a CTD control circuit, the vibration sensor outputs a voltage signal influenced by vibration, the voltage signal is processed and amplified through a conditioning circuit and then is input into an MCU chip through A/D, the MCU is connected with a Zigbee node network through a serial port and is transmitted to an upper computer for display, the whole system flow block diagram is shown in figure 3, and the whole system scene effect is shown in figure 4.
Before formal application of the flexible multi-modal sensing device, the sensing device needs to be verified and calibrated, and the required equipment comprises: the wind tunnel provides a wind environment for the sensing device, can blow wind with a certain wind speed, namely wind in a graph e of fig. 1 and the electromagnetic vibration test bed, and provides a vibration source with a specified size, namely vibration force P in a graph 1d for the sensing device.
After the flexible multi-mode sensing device is calibrated, an online detection system is built under the specific train bogie environment, in the running process of a train, opposite wind flows into a bogie cavity, based on a heat loss principle and a Wheatstone bridge, an integrated hot film sensor outputs a voltage signal, and the wind speed sensed by the sensor on the bogie can be calculated by utilizing the wind speed signal and a calibrated established relation model of the wind speed and the voltage signal. Similarly, the vibration sensor integrated on the flexible multi-mode sensing device can calculate the vibration force sensed by the sensor on the bogie by using the established relation model of the voltage signal and the vibration force.
And finally, carrying out data processing on the obtained wind speed data and the obtained vibration force data, and according to the characteristic that the wind speed data and the vibration force data have simultaneous detection and the characteristic that the wind speed signal and the vibration signal are influenced by the wind environment at the same moment and have certain similarity, knowing that the data change of the vibration force at the same moment is the data change completely containing the wind speed, so that the wind speed data can be utilized to decouple two vibration sources (wind vibration and wheel track feedback vibration) of the vibration force. The method comprises the following specific steps:
(1) acquiring an original signal x (t) by a sensor, and letting h 0 (t)＝x(t)、g 0 (t)＝y(t)；
(2) Obtaining an original signal h k (t) and g 0 (t) an extreme point;
(3) the spline curves are connected to obtain upper and lower envelope lines, e xmax (t)、e xmin (t) and e ymax (t)、e ymin (t)；
(4) Summing the envelopes and taking the average to obtain:
median function of x (t):
median function of y (t):
(5) subtracting m from h (t) x (t) subtracting m from g (t) y (t)
h k (t)＝h k-1 (t)-m x(k-1) (t)
g k (t)＝g k-1 (t)-m y(k-1) (t)
(6) Judgment of h k (t) and g k (t) whether the IMF condition is satisfied:
h satisfying IMF condition k (t) obtaining IMF components: imf x(i) (t)＝h k (t)；
H not satisfying IMF condition k (t) repeating the operations 2, 3, 4, 5 and 6;
g satisfying IMF condition k (t) obtaining IMF component: imf y(i) (t)＝g k (t)；
G not satisfying IMF condition k (t) repeating the operations 2, 3, 4, 5 and 6;
(7) imf obtained by continuously subtracting Shifting algorithm from the original signal k (t) component:
vibration signal x (t) decomposition:
u x(0) (t)＝x(t)、u x(i )(t)＝u x(i-1) (t)-Imf x(i) (t)；
the wind speed signal y (t) is decomposed:
u y(0) (t)＝y(t)、u y(i) (t)＝u y(i-1) (t)-Imf y(i) (t)；
(8) judging u after decomposition of the vibration signal x (t) x(i) (t) whether more than two poles exist, if so, repeating the steps 1, 2, 3, 4, 5, 6, 7 and 8, wherein h is the IMF component not obtained for the first time in the step 1 0(t) ＝u x(i) (t) if satisfied, ending EMD decomposition;
judging u after the decomposition of the wind speed signal y (t) y(i) (t) if there are more than two poles, if yes, repeating steps 1, 2, 3, 4, 5, 6, 7 and 8, wherein h is the IMF component not obtained for the first time in step 1 0 (t)＝u y(i) (t) if satisfied, ending EMD decomposition;
(9) after EMD decomposition is finished, obtaining a formula decomposed by an original signal:
vibration signal x (t) residual component: r is x (t)＝u x(i) (t)；
Vibration signal x (t) decomposition:
wind speed signal y (t) residual component: r is y (t)＝u y(i) (t)；
The wind speed signal y (t) is decomposed:
(10) calculating the autocorrelation function of vibration signal x (t) and its Imfx ( i ) (t) component autocorrelation function:
the autocorrelation function of the wind speed signal y (t) and its Imf are determined y(i) (t) component autocorrelation function:
(11) solving the cross-correlation coefficient of the vibration signal x (t) and the wind speed signal y (t):
imf setting ρ as a filtered vibration signal x (t) x(i) (t) a threshold value;
(12) imf for solving vibration signal x (t) x(i) (t) cross-correlation coefficient of component and wind speed signal y (t):
(13) filtering out Imf where ρ (j) is less than ρ x(i) (t) component, discarding components having ρ (j) greater than ρ Imf x(i) (t) component, since ρ is a coefficient relating the vibration signal x (t) to the wind speed signal y (t), and ρ (j) is ImF of vibration signal x (t) x(i) (t) a coefficient of the degree to which the component is correlated with the wind speed signal y (t):
when rho (j) > rho, the influence of the wind speed signal y (t) on the vibration signal x (t) in the frequency band is large;
when rho (j) < rho, the influence of the wind speed signal y (t) on the vibration signal x (t) in the frequency band is small;
rejection of wind speed signal y (t) with great influence on IMF IMF x(i) (t) the component has the purpose of infinitely reducing the influence of the wind speed on the vibration, thereby obtaining a vibration signal with almost no influence of the wind speed;
(14) imf obtained by filtering x(i) And (t) reconstructing the signal to obtain a decoupled vibration signal X (t).
Before the flexible multi-modal sensing device is applied, calibration experiments need to be carried out on detection data of the flexible multi-modal sensing device. The flow chart of the vibration detection calibration experiment is shown in fig. 6, the flexible multi-mode sensor is placed in a windless environment, vibration forces with different magnitudes are applied to the sensor by using an electromagnetic vibration experiment table to obtain a plurality of groups of output signals with different vibration forces, the relationship between the vibration starting force and the output signals is established by using the output signals, namely, a constant C is obtained by calculation, the operation is repeated for a plurality of times, a plurality of constants C are obtained by calculation, the final vibration calibration constant is obtained by taking the average value, and the vibration force detection calibration is completed.
The experimental flow of wind speed detection and calibration is shown in fig. 7, the flexible multi-mode thin film sensing device is firstly placed in a wind tunnel, wind with different wind speeds is blown to the sensor by the wind tunnel in the environment without other vibration sources to obtain a plurality of groups of output signals with different wind speeds, and two constants C are reversely solved by the data signals based on a King formula 1 And C 2 And establishing a relation between the wind speed and the output signal. Repeating the above operations for multiple times to obtain multiple groups of constants C 1 And C 2 And averaging to obtain a final wind speed calibration constant, and completing the wind speed detection calibration.
The application of the multi-mode flexible sensing device to the bogie is briefly described as follows: as shown in fig. 8, the multi-modal flexible sensing device is placed in an application scene, i.e., the sensing device is attached to the surface of the bogie frame, and a monitoring system is built. In the running process of a train, the thermosensitive sensing unit of the sensor film meter second can output air velocity voltage signals on the surface of the bogie, and the pressure-sensitive unit can output vibration voltage signals of the bogie structure. And then, calculating a wind speed value borne by the surface of the sensor according to the established models of the air flow speed and the output voltage, and calculating a vibration force value sensed by the surface of the sensor according to the established models of the vibration and the output voltage, wherein the multi-mode flexible sensor device completes the functions of monitoring and data acquisition.
After wind speed and vibration data acquired by the device are obtained in an upper computer, the vibration data are decoupled by a method, the decoupling process is shown in figure 9, firstly, the obtained wind speed data and the vibration data are subjected to EMD decomposition to obtain IMF components of the wind speed data and the vibration data from low frequency to high frequency, then, IMF components, wind speed data and vibration data autocorrelation functions are calculated, correlation coefficients (reflecting the similarity degree of the wind speed data and the vibration data) rho of the wind speed data and the vibration data are obtained through the calculated wind speed data and vibration data autocorrelation functions, a threshold value is set, then, the correlation coefficients rho (j) of the IMF components of the vibration data and the wind speed data are solved through the autocorrelation functions of the IMF components of the vibration data and the wind speed data, then, the vibration IMF components are filtered through the relationship of the threshold value rho and the correlation coefficients rho (j), and finally, the IMF components obtained through filtering are reconstructed to obtain vibration signals of wheel track vibration, decoupling is now complete.
To further verify that the flexible multifunctional sensing device is used for online measurement of a bogie vibration signal (caused by wind pressure and wheel rail anti-vibration coupling), as shown in fig. 10, it can be seen that the steering engine vibration signal has a multi-band characteristic. Fig. 11 is a decomposition result of a bogie structure vibration signal by an empirical mode method, and provides a basis for decoupling processing of wind pressure and structure vibration on bogie stress, which is beneficial to accurate analysis of a bogie stress state.
It will be understood by those skilled in the art that the foregoing is only an exemplary embodiment of the present invention, and is not intended to limit the invention to the particular forms disclosed, since various modifications, substitutions and improvements within the spirit and scope of the invention are possible and within the scope of the appended claims.
Claims (7)
1. A flexible multi-mode sensing device for online measurement of air speed and structural vibration of a bogie is characterized by comprising a hot mold sensing module for measuring the air speed on the surface of the bogie and a piezoelectric module for measuring vibration, wherein the hot mold sensing module comprises an air speed thermosensitive unit and two heating resistor units applied to the thermosensitive unit to realize measurement of the air speed and the structural vibration of the bogie; the mapping relation between the piezoelectric output voltage and the structural vibration is calibrated, real-time monitoring of multiple parameters of the bogie is achieved, synchronous monitoring of the structural vibration of the bogie and an environmental signal is the most effective method for guaranteeing train running safety, and the method has an important promoting effect on train running safety monitoring and intelligent operation and maintenance.
2. A decoupling method of bogie surface wind pressure and structural vibration based on flexible multi-modal sensing data is characterized in that the wind pressure directly influences the surface flow field distribution of a bogie and simultaneously influences the structural vibration of the bogie; the structural vibration signal of bogie can be influenced to the anti-vibration power of wheel rail vibration, the surface flow field information of bogie can be gathered to the hot mold sensor, the bogie structural vibration signal that wind pressure and wheel rail vibration coupling arouse can be gathered to piezoelectric sensor, utilize the hot mold sensor only to the sensitive characteristics of air current, the influence of wheel rail vibration anti-vibration power to the hot mold sensor can be ignored, a bogie wind pressure and structural vibration decoupling method based on empirical mode decomposition is proposed, the influence law of wind pressure environment and bogie structural vibration to its structural health and safe driving is assessed, vibration signal x (t) of sensor record, wind speed signal y (t), the bogie structure that provides and environmental perception decoupling algorithm's mainly include: IMF component calculation, empirical mode decomposition, autocorrelation and covariance coefficient calculation, and the method comprises the following specific steps:
(1) acquiring an original signal x (t) by a sensor, and letting h 0 (t)＝x(t)、g 0 (t)＝y(t)；
(2) Obtain the original signal h k (t) and g 0 An extreme point of (t);
(3) the spline curves are connected to obtain upper and lower envelope lines e xmax (t)、e xmin (t) and e ymax (t)、e ymin (t)；
(4) Summing the envelopes and taking the average to obtain:
median function of x (t):
median function of y (t):
(5) subtracting m from h (t) x (t) subtracting m from g (t) y (t)：
h k (t)＝h k-1 (t)-m x(k-1) (t)
g k (t)＝g k-1 (t)-m y(k-1) (t)
(6) Judgment h k (t) and g k (t) whether the IMF condition is satisfied:
h satisfying IMF condition k (t) obtaining IMF components: imf x(i) (t)＝h k (t)；
H not satisfying IMF condition k (t) repeating the operations 2, 3, 4, 5 and 6;
g satisfying IMF conditions k (t) obtaining IMF components: imf y(i) (t)＝g k (t)；
G not satisfying IMF condition k (t) repeating the operations 2, 3, 4, 5 and 6;
(7) imf obtained by continuously subtracting Shifting algorithm from original signal k (t) component:
vibration signal x (t) decomposition:
u x(0) (t)＝x(t)、u x(i) (t)＝u x(i-1) (t)-Imf x(i) (t)；
the wind speed signal y (t) is decomposed:
u y(0) (t)＝y(t)、u y(i) (t)＝u y(i-1) (t)-Imf y(i) (t)；
(8) determining u after decomposition of the vibration signal x (t) x(i) (t) if more than two poles exist, repeating the steps 1, 2, 3, 4, 5, 6, 7 and 8 if the poles are met, wherein h is the IMF component which is not obtained for the first time in the step 1 0 (t)＝u x(i) (t), if satisfied, ending EMD decomposition;
judging u after the decomposition of the wind speed signal y (t) y(i) (t) if there are more than two poles, if yes, repeating steps 1, 2, 3, 4, 5, 6, 7 and 8, wherein h is the IMF component not obtained for the first time in step 1 0 (t)＝u y(i) (t) if satisfied, ending EMD decomposition;
(9) after EMD decomposition is finished, obtaining a formula decomposed by an original signal:
vibration signal x (t) residual component: r is a radical of hydrogen x (t)＝u x(i) (t)；
Vibration ofSignal x (t) decomposition:
wind speed signal y (t) residual component: r is y (t)＝u y(i) (t)；
The wind speed signal y (t) is decomposed:
(10) sum Imf of autocorrelation function of vibration signal x (t) x(i) (t) autocorrelation function of the component:
summing Imf the autocorrelation function of the wind speed signal y (t) y(i) (t) autocorrelation function of the component:
(11) solving the cross-correlation coefficient of the vibration signal x (t) and the wind speed signal y (t):
imf setting ρ as a filtered vibration signal x (t) x(i) (t) a threshold value;
(12) imf of vibration signal x (t) x(i) (t) is divided intoCross-correlation coefficient of the magnitude and wind speed signals y (t):
(13) filtering out Imf where ρ (j) is less than ρ x(i) (t) component, discarding components having ρ (j) greater than ρ Imf x(i) (t) component, since ρ is a coefficient relating the vibration signal x (t) to the wind speed signal y (t), and ρ (j) is Imf of vibration signal x (t) x(i) (t) a coefficient of the degree to which the component is correlated with the wind speed signal y (t):
when rho (j) > rho, the influence of the wind speed signal y (t) on the vibration signal x (t) in the frequency band is large;
when rho (j) < rho, the influence of the wind speed signal y (t) on the vibration signal x (t) in the frequency band is small;
rejection of wind speed signals y (t) with a large effect on IMF IMF x(i) (t) the component has the purpose of infinitely reducing the influence of wind speed on the vibration, thereby obtaining a vibration signal with almost no influence of wind speed;
(14) imf obtained by filtration x(i) And (t) reconstructing the signal to obtain a decoupled vibration signal X (t).
3. The flexible multi-modal sensing device for online measurement of the wind speed and the structural vibration of the bogie according to claim 1, characterized in that the flexible multi-modal sensing device has a flexible characteristic and a small film thickness, and comprises 2 vibration force piezoelectric units, one wind speed thermal sensitive unit and two heating resistor units thereof, all the units are integrated on a flexible substrate, so that the flexible sensing device can be attached to the curved surface structure of the bogie in a conformal manner, no influence is caused on an air flow field of the surface structure of the bogie, sensing detection of the bogie in a complex fluid environment is facilitated, accuracy and precision of fluid detection are improved, and sensitivity and precision of vibration monitoring of the bogie structure are improved by the conformal attachment.
4. The flexible multi-modal sensing device for online measurement of the wind speed and the structural vibration of the bogie according to claims 1 and 3, characterized in that the flexible multi-modal sensing device solves the problem of strong coupling between environmental and structural vibration signals by using the thermal film and the piezoelectric synchronously acquired environmental and structural vibration information of the bogie, and the capability of environment-structure integrated detection realizes accurate sensing and safety monitoring of the bogie.
5. The flexible multi-modal sensing device and the decoupling method of the wind pressure on the surface of the bogie and the structural vibration according to the claims 1 and 2 are characterized in that vibration information acquired by a piezoelectric sensor in the flexible multi-modal sensing device is generated by superposition of wind-induced vibration and structural vibration, and the wind-induced vibration and the structural vibration are coupled together.
6. The flexible multi-modal sensing device and the decoupling method of the surface wind pressure and the structural vibration of the bogie according to the claims 1 and 2, characterized in that the flexible multi-modal sensing device can synchronously sense the information of the surface wind pressure and the structural vibration of the bogie, a piezoelectric sensor in the flexible multi-modal sensing device is simultaneously influenced by the wind pressure and the structural vibration, a hot film sensor is only sensitive to a wind pressure signal, and the decoupling of the bogie influenced by the environmental and the structural vibration is realized based on the current signal characteristics.
7. The method for decoupling the surface wind pressure of the bogie from the structural vibration based on the flexible multi-modal sensing device according to the claims 2, 5 and 6 is characterized in that the decoupling method for the environment and the structural vibration of the bogie is used for carrying out empirical mode decomposition on voltage signals output by a thermal film and a piezoelectric sensor, then IMF components obtained by respective decomposition of multiple sensing signals and autocorrelation functions and correlation coefficients of original collected signals are calculated, threshold setting is carried out on each IMF component of composite vibration signals by obtaining the correlation coefficient of each IMF through a wind speed signal, effective vibration signal IMF components are obtained through filtering and are reconstructed, the influence degree of the wind pressure and the wheel track counter-vibration force on the structural vibration signals of the bogie is obtained respectively, and decoupling of the surface wind pressure of the bogie and the structural vibration signals is realized.
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