CN111258303A - Servo system fault detection method and device, computer equipment and storage medium - Google Patents
Servo system fault detection method and device, computer equipment and storage medium Download PDFInfo
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Abstract
The application relates to a servo system fault detection method, a servo system fault detection device, a computer device and a storage medium. The servo system fault detection method comprises the following steps: acquiring an electrical signal of a power output device in a servo system; counting and extracting characteristics of the electrical signals to obtain voltage ripple characteristic parameters; performing curve fitting on the voltage ripple characteristic parameters to obtain a curve fitting result; and determining the residual time of the fault of the servo system according to the fault threshold and the curve fitting result. The method and the device meet the failure physics and degradation characteristics of the power switch device, the parameters needing to be monitored are few, the design requirement on the testability of the whole system is low, the universality is good, and the real-time fault prediction under the online working condition can be conveniently carried out by a servo system.
Description
Technical Field
The present application relates to the field of automation technologies, and in particular, to a method and an apparatus for detecting a failure of a servo system, a computer device, and a storage medium.
Background
The servo driver is an important component of modern motion control and is widely applied to automation equipment such as industrial robots and numerical control machining centers. Especially, a servo driver applied to control an alternating current permanent magnet synchronous motor has become a research hotspot at home and abroad.
The current alternating current servo driver is generally controlled by a current, speed and position 3 closed-loop control algorithm based on vector control, the servo driver generally comprises a control panel and a driving Power output Module, the Power output Module generally comprises an Insulated Gate Bipolar Transistor (IGBT) or Intelligent Power Module (IPM) Module, the Power output link completes three-phase inversion and outputs alternating current voltage to drive a servo motor for control, the Power output part is one of the components with the highest fault occurrence rate and the lowest reliability as a key link of energy concentration conversion, moreover, once a failure occurs, the whole servo control system cannot work directly, so that the failure prediction of the power output link of the servo system is urgently needed to carry out preventive maintenance, and the failure occurrence rate is reduced.
In the implementation process, the inventor finds that at least the following problems exist in the conventional technology: the power output module in the servo system is used in combination with the general driving chip, so that the output can be timely cut off when the IGBT has a short-circuit fault, the device can be protected, the problem cannot be timely found after the degradation trend of the device performance occurs, and the potential safety hazard of the performance caused by the degradation of the device cannot be timely found and thoroughly eliminated when some key devices with one-time service life, especially equipment in the fields of aerospace and aviation, and the like, have insufficient capacity.
Disclosure of Invention
Therefore, it is necessary to provide a method and an apparatus for detecting a failure of a servo system, a computer device, and a storage medium, which can perform early warning of the failure in time.
In order to achieve the above object, in one aspect, an embodiment of the present invention provides a method for detecting a failure of a servo system, including:
acquiring an electrical signal of a power output device in a servo system; the electrical signals comprise voltage signals between a gate electrode and an emitter electrode of each switching tube in the power output device;
counting and extracting characteristics of the electrical signals to obtain voltage ripple characteristic parameters; the voltage ripple characteristic parameters comprise a switching transient Miller effect voltage peak-to-peak value sequence and a switching transient Miller effect voltage mean value sequence;
performing curve fitting on the voltage ripple characteristic parameters to obtain a curve fitting result; and determining the residual time of the fault of the servo system according to the fault threshold and the curve fitting result.
In one embodiment, the step of obtaining an electrical signal of a power output device in the servo system comprises:
when the servo system finishes the work with preset duration, acquiring voltage signals between gate poles and emitting poles of the switching tubes according to preset acquisition conditions;
the preset acquisition conditions comprise normal load, normal temperature environment, switching tube switching frequency of which the sampling frequency is more than or equal to 5 times, sampling precision of which is more than or equal to 5mV, and switching tube switching period of which the single acquisition time is more than or equal to 2 times.
In one embodiment, the step of performing statistics and feature extraction on the electrical signal to obtain a voltage ripple characteristic parameter includes:
performing integral statistics on each voltage signal to obtain the transient Miller effect voltage area of each switching tube;
extracting the characteristics of each transient Miller effect voltage area in a single acquisition time to obtain each peak value and each mean value;
and respectively arranging the peak value and the mean value according to the time sequence to obtain a switching transient Miller effect voltage peak-peak value sequence and a switching transient Miller effect voltage mean value sequence.
In one embodiment, the step of performing integral statistics on each voltage signal to obtain the transient miller effect voltage area of each switching tube includes:
and processing each voltage signal by adopting discrete accumulation to obtain the transient Miller effect voltage area of each switching tube.
In one embodiment, the step of obtaining the transient miller effect voltage area of each switching tube by processing each voltage signal through discrete accumulation includes:
and acquiring the transient Miller effect voltage area according to the switch control state of each switch tube based on the switch period of the switch tube.
In one embodiment, the curve fitting result comprises a fault prediction model;
and performing curve fitting on the voltage ripple characteristic parameters to obtain a curve fitting result, wherein the step comprises the following steps of:
and performing curve fitting on the switching transient Miller effect voltage peak-to-peak value sequence and the switching transient Miller effect voltage mean value sequence by using a polynomial fitting algorithm to obtain a fault prediction model.
In one embodiment, the fault threshold is obtained according to a gate trigger voltage of the switching tube;
determining the residual time of the fault of the servo system according to the fault threshold and the curve fitting result, wherein the step comprises the following steps:
and fitting a fault prediction model according to a polynomial curve based on the fault threshold value to obtain the residual time of the fault.
On the other hand, an embodiment of the present invention further provides a servo system fault detection apparatus, including:
the signal acquisition module is used for acquiring an electrical signal of a power output device in the servo system; the electrical signals comprise voltage signals between a gate electrode and an emitter electrode of each switching tube in the power output device;
the characteristic extraction module is used for counting and extracting characteristics of the electrical signals to obtain voltage ripple characteristic parameters; the voltage ripple characteristic parameters comprise a switching transient Miller effect voltage peak-to-peak value sequence and a switching transient Miller effect voltage mean value sequence;
the curve fitting module is used for performing curve fitting on the voltage ripple characteristic parameters to obtain a curve fitting result;
and the fault early warning module is used for determining the fault occurrence remaining time of the servo system according to the fault threshold and the curve fitting result.
A computer device comprising a memory storing a computer program and a processor implementing the steps of any of the preceding methods when the computer program is executed by the processor.
A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of any of the methods described above.
One of the above technical solutions has the following advantages and beneficial effects:
the application provides a method capable of detecting and extracting characteristics of an electrical signal of a servo system power output device in real time, wherein offset of voltage drop between a gate electrode and an emitter electrode of a power tube is used as a degradation characteristic parameter, the health condition of the power output device is evaluated through curve fitting, the offset is guaranteed to have reliable margin, under the condition that the safety margin is insufficient, a warning is sent out, replacement and updating of key devices are carried out in time, and stable and reliable operation of the servo system is guaranteed. The method and the device meet the failure physics and degradation characteristics of the power switch device, the parameters needing to be monitored are few, the design requirement on the testability of the whole system is low, the universality is good, and the real-time fault prediction under the online working condition can be conveniently carried out by a servo system.
Drawings
Other features, objects and advantages of the present application will become more apparent upon reading of the following detailed description of non-limiting embodiments thereof, made with reference to the accompanying drawings in which:
FIG. 1 is a diagram of an exemplary embodiment of a servo system fault detection method;
FIG. 2 is a flow chart illustrating a method for detecting a servo system failure according to an embodiment;
FIG. 3 is a schematic diagram of an equivalent circuit of an IGBT switching tube in one embodiment;
FIG. 4 is a diagram illustrating the on/off states of the switching tube in the normal mode according to an embodiment;
FIG. 5 is a graph illustrating a voltage transient Miller effect in one embodiment;
FIG. 6 is a schematic diagram of a servo system fault acquisition and diagnostic prediction process in one embodiment;
FIG. 7 is a block diagram showing a structure of a servo system failure detection apparatus according to an embodiment;
FIG. 8 is a diagram illustrating an internal structure of a computer device in one embodiment;
fig. 9 is an internal structural view of a computer device in another embodiment.
Detailed Description
To facilitate an understanding of the present application, the present application will now be described more fully with reference to the accompanying drawings. Preferred embodiments of the present application are shown in the drawings. This application may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used in the description of the present application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed items.
The traditional control of a power output device (IGBT or IPM) of a servo system mainly utilizes a power module driving chip, the driving chip mainly achieves the functions of receiving a controller pulse command, transmitting signals in an isolated mode and amplifying output, the driving chip provides driving signals for the power output module and detects the pin voltage of the power output device, when the voltage exceeds a certain threshold value, an alarm can be triggered, then the corresponding fault output state bit is used for representing, an upstream controller can acquire the working condition of the power output module from the state bit, in addition, when a fault occurs, a driver prohibits output, and the power output module stops working.
However, the power output module in the conventional servo system is used in combination with the general driving chip, so that although the output can be timely cut off and the device can be protected when the short-circuit fault occurs in the IGBT, the problem cannot be timely found after the degradation trend of the device performance occurs, the capability of some key devices with one-time service life, especially equipment in the fields of aerospace and the like, is obviously insufficient, and the potential safety hazard of the performance caused by the degradation of the device cannot be timely found and thoroughly eliminated.
The scheme is that on the basis of a corresponding device degradation model (such as a fault prediction model), the offset of the voltage drop between a gate electrode and an emitter electrode of a power tube is used as a degradation characteristic parameter, the health condition of the three-phase inverter bridge is evaluated through a polynomial fitting time series prediction algorithm, the offset is guaranteed to have a reliable margin (such as a fault threshold), and under the condition that the safety margin is insufficient, a warning is given out, and key devices are replaced and updated in time to guarantee stable and reliable operation of the servo system. The method and the device meet the failure physics and degradation characteristics of the power switch device, the parameters needing to be monitored are few, the design requirement on the testability of the whole system is low, the universality is good, and the real-time fault prediction under the online working condition can be conveniently carried out by a servo system.
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
The servo system fault detection method is suitable for all drive circuits which adopt IGBT or IPM to realize servo control, and is wide in application range. In one specific example, the present application may be applied in an application environment as shown in FIG. 1. The power output circuit of the servo controller is realized by a three-phase inverter circuit, and the switching device is an IGBT (insulated gate bipolar translator), as shown in figure 1, in which U isDCThe bus voltage of the circuit for power output is obtained by rectifying the input three-phase power or commercial power through a three-phase full-bridge rectifying circuit, the power output adopts a three-phase bridge circuit, and the frequency of the output waveform of the inverter is changed by changing the alternating conduction time of the IGBT (pulse Width modulation) by utilizing the pulse Width modulation technology, so that the on-off time ratio of the transistor in each half period is changed, namely, the size of the output voltage of the inverter is changed by changing the pulse Width so as to achieve the purpose of adjusting the power.
Wherein VT1～VT6Six power switch tubes, UA、UB、UCEach representing 3 bridge arms. The present application makes the following provisions for the switching states of the bridge arms: when the upper bridge arm switch tube is in an 'on' state (at the moment, the lower bridge arm switch tube is in an 'off' state certainly), the switch state is 1; when the lower bridge arm switch tube is in an 'on' state (at the moment, the upper bridge arm switch tube is in an 'off' state inevitably), the switch state is 0. Three bridge arms are only in two states of '0' and '1', so that eight switching tube modes including 000, 001, 010, 011, 100, 101 and 111 are formed by the combination of the switching tubes, the eight switching modes correspond to vector synthesis and output of three-phase voltage of the permanent magnet synchronous motor, and abnormal switching characteristics of the switching tubes can directly cause control failure of the servo motorGE) The method has the characteristics that the faults of the IGBT are diagnosed and predicted, the purposes of early warning and timely replacing devices are achieved, and the normal operation of a servo system is ensured.
In one embodiment, as shown in fig. 2, a servo system fault detection method is provided, which is described by taking the method as an example applied to the IGBT in fig. 1, and includes the following steps:
step 202, acquiring an electrical signal of a power output device in a servo system; the electrical signal comprises a voltage signal between a gate electrode and an emitter electrode of each switching tube in the power output device.
The electrical signal may include the detected output voltage and output current of the servo controller, etc.; however, in practical applications, the driver is subjected to fault prediction and analysis by detecting the output voltage and current of the output servo controller, which involve high-voltage electrical signals, and the implementation difficulty is high and the cost is high. In addition, if the device which may fail is directly detected, such as the related electrical parameters of the clamping triode in the protection circuit, in practical application, the technical difficulty is high, the implementation is not easy, and the false alarm rate is high.
The electric signal comprises a voltage signal between a gate electrode and an emitter electrode of each switching tube in the power output device. Specifically, as shown in fig. 1, the voltage V between the gate and emitter of six switching tubes of the three-phase inverter bridge of the servo driver is acquiredGE_A_up，VGE_A_down，VGE_B_up，VGE_B_down，VGE_C_up，VGEC down. The method and the device have the advantages that the voltage of the monitored parameters is low in the implementation process, the hardware is easy to realize, and the method and the device are easy to popularize in practical engineering application.
Furthermore, continuous voltage signals between the gate electrodes and the emitting electrodes of 6 IGBT switching tubes with a fixed time length can be collected;
in a specific embodiment, the step of acquiring an electrical signal of a power output device in the servo system comprises: acquiring voltage signals between gate electrodes and emitting electrodes of the switching tubes according to preset acquisition conditions; the preset acquisition conditions comprise normal load, normal temperature environment, switching tube switching frequency of which the sampling frequency is more than or equal to 5 times, sampling precision of which is more than or equal to 5mV, and switching tube switching period of which the single acquisition time is more than or equal to 2 times;
specifically, the acquisition conditions can include normal load, normal temperature environment, sampling frequency higher than 5 times of switching frequency, sampling precision strain higher than 5mV, and single acquisition time tcShould not be less than 2 times the switching period. Based on the acquisition conditions, the transient voltage ripple of the servo drive switching circuit can be effectively acquired.
Step 204, counting and extracting characteristics of the electrical signals to obtain voltage ripple characteristic parameters; the voltage ripple characteristic parameters comprise a switching transient Miller effect voltage peak-to-peak value sequence and a switching transient Miller effect voltage mean value sequence.
Specifically, the collected continuous voltage signals of each switching tube are subjected to statistics and feature extraction, so that voltage ripple characteristic parameters can be obtained; the voltage ripple characteristic parameters in the present application may include a switching transient miller effect voltage peak-to-peak sequence and a switching transient miller effect voltage mean sequence; the peak value and the mean value of the transient Miller effect ripples of the upper and lower pair of tubes are used as characteristic parameters, so that the degradation degree of the switching characteristic can be reflected; the characteristic parameter capable of indirectly representing the characteristic degradation of the servo drive switch circuit accords with the failure physics and degradation characteristics of the servo driver switch control, and is good in application effect.
Furthermore, the process of obtaining the switching transient miller effect voltage peak-to-peak value sequence and the switching transient miller effect voltage mean value sequence can adopt various modes; for example, the peak value and the mean value within a single acquisition time are obtained by counting the transient miller effect voltage areas of the switching tubes of the servo motor (a mode that voltage signals are integrated with time can be adopted), and then performing feature extraction on the transient miller effect voltage areas within corresponding time periods, so as to form a peak value sequence and a mean value sequence.
In a specific embodiment, the step of acquiring an electrical signal of a power output device in the servo system comprises:
when the servo system finishes the work with preset duration, acquiring voltage signals between gate poles and emitting poles of the switching tubes according to preset acquisition conditions;
the preset acquisition conditions comprise normal load, normal temperature environment, switching tube switching frequency of which the sampling frequency is more than or equal to 5 times, sampling precision of which is more than or equal to 5mV, and switching tube switching period of which the single acquisition time is more than or equal to 2 times.
In a specific embodiment, the step of performing statistics and feature extraction on the electrical signal to obtain the voltage ripple characteristic parameter includes:
performing integral statistics on each voltage signal to obtain the transient Miller effect voltage area of each switching tube;
extracting the characteristics of each transient Miller effect voltage area in a single acquisition time to obtain each peak value and each mean value;
and respectively arranging the peak value and the mean value according to the time sequence to obtain a switching transient Miller effect voltage peak-peak value sequence and a switching transient Miller effect voltage mean value sequence.
In one embodiment, the step of performing integral statistics on each voltage signal to obtain the transient miller effect voltage area of each switching tube includes:
and processing each voltage signal by adopting discrete accumulation to obtain the transient Miller effect voltage area of each switching tube.
In one embodiment, the step of obtaining the transient miller effect voltage area of each switching tube by processing each voltage signal through discrete accumulation includes:
and acquiring the transient Miller effect voltage area according to the switch control state of each switch tube based on the switch period of the switch tube.
Specifically, voltage ripple characteristic parameters are obtained, namely a switching transient Miller effect voltage peak-to-peak value sequence and a switching transient Miller effect voltage mean value sequence are obtained, and continuous voltage signals between gate electrodes and emitting electrodes of 6 IGBT switching tubes in a fixed time length (namely single acquisition time) can be acquired; respectively counting the transient Miller effect voltage areas of the switching tubes of the servo motor (the voltage signals are integrated (discretely accumulated) with respect to time); and (4) performing feature extraction aiming at the voltage area of the transient Miller effect, and respectively calculating a peak value and an average value.
And (3) the servo driver works for a period of time delta t (namely the work of a preset duration), and the steps are repeated to form a switching transient Miller effect voltage peak-to-peak value and average value sequence of the servo driving switching tube.
The off-line test and test for the driving circuit are not required, so that the method is simple, convenient and low in cost; the method comprises the steps of collecting voltage signals according to preset collection conditions after a servo driving circuit works for a period of time, further counting the voltage signals and extracting features to obtain peak values and mean values, and repeating the steps to form time sequences of the feature values of the peak values and the mean values.
Step 206, performing curve fitting on the voltage ripple characteristic parameters to obtain a curve fitting result; and determining the residual time of the fault of the servo system according to the fault threshold and the curve fitting result.
Specifically, a polynomial fitting algorithm is adopted to perform curve fitting on a peak-to-peak value and a mean value sequence of transient Miller effect voltage of a switching device of a servo driver to obtain a curve fitting result; and further determining the residual time of the fault of the servo system according to the fault threshold and the curve fitting result.
The peak-to-peak value threshold value and the mean value threshold value (namely the fault threshold value) of the transient Miller effect voltage representing the fault state of the peripheral protection circuit of the servo driver switching device can be set, and the time left by the functional failure of the switching device is calculated according to a polynomial fitting curve.
In a particular embodiment, the curve fit results include a fault prediction model;
and performing curve fitting on the voltage ripple characteristic parameters to obtain a curve fitting result, wherein the step comprises the following steps of:
and performing curve fitting on the switching transient Miller effect voltage peak-to-peak value sequence and the switching transient Miller effect voltage mean value sequence by using a polynomial fitting algorithm to obtain a fault prediction model.
Specifically, a polynomial fitting algorithm is adopted to perform curve fitting on a peak-to-peak value and a mean value sequence of transient Miller effect voltage of a switching device of the servo driver, and a fault prediction model is formed.
And further setting a peak-to-peak value threshold value and a mean value threshold value of the transient Miller effect voltage representing the fault state of the peripheral protection circuit of the switching device of the servo driver, and calculating the residual time T \uof the functional failure of the switching device according to a polynomial fitting curvefailuer。
In a specific embodiment, the fault threshold is obtained according to a gate trigger voltage of the switching tube;
determining the residual time of the fault of the servo system according to the fault threshold and the curve fitting result, wherein the step comprises the following steps:
and fitting a fault prediction model according to a polynomial curve based on the fault threshold value to obtain the residual time of the fault.
Specifically, a polynomial fitting algorithm can be adopted to perform curve fitting on the peak value characteristic value and the mean value characteristic value according to a time sequence to form a fault prediction model; and further setting a threshold value according to the actual grid trigger voltage of a switching tube of the servo controller, and calculating the time left by the fault according to a polynomial curve fitting fault prediction model.
According to the servo system fault detection method, the offset of the voltage drop between the gate electrode and the emitter electrode of the power tube is used as a degradation characteristic parameter, the health condition of the power output device is evaluated through curve fitting, the offset is guaranteed to have reliable margin, and under the condition that the safety margin is insufficient, a warning is given out, and the replacement and the updating of key devices are timely carried out, so that the stable and reliable operation of the servo system is guaranteed. The method and the device meet the failure physics and degradation characteristics of the power switch device, the parameters needing to be monitored are few, the design requirement on the testability of the whole system is low, the universality is good, and the real-time fault prediction under the online working condition can be conveniently carried out by a servo system.
Furthermore, the application accords with the failure physics and the degradation characteristics of the switch control of the servo driver, and the application effect is good. Meanwhile, the voltage of the monitoring parameters is low in the implementation process, the hardware is easy to realize, and the method is easy to popularize in the practical engineering application. Compared with the traditional servo controller with the abnormal state informing function, the servo controller further realizes the fault early warning function of the servo controller, so that the reliability of the driver is greatly improved, and the servo controller is applied to some key and even special products requiring high reliability, such as weapons, spacecrafts and the like. The off-line test and the test for the driving circuit are not needed, and the method is simple, convenient and low in cost. The method is suitable for all drive circuits which adopt IGBT or IPM to realize servo control, and has wide application range.
To further illustrate the present embodiments, the following description is given with reference to specific examples:
during the use process of the servo controller, in the power output module link, the reasons for the device failure are various, including the collector and emitter voltage (V)GE) The device is burnt out due to short circuit breakdown caused by overlarge impact and bus short circuit caused by simultaneous conduction of the upper and lower switching tubes, and due to the existence of the Miller capacitance of the IGBT device and the parasitic capacitance of the plate, as shown in the following figure 3, the switching control characteristic of the device is easy to be abnormal, so that the IGBT fails.
As shown in the equivalent circuit shown in fig. 3, where CGCExpressed as miller capacitance, when an IGBT switches, a miller platform is generated due to the turn-on of the parasitic miller capacitance, and due to the presence of the miller effect, a very high transient current is generated in the loop of the gate stage and the collector during the turn-off of the IGBT:
the peak current value is very high, which is very easy to cause catastrophic consequences in the up-down bridge type switch tube circuit, in the bridge type pair tube, one switch tube (upper tube or lower tube) will form a loop because the peak current will flow through the gate-level current-limiting resistor of the other switch tube and the driving resistor of the driving chip, the current is released, when the current is large, a certain voltage difference will be generated on the gate-level current-limiting resistor, refer to the following VGEAccording to a calculation formula, when the differential pressure reaches a certain range, the switching tube which should be closed is abnormally switched on, the condition that the bridge type switch pair tubes are simultaneously switched on is formed, and the short circuit of the bus voltage is caused.
VGE＝IGC*(RG+RDRI)
Wherein:
VGEis the gate level of the switch tube and the emitter voltage, the voltage exceeding the threshold value can make the switch tube conduct directly
RGFor doors connected in series to the switching tubeA current limiting resistor between the stage and the emitter;
RDRIthe driving output resistor is a driving output resistor of the switching tube driving chip;
the miller effect is an inherent characteristic of the IGBT, and is related to the design principle and internal structure thereof, and in the circuit design of the servo driver, a design circuit is often added on a circuit to reduce the influence and harm caused by the miller effect, a capacitor is added between a gate and an emitter to share the gate charging current generated by the miller capacitor, or an active miller clamp circuit is adopted, a triode is added between the gate and the emitter, and when the voltage V between the gate and the emitter is increasedGEAt a certain value, the gate-emitter short-circuit switch (triode) will be triggered, so that the current through the miller capacitance will be cut off by the added triode.
However, as environmental stress changes of the device and accumulated stress in the using process and other factors can cause performance degradation of related electronic devices, the protection circuits also have characteristic degradation and even failure risks, and the influence degree caused by the miller effect is predicted and evaluated by directly detecting the voltages from the gate electrodes to the emitters of the upper and lower switching tubes of the inverter bridge, analyzing the respective amplitude variation characteristics of the voltages and the characteristic values of the miller effect voltage of the switching transients of the upper and lower switching tubes, and under a normal operating mode, when the upper tube is switched on, the V is switched onGEA/B/C _ up is greater than the gate turn-on voltage, at which time the down tube is in the off state, VGEA/B/C _ down is close to about 0V, otherwise, V is set when the upper tube is openedGEA/B/C _ down is greater than the gate turn-on voltage, the upper tube is closed at this time, VGEThe _A/B/C _ up is approximately 0v or so, as shown in FIG. 4.
However, if the function of the circuit for suppressing the miller effect of the driving function circuit is degraded or the miller capacitance is increased, the peak value of the miller effect voltage is increased, so that the switching state of the switching tube is not controlled, as shown in fig. 5, and further, a through short circuit and a device burnout are caused.
The application provides a method for detecting faults of a servo system, which comprises the following steps:
(1) three-phase inversion of acquisition servo driverVoltage V between gate and emitter of six switching tubes of bridgeGE_A_up，VGE_A_down，VGE_B_up，VGE_B_down，VGE_C_up，VGEC _ down, the collection condition is normal load, normal temperature environment, the sampling frequency is more than 5 times higher than the switching frequency, the sampling precision is more than 5mV, and the single collection time tcShould not be less than 2 times the switching period;
(2) for example, the area Σ Vd _ down of the transient miller effect voltage signal from the gate to the emitter of the lower tube starts to be calculated in the state that the upper tube is turned on, and the area Σ Vd _ up of the transient miller effect voltage signal from the gate to the emitter of the upper tube starts to be calculated in the state that the lower tube is turned on.
(3) For the length of time acquired tcThe sigma Vd _ down and sigma Vd _ up of the first and second image frames are subjected to feature extraction, and the feature extraction is calculated at tcPeak-to-peak values PP _ Vsum and average values AVG _ Vsum over a period.
(4) The servo driver works for a period of time delta t, and the steps (2) and (3) are repeated to form a switching transient Miller effect voltage peak value and mean value sequence of the servo driving switching tube, which is recorded as
(5) And performing curve fitting on the peak-to-peak value and mean value sequence of the transient Miller effect voltage of the switching device of the servo driver by adopting a polynomial fitting algorithm to form a fault prediction model.
(6) Setting a peak-to-peak value threshold value and a mean value threshold value of transient Miller effect voltage representing the fault state of a peripheral protection circuit of a switching device of a servo driver, and calculating according to a polynomial fitting curve to obtain the residual time of the functional failure of the switching deviceInterval T \ufailuer。
Furthermore, the application provides a characteristic parameter capable of indirectly representing the characteristic degradation of the servo drive switching circuit, and the peak value and the average value of the transient Miller effect ripples of the upper and lower pair of tubes are used as the characteristic parameter to reflect the degradation degree of the switching characteristic.
The method and the requirement for effectively collecting the transient voltage ripple of the servo drive switching circuit can be met, the collecting conditions are normal load and normal temperature environment, the sampling frequency is more than 5 times higher than the switching frequency, the sampling precision is required to be more than 5mV, and the single collecting time tc is required to be not less than 2 times of the switching period;
as shown in fig. 6:
the method comprises the following steps: collecting continuous voltage signals between gate electrodes and emitting electrodes of 6 IGBT switching tubes with a fixed time length;
step two: respectively cutting the acquired signals according to the switching period, respectively counting the Miller effect transient voltage sum in each switching period according to the switching control state and the actual state of an upper pipe and a lower pipe, and extracting the characteristic value of the voltage sum in fixed acquisition time, including the peak-to-peak value and the mean value
Step three: repeating the first step and the second step after the servo drive circuit works for a period of time to form a time sequence of characteristic values of peak values and mean values;
step four: performing curve fitting on the peak value characteristic value and the mean value characteristic value according to the time sequence by adopting a polynomial fitting algorithm to form a fault prediction model;
step five: and setting a threshold according to the actual grid trigger voltage of a switching tube of the servo controller, and calculating the time left by the fault according to a polynomial curve fitting fault prediction model.
The method can detect the electrical signals of a servo system power output device (three-phase inverter bridge) in real time, based on a degradation model of the device, and uses the offset of the voltage drop between a gate electrode and an emitter electrode of a power tube as a degradation characteristic parameter. The method conforms to the failure physics and degradation characteristics of the power switch device, has few parameters to be monitored, has low design requirement on the testability of the whole system and better universality, and is convenient for the servo system to carry out real-time fault prediction under the online working condition.
It should be understood that, although the steps in the flowcharts of fig. 2 and 6 are shown in sequence as indicated by the arrows, the steps are not necessarily performed in sequence as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least some of the steps in fig. 2 and 6 may include multiple sub-steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of performing the sub-steps or stages is not necessarily sequential, but may be performed alternately or alternately with other steps or at least some of the sub-steps or stages of other steps.
In one embodiment, as shown in fig. 7, there is provided a servo system failure detection apparatus including:
the signal acquisition module 710 is used for acquiring an electrical signal of a power output device in the servo system; the electrical signals comprise voltage signals between a gate electrode and an emitter electrode of each switching tube in the power output device;
the characteristic extraction module 720 is used for counting and extracting characteristics of the electrical signals to obtain voltage ripple characteristic parameters; the voltage ripple characteristic parameters comprise a switching transient Miller effect voltage peak-to-peak value sequence and a switching transient Miller effect voltage mean value sequence;
the curve fitting module 730 is used for performing curve fitting on the voltage ripple characteristic parameters to obtain a curve fitting result;
and the fault early warning module 740 is configured to determine the residual time of the fault of the servo system according to the fault threshold and the curve fitting result.
It should be noted that the servo system fault detection apparatus may further include a plurality of corresponding modules, which are used to implement the steps of the servo system fault detection method.
For the specific definition of the servo system failure detection device, reference may be made to the above definition of the servo system failure detection method, which is not described herein again. All or part of each module in the servo system fault detection device can be realized by software, hardware and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as shown in fig. 8. The computer device includes a processor, a memory, a network interface, and a database connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The database of the computer equipment is used for storing data such as electrical signals, voltage ripple characteristic parameters and the like. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a servo system failure detection method.
In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as shown in fig. 9. The computer device includes a processor, a memory, a network interface, a display screen, and an input device connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a servo system failure detection method. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, a key, a track ball or a touch pad arranged on the shell of the computer equipment, an external keyboard, a touch pad or a mouse and the like.
Those skilled in the art will appreciate that the configurations shown in fig. 8 and 9 are block diagrams of only some of the configurations relevant to the present disclosure, and do not constitute a limitation on the computing devices to which the present disclosure may be applied, and that a particular computing device may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, a computer device is provided, comprising a memory and a processor, the memory having a computer program stored therein, the processor implementing the steps of any of the foregoing servo system failure detection methods when executing the computer program.
In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, which computer program, when being executed by a processor, realizes the steps of any of the aforementioned servo system failure detection methods.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms, such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus DRAM (RDRAM), and interface DRAM (DRDRAM).
The technical features of the embodiments described above may be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the embodiments described above are not described, but should be considered as being within the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. A servo system fault detection method is characterized by comprising the following steps:
acquiring an electrical signal of a power output device in a servo system; the electrical signal comprises a voltage signal between a gate electrode and an emitter electrode of each switching tube in the power output device;
counting and extracting characteristics of the electrical signals to obtain voltage ripple characteristic parameters; the voltage ripple characteristic parameters comprise a switching transient Miller effect voltage peak-to-peak value sequence and a switching transient Miller effect voltage mean value sequence;
performing curve fitting on the voltage ripple characteristic parameters to obtain a curve fitting result; and determining the residual time of the fault of the servo system according to the fault threshold and the curve fitting result.
2. The servo system fault detection method of claim 1, wherein the step of obtaining an electrical signal of a power output device in the servo system comprises:
when the servo system finishes the work with preset duration, acquiring voltage signals between the gate electrode and the emitter of each switching tube according to preset acquisition conditions;
the preset acquisition conditions comprise normal load, normal temperature environment, switching tube switching frequency of which the sampling frequency is more than or equal to 5 times, sampling precision of which is more than or equal to 5mV, and switching tube switching period of which the single acquisition time is more than or equal to 2 times.
3. The method for detecting the servo system fault as claimed in claim 2, wherein the step of performing statistics and feature extraction on the electrical signal to obtain the voltage ripple characteristic parameter comprises:
performing integral statistics on the voltage signals to obtain the transient Miller effect voltage area of each switching tube;
performing feature extraction on the voltage area of each transient Miller effect in the single acquisition time to obtain peak values and mean values of each peak;
and respectively arranging the peak value and the mean value according to the time sequence to obtain the peak-peak value sequence of the switching transient Miller effect voltage and the mean value sequence of the switching transient Miller effect voltage.
4. The method according to claim 3, wherein the step of performing integral statistics on each voltage signal to obtain the voltage area of the switching tube with the transient Miller effect comprises:
and processing each voltage signal by adopting discrete accumulation to obtain the transient Miller effect voltage area of each switching tube.
5. The method of claim 4, wherein the step of obtaining the voltage area of the switching tube with the transient Miller effect by processing the voltage signals with discrete summation comprises:
and acquiring the transient Miller effect voltage area according to the switch control state of each switch tube based on the switch period of the switch tube.
6. The servo system fault detection method of any one of claims 1 to 5, wherein the curve fitting result comprises a fault prediction model;
and performing curve fitting on the voltage ripple characteristic parameters to obtain a curve fitting result, wherein the step comprises the following steps of:
and performing curve fitting on the switching transient Miller effect voltage peak-to-peak value sequence and the switching transient Miller effect voltage mean value sequence by using a polynomial fitting algorithm to obtain the fault prediction model.
7. The method according to claim 6, wherein the fault threshold is obtained according to a gate trigger voltage of a switching tube;
determining the residual time of the fault of the servo system according to the fault threshold and the curve fitting result, wherein the step comprises the following steps:
and fitting the fault prediction model according to a polynomial curve based on the fault threshold value to obtain the residual time of the fault.
8. A servo system failure detection apparatus, comprising:
the signal acquisition module is used for acquiring an electrical signal of a power output device in the servo system; the electrical signal comprises a voltage signal between a gate electrode and an emitter electrode of each switching tube in the power output device;
the characteristic extraction module is used for counting and extracting characteristics of the electrical signals to obtain voltage ripple characteristic parameters; the voltage ripple characteristic parameters comprise a switching transient Miller effect voltage peak-to-peak value sequence and a switching transient Miller effect voltage mean value sequence;
the curve fitting module is used for performing curve fitting on the voltage ripple characteristic parameters to obtain a curve fitting result;
and the fault early warning module is used for determining the fault occurrence remaining time of the servo system according to the fault threshold and the curve fitting result.
9. A computer device comprising a memory and a processor, the memory storing a computer program, wherein the processor implements the steps of the method of any one of claims 1 to 7 when executing the computer program.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 7.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113433480A (en) * | 2021-06-29 | 2021-09-24 | 北京交通大学 | Fault early warning method for control power supply system |
| CN114034902A (en) * | 2021-09-28 | 2022-02-11 | 海信（山东）空调有限公司 | Phase voltage detection method and device, variable frequency air conditioner and control method and device thereof |
| CN114154760A (en) * | 2021-12-30 | 2022-03-08 | 中国电子产品可靠性与环境试验研究所（（工业和信息化部电子第五研究所）（中国赛宝实验室）） | Fault prediction method and device of switching power supply, computer equipment and storage medium |
| CN115632593A (en) * | 2022-11-07 | 2023-01-20 | 歌尔股份有限公司 | Protection method of linear motor, terminal device and computer readable storage medium |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6541933B1 (en) * | 2001-11-20 | 2003-04-01 | Rockwell Automation Technologies, Inc. | Angle control of modulating wave to reduce reflected wave overvoltage transients |
| EP2405570A1 (en) * | 2010-07-07 | 2012-01-11 | Technische Universität Wien | A method and system for tracking inherent saliencies of ac machines |
| CN102393502A (en) * | 2011-12-15 | 2012-03-28 | 苏州凌创电子科技有限公司 | IGBT (Insulated Gate Bipolar Translator) test device and method of automobile engine control module (ECM) |
| CN104570789A (en) * | 2013-10-18 | 2015-04-29 | 瑞萨电子株式会社 | Semiconductor device and electronic control device |
| CN108169654A (en) * | 2018-01-02 | 2018-06-15 | 中国电子产品可靠性与环境试验研究所（（工业和信息化部电子第五研究所）（中国赛宝实验室）） | Power module HTRB reliability test systems |
| CN110175388A (en) * | 2019-05-21 | 2019-08-27 | 中国电子产品可靠性与环境试验研究所（（工业和信息化部电子第五研究所）（中国赛宝实验室）） | Switching Power Supply failure prediction method, device, computer equipment and storage medium |
-
2020
- 2020-02-18 CN CN202010098380.2A patent/CN111258303B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6541933B1 (en) * | 2001-11-20 | 2003-04-01 | Rockwell Automation Technologies, Inc. | Angle control of modulating wave to reduce reflected wave overvoltage transients |
| EP2405570A1 (en) * | 2010-07-07 | 2012-01-11 | Technische Universität Wien | A method and system for tracking inherent saliencies of ac machines |
| CN102393502A (en) * | 2011-12-15 | 2012-03-28 | 苏州凌创电子科技有限公司 | IGBT (Insulated Gate Bipolar Translator) test device and method of automobile engine control module (ECM) |
| CN104570789A (en) * | 2013-10-18 | 2015-04-29 | 瑞萨电子株式会社 | Semiconductor device and electronic control device |
| CN108169654A (en) * | 2018-01-02 | 2018-06-15 | 中国电子产品可靠性与环境试验研究所（（工业和信息化部电子第五研究所）（中国赛宝实验室）） | Power module HTRB reliability test systems |
| CN110175388A (en) * | 2019-05-21 | 2019-08-27 | 中国电子产品可靠性与环境试验研究所（（工业和信息化部电子第五研究所）（中国赛宝实验室）） | Switching Power Supply failure prediction method, device, computer equipment and storage medium |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113433480A (en) * | 2021-06-29 | 2021-09-24 | 北京交通大学 | Fault early warning method for control power supply system |
| CN114034902A (en) * | 2021-09-28 | 2022-02-11 | 海信（山东）空调有限公司 | Phase voltage detection method and device, variable frequency air conditioner and control method and device thereof |
| CN114154760A (en) * | 2021-12-30 | 2022-03-08 | 中国电子产品可靠性与环境试验研究所（（工业和信息化部电子第五研究所）（中国赛宝实验室）） | Fault prediction method and device of switching power supply, computer equipment and storage medium |
| CN115632593A (en) * | 2022-11-07 | 2023-01-20 | 歌尔股份有限公司 | Protection method of linear motor, terminal device and computer readable storage medium |
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|---|---|
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