WO2020142945A1 - 电机失效检测方法、设备及存储介质 - Google Patents

电机失效检测方法、设备及存储介质 Download PDF

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Publication number
WO2020142945A1
WO2020142945A1 PCT/CN2019/071030 CN2019071030W WO2020142945A1 WO 2020142945 A1 WO2020142945 A1 WO 2020142945A1 CN 2019071030 W CN2019071030 W CN 2019071030W WO 2020142945 A1 WO2020142945 A1 WO 2020142945A1
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sampling
value
sampling period
values
sampled
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PCT/CN2019/071030
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English (en)
French (fr)
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刘祯
王闯
赵进
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深圳市大疆创新科技有限公司
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Priority to PCT/CN2019/071030 priority Critical patent/WO2020142945A1/zh
Priority to CN201980005352.7A priority patent/CN111727375A/zh
Publication of WO2020142945A1 publication Critical patent/WO2020142945A1/zh

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/34—Testing dynamo-electric machines

Definitions

  • Embodiments of the present invention relate to the field of motor detection, and in particular, to a motor failure detection method, device, and storage medium.
  • a DC motor or DC motor, is a motor that converts DC electrical energy into mechanical energy.
  • DC motors are widely used in various fields due to their good speed control performance and large starting torque.
  • mechanical laser radar drives optical components to rotate through the motor to generate a scanning surface to achieve the distance and contour measurement functions of objects ;
  • unmanned aerial vehicles or remote control vehicles that need to be driven by a motor to provide power. Due to the load of the motor, long-term working conditions and some extreme measurement environments (high temperature and high humidity, etc.), the motor has a high risk of failure.
  • the causes of motor failure include burnout of external control circuits, damage to motor windings, damage to bearings, deformation of motor shafts, and entry of external impurities. Among them, burnout of external control circuits and damage to motor windings are now very rare, so it is necessary to focus on the failure of the motor caused by factors such as bearing damage, motor shaft deformation and external impurities.
  • Existing methods for detecting abnormal motor status mainly monitor the surface temperature of the motor. If the motor fails, the temperature of the motor casing will increase significantly. Therefore, it is possible to determine whether the motor is abnormal by monitoring the temperature of the motor casing. Alternatively, the power consumption of the motor can be monitored to make judgments on the operating state of the motor.
  • the method of monitoring the surface temperature of the motor is not robust to the ambient temperature, and correct judgment cannot be made in high and low temperature environments; in addition, this method requires the use of external temperature measurement equipment Measurement, for example, using a non-contact infrared thermometer to measure the surface temperature of the motor, is not convenient enough, and is not suitable for applications such as vehicle and robot.
  • the power consumption of the motor is not only affected by the damage and failure of the motor components, but the ambient temperature, circuit system, and power supply stability all have an impact on the power consumption of the motor.
  • Embodiments of the present invention provide a motor failure detection method, equipment, and storage medium to accurately predict the motor failure and avoid the adverse consequences caused by the sudden failure of the motor.
  • a first aspect of an embodiment of the present invention is to provide a motor failure detection method, including:
  • the state parameters include current parameters and/or speed parameters
  • a second aspect of an embodiment of the present invention is to provide a motor failure detection device, including: a processor, the processor is configured to perform the following operations:
  • the state parameters include current parameters and/or speed parameters
  • a third aspect of the embodiments of the present invention is to provide a radar system, including:
  • Distance measuring component used to emit light pulse sequence and receive light pulse sequence reflected by the detected object
  • a scanning assembly including an optical element and a driving motor that drives the optical element to rotate, the optical element being disposed on the optical path of the light pulse sequence of the distance measuring assembly;
  • a processor the processor is used to perform the following operations:
  • the state parameters include current parameters and/or speed parameters
  • a fourth aspect of the embodiments of the present invention is to provide a movable platform, including:
  • the radar system as described in the third aspect is described.
  • a fifth aspect of the embodiments of the present invention is to provide a computer-readable storage medium on which a computer program is stored, which is executed by a processor to implement the method of the first aspect.
  • the motor failure detection method, device and storage medium provided in this embodiment, by acquiring the state parameters of the motor, the state parameters include current parameters and/or speed parameters, and determine whether the state parameters exceed a preset threshold, if the state If the parameter exceeds the preset threshold, it is judged that the motor is about to fail.
  • the method provided in this embodiment can accurately predict the motor failure based on current parameters and/or speed parameters, can avoid the influence of environmental temperature, power supply stability and other factors on the prediction results, and has good robustness, so that the motor can be effectively avoided The undesirable consequences brought by sudden failure are easy to implement and highly automated.
  • FIG. 1 is a flowchart of a motor failure detection method provided by an embodiment of the present invention.
  • 2a is a speed curve diagram of a motor during operation provided by an embodiment of the present invention
  • 2b is a current curve diagram of a motor during operation provided by an embodiment of the present invention.
  • FIG. 3 is a flowchart of a motor failure detection method according to another embodiment of the present invention.
  • FIG. 4 is a flowchart of a motor failure detection method according to another embodiment of the present invention.
  • FIG. 5 is a flowchart of a motor failure detection method according to another embodiment of the present invention.
  • FIG. 6 is a flowchart of a motor failure detection method according to another embodiment of the present invention.
  • FIG. 7 is a flowchart of a motor failure detection method according to another embodiment of the present invention.
  • FIG. 8 is a flowchart of a motor failure detection method according to another embodiment of the present invention.
  • FIG. 9 is a structural diagram of a motor failure detection device provided by an embodiment of the present invention.
  • FIG. 10 is a structural diagram of a radar system provided by an embodiment of the present invention.
  • FIG. 11 is a structural diagram of a radar system provided by another embodiment of the present invention.
  • FIG. 12 is a structural diagram of a radar system provided by another embodiment of the present invention.
  • FIG. 13 is a structural diagram of a movable platform provided by an embodiment of the present invention.
  • a component when a component is said to be “fixed” to another component, it can be directly on another component or there can be a centered component. When a component is considered to be “connected” to another component, it can be directly connected to another component or there may be a centered component at the same time.
  • the motor of the present invention may be a driving motor of the radar system, and the driving motor is used to drive the scanning component in the radar system to rotate.
  • the motor of the present invention may also be a driving motor of the power system of the movable platform, and the movable platform may be an unmanned aerial vehicle or a remote control car.
  • the motor of the present invention may also be a motor in any other equipment, and the motor failure detection method provided by the embodiment of the present invention may be used to predict whether the motor is about to fail.
  • FIG. 1 is a flowchart of a motor failure detection method provided by an embodiment of the present invention. As shown in FIG. 1, the method in this embodiment may include:
  • Step S101 Obtain a state parameter of the motor, where the state parameter includes a current parameter and/or a speed parameter.
  • the state parameter of the motor is used as a judgment index of whether the motor is about to fail, wherein the state parameter of the motor is selected as the current parameter and/or the speed parameter.
  • the current parameter and/or the speed parameter are selected as the state parameter of the motor, because the running current and speed of the motor will fluctuate when the motor is about to fail.
  • the motor shown in FIGS. 2a and 2b is running for 1600 hours During the speed curve and current curve in the process, after about 1600 hours, the motor 1 fails and stops. It can be seen from Fig. 2 that the running current of the motor 1 started to increase within 500 hours before the failure, and a large fluctuation occurred at the same time. At the same time, it can be seen from the speed curve that the speed of the motor also began to fluctuate to a certain extent; For the normally running motor 2, the running current and motor speed are relatively stable.
  • the current parameter may specifically include the average value of the current and/or the stability parameter of the current;
  • the rotation speed parameter may specifically include the average value of the rotation speed and/or the stability parameter of the rotation speed.
  • the stability parameter can choose concentration, variance, standard deviation, etc. It should be noted that, in this embodiment, any one of the above various state parameters or a combination of several state parameters may be selected as the state parameter of the motor.
  • Step S102 Determine whether the state parameter exceeds a preset threshold.
  • any of a state parameter with a predetermined threshold value corresponds, for example, the motor 2 in FIG, I_mean current average value
  • the preset threshold can be selected according to actual needs.
  • Step S103 If the state parameter exceeds the preset threshold, it is determined that the motor is about to fail.
  • the state parameters of the motor can be obtained in real time or at a preset period, and the state of the motor can be monitored, so that it can be judged in time that the motor is about to fail.
  • the current and rotation speed of the motor 1 only start to fluctuate within 500 hours before the failure, but there is no significant fluctuation during the first 1100 hours, so in this embodiment
  • the state parameters of the motor are obtained in real time or at a preset period when the motor starts to run.
  • the state parameters of the motor can be obtained in real time or at a preset period after the motor runs for a certain period of time to monitor the state of the motor.
  • the state parameters include a current parameter and/or a speed parameter, and determine whether the state parameter exceeds a preset threshold, and if the state parameter exceeds the preset If a threshold is set, it is judged that the motor is about to fail.
  • the method provided in this embodiment can accurately predict motor failure based on current parameters and/or speed parameters, can avoid the influence of environmental temperature, power supply stability and other factors on the prediction results, and has good robustness, thereby effectively avoiding motors The undesirable consequences brought by sudden failure are easy to implement and highly automated.
  • FIG. 3 is a flowchart of a motor failure detection method according to another embodiment of the present invention. As shown in FIG. 3, on the basis of the embodiment shown in FIG. 1, acquiring the state parameter of the motor in step S101 may include:
  • Step S201 Acquire a sampling value of the motor at a predetermined frequency within a sampling period, the sampling value includes a real-time current and/or a real-time rotational speed.
  • Step S202 Obtain the average value of the sampling values in the sampling period according to the sampling value; and/or acquire the stability parameters of the sampling values in the sampling period according to the sampling value.
  • the real-time current and/or real-time speed of the motor is collected at a predetermined frequency as the sampling value of the motor, and then the average value of the sampling value in the period is obtained based on the sampling value of the motor and/or or
  • the stability parameter of the sampled value taking the real-time current as an example, can set the sampling period to 5min, and collect the real-time current of the motor at a frequency of 5Hz, so that when the sampling time reaches 5min, a total of 1500 sampled values are collected for the real-time current.
  • the average value (such as arithmetic average) and/or stability parameters (such as concentration, variance, and standard deviation) of the 1500 sampled values in this sampling period can be obtained as the state parameters of the motor in this sampling period, and then the preset threshold A comparison is made to determine whether the motor is about to fail; the above process is repeated in the next sampling period until it is determined that the motor is about to fail.
  • the step S201 of acquiring the sampling value of the motor at a predetermined frequency within the sampling period may specifically include:
  • the real-time rotational speed of the motor is collected from the code wheel at a predetermined frequency during the sampling period, wherein the motor is electrically connected to the code wheel.
  • the motor is electrically connected to the ESC, and the power supply and control of the motor are realized through the ESC.
  • the real-time current of the motor can be collected from the ESC. More specifically, it can be passed The sampling resistor collects current from the ESC; in addition, the motor is also electrically connected to the code wheel.
  • the code wheel is used to monitor the motor speed in real time. In this embodiment, the real-time speed of the motor can be collected from the code wheel.
  • obtaining the average value of the sampled values in the sampling period according to the sampled values may specifically include:
  • Step S301 When acquiring the sampling value of the motor at a predetermined frequency within the sampling period, accumulate the collected sampling value through the first accumulator;
  • Step S302 At the end of the sampling period, obtain the average value of the sampling values in the sampling period according to the accumulation result of the first accumulator and the total number of sampling values in the sampling period.
  • the collected sampled value is accumulated by the first accumulator, and the accumulated sampled value is accumulated once, so there is no need to store the sampled value;
  • the accumulated result of the sampled values can be obtained.
  • the accumulated result is I_sum
  • the first accumulator can be cleared before the start of the next sampling period.
  • a method of calculating the average value after storing the sampled values may also be used.
  • the stability parameter of the sampled value includes the concentration of the sampled value, where the concentration is a parameter that measures the number of sampled values that fall within a predetermined sample value fluctuation range.
  • the step S202 of obtaining the stability parameter of the sampled value in the sampling period according to the sampled value may specifically include:
  • the predetermined sampling value fluctuation range is any one of the following:
  • Preset range sample value range obtained based on the average value of sample values in the first sampling period, sample value range obtained based on the average value of sample values in the previous sampling period, sample value range obtained based on the average value of sample values in the current sampling period .
  • the predetermined sampled value fluctuation range can be a preset range, or can be obtained based on the average value of the sampled value, for example, for real-time current, the average value of the current
  • the concentration of the sampling value cannot be obtained in the first sampling period .
  • the concentration of the sampled values can only be obtained from the second sampling period; of course, if the average value is calculated after storing the sampled values, the concentration of the sampled values can also be obtained in the first sampling period;
  • the sampling value of the sampling period is to consider that there will be slow changes in the real-time current or real-time speed during the operation of the motor, but there is no large fluctuation during the slow change.
  • the predetermined current fluctuation range is a preset range, or a range of sampling values obtained according to an average value of sampling values in a first sampling period, or an average value according to sampling values in a previous sampling period
  • the acquired sampling value range the ratio of the number of sampling values within the predetermined sampling value fluctuation range to the total number of sampling values in the sampling period in the acquisition sampling period includes:
  • Step S401 When acquiring the sampling value of the motor at a predetermined frequency within the sampling period, count the number of sampling values within the fluctuation range of the predetermined sampling value through a counter;
  • Step S402 At the end of the sampling period, according to the counting result of the counter and the total number of sampling values in the sampling period, obtain the concentration of the sampling values in the sampling period.
  • the predetermined current fluctuation range is a preset range, or a sampling value range obtained according to an average value of sampling values in a first sampling period, or a sampling value range obtained according to an average value of sampling values in a previous sampling period, In other words, it is not necessary to calculate the average value of the sampling values in this sampling period, the number of sampling values within the fluctuation range of the predetermined sampling value can be directly counted by the counter.
  • the counter increments by 1 (otherwise it does not increment). At the end of the sampling period, the current counting result of the counter is used as the sampling within the predetermined sampling value fluctuation range.
  • the number of values, and then the concentration of the sampled values in the sampling period is obtained according to the counting result of the counter and the total number of sampled values in the sampling period. It should be noted that the counter can be cleared before the beginning of the next sampling period. In this embodiment, there is no need to store the sampled values, which greatly saves storage resources and at the same time improves the efficiency of acquiring the concentration of the sampled values.
  • the predetermined sampling value fluctuation range is a sampling value range acquired according to an average value of sampling values in the current sampling period, then sampling within the predetermined sampling value fluctuation range within the acquisition sampling period
  • the ratio of the number of values to the total number of samples in the sampling period including:
  • Step S501 When acquiring the sampling value of the motor at a predetermined frequency within a sampling period, storing the sampling value;
  • Step S502 At the end of the sampling period, obtain the average value of the sampling value of the sampling period according to the stored sampling value, and obtain the predetermined sampling value fluctuation range according to the average value of the sampling value of the sampling period;
  • Step S503 Acquire the concentration of the sampling values in the sampling period according to the stored sampling values and the predetermined sampling value fluctuation range.
  • the predetermined sampling value fluctuation range is the sampling value range obtained based on the average value of the sampling values in the current sampling period. Since the average value of the sampling value in the sampling period must be obtained first, the predetermined sampling value fluctuation range can be obtained, and In order to determine whether each sampling value is within the predetermined sampling value fluctuation range, it is necessary to store the sampling value during sampling.
  • each stored sample value is compared with the predetermined sampling value fluctuation range, and the statistical sampling period is within the predetermined sampling value fluctuation range
  • the number of sampled values within, and then the concentration of sampled values within the sampling period is obtained according to the number of sampled values within the fluctuation range of the predetermined sampled value in the current sampling period and the total number of sampled values in the current sampling period.
  • the stability parameter of the sampled value includes the variance or standard deviation of the sampled value, and the degree of deviation between the sampled value and the expected value (average value of the sampled value) is measured by the variance or standard deviation.
  • the step S202 of obtaining the stability parameter of the sampled value in the sampling period according to the sampled value includes:
  • the preset average value, the average value of the sampling values in the first sampling period, the average value of the sampling values in the previous sampling period, and the average value of the sampling values in the current sampling period are the preset average value, the average value of the sampling values in the first sampling period, the average value of the sampling values in the previous sampling period, and the average value of the sampling values in the current sampling period.
  • the variance or standard deviation of the sampled value within the sampling period can be obtained from the sampled value and the average value of the sampled value, for example, the variance of the rotation speed can be calculated using the following formula:
  • the standard deviation of the speed can be calculated using the following formula:
  • S_i is the sampling value of the rotation speed in the sampling period (real-time rotation speed)
  • S_0 is the average value of the rotation speed
  • n_sum is the total number of sampling values in the sampling period.
  • the average value of the sampled value needs to be obtained, wherein the average value of the sampled value can be selected from a preset average value such as a target current value, a target speed value, etc.;
  • the average value of the sampled values in the first sampling period, or the average value of the sampled values in the previous sampling period, or the average value of the sampled values in the current sampling period may be used.
  • the average value of the sampled value in the first sampling period or the average value of the sampled value in the previous sampling period is used, if the above-mentioned first accumulator is used to obtain the average value of the sampled value, the sampled value cannot be obtained in the first sampling period Variance or standard deviation; of course, if the average value is calculated after storing the sampled value, the variance or standard deviation of the sampled value can also be obtained in the first sampling period; for the case of using the average value of the sampled value of this sampling period Since the average value of the sampling value in this sampling period must be obtained before the variance or standard deviation of the sampling value in this sampling period can be calculated, it is necessary to store the sampling value in this sampling period when acquiring the sampling value of the motor.
  • the sampling value and the average value of the sampling value acquiring the variance or standard deviation of the sampling value in the sampling period include:
  • Step S601 When acquiring the sampling value of the motor at a predetermined frequency within the sampling period, accumulate the square value of the difference between the sampling value and the average value of the sampling value through the second accumulator;
  • Step S602 At the end of the sampling period, obtain the variance or standard deviation of the sampling values in the sampling period according to the accumulation result of the second accumulator and the total number of sampling values in the sampling period.
  • the average value of the sampled value is the preset average value, or the average value of the sampled value of the first sampling period, or the average value of the sampled value of the previous sampling period, that is, the sampled value of the current sampling period does not need to be calculated
  • the accumulation result of the second accumulator is Furthermore, the variance or standard deviation of the sampled values in the current sampling period is calculated according to the accumulation result of the second accumulator and the total number of sampled values in the sampling period.
  • the average value of the sampled values is the average value of the sampled values in the sampling period
  • the sampled value in the sampling period is obtained according to the sampled value and the average value of the sampled values Variance or standard deviation, including:
  • Step S701 When acquiring the sampling value of the motor at a predetermined frequency within the sampling period, storing the sampling value;
  • Step S702 At the end of the sampling period, obtain the average value of the sampling value of the sampling period according to the stored sampling value, and obtain the sampling period according to the stored sampling value and the average value of the sampling value of the sampling period The variance or standard deviation of the internally sampled values.
  • the average value of the sampled value is the average value of the sampled value in the sampling period.
  • the average value of the sampled value in the sampling period must be obtained. Therefore, the sampled value needs to be stored during sampling.
  • the average value of the sampling value and the sampling value is obtained according to the stored sampling value and the average value of the sampling value of the sampling period.
  • the accumulation result of the square value of the difference, and then the variance or standard deviation of the sampled value in the sampling period is obtained according to the accumulation result and the total number of sampled values in the sampling period.
  • the motor failure detection method by acquiring the state parameters of the motor, the state parameters include a current parameter and/or a speed parameter (specifically may be an average value and/or a stability parameter), and determine whether the state parameter exceeds A preset threshold, if the state parameter exceeds the preset threshold, it is determined that the motor is about to fail.
  • the method provided in this embodiment can accurately predict the motor failure based on current parameters and/or speed parameters, can avoid the influence of environmental temperature, power supply stability and other factors on the prediction results, and has good robustness, so that the motor can be effectively avoided The undesirable consequences brought by sudden failure are easy to implement and highly automated.
  • FIG. 9 is a structural diagram of a motor failure detection device according to an embodiment of the present invention.
  • the motor failure detection device 80 includes a processor 81.
  • the motor failure detection device 80 of this embodiment may further include: a memory 82, a communication interface 83, and the like.
  • the processor 81 is used to perform the following operations:
  • the state parameters include current parameters and/or speed parameters
  • the current parameter includes an average value of current and/or a stability parameter of current
  • the speed parameter includes an average speed value and/or a speed stability parameter.
  • the processor 81 when the processor 81 acquires the state parameter of the motor, the processor 81 is configured to:
  • the sampling value includes real-time current and/or real-time speed
  • the processor 81 when the processor 81 obtains the average value of the sampled values in the sampling period according to the sampled values, the processor 81 is configured to:
  • the collected sampling value is accumulated by the first accumulator
  • the average value of the sampling values in the sampling period is obtained according to the accumulation result of the first accumulator and the total number of sampling values in the sampling period.
  • the stability parameter of the sampled value includes the concentration of the sampled value
  • the processor 81 When the processor 81 obtains the stability parameter of the sampled value in the sampling period according to the sampled value, the processor 81 is configured to:
  • the predetermined sampling value fluctuation range is any one of the following:
  • sampling value range obtained based on the average value of sampling values in the first sampling period sampling value range obtained based on the average value of sampling values in the previous sampling period, sampling value range obtained based on the average value of sampling values in the current sampling period .
  • the processor 81 acquires the ratio of the number of sample values within the predetermined sample value fluctuation range in the sampling period to the total number of sample values in the sampling period, the processor 81 is configured to:
  • the number of sampling values within the fluctuation range of the predetermined sampling value is counted by a counter
  • the concentration of the sampling values in the sampling period is obtained.
  • the predetermined sampling value fluctuation range is a sampling value range acquired according to the average value of the sampling values in the current sampling period
  • the predetermined sampling value fluctuation is within the sampling period acquired by the processor 81
  • the processor 81 is configured to:
  • the concentration of the sampled value in the sampling period is obtained according to the stored sampled value and the predetermined sampled value fluctuation range.
  • the stability parameter of the sampled value includes the variance or standard deviation of the sampled value
  • the processor 81 When the processor 81 obtains the stability parameter of the sampling value in the sampling period according to the sampling value, the processor 81 is configured to:
  • the preset average value, the average value of the sampling values in the first sampling period, the average value of the sampling values in the previous sampling period, and the average value of the sampling values in the current sampling period are the preset average value, the average value of the sampling values in the first sampling period, the average value of the sampling values in the previous sampling period, and the average value of the sampling values in the current sampling period.
  • the processor 81 When the processor 81 obtains the variance or standard deviation of the sampled values in the sampling period according to the sampled values and the average value of the sampled values, the processor 81 is configured to:
  • the square value of the difference between the sampling value and the average value of the sampling value is accumulated by the second accumulator;
  • the variance or standard deviation of the sampling values in the sampling period is obtained according to the accumulation result of the second accumulator and the total number of sampling values in the sampling period.
  • the processor 81 obtains the sample based on the sampled value and the average value of the sampled values When the variance or standard deviation of the sampled values in the period, the processor 81 is configured to:
  • the processor 81 when the processor 81 acquires the sampling value of the motor at a predetermined frequency within the sampling period, the processor 81 is configured to:
  • the real-time rotational speed of the motor is collected from the code wheel at a predetermined frequency during the sampling period, wherein the motor is electrically connected to the code wheel.
  • the motor is a driving motor of a radar system, and the driving motor is used to drive the scanning component in the radar system to rotate.
  • the motor is a drive motor of the power system of the movable platform.
  • the movable platform includes at least one of the following: unmanned aerial vehicle and remote control vehicle.
  • the motor failure detection device obtains the state parameters of the motor, the state parameters include a current parameter and/or a speed parameter, and determines whether the state parameter exceeds a preset threshold, and if the state parameter exceeds the preset If a threshold is set, it is judged that the motor is about to fail.
  • the device provided in this embodiment can accurately predict motor failure based on current parameters and/or speed parameters, can avoid the influence of environmental temperature, power supply stability and other factors on the prediction results, and has good robustness, thereby effectively avoiding motors The undesirable consequences brought by sudden failure are easy to implement and highly automated.
  • FIG. 10 is a structural diagram of a radar system provided by an embodiment of the present invention. As shown in FIG. 10, the radar system 90 includes a ranging component 91, a scanning component 92, and a processor 93.
  • the distance measuring assembly 91 is used to emit a light pulse sequence and receive the light pulse sequence reflected by the object to be detected;
  • the scanning assembly 92 includes an optical element and a driving motor that drives the optical element to rotate, the optical element Set on the optical path of the light pulse sequence of the distance measuring assembly 91;
  • the processor 93 is used to perform the following operations: obtain a state parameter of the motor, the state parameter includes a current parameter and/or a speed parameter; determine whether the state parameter The preset threshold is exceeded; if the state parameter exceeds the preset threshold, the motor is judged to be invalid.
  • the ranging component 91 may include a transmitting circuit 911, a receiving circuit 912, a sampling circuit 913, and an arithmetic circuit 914.
  • the transmission circuit 911 may transmit a sequence of light pulses (for example, a sequence of laser pulses).
  • the receiving circuit 912 can receive the optical pulse sequence reflected by the detected object, and photoelectrically convert the optical pulse sequence to obtain an electrical signal, which can be output to the sampling circuit 913 after processing the electrical signal.
  • the sampling circuit 913 can sample the electrical signal to obtain the sampling result.
  • the arithmetic circuit 914 may determine the distance between the radar system 100 and the detected object based on the sampling result of the sampling circuit 913.
  • the radar system shown in FIG. 11 includes a transmitting circuit, a receiving circuit, a sampling circuit, and an arithmetic circuit for emitting a beam of light for detection, the embodiments of the present application are not limited thereto.
  • the transmitting circuit, The number of any one of the receiving circuit, the sampling circuit, and the arithmetic circuit may also be at least two, for emitting at least two light beams in the same direction or respectively in different directions; wherein, the at least two light paths may be emitted simultaneously , Can also be shot at different times.
  • the light-emitting chips in the at least two emission circuits are packaged in the same module.
  • each emitting circuit includes one laser emitting chip, and the die (bare die) in the laser emitting chips in the at least two emitting circuits are packaged together and housed in the same packaging space.
  • the distance measuring assembly may further include a control circuit 915, which may control other circuits, for example, may control the working time of each circuit and/or set parameters for each circuit.
  • a control circuit 915 may control other circuits, for example, may control the working time of each circuit and/or set parameters for each circuit.
  • the scanning component is used to output at least one laser pulse sequence emitted from the transmitting circuit by changing the propagation direction.
  • a coaxial optical path may be used, that is, the light beam emitted by the radar system and the reflected light beam share at least part of the optical path in the radar system.
  • the laser pulse sequence reflected by the detection object passes through the scanning module and enters the receiving circuit.
  • the radar system may also adopt an off-axis optical path, that is, the light beam emitted by the radar system and the reflected light beam are transmitted along different optical paths in the radar system, respectively.
  • FIG. 12 shows a schematic diagram of an embodiment of the radar system of the present invention using a coaxial optical path.
  • the radar system 9000 includes a ranging component 9001, and the ranging component 9001 includes a transmitter 9003 (which may include the above-mentioned transmitting circuit), a collimating element 9004, and a detector 9005 (which may include the above-mentioned receiving circuit and sampling circuit And arithmetic circuit) and optical path changing element 9006.
  • the distance measuring assembly 9001 is used to emit a light beam and receive the return light, and convert the return light into an electrical signal.
  • the transmitter 9003 may be used to transmit a sequence of light pulses. In one embodiment, the transmitter 9003 may emit a sequence of laser pulses.
  • the laser beam emitted by the transmitter 9003 is a narrow-bandwidth beam with a wavelength outside the visible light range.
  • the collimating element 9004 is disposed on the exit optical path of the emitter, and is used to collimate the light beam emitted from the emitter 9003, and collimate the light beam emitted from the emitter 9003 into parallel light to the scanning component.
  • the collimating element is also used to converge at least a part of the return light reflected by the detection object.
  • the collimating element 9004 may be a collimating lens or other element capable of collimating the light beam.
  • the optical path changing element 9006 is used to combine the transmitting optical path and the receiving optical path in the radar system before the collimating element 9004, so that the transmitting optical path and the receiving optical path can share the same collimating element, making the optical path more compact.
  • the transmitter 9003 and the detector 9005 may respectively use respective collimating elements, and the optical path changing element 9006 is disposed on the optical path behind the collimating element.
  • the light path changing element can use a small-area mirror to emit The optical path and the receiving optical path are merged.
  • the light path changing element may also use a mirror with a through hole, where the through hole is used to transmit the light emitted from the emitter 9003, and the mirror is used to reflect the return light to the detector 9005. In this way, it is possible to reduce the blocking of the return light by the support of the small mirror in the case of using the small mirror.
  • the optical path changing element is offset from the optical axis of the collimating element 9004. In some other implementations, the optical path changing element may also be located on the optical axis of the collimating element 9004.
  • the radar system 9000 also includes a scanning assembly 9002.
  • the scanning component 9002 is placed on the exit optical path of the distance measuring component 9001.
  • the scanning component 9002 is used to change the transmission direction of the collimated light beam 9019 emitted through the collimating element 9004 and project it to the external environment, and project the return light to the collimating element 9004. .
  • the returned light is converged on the detector 9005 via the collimating element 9004.
  • the scanning assembly 9002 may include at least one optical element for changing the propagation path of the light beam, wherein the optical element may change the propagation path of the light beam by reflecting, refracting, diffracting, etc. the light beam.
  • the scanning assembly 9002 includes a lens, a mirror, a prism, a galvanometer, a grating, a liquid crystal, an optical phased array (Optical Phased Array), or any combination of the above optical elements.
  • at least part of the optical element is moving, for example, the at least part of the optical element is driven to move by a driving module, and the moving optical element can reflect, refract or diffract the light beam to different directions at different times.
  • multiple optical elements of the scanning assembly 9002 can rotate or vibrate about a common axis 9009, and each rotating or vibrating optical element is used to continuously change the direction of propagation of the incident light beam.
  • the multiple optical elements of the scanning assembly 9002 can rotate at different rotation speeds, or vibrate at different speeds.
  • at least part of the optical elements of the scanning assembly 9002 can rotate at substantially the same rotational speed.
  • the multiple optical elements of the scanning assembly may also rotate around different axes.
  • the multiple optical elements of the scanning assembly may also rotate in the same direction, or rotate in different directions; or vibrate in the same direction, or vibrate in different directions, which is not limited herein.
  • the scanning assembly 9002 includes a first optical element 9014 and a driver 9016 connected to the first optical element 9014.
  • the driver 9016 is used to drive the first optical element 9014 to rotate about a rotation axis 9009 to change the first optical element 9014 Collimate the direction of the beam 9019.
  • the first optical element 9014 projects the collimated light beam 9019 in different directions.
  • the angle between the direction of the collimated light beam 9019 changed by the first optical element and the rotation axis 9009 changes as the first optical element 9014 rotates.
  • the first optical element 9014 includes a pair of opposing non-parallel surfaces through which the collimated light beam 9019 passes.
  • the first optical element 9014 includes a prism whose thickness varies along at least one radial direction.
  • the first optical element 9014 includes a wedge-angle prism, aligning the straight beam 9019 for refraction.
  • the scanning assembly 9002 further includes a second optical element 9015.
  • the second optical element 9015 rotates about a rotation axis 9009.
  • the rotation speed of the second optical element 9015 is different from the rotation speed of the first optical element 9014.
  • the second optical element 9015 is used to change the direction of the light beam projected by the first optical element 9014.
  • the second optical element 9015 is connected to another driver 9017, and the driver 9017 drives the second optical element 9015 to rotate.
  • the first optical element 9014 and the second optical element 9015 may be driven by the same or different drivers, so that the rotation speed and/or rotation of the first optical element 9014 and the second optical element 9015 are different, thereby projecting the collimated light beam 9019 to the outside space Different directions can scan a larger spatial range.
  • the controller 9018 controls the drivers 9016 and 9017 to drive the first optical element 9014 and the second optical element 9015, respectively.
  • the rotation speeds of the first optical element 9014 and the second optical element 9015 can be determined according to the area and pattern expected to be scanned in practical applications.
  • the drivers 9016 and 9017 may include driving motors, and of course other drivers.
  • the second optical element 9015 includes a pair of opposed non-parallel surfaces through which the light beam passes. In one embodiment, the second optical element 9015 includes a prism whose thickness varies along at least one radial direction. In one embodiment, the second optical element 9015 includes a wedge angle prism.
  • the scanning assembly 9002 further includes a third optical element (not shown) and a driver for driving the third optical element to move.
  • the third optical element includes a pair of opposed non-parallel surfaces through which the light beam passes.
  • the third optical element includes a prism whose thickness varies along at least one radial direction.
  • the third optical element includes a wedge angle prism. At least two of the first, second and third optical elements rotate at different rotational speeds and/or turns.
  • each optical element in the scanning assembly 9002 can project light into different directions, such as directions 9011 and 9013, so as to scan the space around the radar system 9000.
  • the detector 9005 and the transmitter 9003 are placed on the same side of the collimating element 9004.
  • the detector 9005 is used to convert at least part of the returned light passing through the collimating element 9004 into an electrical signal.
  • each optical element is coated with an antireflection coating.
  • the thickness of the AR coating is equal to or close to the wavelength of the beam emitted by the emitter 9003, which can increase the intensity of the transmitted beam.
  • a surface of an element on the beam propagation path of the radar system is coated with a filter layer, or a filter is provided on the beam propagation path for transmitting at least the wavelength band of the beam emitted by the transmitter and reflecting Other bands to reduce the noise caused by ambient light to the receiver.
  • the transmitter 9003 may include a laser diode through which laser pulses in the order of nanoseconds are emitted.
  • the laser pulse receiving time may be determined, for example, by detecting the rising edge time and/or the falling edge time of the electrical signal pulse. In this way, the radar system 9000 can use the pulse reception time information and the pulse emission time information to calculate the TOF, thereby determining the distance between the detection object 9010 and the radar system 9000.
  • the distance and orientation detected by the radar system 9000 can be used for remote sensing, obstacle avoidance, mapping, modeling, navigation, etc.
  • the radar system of the embodiment of the present invention can be applied to a movable platform, and the radar system can be installed on the platform body of the movable platform.
  • a mobile platform with a radar system can measure the external environment, for example, measuring the distance between the mobile platform and obstacles for obstacle avoidance and other purposes, and performing two-dimensional or three-dimensional mapping on the external environment.
  • the movable platform includes at least one of an unmanned aerial vehicle, a car, a remote control car, a robot, and a camera. When the radar system is applied to an unmanned aerial vehicle, the platform body is the fuselage of the unmanned aerial vehicle.
  • the platform body When the radar system is applied to a car, the platform body is the car body.
  • the car may be a self-driving car or a semi-automatic car, and no restriction is made here.
  • the platform body When the radar system is applied to a remote control car, the platform body is the body of the remote control car.
  • the platform body When the radar system is applied to a robot, the platform body is a robot.
  • the radar system is applied to a camera, the platform body is the camera itself.
  • the processor 93 is configured to perform the following operations: obtain a state parameter of the motor, the state parameter including a current parameter and/or a speed parameter; determine whether the state parameter exceeds a preset threshold; if If the state parameter exceeds the preset threshold, the motor is judged to be invalid.
  • the current parameter includes an average value of current and/or a stability parameter of current
  • the speed parameter includes an average speed value and/or a speed stability parameter.
  • the processor 93 when the processor 93 obtains the state parameter of the motor, the processor 93 is configured to:
  • the sampling value includes real-time current and/or real-time speed
  • the processor 93 when the processor 93 obtains the average value of the sampled values in the sampling period according to the sampled values, the processor 93 is configured to:
  • the collected sampling value is accumulated by the first accumulator
  • the average value of the sampling values in the sampling period is obtained according to the accumulation result of the first accumulator and the total number of sampling values in the sampling period.
  • the stability parameter of the sampled value includes the concentration of the sampled value
  • the processor 93 When the processor 93 obtains the stability parameter of the sampled value in the sampling period according to the sampled value, the processor 93 is configured to:
  • the predetermined sampling value fluctuation range is any one of the following:
  • Preset range sample value range obtained based on the average value of sample values in the first sampling period, sample value range obtained based on the average value of sample values in the previous sampling period, sample value range obtained based on the average value of sample values in the current sampling period .
  • the processor 93 acquires the ratio of the number of sampling values within a predetermined sampling value fluctuation range in the sampling period to the total number of sampling values in the sampling period, the processor 93 is configured to:
  • the number of sampling values within the fluctuation range of the predetermined sampling value is counted by a counter
  • the concentration of the sampling values in the sampling period is obtained.
  • the processor 93 is within the predetermined sampling value fluctuation within the sampling period
  • the processor 93 is configured to:
  • the concentration of the sampled value in the sampling period is obtained according to the stored sampled value and the predetermined sampled value fluctuation range.
  • the stability parameter of the sampled value includes the variance or standard deviation of the sampled value
  • the processor 93 When the processor 93 obtains the stability parameter of the sampled value in the sampling period according to the sampled value, the processor 93 is configured to:
  • the preset average value, the average value of the sampling values in the first sampling period, the average value of the sampling values in the previous sampling period, and the average value of the sampling values in the current sampling period are the preset average value, the average value of the sampling values in the first sampling period, the average value of the sampling values in the previous sampling period, and the average value of the sampling values in the current sampling period.
  • the processor 93 obtains the variance or standard deviation of the sampled values in the sampling period according to the sampled values and the average value of the sampled values, the processor 93 is configured to:
  • the square value of the difference between the sampling value and the average value of the sampling value is accumulated by the second accumulator;
  • the variance or standard deviation of the sampling values in the sampling period is obtained according to the accumulation result of the second accumulator and the total number of sampling values in the sampling period.
  • the processor 93 obtains the sample based on the sampled value and the average value of the sampled values
  • the processor 93 is configured to:
  • the processor 93 when the processor 93 acquires the sampling value of the motor at a predetermined frequency within the sampling period, the processor 93 is configured to:
  • the real-time rotational speed of the motor is collected from the code wheel at a predetermined frequency during the sampling period, wherein the motor is electrically connected to the code wheel.
  • the state parameters include a current parameter and/or a speed parameter, and determine whether the state parameter exceeds a preset threshold, and if the state parameter exceeds the preset threshold , It is judged that the motor is about to fail.
  • the radar system provided in this embodiment can accurately predict motor failure based on current parameters and/or speed parameters, can avoid the influence of environmental temperature, power supply stability and other factors on the prediction results, and has good robustness, which can be effectively avoided The adverse consequences of the sudden failure of the motor are easy to implement and highly automated.
  • FIG. 13 is a structural diagram of an unmanned aerial vehicle according to an embodiment of the present invention.
  • the movable platform 1000 includes: a fuselage 1010, a power system 1020, and a radar system 1030.
  • the movable platform 1000 includes, but is not limited to, unmanned aerial vehicles, remote control vehicles, and the like.
  • the power system 1020 is installed on the fuselage 1010 for providing power.
  • the power system 1020 includes a driving motor 1021; the radar system 1030 may be the radar system described in the foregoing embodiment.
  • the movable platform may further include one or more processors 1040, and the processor 1040 is used to perform the following operations on the driving motor 1010 in the power system 1020: acquiring the state parameters of the motor, the state parameters including Current parameter and/or speed parameter; determine whether the state parameter exceeds a preset threshold; if the state parameter exceeds the preset threshold, determine that the motor is invalid.
  • the processor 1040 may also perform the above operation on the driving motor in the scanning system of the radar system 1030.
  • the movable platform 1000 may further include: a controller, a sensing system, a communication system, a supporting device, a photographing device, etc. (not shown in the figure), where the controller includes an inertial measurement unit (Inertial Measurement Unit (IMU for short)
  • IMU Inertial Measurement Unit
  • the inertial measurement unit generally includes a gyroscope and an accelerometer.
  • the inertial measurement unit is used to detect the pitch angle, roll angle, yaw angle, and acceleration of the agricultural drone;
  • the supporting device may specifically be a gimbal; communication
  • the system may specifically include a receiver for receiving the wireless signal sent by the antenna of the ground station.
  • the movable platform provided in this embodiment may be used to implement the technical solutions of the foregoing method embodiments for the drive motor of the power system and/or the drive motor of the radar system.
  • the implementation principles and technical effects are similar, and are not described herein again.
  • the movable platform provided in this embodiment obtains the state parameters of the motor by the state parameters including current parameters and/or speed parameters, and determines whether the state parameters exceed a preset threshold, and if the state parameters exceed the preset Threshold, it is judged that the motor is about to fail.
  • the mobile platform provided in this embodiment can accurately predict motor failure based on current parameters and/or speed parameters, can avoid the influence of environmental temperature, power supply stability and other factors on the prediction results, and has good robustness, which can be effectively It avoids the bad consequences caused by the sudden failure of the motor, and is easy to implement and has a high degree of automation.
  • this embodiment also provides a computer-readable storage medium on which a computer program is stored, and the computer program is executed by a processor to implement the method described in the above embodiment.
  • the disclosed device and method may be implemented in other ways.
  • the device embodiments described above are only schematic.
  • the division of the unit is only a logical function division, and there may be other divisions in actual implementation, for example, multiple units or components may be combined or Can be integrated into another system, or some features can be ignored, or not implemented.
  • the displayed or discussed mutual coupling or direct coupling or communication connection may be indirect coupling or communication connection through some interfaces, devices or units, and may be in electrical, mechanical, or other forms.
  • the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place or may be distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
  • each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units may be integrated into one unit.
  • the above integrated unit can be implemented in the form of hardware, or in the form of hardware plus software functional units.
  • the above integrated unit implemented in the form of a software functional unit may be stored in a computer-readable storage medium.
  • the above software functional units are stored in a storage medium, and include several instructions to enable a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute the method described in each embodiment of the present invention Partial steps.
  • the foregoing storage media include: U disk, mobile hard disk, read-only memory (Read-Only Memory, ROM), random access memory (Random Access Memory, RAM), magnetic disk or optical disk and other media that can store program code .

Abstract

一种电机失效检测方法、设备及存储介质，通过获取电机的状态参数，所述状态参数包括电流参数和/或转速参数（S101），并判断所述状态参数是否超过预设阈值（S102），若所述状态参数超过所述预设阈值，则判断所述电机即将失效（S103）。上述方法基于电流参数和/或转速参数可以准确的预测电机失效，能够避免环境温度、电源稳定性等因素对预测结果的影响，具有良好的鲁棒性，从而可以有效的避免电机突然失效带来的不良后果，且易于实现、具有高度自动化的特点。

Description

电机失效检测方法、设备及存储介质 技术领域
本发明实施例涉及电机检测领域，尤其涉及一种电机失效检测方法、设备及存储介质。
背景技术
直流电机，或直流电动机，是将直流电能转换为机械能的电动机。直流电机因其良好的调速性能和较大的启动力矩，被广泛应用到各个领域中，例如机械式激光雷达中通过电机驱动光学部件旋转，产生扫描面，实现对物体的距离和轮廓测量功能；再如无人飞行器或遥控车等需要通过电机驱动以提供动力。由于电机的负载、长时间的工作状态以及一些极端的测量环境(高温高湿等)使得电机具有较高的失效风险，在自动驾驶、机器人等领域，若激光雷达驱动电机突然失效将会严重影响系统对外部环境的探测和感知，使得系统无法正常工作，甚至发生危险；而对于无人飞行器或遥控车等的动力系统，驱动电机突然失效将会发送安全事故。
电机的失效原因包括外部控制电路烧坏、电机绕组损坏、轴承损坏、电机轴变形、外部杂质进入等。其中，外部控制电路烧坏和电机绕组损坏现已非常罕见，因此需要重点关注轴承损坏、电机轴变形和外部杂质等因素造成的电机的失效。现有检测电机状态异常的方法，主要是监测电机表面温度，若电机发生故障，电机外壳温度会明显增加，因此可以通过监测电机外壳温度判断电机是否存在异常。或者也可监测电机的功耗对电机的运行状态作出判断。
由于电机的温度受到环境温度的影响，因此监测电机表面温度的方法对环境温度不具有鲁棒性，在高温和低温环境下不能作出正确的判断；此外，这种方法需要借助外部温度测量设备进行测量，例如利用非接触式红外测温仪测量电机表面温度，因此不够便捷，也不适用与车载、机器人等应用场合。而对于监测电机功耗的方法，电机的功耗不仅受电机组件损坏失效的影响，环境温度、电路系统、电源稳定性都会对电机的功耗产生影 响。
发明内容
本发明实施例提供一种电机失效检测方法、设备及存储介质，以准确的预测电机失效，避免电机突然失效带来的不良后果。
本发明实施例的第一方面是提供一种电机失效检测方法，包括：
获取电机的状态参数，所述状态参数包括电流参数和/或转速参数；
判断所述状态参数是否超过预设阈值；
若所述状态参数超过所述预设阈值，则判断所述电机即将失效。
本发明实施例的第二方面是提供一种电机失效检测装置，包括：处理器，所述处理器用于执行以下操作：
获取电机的状态参数，所述状态参数包括电流参数和/或转速参数；
判断所述状态参数是否超过预设阈值；
若所述状态参数超过所述预设阈值，则判断所述电机失效。
本发明实施例的第三方面是提供一种雷达系统，包括：
测距组件，用于发射光脉冲序列并接收经过被探测物反射的光脉冲序列；
扫描组件，所述扫描组件包括光学元件和驱动所述光学元件转动的驱动电机，所述光学元件设置于所述测距组件的光脉冲序列的光路上；以及
处理器，所述处理器用于执行以下操作：
获取电机的状态参数，所述状态参数包括电流参数和/或转速参数；
判断所述状态参数是否超过预设阈值；
若所述状态参数超过所述预设阈值，则判断所述电机失效。
本发明实施例的第四方面是提供一种可移动平台，包括：
机身；
动力系统，安装在所述机身，用于提供动力，所述动力系统包括驱动电机；以及
如第三方面所述的雷达系统。
本发明实施例的第五方面是提供一种计算机可读存储介质，其上存储有计算机程序，所述计算机程序被处理器执行以实现第一方面所述的方法。
本实施例提供的电机失效检测方法、设备及存储介质，通过获取电机的状态参数所述状态参数包括电流参数和/或转速参数，并判断所述状态参数是否超过预设阈值，若所述状态参数超过所述预设阈值，则判断所述电机即将失效。本实施例提供的方法基于电流参数和/或转速参数可以准确的预测电机失效，能够避免环境温度、电源稳定性等因素对预测结果的影响，具有良好的鲁棒性，从而可以有效的避免电机突然失效带来的不良后果，且易于实现、具有高度自动化的特点。
附图说明
为了更清楚地说明本发明实施例中的技术方案，下面将对实施例描述中所需要使用的附图作一简单地介绍，显而易见地，下面描述中的附图是本发明的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动性的前提下，还可以根据这些附图获得其他的附图。
图1为本发明实施例提供的电机失效检测方法的流程图；
图2a为本发明实施例提供的电机运行过程中的转速曲线图；
图2b为本发明实施例提供的电机运行过程中的电流曲线图；
图3为本发明另一实施例提供的电机失效检测方法的流程图；
图4为本发明另一实施例提供的电机失效检测方法的流程图；
图5为本发明另一实施例提供的电机失效检测方法的流程图；
图6为本发明另一实施例提供的电机失效检测方法的流程图；
图7为本发明另一实施例提供的电机失效检测方法的流程图；
图8为本发明另一实施例提供的电机失效检测方法的流程图；
图9为本发明实施例提供的电机失效检测装置的结构图；
图10为本发明实施例提供的雷达系统的结构图；
图11为本发明另一实施例提供的雷达系统的结构图；
图12为本发明另一实施例提供的雷达系统的结构图；
图13为本发明实施例提供的可移动平台的结构图。
具体实施方式
下面将结合本发明实施例中的附图，对本发明实施例中的技术方案进 行清楚地描述，显然，所描述的实施例仅仅是本发明一部分实施例，而不是全部的实施例。基于本发明中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都属于本发明保护的范围。
需要说明的是，当组件被称为“固定于”另一个组件，它可以直接在另一个组件上或者也可以存在居中的组件。当一个组件被认为是“连接”另一个组件，它可以是直接连接到另一个组件或者可能同时存在居中组件。
除非另有定义，本文所使用的所有的技术和科学术语与属于本发明的技术领域的技术人员通常理解的含义相同。本文中在本发明的说明书中所使用的术语只是为了描述具体的实施例的目的，不是旨在于限制本发明。本文所使用的术语“及/或”包括一个或多个相关的所列项目的任意的和所有的组合。
下面结合附图，对本发明的一些实施方式作详细说明。在不冲突的情况下，下述的实施例及实施例中的特征可以相互组合。
需要说明的是，本发明的电机可以为电机为雷达系统的驱动电机，所述驱动电机用于驱动所述雷达系统中的扫描组件转动。此外，本发明的电机也可以为可移动平台的动力系统的驱动电机，可移动平台可以为无人飞行器、遥控车。当然本发明的电机也可以为其他任一设备中的电机，均可采用本发明实施例提供的电机失效检测方法预测电机是否即将失效。
本发明实施例提供一种电机失效检测方法。图1为本发明实施例提供的电机失效检测方法的流程图。如图1所示，本实施例中的方法，可以包括：
步骤S101、获取电机的状态参数，所述状态参数包括电流参数和/或转速参数。
在本实施例中，通过获取电机的状态参数来作为电机是否即将失效的判断指标，其中电机的状态参数选择电流参数和/或转速参数。本实施例中选择电流参数和/或转速参数作为电机的状态参数，是由于当电机即将失效时电机的运行电流、转速都将出现波动，如图2a和图2b所示的电机在运行1600小时过程中的转速曲线和电流曲线，在约1600小时后，电机1失效停转。从图2中可以看到，电机1在失效前500小时内，运行电流 开始增大，同时出现了较大的波动，同时从转速曲线可以看出，电机的转速也开始出现一定程度的波动；而对于正常运转的电机2，运行电流和电机转速均表现比较平稳。
本实施例中，在所选择的状态参数中，电流参数具体可包括电流的平均值和/或电流的稳定性参数；转速参数具体可包括转速的平均值和/或转速的稳定性参数。更具体的，稳定性参数可以选择集中度、方差、标准差等。需要说明的是，本实施例中可以选择上述各种状态参数中的任意一种状态参数或几种状态参数组合作为所述电机的状态参数。
步骤S102、判断所述状态参数是否超过预设阈值。
在本实施例中，对于任一状态参数均对应有预设阈值，例如针对图2中的电机，对于电流的平均值I_mean，可以设定预设阈值为区间[I mean -,I mean +]＝[0,500mA]；再如对于电流的集中度I_central，可以设定预设阈值为区间[I central -,I central +]＝[0.9,1]；再如对于转速的方差S_std，可以设定预设阈值为区间[S std -,S std +]＝[0,10]。当然预设阈值可根据实际需要进行选取。
步骤S103、若所述状态参数超过所述预设阈值，则判断所述电机即将失效。
在本实施例中，通过将获取的状态参数与预设阈值进行比较，当状态参数超过所述预设阈值，则判断电机即将失效，从而实现对电机失效进行预测，避免电机突然失效带来的不良后果。
本实施例中可实时或以预设周期获取电机的状态参数，可对电机状态进行监控，从而可及时判断出电机即将失效。此外需要说明的是，从图2中可以看出，电机1在失效前500小时内电流和转速才开始发生较大波动，而在前1100小时未产生较大波动，因此本实施例中可从电机开始运行时即实时或以预设周期获取电机的状态参数，当然也可在电机运行一定时间后再开始实时或以预设周期获取电机的状态参数，对电机状态进行监控。
本实施例提供的电机失效检测方法，通过获取电机的状态参数所述状态参数包括电流参数和/或转速参数，并判断所述状态参数是否超过预设阈值，若所述状态参数超过所述预设阈值，则判断所述电机即将失效。本实施例提供的方法基于电流参数和/或转速参数可以准确的预测电机失效， 能够避免环境温度、电源稳定性等因素对预测结果的影响，具有良好的鲁棒性，从而可以有效的避免电机突然失效带来的不良后果，且易于实现、具有高度自动化的特点。
本发明实施例提供一种电机失效检测方法。图3为本发明另一实施例提供的电机失效检测方法的流程图。如图3所示，在图1所示实施例的基础上，步骤S101所述获取电机的状态参数，可以包括：
步骤S201、在采样周期内以预定频率获取所述电机的采样值，所述采样值包括实时电流和/或实时转速。
步骤S202、根据所述采样值获取所述采样周期内采样值的平均值；和/或根据所述采样值获取所述采样周期内采样值的稳定性参数。
在本实施例中，在一个采样周期内，以预定频率采集电机的实时电流和/或实时转速，作为电机的采样值，然后根据电机的采样值获取该周期内采样值的平均值/和或采样值的稳定性参数，以实时电流为例，可以设定采样周期为5min，以5Hz的频率采集电机的实时电流，从而在采样时间达到5min时，共对实时电流采集了1500个采样值，可获取本采样周期内这1500个采样值的平均值(如算术平均值)和/或稳定性参数(如集中度、方差、标准差)作为本采样周期电机的状态参数，进而与预设阈值进行比较判断电机是否即将失效；在下一个采样周期内重复上述过程，直至判断所述电机即将失效。
在上述任一实施例的基础上，步骤S201所述在采样周期内以预定频率获取所述电机的采样值，具体可包括：
在采样周期内以预定频率从电调板采集所述电机的实时电流，其中所述电机与所述电调板电连接；和/或
在采样周期内以预定频率从码盘采集所述电机的实时转速，其中所述电机与所述码盘电连接。
在本实施例中，电机与电调板电连接，通过电调板实现对电机的供电以及对电机的控制，本实施例中电机的实时电流可从电调板采集，更具体的，可通过采样电阻从电调板上采集电流；此外电机还与码盘电连接，码盘用于对电机转速进行实时监控，本实施例中电机的实时转速可从码盘采 集。本实施例中不需要如现有技术中的监测电机表面温度的方法借助温度测量设备等外部的测量设备，只需借助原有的电调板和/或码盘即可，较为便捷，适用与车载、机器人等应用场合。
在上述任一实施例的基础上，如图4所示，对于步骤S202所述根据所述采样值获取所述采样周期内采样值的平均值，具体可包括：
步骤S301、在采样周期内以预定频率获取所述电机的采样值时，通过第一累加器对采集的采样值进行累加；
步骤S302、在采样周期结束时，根据所述第一累加器的累加结果以及采样周期的总采样值数量，获取所述采样周期内采样值的平均值。
在本实施例中，在对电机的采样值进行采样时，通过第一累加器对所采集的采样值进行累加，每采集一个采样值进行一次累加，因此不需要对采样值进行存储；在采样周期结束时，可得到采样值的累加结果，例如对于实时电流，累加结果为I_sum，采样周期的总采样值数量n_sum，从而可以计算电流的平均值I_mean＝I_sum/n_sum。本实施例中在采样周期内只需要通过累加器对采样值进行累加，而不需要对采样值进行存储，极大的节约了存储资源，同时提高了采样值的平均值的获取效率。需要说明的是在下一采样周期开始前可对第一累加器进行清零。当然本实施例中也可采用对采样值进行存储后再计算平均值的方式。
在上述任一实施例的基础上，采样值的稳定性参数包括采样值的集中度，其中集中度为衡量采样值落入预定采样值波动范围内数量的参数。
针对采样值的集中度，步骤S202所述根据所述采样值获取所述采样周期内采样值的稳定性参数，具体可包括：
获取采样周期内处于预定采样值波动范围内的采样值数量占采样周期的总采样值数量的比例，作为所述采样值的集中度；其中所述预定采样值波动范围为如下任意一种：
预设范围、根据第一采样周期采样值的平均值获取的采样值范围、根据上一采样周期采样值的平均值获取的采样值范围、根据本采样周期采样值的平均值获取的采样值范围。
在本实施例中，通过统计采样周期内处于预定采样值波动范围内的采样值数量m，然后通过如下公式获取采样值的集中度I_central＝m/n_sum。
在获取采样值的集中度前，首先需要获取预定采样值波动范围，其中预定采样值波动范围可以为预设范围，也可根据采样值的平均值获取，例如对于实时电流而言，电流的平均值为I_mean，以I_mean为中心，±20mA为上下限，得到电流范围[I_min,Imax]＝[I_mean‐20mA,I_mean+20mA]，作为所述预定采样值波动范围，其中采样值的平均值可以采用第一采样周期采样值、或上一采样周期采样值的平均值、或本采样周期采样值的平均值。对于采用第一采样周期采样值、或上一采样周期采样值的平均值的情况，若采用上述的第一累加器获取采样值的平均值，则第一采样周期无法获取到采样值的集中度，从第二采样周期起才可获取采样值的集中度；当然若采用对采样值进行存储后再计算平均值的方式则第一采样周期也可获取到采样值的集中度；此外采用上一采样周期采样值的情况，是考虑到电机运行过程中实时电流或实时转速会存在缓慢的变化，但缓慢的变化过程中并未出现较大的波动，这种情况不视为电机即将失效；对于采用本采样周期采样值的平均值的情况，由于必须先获取到本采样周期采样值的平均值后才能判断采样周期内处于预定采样值波动范围内的采样值数量占采样周期的总采样值数量的比例，因此需要在获取电机的采样值时对本采样周期采样值进行存储。
可选的，如图5所示，若所述预定电流波动范围为预设范围、或根据第一采样周期采样值的平均值获取的采样值范围、或根据上一采样周期采样值的平均值获取的采样值范围，则所述获取采样周期内处于预定采样值波动范围内的采样值数量占采样周期的总采样值数量的比例，包括：
步骤S401、在采样周期内以预定频率获取所述电机的采样值时，通过计数器对处于所述预定采样值波动范围内的采样值数量进行计数；
步骤S402、在采样周期结束时，根据所述计数器的计数结果以及采样周期的总采样值数量，获取所述采样周期内采样值的集中度。
在本实施例中，对于预定电流波动范围为预设范围、或根据第一采样周期采样值的平均值获取的采样值范围、或根据上一采样周期采样值的平均值获取的采样值范围，也即不需要计算本采样周期采样值的平均值的情 况，可直接通过计数器对处于预定采样值波动范围内的采样值数量进行计数，具体的，可在采样时判断采样值是否处于预定采样值波动范围内，若处于预定采样值波动范围内，则计数器自增1(否则不自增)，在采样周期结束时，以计数器当前的计数结果作为本采样周期处于预定采样值波动范围内的采样值数量，进而根据计数器的计数结果以及采样周期的总采样值数量，获取采样周期内采样值的集中度。需要说明的是，在下一采样周期开始前可对计数器进行清零。本实施例中不需要对采样值进行存储，极大的节约了存储资源，同时提高了采样值的集中度的获取效率。
可选的，如图6所示，若所述预定采样值波动范围为根据本采样周期采样值的平均值获取的采样值范围，则所述获取采样周期内处于预定采样值波动范围内的采样值数量占采样周期的总采样值数量的比例，包括：
步骤S501、在采样周期内以预定频率获取所述电机的采样值时，对所述采样值进行存储；
步骤S502、在采样周期结束时，根据存储的所述采样值获取本采样周期采样值的平均值，并根据本采样周期采样值的平均值获取预定采样值波动范围；
步骤S503、根据存储的所述采样值及所述预定采样值波动范围获取所述采样周期内采样值的集中度。
在本实施例中，预定采样值波动范围为根据本采样周期采样值的平均值获取的采样值范围，由于先要获取本采样周期采样值的平均值，然后才能得到预定采样值波动范围，进而才能判断每一采样值是否处于预定采样值波动范围，因此需要在采样时对采样值进行存储。本实施例中在根据本采样周期采样值的平均值获取到预定采样值波动范围后，对存储的每一采样值与预定采样值波动范围进行比对，统计本采样周期处于预定采样值波动范围内的采样值数量，进而根据本采样周期处于预定采样值波动范围内的采样值数量以及本采样周期的总采样值数量获取采样周期内采样值的集中度。
在上述任一实施例的基础上，采样值的稳定性参数包括采样值的方差或标准差，通过方差或标准差度量采样值和期望值(采样值的平均值)之 间的偏离程度。
针对采样值的方差或标准差，步骤S202所述根据所述采样值获取所述采样周期内采样值的稳定性参数，包括：
根据所述采样值以及采样值的平均值获取所述采样周期内采样值的方差或标准差；其中所述采样值的平均值为如下任意一种：
预设平均值、第一采样周期采样值的平均值、上一采样周期采样值的平均值、本采样周期采样值的平均值。
在本实施例中，可通过采样值以及采样值的平均值获取采样周期内采样值的方差或标准差，例如对于转速的方差可采用如下公式进行计算：
Figure PCTCN2019071030-appb-000001
对于转速的标准差可采用如下公式进行计算：
Figure PCTCN2019071030-appb-000002
其中，S_i为本采样周期转速的采样值(实时转速)，S_0为转速的平均值，n_sum为采样周期的总采样值数量。
在本实施例中，获取采样值的方差或标准差前，需要获取采样值的平均值，其中采样值的平均值可以选择目标电流值、目标转速值等预设平均值；也可根据采样值计算平均值，可以采用第一采样周期采样值的平均值、或上一采样周期采样值的平均值、或本采样周期采样值的平均值。对于采用第一采样周期采样值的平均值、或上一采样周期采样值的平均值的情况，若采用上述的第一累加器获取采样值的平均值，则第一采样周期无法获取到采样值的方差或标准差；当然若采用对采样值进行存储后再计算平均值的方式则第一采样周期也可获取到采样值的方差或标准差；对于采用本采样周期采样值的平均值的情况，由于必须先获取到本采样周期采样值的平均值后才能计算本采样周期内采样值的方差或标准差，因此需要在获取电机的采样值时对本采样周期采样值进行存储。
可选的，如图7所示，若所述采样值的平均值为预设平均值、或第一采样周期采样值的平均值、或上一采样周期采样值的平均值，则所述根据所述采样值以及采样值的平均值获取所述采样周期内采样值的方差或标 准差，包括：
步骤S601、在采样周期内以预定频率获取所述电机的采样值时，通过第二累加器对所述采样值与所述采样值的平均值之差的平方值进行累加；
步骤S602、在采样周期结束时，根据所述第二累加器的累加结果以及采样周期的总采样值数量，获取所述采样周期内采样值的方差或标准差。
在本实施例中，对于采样值的平均值为预设平均值、或第一采样周期采样值的平均值、或上一采样周期采样值的平均值，也即不需要计算本采样周期采样值的平均值的情况，可直接通过第二累加器对采样值与采样值的平均值之差的平方值进行累加，也即(S_i-S_0) 2，在采样周期内每采集一个采样值S_i，则进行一次(S_i-S_0) 2的累加，在采样周期结束时，第二累加器的累加结果即为
Figure PCTCN2019071030-appb-000003
进而根据第二累加器的累加结果以及采样周期的总采样值数量计算本采样周期内采样值的方差或标准差。
可选的，如图8所示，若所述采样值的平均值为本采样周期采样值的平均值，则所述根据所述采样值以及采样值的平均值获取所述采样周期内采样值的方差或标准差，包括：
步骤S701、在采样周期内以预定频率获取所述电机的采样值时，对所述采样值进行存储；
步骤S702、在采样周期结束时，根据存储的所述采样值获取本采样周期采样值的平均值，并根据存储的所述采样值及所述本采样周期采样值的平均值获取所述采样周期内采样值的方差或标准差。
在本实施例中，采样值的平均值为本采样周期采样值的平均值，则首先要获取本采样周期采样值的平均值，因此需要在采样时对采样值进行存储。本实施例中根据本采样周期存储的采样值获取到本采样周期采样值的平均值后，再根据存储的采样值及本采样周期采样值的平均值获取采样值与所述采样值的平均值之差的平方值的累加结果，进而根据累加结果以及采样周期的总采样值数量，获取采样周期内采样值的方差或标准差。
上述实施例提供的电机失效检测方法，通过获取电机的状态参数所述状态参数包括电流参数和/或转速参数(具体可以为平均值和/或稳定性参数)，并判断所述状态参数是否超过预设阈值，若所述状态参数超过所述 预设阈值，则判断所述电机即将失效。本实施例提供的方法基于电流参数和/或转速参数可以准确的预测电机失效，能够避免环境温度、电源稳定性等因素对预测结果的影响，具有良好的鲁棒性，从而可以有效的避免电机突然失效带来的不良后果，且易于实现、具有高度自动化的特点。
本发明实施例提供一种电机失效检测装置。图9为本发明实施例提供的电机失效检测装置的结构图，如图9所示，电机失效检测装置80包括处理器81。此外，本实施例的电机失效检测装置80还可包括：存储器82、通讯接口83等。
其中，所述处理器81用于执行以下操作：
获取电机的状态参数，所述状态参数包括电流参数和/或转速参数；
判断所述状态参数是否超过预设阈值；
若所述状态参数超过所述预设阈值，则判断所述电机失效。
在上述实施例的基础上，所述电流参数包括电流的平均值和/或电流的稳定性参数；
所述转速参数包括转速的平均值和/或转速的稳定性参数。
在上述任一实施例的基础上，在所述处理器81获取电机的状态参数时，所述处理器81被配置为：
在采样周期内以预定频率获取所述电机的采样值，所述采样值包括实时电流和/或实时转速；
根据所述采样值获取所述采样周期内采样值的平均值；和/或
根据所述采样值获取所述采样周期内采样值的稳定性参数。
在上述任一实施例的基础上，在所述处理器81根据所述采样值获取所述采样周期内采样值的平均值时，所述处理器81被配置为：
在采样周期内以预定频率获取所述电机的采样值时，通过第一累加器对采集的采样值进行累加；
在采样周期结束时，根据所述第一累加器的累加结果以及采样周期的总采样值数量，获取所述采样周期内采样值的平均值。
在上述任一实施例的基础上，所述采样值的稳定性参数包括采样值的集中度；
在所述处理器81根据所述采样值获取所述采样周期内采样值的稳定性参数时，所述处理器81被配置为：
获取采样周期内处于预定采样值波动范围内的采样值数量占采样周期的总采样值数量的比例，作为所述采样值的集中度；其中所述预定采样值波动范围为如下任意一种：
预设范围、根据第一采样周期采样值的平均值获取的采样值范围、根据上一采样周期采样值的平均值获取的采样值范围、根据本采样周期采样值的平均值获取的采样值范围。
在上述任一实施例的基础上，若所述预定电流波动范围为预设范围、或根据第一采样周期采样值的平均值获取的采样值范围、或根据上一采样周期采样值的平均值获取的采样值范围，则在所述处理器81获取采样周期内处于预定采样值波动范围内的采样值数量占采样周期的总采样值数量的比例时，所述处理器81被配置为：
在采样周期内以预定频率获取所述电机的采样值时，通过计数器对处于所述预定采样值波动范围内的采样值数量进行计数；
在采样周期结束时，根据所述计数器的计数结果以及采样周期的总采样值数量，获取所述采样周期内采样值的集中度。
在上述任一实施例的基础上，若所述预定采样值波动范围为根据本采样周期采样值的平均值获取的采样值范围，则在所述处理器81获取采样周期内处于预定采样值波动范围内的采样值数量占采样周期的总采样值数量的比例时，所述处理器81被配置为：
在采样周期内以预定频率获取所述电机的采样值时，对所述采样值进行存储；
在采样周期结束时，根据存储的所述采样值获取本采样周期采样值的平均值，并根据本采样周期采样值的平均值获取预定采样值波动范围；
根据存储的所述采样值及所述预定采样值波动范围获取所述采样周期内采样值的集中度。
在上述任一实施例的基础上，所述采样值的稳定性参数包括采样值的方差或标准差；
在所述处理器81根据所述采样值获取所述采样周期内采样值的稳定 性参数时，所述处理器81被配置为：
根据所述采样值以及采样值的平均值获取所述采样周期内采样值的方差或标准差；其中所述采样值的平均值为如下任意一种：
预设平均值、第一采样周期采样值的平均值、上一采样周期采样值的平均值、本采样周期采样值的平均值。
在上述任一实施例的基础上，若所述采样值的平均值为预设平均值、或第一采样周期采样值的平均值、或上一采样周期采样值的平均值，则在所述处理器81根据所述采样值以及采样值的平均值获取所述采样周期内采样值的方差或标准差时，所述处理器81被配置为：
在采样周期内以预定频率获取所述电机的采样值时，通过第二累加器对所述采样值与所述采样值的平均值之差的平方值进行累加；
在采样周期结束时，根据所述第二累加器的累加结果以及采样周期的总采样值数量，获取所述采样周期内采样值的方差或标准差。
在上述任一实施例的基础上，若所述采样值的平均值为本采样周期采样值的平均值，则在所述处理器81根据所述采样值以及采样值的平均值获取所述采样周期内采样值的方差或标准差时，所述处理器81被配置为：
在采样周期内以预定频率获取所述电机的采样值时，对所述采样值进行存储；
在采样周期结束时，根据存储的所述采样值获取本采样周期采样值的平均值，并根据存储的所述采样值及所述本采样周期采样值的平均值获取所述采样周期内采样值的方差或标准差。
在上述任一实施例的基础上，在所述处理器81在采样周期内以预定频率获取所述电机的采样值时，所述处理器81被配置为：
在采样周期内以预定频率从电调板采集所述电机的实时电流，其中所述电机与所述电调板电连接；和/或
在采样周期内以预定频率从码盘采集所述电机的实时转速，其中所述电机与所述码盘电连接。
在上述任一实施例的基础上，所述电机为雷达系统的驱动电机，所述驱动电机用于驱动所述雷达系统中的扫描组件转动。
在上述任一实施例的基础上，所述电机为可移动平台的动力系统的驱 动电机。
在上述任一实施例的基础上，所述可移动平台包括如下至少一种：无人飞行器、遥控车。
本实施例的电机失效检测装置的实现原理和技术效果与上述实施例类似，此处不再赘述。
本实施例提供的电机失效检测装置，通过获取电机的状态参数所述状态参数包括电流参数和/或转速参数，并判断所述状态参数是否超过预设阈值，若所述状态参数超过所述预设阈值，则判断所述电机即将失效。本实施例提供的装置基于电流参数和/或转速参数可以准确的预测电机失效，能够避免环境温度、电源稳定性等因素对预测结果的影响，具有良好的鲁棒性，从而可以有效的避免电机突然失效带来的不良后果，且易于实现、具有高度自动化的特点。
本发明实施例提供一种雷达系统。图10为本发明实施例提供的雷达系统的结构图，如图10所示，雷达系统90包括测距组件91、扫描组件92以及处理器93。
其中，测距组件91用于发射光脉冲序列并接收经过被探测物反射的光脉冲序列；扫描组件92所述扫描组件92包括光学元件和驱动所述光学元件转动的驱动电机，所述光学元件设置于所述测距组件91的光脉冲序列的光路上；处理器93用于执行以下操作：获取电机的状态参数，所述状态参数包括电流参数和/或转速参数；判断所述状态参数是否超过预设阈值；若所述状态参数超过所述预设阈值，则判断所述电机失效。
本实施例中，如图11所示，测距组件91可包括发射电路911、接收电路912、采样电路913和运算电路914。发射电路911可以发射光脉冲序列(例如激光脉冲序列)。接收电路912可以接收经过被探测物反射的光脉冲序列，并对该光脉冲序列进行光电转换，以得到电信号，再对电信号进行处理之后可以输出给采样电路913。采样电路913可以对电信号进行采样，以获取采样结果。运算电路914可以基于采样电路913的采样结果，以确定雷达系统100与被探测物之间的距离。
应理解，虽然图11示出的雷达系统中包括一个发射电路、一个接收 电路、一个采样电路和一个运算电路，用于出射一路光束进行探测，但是本申请实施例并不限于此，发射电路、接收电路、采样电路、运算电路中的任一种电路的数量也可以是至少两个，用于沿相同方向或分别沿不同方向出射至少两路光束；其中，该至少两束光路可以是同时出射，也可以是分别在不同时刻出射。一个示例中，该至少两个发射电路中的发光芯片封装在同一个模块中。例如，每个发射电路包括一个激光发射芯片，该至少两个发射电路中的激光发射芯片中的die(裸片)封装到一起，容置在同一个封装空间中。
可选的，所述测距组件还可以包括控制电路915，该控制电路915可以实现对其他电路的控制，例如，可以控制各个电路的工作时间和/或对各个电路进行参数设置等。
本实施例中扫描组件用于将发射电路出射的至少一路激光脉冲序列改变传播方向出射。本实施例中的雷达系统中可以采用同轴光路，也即雷达系统出射的光束和经反射回来的光束在雷达系统内共用至少部分光路。例如，发射电路出射的至少一路激光脉冲序列经扫描模块改变传播方向出射后，经探测物反射回来的激光脉冲序列经过扫描模块后入射至接收电路。或者，雷达系统也可以采用异轴光路，也即雷达系统出射的光束和经反射回来的光束在雷达系统内分别沿不同的光路传输。图12示出了本发明的雷达系统采用同轴光路的一种实施例的示意图。
如图12所示，雷达系统9000包括测距组件9001，测距组件9001包括发射器9003(可以包括上述的发射电路)、准直元件9004、探测器9005(可以包括上述的接收电路、采样电路和运算电路)和光路改变元件9006。测距组件9001用于发射光束，且接收回光，将回光转换为电信号。其中，发射器9003可以用于发射光脉冲序列。在一个实施例中，发射器9003可以发射激光脉冲序列。可选的，发射器9003发射出的激光束为波长在可见光范围之外的窄带宽光束。准直元件9004设置于发射器的出射光路上，用于准直从发射器9003发出的光束，将发射器9003发出的光束准直为平行光出射至扫描组件。准直元件还用于会聚经探测物反射的回光的至少一部分。该准直元件9004可以是准直透镜或者是其他能够准直光束的元件。
在图12所示实施例中，通过光路改变元件9006来将雷达系统内的发 射光路和接收光路在准直元件9004之前合并，使得发射光路和接收光路可以共用同一个准直元件，使得光路更加紧凑。在其他的一些实现方式中，也可以是发射器9003和探测器9005分别使用各自的准直元件，将光路改变元件9006设置在准直元件之后的光路上。
在图12所示实施例中，由于发射器9003出射的光束的光束孔径较小，雷达系统所接收到的回光的光束孔径较大，所以光路改变元件可以采用小面积的反射镜来将发射光路和接收光路合并。在其他的一些实现方式中，光路改变元件也可以采用带通孔的反射镜，其中该通孔用于透射发射器9003的出射光，反射镜用于将回光反射至探测器9005。这样可以减小采用小反射镜的情况中小反射镜的支架会对回光的遮挡。
在图12所示实施例中，光路改变元件偏离了准直元件9004的光轴。在其他的一些实现方式中，光路改变元件也可以位于准直元件9004的光轴上。
雷达系统9000还包括扫描组件9002。扫描组件9002放置于测距组件9001的出射光路上，扫描组件9002用于改变经准直元件9004出射的准直光束9019的传输方向并投射至外界环境，并将回光投射至准直元件9004。回光经准直元件9004汇聚到探测器9005上。
在一个实施例中，扫描组件9002可以包括至少一个光学元件，用于改变光束的传播路径，其中，该光学元件可以通过对光束进行反射、折射、衍射等等方式来改变光束传播路径。例如，扫描组件9002包括透镜、反射镜、棱镜、振镜、光栅、液晶、光学相控阵(Optical Phased Array)或上述光学元件的任意组合。一个示例中，至少部分光学元件是运动的，例如通过驱动模块来驱动该至少部分光学元件进行运动，该运动的光学元件可以在不同时刻将光束反射、折射或衍射至不同的方向。在一些实施例中，扫描组件9002的多个光学元件可以绕共同的轴9009旋转或振动，每个旋转或振动的光学元件用于不断改变入射光束的传播方向。在一个实施例中，扫描组件9002的多个光学元件可以以不同的转速旋转，或以不同的速度振动。在另一个实施例中，扫描组件9002的至少部分光学元件可以以基本相同的转速旋转。在一些实施例中，扫描组件的多个光学元件也可以是绕不同的轴旋转。在一些实施例中，扫描组件的多个光学元件也可 以是以相同的方向旋转，或以不同的方向旋转；或者沿相同的方向振动，或者沿不同的方向振动，在此不作限制。
在一个实施例中，扫描组件9002包括第一光学元件9014和与第一光学元件9014连接的驱动器9016，驱动器9016用于驱动第一光学元件9014绕转动轴9009转动，使第一光学元件9014改变准直光束9019的方向。第一光学元件9014将准直光束9019投射至不同的方向。在一个实施例中，准直光束9019经第一光学元件改变后的方向与转动轴9009的夹角随着第一光学元件9014的转动而变化。在一个实施例中，第一光学元件9014包括相对的非平行的一对表面，准直光束9019穿过该对表面。在一个实施例中，第一光学元件9014包括厚度沿至少一个径向变化的棱镜。在一个实施例中，第一光学元件9014包括楔角棱镜，对准直光束9019进行折射。
在一个实施例中，扫描组件9002还包括第二光学元件9015，第二光学元件9015绕转动轴9009转动，第二光学元件9015的转动速度与第一光学元件9014的转动速度不同。第二光学元件9015用于改变第一光学元件9014投射的光束的方向。在一个实施例中，第二光学元件9015与另一驱动器9017连接，驱动器9017驱动第二光学元件9015转动。第一光学元件9014和第二光学元件9015可以由相同或不同的驱动器驱动，使第一光学元件9014和第二光学元件9015的转速和/或转向不同，从而将准直光束9019投射至外界空间不同的方向，可以扫描较大的空间范围。在一个实施例中，控制器9018控制驱动器9016和9017，分别驱动第一光学元件9014和第二光学元件9015。第一光学元件9014和第二光学元件9015的转速可以根据实际应用中预期扫描的区域和样式确定。驱动器9016和9017可以包括驱动电机，当然也可为其他驱动器。
在一个实施例中，第二光学元件9015包括相对的非平行的一对表面，光束穿过该对表面。在一个实施例中，第二光学元件9015包括厚度沿至少一个径向变化的棱镜。在一个实施例中，第二光学元件9015包括楔角棱镜。
一个实施例中，扫描组件9002还包括第三光学元件(图未示)和用于驱动第三光学元件运动的驱动器。可选地，该第三光学元件包括相对的非平行的一对表面，光束穿过该对表面。在一个实施例中，第三光学元件 包括厚度沿至少一个径向变化的棱镜。在一个实施例中，第三光学元件包括楔角棱镜。第一、第二和第三光学元件中的至少两个光学元件以不同的转速和/或转向转动。
扫描组件9002中的各光学元件旋转可以将光投射至不同的方向，例如方向9011和9013，如此对雷达系统9000周围的空间进行扫描。当扫描组件9002投射出的光9011打到探测物9010时，一部分光被探测物9010沿与投射的光9011相反的方向反射至雷达系统9000。探测物9010反射的回光9012经过扫描组件9002后入射至准直元件9004。
探测器9005与发射器9003放置于准直元件9004的同一侧，探测器9005用于将穿过准直元件9004的至少部分回光转换为电信号。
一个实施例中，各光学元件上镀有增透膜。可选的，增透膜的厚度与发射器9003发射出的光束的波长相等或接近，能够增加透射光束的强度。
一个实施例中，雷达系统中位于光束传播路径上的一个元件表面上镀有滤光层，或者在光束传播路径上设置有滤光器，用于至少透射发射器所出射的光束所在波段，反射其他波段，以减少环境光给接收器带来的噪音。
在一些实施例中，发射器9003可以包括激光二极管，通过激光二极管发射纳秒级别的激光脉冲。进一步地，可以确定激光脉冲接收时间，例如，通过探测电信号脉冲的上升沿时间和/或下降沿时间确定激光脉冲接收时间。如此，雷达系统9000可以利用脉冲接收时间信息和脉冲发出时间信息计算TOF，从而确定探测物9010到雷达系统9000的距离。
雷达系统9000探测到的距离和方位可以用于遥感、避障、测绘、建模、导航等。在一种实施方式中，本发明实施方式的雷达系统可应用于可移动平台，雷达系统可安装在可移动平台的平台本体。具有雷达系统的可移动平台可对外部环境进行测量，例如，测量可移动平台与障碍物的距离用于避障等用途，和对外部环境进行二维或三维的测绘。在某些实施方式中，可移动平台包括无人飞行器、汽车、遥控车、机器人、相机中的至少一种。当雷达系统应用于无人飞行器时，平台本体为无人飞行器的机身。当雷达系统应用于汽车时，平台本体为汽车的车身。该汽车可以是自动驾驶汽车或者半自动驾驶汽车，在此不做限制。当雷达系统应用于遥控车时，平台本体为遥控车的车身。当雷达系统应用于机器人时，平台本体为机器 人。当雷达系统应用于相机时，平台本体为相机本身。
在上述任一实施例的基础上，处理器93用于执行以下操作：获取电机的状态参数，所述状态参数包括电流参数和/或转速参数；判断所述状态参数是否超过预设阈值；若所述状态参数超过所述预设阈值，则判断所述电机失效。
在上述任一实施例的基础上，所述电流参数包括电流的平均值和/或电流的稳定性参数；
所述转速参数包括转速的平均值和/或转速的稳定性参数。
在上述任一实施例的基础上，在所述处理器93获取电机的状态参数时，所述处理器93被配置为：
在采样周期内以预定频率获取所述电机的采样值，所述采样值包括实时电流和/或实时转速；
根据所述采样值获取所述采样周期内采样值的平均值；和/或
根据所述采样值获取所述采样周期内采样值的稳定性参数。
在上述任一实施例的基础上，在所述处理器93根据所述采样值获取所述采样周期内采样值的平均值时，所述处理器93被配置为：
在采样周期内以预定频率获取所述电机的采样值时，通过第一累加器对采集的采样值进行累加；
在采样周期结束时，根据所述第一累加器的累加结果以及采样周期的总采样值数量，获取所述采样周期内采样值的平均值。
在上述任一实施例的基础上，所述采样值的稳定性参数包括采样值的集中度；
在所述处理器93根据所述采样值获取所述采样周期内采样值的稳定性参数时，所述处理器93被配置为：
获取采样周期内处于预定采样值波动范围内的采样值数量占采样周期的总采样值数量的比例，作为所述采样值的集中度；其中所述预定采样值波动范围为如下任意一种：
预设范围、根据第一采样周期采样值的平均值获取的采样值范围、根据上一采样周期采样值的平均值获取的采样值范围、根据本采样周期采样值的平均值获取的采样值范围。
在上述任一实施例的基础上，若所述预定电流波动范围为预设范围、或根据第一采样周期采样值的平均值获取的采样值范围、或根据上一采样周期采样值的平均值获取的采样值范围，则在所述处理器93获取采样周期内处于预定采样值波动范围内的采样值数量占采样周期的总采样值数量的比例时，所述处理器93被配置为：
在采样周期内以预定频率获取所述电机的采样值时，通过计数器对处于所述预定采样值波动范围内的采样值数量进行计数；
在采样周期结束时，根据所述计数器的计数结果以及采样周期的总采样值数量，获取所述采样周期内采样值的集中度。
在上述任一实施例的基础上，若所述预定采样值波动范围为根据本采样周期采样值的平均值获取的采样值范围，则在所述处理器93获取采样周期内处于预定采样值波动范围内的采样值数量占采样周期的总采样值数量的比例时，所述处理器93被配置为：
在采样周期内以预定频率获取所述电机的采样值时，对所述采样值进行存储；
在采样周期结束时，根据存储的所述采样值获取本采样周期采样值的平均值，并根据本采样周期采样值的平均值获取预定采样值波动范围；
根据存储的所述采样值及所述预定采样值波动范围获取所述采样周期内采样值的集中度。
在上述任一实施例的基础上，所述采样值的稳定性参数包括采样值的方差或标准差；
在所述处理器93根据所述采样值获取所述采样周期内采样值的稳定性参数时，所述处理器93被配置为：
根据所述采样值以及采样值的平均值获取所述采样周期内采样值的方差或标准差；其中所述采样值的平均值为如下任意一种：
预设平均值、第一采样周期采样值的平均值、上一采样周期采样值的平均值、本采样周期采样值的平均值。
在上述任一实施例的基础上，若所述采样值的平均值为预设平均值、或第一采样周期采样值的平均值、或上一采样周期采样值的平均值，则在所述处理器93根据所述采样值以及采样值的平均值获取所述采样周期内 采样值的方差或标准差时，所述处理器93被配置为：
在采样周期内以预定频率获取所述电机的采样值时，通过第二累加器对所述采样值与所述采样值的平均值之差的平方值进行累加；
在采样周期结束时，根据所述第二累加器的累加结果以及采样周期的总采样值数量，获取所述采样周期内采样值的方差或标准差。
在上述任一实施例的基础上，若所述采样值的平均值为本采样周期采样值的平均值，则在所述处理器93根据所述采样值以及采样值的平均值获取所述采样周期内采样值的方差或标准差时，所述处理器93被配置为：
在采样周期内以预定频率获取所述电机的采样值时，对所述采样值进行存储；
在采样周期结束时，根据存储的所述采样值获取本采样周期采样值的平均值，并根据存储的所述采样值及所述本采样周期采样值的平均值获取所述采样周期内采样值的方差或标准差。
在上述任一实施例的基础上，在所述处理器93在采样周期内以预定频率获取所述电机的采样值时，所述处理器93被配置为：
在采样周期内以预定频率从电调板采集所述电机的实时电流，其中所述电机与所述电调板电连接；和/或
在采样周期内以预定频率从码盘采集所述电机的实时转速，其中所述电机与所述码盘电连接。
本实施例的雷达系统的实现原理和技术效果与上述实施例类似，此处不再赘述。
本实施例提供的雷达系统，通过获取电机的状态参数所述状态参数包括电流参数和/或转速参数，并判断所述状态参数是否超过预设阈值，若所述状态参数超过所述预设阈值，则判断所述电机即将失效。本实施例提供的雷达系统基于电流参数和/或转速参数可以准确的预测电机失效，能够避免环境温度、电源稳定性等因素对预测结果的影响，具有良好的鲁棒性，从而可以有效的避免电机突然失效带来的不良后果，且易于实现、具有高度自动化的特点。
本发明实施例提供一种可移动平台。图13为本发明实施例提供的无 人机的结构图，如图13所示，可移动平台1000包括：机身1010、动力系统1020和雷达系统1030。可移动平台1000包括但不限于无人飞行器、遥控车等。
其中，动力系统1020安装在所述机身1010，用于提供动力，所述动力系统1020包括驱动电机1021；雷达系统1030可以为上述实施例所述的雷达系统。
进一步的，所述可移动平台还可包括一个或多个处理器1040，所述处理器1040用于对动力系统1020中的驱动电机1010执行以下操作：获取电机的状态参数，所述状态参数包括电流参数和/或转速参数；判断所述状态参数是否超过预设阈值；若所述状态参数超过所述预设阈值，则判断所述电机失效。可选的，所述处理器1040也可对雷达系统1030扫描组件中的驱动电机执行上述操作。
另外，可移动平台1000还可包括：控制器、传感系统、通信系统、支撑设备、拍摄装置等(图中未示出)，其中，控制器包括惯性测量单元(Inertial Measurement Unit，简称IMU)，惯性测量单元一般包括陀螺仪和加速度计，所述惯性测量单元用于检测所述农业无人机的俯仰角、横滚角、偏航角和加速度等；支撑设备具体可以是云台；通信系统具体可以包括接收机，接收机用于接收地面站的天线发送的无线信号。
本实施例提供的可移动平台可用于对其动力系统的驱动电机和/或雷达系统的驱动电机执行上述方法实施例的技术方案，其实现原理和技术效果类似，此处不再赘述。
本实施例提供的可移动平台，通过获取电机的状态参数所述状态参数包括电流参数和/或转速参数，并判断所述状态参数是否超过预设阈值，若所述状态参数超过所述预设阈值，则判断所述电机即将失效。本实施例提供的可移动平台基于电流参数和/或转速参数可以准确的预测电机失效，能够避免环境温度、电源稳定性等因素对预测结果的影响，具有良好的鲁棒性，从而可以有效的避免电机突然失效带来的不良后果，且易于实现、具有高度自动化的特点。
另外，本实施例还提供一种计算机可读存储介质，其上存储有计算机 程序，所述计算机程序被处理器执行以实现上述实施例所述的…方法。
在本发明所提供的几个实施例中，应该理解到，所揭露的装置和方法，可以通过其它的方式实现。例如，以上所描述的装置实施例仅仅是示意性的，例如，所述单元的划分，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式，例如多个单元或组件可以结合或者可以集成到另一个系统，或一些特征可以忽略，或不执行。另一点，所显示或讨论的相互之间的耦合或直接耦合或通信连接可以是通过一些接口，装置或单元的间接耦合或通信连接，可以是电性，机械或其它的形式。
所述作为分离部件说明的单元可以是或者也可以不是物理上分开的，作为单元显示的部件可以是或者也可以不是物理单元，即可以位于一个地方，或者也可以分布到多个网络单元上。可以根据实际的需要选择其中的部分或者全部单元来实现本实施例方案的目的。
另外，在本发明各个实施例中的各功能单元可以集成在一个处理单元中，也可以是各个单元单独物理存在，也可以两个或两个以上单元集成在一个单元中。上述集成的单元既可以采用硬件的形式实现，也可以采用硬件加软件功能单元的形式实现。
上述以软件功能单元的形式实现的集成的单元，可以存储在一个计算机可读取存储介质中。上述软件功能单元存储在一个存储介质中，包括若干指令用以使得一台计算机设备(可以是个人计算机，服务器，或者网络设备等)或处理器(processor)执行本发明各个实施例所述方法的部分步骤。而前述的存储介质包括：U盘、移动硬盘、只读存储器(Read-Only Memory，ROM)、随机存取存储器(Random Access Memory，RAM)、磁碟或者光盘等各种可以存储程序代码的介质。
本领域技术人员可以清楚地了解到，为描述的方便和简洁，仅以上述各功能模块的划分进行举例说明，实际应用中，可以根据需要而将上述功能分配由不同的功能模块完成，即将装置的内部结构划分成不同的功能模块，以完成以上描述的全部或者部分功能。上述描述的装置的具体工作过程，可以参考前述方法实施例中的对应过程，在此不再赘述。
最后应说明的是：以上各实施例仅用以说明本发明的技术方案，而非对其限制；尽管参照前述各实施例对本发明进行了详细的说明，本领域的 普通技术人员应当理解：其依然可以对前述各实施例所记载的技术方案进行修改，或者对其中部分或者全部技术特征进行等同替换；而这些修改或者替换，并不使相应技术方案的本质脱离本发明各实施例技术方案的范围。

Claims (44)

  1. 一种电机失效检测方法，其特征在于，包括：
    获取电机的状态参数，所述状态参数包括电流参数和/或转速参数；
    判断所述状态参数是否超过预设阈值；
    若所述状态参数超过所述预设阈值，则判断所述电机即将失效。
  2. 根据权利要求1所述的方法，其特征在于，
    所述电流参数包括电流的平均值和/或电流的稳定性参数；
    所述转速参数包括转速的平均值和/或转速的稳定性参数。
  3. 根据权利要求2所述的方法，其特征在于，所述获取电机的状态参数，包括：
    在采样周期内以预定频率获取所述电机的采样值，所述采样值包括实时电流和/或实时转速；
    根据所述采样值获取所述采样周期内采样值的平均值；和/或
    根据所述采样值获取所述采样周期内采样值的稳定性参数。
  4. 根据权利要求3所述的方法，其特征在于，所述根据所述采样值获取所述采样周期内采样值的平均值，包括：
    在采样周期内以预定频率获取所述电机的采样值时，通过第一累加器对采集的采样值进行累加；
    在采样周期结束时，根据所述第一累加器的累加结果以及采样周期的总采样值数量，获取所述采样周期内采样值的平均值。
  5. 根据权利要求3所述的方法，其特征在于，所述采样值的稳定性参数包括采样值的集中度；
    所述根据所述采样值获取所述采样周期内采样值的稳定性参数，包括：
    获取采样周期内处于预定采样值波动范围内的采样值数量占采样周期的总采样值数量的比例，作为所述采样值的集中度；其中所述预定采样值波动范围为如下任意一种：
    预设范围、根据第一采样周期采样值的平均值获取的采样值范围、根据上一采样周期采样值的平均值获取的采样值范围、根据本采样周期采样值的平均值获取的采样值范围。
  6. 根据权利要求5所述的方法，其特征在于，若所述预定电流波动 范围为预设范围、或根据第一采样周期采样值的平均值获取的采样值范围、或根据上一采样周期采样值的平均值获取的采样值范围，则所述获取采样周期内处于预定采样值波动范围内的采样值数量占采样周期的总采样值数量的比例，包括：
    在采样周期内以预定频率获取所述电机的采样值时，通过计数器对处于所述预定采样值波动范围内的采样值数量进行计数；
    在采样周期结束时，根据所述计数器的计数结果以及采样周期的总采样值数量，获取所述采样周期内采样值的集中度。
  7. 根据权利要求5所述的方法，其特征在于，若所述预定采样值波动范围为根据本采样周期采样值的平均值获取的采样值范围，则所述获取采样周期内处于预定采样值波动范围内的采样值数量占采样周期的总采样值数量的比例，包括：
    在采样周期内以预定频率获取所述电机的采样值时，对所述采样值进行存储；
    在采样周期结束时，根据存储的所述采样值获取本采样周期采样值的平均值，并根据本采样周期采样值的平均值获取预定采样值波动范围；
    根据存储的所述采样值及所述预定采样值波动范围获取所述采样周期内采样值的集中度。
  8. 根据权利要求3所述的方法，其特征在于，所述采样值的稳定性参数包括采样值的方差或标准差；
    所述根据所述采样值获取所述采样周期内采样值的稳定性参数，包括：
    根据所述采样值以及采样值的平均值获取所述采样周期内采样值的方差或标准差；其中所述采样值的平均值为如下任意一种：
    预设平均值、第一采样周期采样值的平均值、上一采样周期采样值的平均值、本采样周期采样值的平均值。
  9. 根据权利要求8所述的方法，其特征在于，若所述采样值的平均值为预设平均值、或第一采样周期采样值的平均值、或上一采样周期采样值的平均值，则所述根据所述采样值以及采样值的平均值获取所述采样周期内采样值的方差或标准差，包括：
    在采样周期内以预定频率获取所述电机的采样值时，通过第二累加器 对所述采样值与所述采样值的平均值之差的平方值进行累加；
    在采样周期结束时，根据所述第二累加器的累加结果以及采样周期的总采样值数量，获取所述采样周期内采样值的方差或标准差。
  10. 根据权利要求8所述的方法，其特征在于，若所述采样值的平均值为本采样周期采样值的平均值，则所述根据所述采样值以及采样值的平均值获取所述采样周期内采样值的方差或标准差，包括：
    在采样周期内以预定频率获取所述电机的采样值时，对所述采样值进行存储；
    在采样周期结束时，根据存储的所述采样值获取本采样周期采样值的平均值，并根据存储的所述采样值及所述本采样周期采样值的平均值获取所述采样周期内采样值的方差或标准差。
  11. 根据权利要求3-10任一项所述的方法，其特征在于，所述在采样周期内以预定频率获取所述电机的采样值，包括：
    在采样周期内以预定频率从电调板采集所述电机的实时电流，其中所述电机与所述电调板电连接；和/或
    在采样周期内以预定频率从码盘采集所述电机的实时转速，其中所述电机与所述码盘电连接。
  12. 根据权利要求1-11任一项所述的方法，其特征在于，所述电机为雷达系统的驱动电机，所述驱动电机用于驱动所述雷达系统中的扫描组件转动。
  13. 根据权利要求1-11任一项所述的方法，其特征在于，所述电机为可移动平台的动力系统的驱动电机。
  14. 根据权利要求13所述的方法，其特征在于，所述可移动平台包括如下至少一种：
    无人飞行器、遥控车。
  15. 一种电机失效检测装置，其特征在于，包括：处理器，所述处理器用于执行以下操作：
    获取电机的状态参数，所述状态参数包括电流参数和/或转速参数；
    判断所述状态参数是否超过预设阈值；
    若所述状态参数超过所述预设阈值，则判断所述电机失效。
  16. 根据权利要求15所述的装置，其特征在于，
    所述电流参数包括电流的平均值和/或电流的稳定性参数；
    所述转速参数包括转速的平均值和/或转速的稳定性参数。
  17. 根据权利要求16所述的装置，其特征在于，在所述处理器获取电机的状态参数时，所述处理器被配置为：
    在采样周期内以预定频率获取所述电机的采样值，所述采样值包括实时电流和/或实时转速；
    根据所述采样值获取所述采样周期内采样值的平均值；和/或
    根据所述采样值获取所述采样周期内采样值的稳定性参数。
  18. 根据权利要求17所述的装置，其特征在于，在所述处理器根据所述采样值获取所述采样周期内采样值的平均值时，所述处理器被配置为：
    在采样周期内以预定频率获取所述电机的采样值时，通过第一累加器对采集的采样值进行累加；
    在采样周期结束时，根据所述第一累加器的累加结果以及采样周期的总采样值数量，获取所述采样周期内采样值的平均值。
  19. 根据权利要求17所述的装置，其特征在于，所述采样值的稳定性参数包括采样值的集中度；
    在所述处理器根据所述采样值获取所述采样周期内采样值的稳定性参数时，所述处理器被配置为：
    获取采样周期内处于预定采样值波动范围内的采样值数量占采样周期的总采样值数量的比例，作为所述采样值的集中度；其中所述预定采样值波动范围为如下任意一种：
    预设范围、根据第一采样周期采样值的平均值获取的采样值范围、根据上一采样周期采样值的平均值获取的采样值范围、根据本采样周期采样值的平均值获取的采样值范围。
  20. 根据权利要求19所述的装置，其特征在于，若所述预定电流波动范围为预设范围、或根据第一采样周期采样值的平均值获取的采样值范围、或根据上一采样周期采样值的平均值获取的采样值范围，则在所述处理器获取采样周期内处于预定采样值波动范围内的采样值数量占采样周期的总采样值数量的比例时，所述处理器被配置为：
    在采样周期内以预定频率获取所述电机的采样值时，通过计数器对处于所述预定采样值波动范围内的采样值数量进行计数；
    在采样周期结束时，根据所述计数器的计数结果以及采样周期的总采样值数量，获取所述采样周期内采样值的集中度。
  21. 根据权利要求19所述的装置，其特征在于，若所述预定采样值波动范围为根据本采样周期采样值的平均值获取的采样值范围，则在所述处理器获取采样周期内处于预定采样值波动范围内的采样值数量占采样周期的总采样值数量的比例时，所述处理器被配置为：
    在采样周期内以预定频率获取所述电机的采样值时，对所述采样值进行存储；
    在采样周期结束时，根据存储的所述采样值获取本采样周期采样值的平均值，并根据本采样周期采样值的平均值获取预定采样值波动范围；
    根据存储的所述采样值及所述预定采样值波动范围获取所述采样周期内采样值的集中度。
  22. 根据权利要求17所述的装置，其特征在于，所述采样值的稳定性参数包括采样值的方差或标准差；
    在所述处理器根据所述采样值获取所述采样周期内采样值的稳定性参数时，所述处理器被配置为：
    根据所述采样值以及采样值的平均值获取所述采样周期内采样值的方差或标准差；其中所述采样值的平均值为如下任意一种：
    预设平均值、第一采样周期采样值的平均值、上一采样周期采样值的平均值、本采样周期采样值的平均值。
  23. 根据权利要求22所述的装置，其特征在于，若所述采样值的平均值为预设平均值、或第一采样周期采样值的平均值、或上一采样周期采样值的平均值，则在所述处理器根据所述采样值以及采样值的平均值获取所述采样周期内采样值的方差或标准差时，所述处理器被配置为：
    在采样周期内以预定频率获取所述电机的采样值时，通过第二累加器对所述采样值与所述采样值的平均值之差的平方值进行累加；
    在采样周期结束时，根据所述第二累加器的累加结果以及采样周期的总采样值数量，获取所述采样周期内采样值的方差或标准差。
  24. 根据权利要求22所述的装置，其特征在于，若所述采样值的平均值为本采样周期采样值的平均值，则在所述处理器根据所述采样值以及采样值的平均值获取所述采样周期内采样值的方差或标准差时，所述处理器被配置为：
    在采样周期内以预定频率获取所述电机的采样值时，对所述采样值进行存储；
    在采样周期结束时，根据存储的所述采样值获取本采样周期采样值的平均值，并根据存储的所述采样值及所述本采样周期采样值的平均值获取所述采样周期内采样值的方差或标准差。
  25. 根据权利要求17-24任一项所述的装置，其特征在于，在所述处理器在采样周期内以预定频率获取所述电机的采样值时，所述处理器被配置为：
    在采样周期内以预定频率从电调板采集所述电机的实时电流，其中所述电机与所述电调板电连接；和/或
    在采样周期内以预定频率从码盘采集所述电机的实时转速，其中所述电机与所述码盘电连接。
  26. 根据权利要求15-25任一项所述的装置，其特征在于，所述电机为雷达系统的驱动电机，所述驱动电机用于驱动所述雷达系统中的扫描组件转动。
  27. 根据权利要求15-25任一项所述的装置，其特征在于，所述电机为可移动平台的动力系统的驱动电机。
  28. 根据权利要求27所述的装置，其特征在于，所述可移动平台包括如下至少一种：
    无人飞行器、遥控车。
  29. 一种雷达系统，其特征在于，包括：
    测距组件，用于发射光脉冲序列并接收经过被探测物反射的光脉冲序列；
    扫描组件，所述扫描组件包括光学元件和驱动所述光学元件转动的驱动电机，所述光学元件设置于所述测距组件的光脉冲序列的光路上；以及
    处理器，所述处理器用于执行以下操作：
    获取电机的状态参数，所述状态参数包括电流参数和/或转速参数；
    判断所述状态参数是否超过预设阈值；
    若所述状态参数超过所述预设阈值，则判断所述电机失效。
  30. 根据权利要求29所述的雷达系统，其特征在于，
    所述电流参数包括电流的平均值和/或电流的稳定性参数；
    所述转速参数包括转速的平均值和/或转速的稳定性参数。
  31. 根据权利要求30所述的雷达系统，其特征在于，在所述处理器获取电机的状态参数时，所述处理器被配置为：
    在采样周期内以预定频率获取所述电机的采样值，所述采样值包括实时电流和/或实时转速；
    根据所述采样值获取所述采样周期内采样值的平均值；和/或
    根据所述采样值获取所述采样周期内采样值的稳定性参数。
  32. 根据权利要求31所述的雷达系统，其特征在于，在所述处理器根据所述采样值获取所述采样周期内采样值的平均值时，所述处理器被配置为：
    在采样周期内以预定频率获取所述电机的采样值时，通过第一累加器对采集的采样值进行累加；
    在采样周期结束时，根据所述第一累加器的累加结果以及采样周期的总采样值数量，获取所述采样周期内采样值的平均值。
  33. 根据权利要求31所述的雷达系统，其特征在于，所述采样值的稳定性参数包括采样值的集中度；
    在所述处理器根据所述采样值获取所述采样周期内采样值的稳定性参数时，所述处理器被配置为：
    获取采样周期内处于预定采样值波动范围内的采样值数量占采样周期的总采样值数量的比例，作为所述采样值的集中度；其中所述预定采样值波动范围为如下任意一种：
    预设范围、根据第一采样周期采样值的平均值获取的采样值范围、根据上一采样周期采样值的平均值获取的采样值范围、根据本采样周期采样值的平均值获取的采样值范围。
  34. 根据权利要求33所述的雷达系统，其特征在于，若所述预定电 流波动范围为预设范围、或根据第一采样周期采样值的平均值获取的采样值范围、或根据上一采样周期采样值的平均值获取的采样值范围，则在所述处理器获取采样周期内处于预定采样值波动范围内的采样值数量占采样周期的总采样值数量的比例时，所述处理器被配置为：
    在采样周期内以预定频率获取所述电机的采样值时，通过计数器对处于所述预定采样值波动范围内的采样值数量进行计数；
    在采样周期结束时，根据所述计数器的计数结果以及采样周期的总采样值数量，获取所述采样周期内采样值的集中度。
  35. 根据权利要求33所述的雷达系统，其特征在于，若所述预定采样值波动范围为根据本采样周期采样值的平均值获取的采样值范围，则在所述处理器获取采样周期内处于预定采样值波动范围内的采样值数量占采样周期的总采样值数量的比例时，所述处理器被配置为：
    在采样周期内以预定频率获取所述电机的采样值时，对所述采样值进行存储；
    在采样周期结束时，根据存储的所述采样值获取本采样周期采样值的平均值，并根据本采样周期采样值的平均值获取预定采样值波动范围；
    根据存储的所述采样值及所述预定采样值波动范围获取所述采样周期内采样值的集中度。
  36. 根据权利要求31所述的雷达系统，其特征在于，所述采样值的稳定性参数包括采样值的方差或标准差；
    在所述处理器根据所述采样值获取所述采样周期内采样值的稳定性参数时，所述处理器被配置为：
    根据所述采样值以及采样值的平均值获取所述采样周期内采样值的方差或标准差；其中所述采样值的平均值为如下任意一种：
    预设平均值、第一采样周期采样值的平均值、上一采样周期采样值的平均值、本采样周期采样值的平均值。
  37. 根据权利要求36所述的雷达系统，其特征在于，若所述采样值的平均值为预设平均值、或第一采样周期采样值的平均值、或上一采样周期采样值的平均值，则在所述处理器根据所述采样值以及采样值的平均值获取所述采样周期内采样值的方差或标准差时，所述处理器被配置为：
    在采样周期内以预定频率获取所述电机的采样值时，通过第二累加器对所述采样值与所述采样值的平均值之差的平方值进行累加；
    在采样周期结束时，根据所述第二累加器的累加结果以及采样周期的总采样值数量，获取所述采样周期内采样值的方差或标准差。
  38. 根据权利要求36所述的雷达系统，其特征在于，若所述采样值的平均值为本采样周期采样值的平均值，则在所述处理器根据所述采样值以及采样值的平均值获取所述采样周期内采样值的方差或标准差时，所述处理器被配置为：
    在采样周期内以预定频率获取所述电机的采样值时，对所述采样值进行存储；
    在采样周期结束时，根据存储的所述采样值获取本采样周期采样值的平均值，并根据存储的所述采样值及所述本采样周期采样值的平均值获取所述采样周期内采样值的方差或标准差。
  39. 根据权利要求31-38任一项所述的雷达系统，其特征在于，在所述处理器在采样周期内以预定频率获取所述电机的采样值时，所述处理器被配置为：
    在采样周期内以预定频率从电调板采集所述电机的实时电流，其中所述电机与所述电调板电连接；和/或
    在采样周期内以预定频率从码盘采集所述电机的实时转速，其中所述电机与所述码盘电连接。
  40. 根据权利要求29-39任一项所述的雷达系统，其特征在于，所述雷达系统设置于可移动平台。
  41. 根据权利要求40所述的雷达系统，其特征在于，所述可移动平台包括如下至少一种：
    无人飞行器、遥控车。
  42. 一种可移动平台，其特征在于，包括：
    机身；
    动力系统，安装在所述机身，用于提供动力，所述动力系统包括驱动电机；以及
    如权利要求29-41任一项所述的雷达系统。
  43. 根据权利要求42所述的可移动平台，其特征在于，所述可移动平台包括如下至少一种：
    无人飞行器、遥控车。
  44. 一种计算机可读存储介质，其特征在于，其上存储有计算机程序，所述计算机程序被处理器执行以实现如权利要求1-14任一项所述的方法。
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CN115535296B (zh) * 2022-11-29 2023-04-14 北京卓翼智能科技有限公司 无人机电机测试方法、装置、电子设备及存储介质
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Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20090079380A1 (en) * 2007-09-20 2009-03-26 Rockwell Automation Technologies, Inc. Motor controller having counter to count position error events and method of motor control using same
CN104422883A (zh) * 2013-08-21 2015-03-18 华为技术有限公司 一种电机失步的检测方法和检测设备
CN104793139A (zh) * 2015-04-22 2015-07-22 上海中科深江电动车辆有限公司 一种电机故障诊断及处理方法
CN105572585A (zh) * 2014-10-30 2016-05-11 德尔福技术有限公司 电机故障检测的系统和方法
CN107074351A (zh) * 2016-09-30 2017-08-18 深圳市大疆创新科技有限公司 无人机的控制方法、装置及无人飞行器

Family Cites Families (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103954971B (zh) * 2014-05-22 2016-03-30 武汉大学 机载彩色三维扫描激光雷达
CN105182361A (zh) * 2015-08-06 2015-12-23 哈尔滨工业大学 一种基于复合调制脉冲编码的4d成像光子计数激光雷达

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20090079380A1 (en) * 2007-09-20 2009-03-26 Rockwell Automation Technologies, Inc. Motor controller having counter to count position error events and method of motor control using same
CN104422883A (zh) * 2013-08-21 2015-03-18 华为技术有限公司 一种电机失步的检测方法和检测设备
CN105572585A (zh) * 2014-10-30 2016-05-11 德尔福技术有限公司 电机故障检测的系统和方法
CN104793139A (zh) * 2015-04-22 2015-07-22 上海中科深江电动车辆有限公司 一种电机故障诊断及处理方法
CN107074351A (zh) * 2016-09-30 2017-08-18 深圳市大疆创新科技有限公司 无人机的控制方法、装置及无人飞行器

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