CN111965609A - Radar reliability evaluation method and device, electronic equipment and readable storage medium - Google Patents
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Abstract
The application provides a radar reliability assessment method and device, electronic equipment and a readable storage medium, and relates to the technical field of vehicle driving. The method comprises the following steps: acquiring fault data of each radar in a plurality of radars when the radar fails in the using process; obtaining a corresponding fault rate function according to fault data, wherein the fault rate function is used for representing the fault rate of the radar, and the fault rate function is a poisson process; determining a reliability function for evaluating radar reliability based on the fault rate function; performing a reliability evaluation on the plurality of radars based on the reliability function. The reliability evaluation of the whole radar can be realized without special test environment in the scheme, the test cost is low, and the method is applicable to reliability test of large-scale radars. In addition, the mathematical law that the radar fails is considered in the scheme, so that the obtained failure rate function is more reasonable, the failure conditions of a plurality of radars can be better reflected, and the reliability of the whole radar can be more effectively evaluated.
Description
Technical Field
The application relates to the technical field of vehicle driving, in particular to a radar reliability assessment method and device, electronic equipment and a readable storage medium.
Background
With the rapid development of artificial intelligence technology, automatic driving of automobiles becomes the main target of automobile enterprises at present. The automatic driving technology is a technology which relies on a multi-source sensor to collect data, and an embedded system on a vehicle independently completes data processing and driving functions. In the current research stage of automatic driving, millimeter wave radar is used as a main sensor, and the reliability level of the millimeter wave radar determines the level of an automatic driving automobile to a great extent.
Currently, reliability test methods related to millimeter wave radars are few, for example, complete machine reliability tests of millimeter wave radars can be realized, and complete machine reliability tests can be performed in a high-low temperature test mode, a vibration impact test mode and the like. However, for these tests, the tests can be performed only under special environments, which has high requirements for the test environment and is not suitable for the reliability tests of large-scale radars.
Disclosure of Invention
An object of the embodiments of the present application is to provide a radar reliability assessment method, apparatus, electronic device, and readable storage medium, so as to solve the problem that the reliability test for a large-scale radar is not suitable for the prior art due to a high test environment requirement.
In a first aspect, an embodiment of the present application provides a radar reliability assessment method, where the method includes: acquiring fault data of each radar in a plurality of radars when the radar fails in the using process; obtaining a corresponding fault rate function according to the fault data, wherein the fault rate function is used for representing the fault rate of the radar, and the fault rate function is a poisson process; determining a reliability function for evaluating radar reliability based on the fault rate function; performing a reliability evaluation on the plurality of radars based on the reliability function.
In the implementation process, the corresponding fault rate function is obtained according to the fault data, then the corresponding reliability function is obtained to evaluate the reliability of the radar, the reliability evaluation of the whole radar can be realized without a special test environment in the scheme, the test cost is low, and the method is applicable to the reliability test of large-scale radars. In addition, the mathematical law that the radar fails is considered in the scheme, so that the obtained failure rate function is more reasonable, the failure conditions of a plurality of radars can be better reflected, and the reliability of the whole radar can be more effectively evaluated.
Optionally, the obtaining the corresponding fault rate function according to the fault data includes:
obtaining a plurality of initial fault rate functions from the fault data for each radar;
obtaining a target parameter value in each initial fault rate function, and obtaining a plurality of target parameter values in total, wherein the target parameter values are the variances of normal distribution;
calculating a mean value of the plurality of target parameter values;
and changing the target parameter value in each initial fault rate function into a corresponding mean value to obtain a changed fault rate function.
In the implementation process, because the radars have mutual independence and the reliability of the whole radar in the same batch cannot be evaluated by the fault rate function corresponding to any one of the radars, the target parameter value in the initial fault rate function corresponding to each radar is correspondingly processed, so that a more effective reliability function can be obtained based on the changed fault rate function.
Optionally, the number of the plurality of radars is greater than a preset number. Since the failure rate of the radar can be occasionally represented by the obtained failure rate function when the number is small, the failure rate function obtained by the method is more universal when the number of the radars is large.
Optionally, the obtaining the corresponding fault rate function according to the fault data includes:
obtaining a plurality of initial fault rate functions from the fault data for each radar;
obtaining a target parameter value in each initial fault rate function, and obtaining a plurality of target parameter values in total, wherein the target parameter values are the variances of normal distribution;
sampling the target parameter values by using a Markov chain Monte Carlo sampling method to obtain a plurality of sample values;
obtaining a correlation function characterizing a value of a target parameter over time based on the plurality of sample values;
and changing the target parameter value in each initial fault rate function into a corresponding correlation function to obtain a changed fault rate function.
In the implementation process, because the radars have mutual independence and the reliability of the whole radar in the same batch cannot be evaluated by the fault rate function corresponding to any one of the radars, the target parameter value in the initial fault rate function corresponding to each radar is correspondingly processed, so that a more effective reliability function can be obtained based on the changed fault rate function.
Optionally, the number of the plurality of radars is less than a preset number. Because the fault rate of the radar represented by the obtained fault rate function may have contingency when the number is small, sampling is performed by a Markov chain Monte Carlo sampling method when the number of the radars is small, so that large sample data can be obtained by simulating small sample data, and subsequent reliability index evaluation can be performed according to the large sample data.
Optionally, the performing reliability evaluation on the plurality of radars based on the reliability function includes:
calculating and obtaining the mean time between failures of the plurality of radars based on the reliability function;
performing reliability evaluation on the plurality of radars based on the mean time to failure.
In the implementation process, reliability evaluation is carried out on a plurality of radars through mean time between failures, so that the reliability evaluation of the radars can be realized from the dimension of the mean time between failures.
Optionally, after obtaining the corresponding fault rate function, the method further includes:
calculating and obtaining average fault interval time of the plurality of radars based on the fault rate function;
performing reliability evaluation on the plurality of radars based on the mean time between failures.
In the implementation process, the reliability evaluation is carried out on the plurality of radars through the mean fault interval time, so that the reliability evaluation on the radars can be realized from the dimension of the mean fault interval time.
In a second aspect, an embodiment of the present application provides a radar reliability evaluation apparatus, including:
the fault data acquisition module is used for acquiring fault data of faults of each radar in the plurality of radars in the using process;
the fault rate function determining module is used for obtaining a corresponding fault rate function according to the fault data, the fault rate function is used for representing the fault rate of the radar, and the fault rate function is a poisson process;
the reliability function determination module is used for determining a reliability function for evaluating the reliability of the radar based on the fault rate function;
and the reliability evaluation module is used for evaluating the reliability of the plurality of radars based on the reliability function.
Optionally, the failure rate function is a failure rate function corresponding to each radar, and the failure rate function determining module is configured to obtain a plurality of initial failure rate functions according to the failure data of each radar; obtaining a target parameter value in each initial fault rate function, and obtaining a plurality of target parameter values in total, wherein the target parameter values are the variances of normal distribution; calculating a mean value of the plurality of target parameter values; and changing the target parameter value in each initial fault rate function into a corresponding mean value to obtain a changed fault rate function.
Optionally, the number of the plurality of radars is greater than a preset number.
Optionally, the failure rate function is a failure rate function corresponding to each radar, and the failure rate function determining module is configured to obtain a plurality of initial failure rate functions according to the failure data of each radar; obtaining a target parameter value in each initial fault rate function, and obtaining a plurality of target parameter values in total, wherein the target parameter values are the variances of normal distribution; sampling the target parameter values by using a Markov chain Monte Carlo sampling method to obtain a plurality of sample values; obtaining a correlation function characterizing a value of a target parameter over time based on the plurality of sample values; and changing the target parameter value in each initial fault rate function into a corresponding correlation function to obtain a changed fault rate function.
Optionally, the number of the plurality of radars is less than a preset number.
Optionally, the reliability function determining module is configured to calculate and obtain a mean time to failure of the plurality of radars based on the reliability function; performing reliability evaluation on the plurality of radars based on the mean time to failure.
Optionally, the reliability evaluation module is further configured to calculate and obtain an average time between failures of the plurality of radars based on the failure rate function; performing reliability evaluation on the plurality of radars based on the mean time between failures.
In a third aspect, an embodiment of the present application provides an electronic device, including a processor and a memory, where the memory stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, the steps in the method as provided in the first aspect are executed.
In a fourth aspect, embodiments of the present application provide a readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, performs the steps in the method as provided in the first aspect.
Additional features and advantages of the present application will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by the practice of the embodiments of the present application. The objectives and other advantages of the application may be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments of the present application will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and that those skilled in the art can also obtain other related drawings based on the drawings without inventive efforts.
Fig. 1 is a schematic structural diagram of an electronic device for performing a radar reliability evaluation method according to an embodiment of the present disclosure;
fig. 2 is a flowchart of a radar reliability evaluation method according to an embodiment of the present disclosure;
fig. 3 is a block diagram of a radar reliability evaluation apparatus according to an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application.
The embodiment of the application provides a radar reliability assessment method, a corresponding fault rate function is obtained according to fault data of a radar which breaks down, then the corresponding reliability function is obtained to assess the reliability of the radar, the reliability assessment of the whole radar can be achieved without a special testing environment in the scheme, the testing cost is low, and the radar reliability assessment method is applicable to reliability testing of large-scale radars. In addition, the mathematical law of radar fault is also considered in the scheme, so that the obtained fault rate function is more reasonable, the fault conditions of a plurality of radars can be better reflected, and the reliability of the whole radar can be more effectively evaluated.
Referring to fig. 1, fig. 1 is a schematic structural diagram of an electronic device for executing a radar reliability evaluation method according to an embodiment of the present disclosure, where the electronic device may include: at least one processor 110, such as a CPU, at least one communication interface 120, at least one memory 130, and at least one communication bus 140. Wherein the communication bus 140 is used for realizing direct connection communication of these components. The communication interface 120 of the device in the embodiment of the present application is used for performing signaling or data communication with other node devices. The memory 130 may be a high-speed RAM memory or a non-volatile memory (e.g., at least one disk memory). Memory 130 may optionally be at least one memory device located remotely from the aforementioned processor. The memory 130 stores computer readable instructions, and when the computer readable instructions are executed by the processor 110, the electronic device executes the method process shown in fig. 2, for example, the memory 130 may be used to store fault data of a radar, the processor 110 may be used to obtain corresponding fault data from the memory 130, then determine a corresponding fault rate function based on the fault data, determine a reliability function based on the fault rate function, and then perform reliability evaluation on the radar.
It will be appreciated that the configuration shown in fig. 1 is merely illustrative and that the electronic device may also include more or fewer components than shown in fig. 1 or have a different configuration than shown in fig. 1. The components shown in fig. 1 may be implemented in hardware, software, or a combination thereof.
Referring to fig. 2, fig. 2 is a flowchart of a radar reliability evaluation method according to an embodiment of the present disclosure, where the method includes the following steps:
step S110: and acquiring fault data of each radar in the plurality of radars, wherein the fault data is generated when each radar is in fault in the using process.
The fault data can be obtained by the following method: the method comprises the steps that all radars are installed on a vehicle in advance, in the running process of the vehicle, the radars are controlled through a vehicle control system to carry out target detection, and then the total detection times and fault data of the radars in the detection process are obtained. The fault data can comprise the fault times, or the time point of the fault of the radar, and the fault times refer to the false alarm and the false failure times of the radar detection target, and the fault times can be manually recorded and then input into the electronic equipment, namely, whether the radar can accurately detect the target every time is manually recorded, and then the total times of the radar detection error and the target non-detection are recorded as the fault times.
Step S120: and obtaining a corresponding fault rate function according to the fault data.
The fault rate function is used for representing the fault rate of the radar, and can be understood as the frequency of the fault of the radar in a certain time or the probability of the fault of the radar in unit time, or the times of false alarm and false negative alarm of the radar in a certain time interval, and the like. It is understood that, in the actual application process, the meaning of the failure rate function may be defined according to the actual demand.
The fault rate function is a poisson process, and if fault data is substituted into an expression of the poisson process, a corresponding fault rate function can be obtained, where the expression of the poisson process is as follows:
after obtaining the fault data, substituting the fault data into the formula to obtain a corresponding fault rate function, wherein an expression of the fault rate function is as follows:
where n represents the total number of times the radar has detected the target in total.
Step S130: a reliability function for evaluating radar reliability is determined based on the failure rate function.
The reliability function is understood to be the probability that a product completes a specified function within a specified time under specified conditions, and is a function of time, such as the probability that a radar completes a target detection function within a specified actual time, and can be used for evaluating the reliability of the radar.
After the failure rate function is obtained, the failure rate function can be converted into a reliability function for evaluating the reliability of the radar based on a certain derivation process.
Step S140: performing a reliability evaluation on the plurality of radars based on the reliability function.
After the reliability function is obtained as described above, the reliability function may be used to perform a reliability evaluation on the radar. For example, a value calculated using the reliability function may be used to characterize the reliability, which may be lower when the calculated value is less than a predetermined value and higher when the calculated value is greater than the predetermined value. The overall reliability of the plurality of radars is evaluated, the plurality of radars can refer to the radars produced in the same batch, and therefore the production quality of the radars can be evaluated based on the reliability so as to evaluate whether the radars produced in the same batch meet the quality inspection requirements and the like.
In the implementation process, the corresponding fault rate function is obtained according to the fault data, then the corresponding reliability function is obtained to evaluate the reliability of the radar, the reliability evaluation of the whole radar can be realized without a special test environment in the scheme, the test cost is low, and the method is applicable to the reliability test of large-scale radars. In addition, the mathematical law that the radar fails is considered in the scheme, so that the obtained failure rate function is more reasonable, the failure conditions of a plurality of radars can be better reflected, and the reliability of the whole radar can be more effectively evaluated.
As an embodiment, the fault rate function may also be other mathematical rules, such as a stochastic process. The failure rate function is a failure rate function corresponding to each radar, and the failure rate functions corresponding to each radar have different parameters and are mutually independent, so that if the failure rate function of one radar is used for evaluating the overall reliability of a plurality of radars in the same batch, the failure rate function does not have universality and cannot represent the reliability of all radars. Therefore, parameters in each fault rate function can be correspondingly processed, and then a uniform fault rate function is obtained.
The process of obtaining the fault rate function may be: the method comprises the steps of obtaining a plurality of initial fault rate functions according to fault data of each radar, then obtaining target parameter values in each initial fault rate function, obtaining a plurality of target parameter values in total, wherein the target parameter values are the variance of normal distribution, then calculating the mean value of the target parameter values, changing the target parameter values in each initial fault rate function into the corresponding mean value, and obtaining the changed fault rate functions, so that the fault rate parameters corresponding to each radar are the same fault rate parameters.
For example, the poisson process described above may be expressed as:
where k denotes the number of failures of the radar within the time interval τ, l denotes the value of the target parameter in the failure rate function, i.e. denotes the variance of the normal distribution, and l τ denotes the average occurrence rate of random events (i.e. failures) per unit time.
The poisson process is suitable for describing the number of random events occurring in a unit time, so that the poisson process can be used for better representing the number of times of faults of the radar in a certain time. After obtaining the expression of the poisson process, the obtained number of faults of each radar and the total number of collected times may be substituted into the above expression of the poisson process, and the obtained initial fault rate function may be represented as follows:
where n represents the total number of times the radar has detected the target in total.
When there are multiple radars, there are multiple corresponding initial failure rate functions, although the initial failure rate functions of all radars are distributed independently, in the whole sample space, the parameter of the initial failure rate function of each radar also obeys a certain distribution, such as a normal distribution, so according to the idea of normal distribution, in all the parameters, the probability of being at the mean value is the largest, so that the multiple target parameter values are correspondingly processed, such as calculating the mean value of the multiple target parameter values, and the calculation formula is as follows:
where m is the number of radars.
After obtaining the mean value of a plurality of target parameter values, that is, a mean value is obtained for each initial failure rate function, and then the corresponding mean value is substituted into the corresponding initial failure rate function, so that a modified failure rate function can be obtained, wherein the expression is as follows:
in the implementation process, because the radars have mutual independence and the reliability of the whole radar in the same batch cannot be evaluated by the fault rate function corresponding to any one of the radars, the target parameter value in the initial fault rate function corresponding to each radar is correspondingly processed, so that a more effective reliability function can be obtained based on the changed fault rate function.
As an embodiment, the condition that the target parameter values in the initial failure rate function are processed as described above may be that the number of the plurality of radars is larger than a preset number, because if the number of the radars is too small, the failure rate function calculated in the above manner may have contingency and may not be suitable for the reliability evaluation of the whole plurality of radars. Therefore, the failure rate function can be calculated in the above manner when the number of radars is greater than the preset number.
The preset number can be flexibly set according to actual requirements.
As another embodiment, the above-mentioned manner of obtaining the failure rate function may be further: the method comprises the steps of obtaining a plurality of initial fault rate functions according to fault data of each radar, then obtaining target parameter values in each initial fault rate function, obtaining a plurality of target parameter values in total, wherein the target parameter values are the variances of normal distribution, then sampling the target parameter values by using a Markov chain Monte Carlo sampling method to obtain a plurality of sample values, then obtaining a correlation function representing the target parameter values changing along with time based on the sample values, changing the target parameter values in each initial fault rate function into corresponding correlation functions, and obtaining changed fault rate functions.
The Markov chain Monte Carlo is defined by sampling through probability distribution, estimating the parameter of the model under the given observation data, and approximating the parameter distribution by a group of possible parameter values (sampling according to certain probability distribution) due to the inconvenience of directly calculating the model parameter, namely a Monte Carlo part, wherein the assumption is provided with a guiding principle, and the next parameter value is sampled according to the parameter value sampled currently and the prior of the parameter, so that the Markov chain Monte Carlo has the property of the Markov chain.
The basic idea of the Markov chain Monte Carlo sampling method is as follows: aiming at a target distribution (such as a poisson distribution), a markov chain is constructed, so that the stable distribution of the markov chain is the target distribution, then starting from any initial state, the transition is carried out along the markov chain, a final state transition sequence converges to the target distribution, then a series of obtained samples are sampled, the obtained series of samples obey the target distribution, namely a plurality of sampling values obtained by sampling in the embodiment of the application obey the poisson distribution, and the correlation function refers to a function for representing the plurality of sampling values obey the poisson distribution.
If the correlation function is l (t), after the target parameter value in the fault rate function is changed into the corresponding correlation function, the obtained changed fault rate function is expressed as follows:
the specific implementation of the above-mentioned sampling by using the markov chain monte carlo sampling method is not described in detail herein, and those skilled in the art may refer to the related implementation in the prior art.
In the implementation process, because the radars have mutual independence and the reliability of the whole radar in the same batch cannot be evaluated by the fault rate function corresponding to any one of the radars, the target parameter value in the initial fault rate function corresponding to each radar is correspondingly processed, so that a more effective reliability function can be obtained based on the changed fault rate function.
As an implementation manner, the condition for obtaining the changed fault rate function through the above manner may be that the number of the plurality of radars is smaller than a preset number, that is, when the number of samples is small, the markov chain monte carlo sampling method is applied to sampling, and small sample data may be used to perform simulation to obtain large sample data, so that subsequent reliability index evaluation may be performed according to the large sample data.
After the failure rate function is obtained, a reliability function can be derived through the failure rate function, and the expression of the reliability function is as follows:
wherein R (t) represents a reliability function,
representing a failure rate function.
The derivation process described above can be roughly as follows:
if the reliability function r (t) is defined as the probability that the radar has successfully completed the target detection at the time t, and the cumulative distribution function f (t) is defined as the probability that the radar has failed in the alarm or failed in the alarm (i.e., the target is not detected) at the time t, it can be known that r (t) + f (t) ═ 1. Wherein f (t) is obtained by deriving F (t), F (t) represents that the radar has failed to report or has reported a false at the time t,
cumulative distribution function f (t) and failure rate function
Can be expressed as:
while
In this way, a reliability function can be derived from the failure rate function.
It should be noted that the above detailed derivation process for deriving the reliability function through the fault rate function derivation can refer to related implementation processes in the prior art, and will not be described in detail here.
The reliability function obtained by the above formula can be directly used for reliability evaluation, that is, the obtained fault data of each radar is substituted into the fault rate function, that is, the fault rate can be calculated based on the fault rate function, and then the fault rate function is substituted into the reliability function, that is, the corresponding value can be obtained, and the value can be used for representing the reliability of a plurality of radars.
As an embodiment, the reliability evaluation index for the radar may further include a mean time between failures, for example, the mean time between failures of a plurality of radars may be calculated based on the reliability function, and then the reliability evaluation may be performed on the plurality of radars based on the mean time between failures.
The calculation formula of the mean time between failures is as follows:
it is understood that the mean time between failures can be calculated by substituting the reliability function into the equation, and reliability evaluation can be performed on a plurality of radars after the mean time between failures is obtained. The reliability evaluation mode can be set by self, for example, when the mean time between failures is greater than a preset value, the reliability of a plurality of radars is high, and when the mean time between failures is less than the preset value, the reliability of the radars is low, the production quality is possibly unqualified, rework is needed, and the like.
The reliability calculated by the reliability function and the mean time to failure can be used for comprehensively evaluating the reliability of the plurality of radars, and the comprehensive evaluation mode can be set according to actual requirements, for example, when the reliability is greater than a preset value and the mean time to failure is greater than another preset value, the reliability of the plurality of radars is high, namely the quality of the radars produced in the batch is high, and when any one of the reliability or the mean time to failure does not meet the requirement, the reliability of the plurality of radars is low, and correspondingly, the production quality is low.
In the implementation process, reliability evaluation is carried out on a plurality of radars through mean time between failures, so that the reliability evaluation of the radars can be realized from the dimension of the mean time between failures.
As an embodiment, the reliability evaluation index for the radar may further include a mean time between failures, for example, the mean time between failures of a plurality of radars may be calculated based on a failure rate function, and the reliability evaluation may be performed on the plurality of radars based on the mean time between failures.
Wherein, the calculation formula of the mean-time between failures is as follows:
it is understood that the mean time between failures can be calculated by substituting the above-mentioned function of failure rate into the formula, and reliability evaluation can be performed on a plurality of radars after obtaining the mean time between failures. The reliability evaluation mode can be set by self, for example, when the mean fault interval time is greater than the preset interval, the reliability of a plurality of radars is high, and when the mean fault interval time is less than the preset interval, the reliability of the radars is low.
Of course, the mean-time-between-failure may be combined with the reliability calculated by the reliability function to evaluate the reliability of the plurality of radars, or may be combined with the mean-time-between-failure to evaluate comprehensively, and the comprehensive evaluation mode may be defined according to the actual requirement, where if all the three data satisfy the requirement, the reliability of the plurality of radars is high, and if any one of the three data does not satisfy the requirement, the reliability of the plurality of radars is low.
In the implementation process, the reliability evaluation is carried out on the plurality of radars through the mean fault interval time, so that the reliability evaluation on the radars can be realized from the dimension of the mean fault interval time.
Referring to fig. 3, fig. 3 is a block diagram of a radar reliability evaluation apparatus 200 according to an embodiment of the present disclosure, where the apparatus 200 may be a module, a program segment, or a code on an electronic device. It should be understood that the apparatus 200 corresponds to the above-mentioned embodiment of the method of fig. 2, and can perform various steps related to the embodiment of the method of fig. 2, and the specific functions of the apparatus 200 can be referred to the above description, and the detailed description is appropriately omitted here to avoid redundancy.
Optionally, the apparatus 200 comprises:
a fault data acquiring module 210, configured to acquire fault data of a fault occurring in a use process of each radar in the multiple radars;
a failure rate function determining module 220, configured to obtain a corresponding failure rate function according to the failure data, where the failure rate function is used to characterize a failure rate of a radar;
a reliability function determining module 230, configured to determine a reliability function for evaluating radar reliability based on the fault rate function, where the fault rate function is a poisson process;
a reliability evaluation module 240 configured to perform reliability evaluation on the plurality of radars based on the reliability function.
Optionally, the fault rate function is a fault rate function corresponding to each radar, and the fault rate function determining module 220 is configured to obtain a plurality of initial fault rate functions according to the fault data of each radar; obtaining a target parameter value in each initial fault rate function, and obtaining a plurality of target parameter values in total, wherein the target parameter values are the variances of normal distribution; calculating a mean value of the plurality of target parameter values; and changing the target parameter value in each initial fault rate function into a corresponding mean value to obtain a changed fault rate function.
Optionally, the number of the plurality of radars is greater than a preset number.
Optionally, the fault rate function is a fault rate function corresponding to each radar, and the fault rate function determining module 220 is configured to obtain a plurality of initial fault rate functions according to the fault data of each radar; obtaining a target parameter value in each initial fault rate function, and obtaining a plurality of target parameter values in total, wherein the target parameter values are the variances of normal distribution; sampling the target parameter values by using a Markov chain Monte Carlo sampling method to obtain a plurality of sample values; obtaining a correlation function characterizing a value of a target parameter over time based on the plurality of sample values; and changing the target parameter value in each initial fault rate function into a corresponding correlation function to obtain a changed fault rate function.
Optionally, the number of the plurality of radars is less than a preset number.
Optionally, the reliability function determining module 230 is configured to calculate and obtain a mean time to failure of the plurality of radars based on the reliability function; performing reliability evaluation on the plurality of radars based on the mean time to failure.
Optionally, the reliability evaluation module 240 is further configured to calculate and obtain an average time between failures of the plurality of radars based on the failure rate function; performing reliability evaluation on the plurality of radars based on the mean time between failures.
The embodiment of the present application provides a readable storage medium, and when being executed by a processor, the computer program performs the method process performed by the electronic device in the method embodiment shown in fig. 2.
The present embodiments disclose a computer program product comprising a computer program stored on a non-transitory computer readable storage medium, the computer program comprising program instructions which, when executed by a computer, enable the computer to perform the methods provided by the above-described method embodiments, for example, comprising: acquiring fault data of each radar in a plurality of radars when the radar fails in the using process; obtaining a corresponding fault rate function according to the fault data, wherein the fault rate function is used for representing the fault rate of the radar, and the fault rate function is a poisson process; determining a reliability function for evaluating radar reliability based on the fault rate function; performing a reliability evaluation on the plurality of radars based on the reliability function.
In summary, the embodiments of the present application provide a radar reliability assessment method, apparatus, electronic device, and readable storage medium, where the reliability assessment of the entire radar can be implemented without a special test environment by obtaining a corresponding failure rate function according to the failure data and then obtaining a corresponding reliability function to perform reliability assessment on the radar, and the test cost is low, and the method and apparatus are applicable to reliability tests of large-scale radars. In addition, the mathematical law that the radar fails is considered in the scheme, so that the obtained failure rate function is more reasonable, the failure conditions of a plurality of radars can be better reflected, and the reliability of the whole radar can be more effectively evaluated.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one logical division, and there may be other divisions when actually implemented, and for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of devices or units through some communication interfaces, and may be in an electrical, mechanical or other form.
In addition, units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
Furthermore, the functional modules in the embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.
In this document, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions.
The above description is only an example of the present application and is not intended to limit the scope of the present application, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application.
Claims (10)
1. A radar reliability assessment method, the method comprising:
acquiring fault data of each radar in a plurality of radars when the radar fails in the using process;
obtaining a corresponding fault rate function according to the fault data, wherein the fault rate function is used for representing the fault rate of the radar, and the fault rate function is a poisson process;
determining a reliability function for evaluating radar reliability based on the fault rate function;
performing a reliability evaluation on the plurality of radars based on the reliability function.
2. The method of claim 1, wherein the failure rate function is a failure rate function for each radar, and wherein obtaining the corresponding failure rate function from the failure data comprises:
obtaining a plurality of initial fault rate functions from the fault data for each radar;
obtaining a target parameter value in each initial fault rate function, and obtaining a plurality of target parameter values in total, wherein the target parameter values are the variances of normal distribution;
calculating a mean value of the plurality of target parameter values;
and changing the target parameter value in each initial fault rate function into a corresponding mean value to obtain a changed fault rate function.
3. The method of claim 2, wherein the number of the plurality of radars is greater than a preset number.
4. The method of claim 1, wherein the failure rate function is a failure rate function for each radar, and wherein obtaining the corresponding failure rate function from the failure data comprises:
obtaining a plurality of initial fault rate functions from the fault data for each radar;
obtaining a target parameter value in each initial fault rate function, and obtaining a plurality of target parameter values in total, wherein the target parameter values are the variances of normal distribution;
sampling the target parameter values by using a Markov chain Monte Carlo sampling method to obtain a plurality of sample values;
obtaining a correlation function characterizing a value of a target parameter over time based on the plurality of sample values;
and changing the target parameter value in each initial fault rate function into a corresponding correlation function to obtain a changed fault rate function.
5. The method of claim 4, wherein the number of the plurality of radars is less than a preset number.
6. The method of any of claims 1-5, wherein said reliability evaluating said plurality of radars based on said reliability function comprises:
calculating and obtaining the mean time between failures of the plurality of radars based on the reliability function;
performing reliability evaluation on the plurality of radars based on the mean time to failure.
7. The method according to any one of claims 1-5, wherein after obtaining the corresponding fault rate function, further comprising:
calculating and obtaining average fault interval time of the plurality of radars based on the fault rate function;
performing reliability evaluation on the plurality of radars based on the mean time between failures.
8. A radar reliability evaluation apparatus, characterized in that the apparatus comprises:
the fault data acquisition module is used for acquiring fault data of faults of each radar in the plurality of radars in the using process;
the fault rate function determining module is used for obtaining a corresponding fault rate function according to the fault data, the fault rate function is used for representing the fault rate of the radar, and the fault rate function is a poisson process;
the reliability function determination module is used for determining a reliability function for evaluating the reliability of the radar based on the fault rate function;
and the reliability evaluation module is used for evaluating the reliability of the plurality of radars based on the reliability function.
9. An electronic device comprising a processor and a memory, the memory storing computer readable instructions that, when executed by the processor, perform the method of any of claims 1-7.
10. A readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the method according to any one of claims 1-7.
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