CN117370908A - Reliability analysis method, system and computing equipment for road infrastructure monitoring system - Google Patents
Reliability analysis method, system and computing equipment for road infrastructure monitoring system Download PDFInfo
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Abstract
The invention discloses a reliability analysis method, a system and a computing device of a road infrastructure monitoring system. Analyzing the operation mode of the road infrastructure monitoring system, determining the logic relation and the data processing flow of the road infrastructure monitoring process, and dividing the road infrastructure monitoring system into a plurality of functional links according to the logic relation and the data processing flow of the road infrastructure monitoring process; reliability calculation is respectively carried out on each functional link, and reliability calculation results corresponding to each functional link are obtained; and calculating to obtain the reliability index of the road infrastructure monitoring system based on the reliability calculation result of each functional link and the logic relation of the road infrastructure monitoring system. The invention can be oriented to monitoring systems aiming at different road infrastructure types, can respectively calculate the reliability according to the divided functional links, and finally integrate and determine the reliability index of the whole road infrastructure monitoring system.
Description
Technical Field
The invention relates to the technical field of infrastructure safety monitoring, in particular to a reliability analysis method, a system and computing equipment of a road infrastructure monitoring system.
Background
Along with the rapid development of social economy, the road infrastructure construction of China is gradually perfected, and the road infrastructure network which is huge and complex worldwide is gradually built. Due to the application purpose and the use condition of the road infrastructure, the whole society has high requirements on the safety and the reliability of the infrastructure. Based on this, monitoring systems that can monitor, pre-warn, evaluate and predict the status are emerging for various different types of road infrastructure. Further, in order to ensure the safety of the road infrastructure, the reliability of the road infrastructure monitoring system itself needs to be determined, and if the reliability of the road infrastructure monitoring system itself is doubtful, the safety of the infrastructure cannot be accurately and effectively determined according to the monitoring result.
In the first prior art, application number 202210956542.0 discloses an abnormal road infrastructure monitoring method based on artificial intelligence, sensors are added in the road infrastructure to monitor and collect related data, and according to the sensor measuring point layout principle, the data are classified according to the current situation of an original monitoring system, existing diseases of bridges, the environment where the existing monitoring system is located, the affected and structural characteristics, mechanical behavior characteristics, state evaluation requirements, management maintenance requirements and other factors to judge whether to monitor, the data are analyzed and processed by adopting a neural network deep learning method, the predicted alarm level is output, different alarm thresholds are set according to different categories, and the thresholds are reasonably corrected in daily maintenance, so that although the monitoring automation of the road infrastructure is realized, the reliability of the road infrastructure monitoring system itself is indirectly judged or optimized by optimizing the type selection of the sensors, and the reliability of the road infrastructure monitoring system cannot be quantified.
In the second prior art, application number 202211106101.8 discloses a hybrid coding and optimizing method for a virtual three-dimensional digital road infrastructure. The principle of hybrid coding and optimization according to the digital road infrastructure is as follows: the file is embodied, the structure standard, the parameter is detailed, the use is convenient, and the volume is reduced. Digital road infrastructure is encoded into an electronic file format that is created, opened, used, stored, added or deleted, copied, and more customary for social applications. Meanwhile, the member parameters of the digital road infrastructure with similar change frequency and use frequency but different types are adopted to generate the digital road infrastructure by adopting a hybrid coding method; the method is convenient to use and reduces repeated expression. The separator is used for realizing multi-layer nesting of the member parameters, and auxiliary bytes expressed by nesting, arrays, classes and the like of the member parameters are reduced. Although the body quantity of the digital road infrastructure is reduced as much as possible by compounding and using various optimization methods according to the expression form of the member parameters, the reliability of the road infrastructure monitoring system cannot be quantified by judging the reliability of the monitoring data, so that the reliability of the road infrastructure monitoring system can be intuitively and accurately reflected.
In the third prior art, application number 202211005360.1 discloses a system and a method for monitoring a road infrastructure terminal, wherein the system comprises an intelligent monitoring terminal, which is arranged in the infrastructure and is in communication connection with a host terminal for monitoring the working state of the infrastructure; the inspection module is in communication connection with the host terminal and is used for monitoring dead angles which cannot be covered by the intelligent monitoring terminal; the image acquisition module is in communication connection with the host terminal and is arranged beside the infrastructure and is used for adopting the image information of the infrastructure; the host terminal is used for receiving and processing the information of the intelligent monitoring terminal, the inspection module and the image acquisition module and sending the result to the background processing module; the background processing module is in communication connection with the host terminal; and the alarm module is used for receiving the control information sent by the host terminal and sending out an alarm. Although the state of the road infrastructure is monitored in real time by arranging the intelligent monitoring terminal and is matched with the host terminal, if a fault is found, an alarm is immediately sent out to avoid safety accidents; but the reliability of the road infrastructure monitoring system cannot be intuitively and accurately reflected, and the monitoring system is difficult to be optimized and adjusted in a targeted manner.
Currently, most approaches are to indirectly judge or optimize the reliability of the road infrastructure monitoring system itself, either by judging the reliability of the monitoring data or by optimizing the sensor's choice. The reliability of the road infrastructure monitoring system cannot be quantified by the methods, so that the reliability of the road infrastructure monitoring system can be intuitively and accurately reflected, and the monitoring system is difficult to be optimized and adjusted in a targeted manner. Therefore, a technical solution for reliability analysis directly facing the road infrastructure monitoring system is urgently needed.
Disclosure of Invention
In order to solve the technical problems, the invention provides a reliability analysis method of a road infrastructure monitoring system, a reliability analysis system of the corresponding road infrastructure monitoring system, a computing device and a computer storage medium.
According to one aspect of the present invention, there is provided a method of analyzing reliability of a road infrastructure monitoring system, the method comprising:
analyzing the operation mode of the road infrastructure monitoring system, determining the logic relation and the data processing flow of the road infrastructure monitoring process, and dividing the road infrastructure monitoring system into a plurality of functional links according to the logic relation and the data processing flow of the road infrastructure monitoring process;
Reliability calculation is respectively carried out on each functional link, and reliability calculation results corresponding to each functional link are obtained;
and calculating to obtain the reliability index of the road infrastructure monitoring system based on the reliability calculation result of each functional link and the logic relation of the road infrastructure monitoring.
In the above scheme, the plurality of functional links at least include: the system comprises an acquisition link, a transmission link, an abnormality identification link and a storage link.
In the above scheme, reliability calculation is performed for each functional link, so as to obtain reliability calculation results corresponding to each functional link, and the method further includes:
evaluating the basic characteristics of the sensor through sensor calibration, and calculating to obtain the first reliability of the acquisition link;
determining a packet loss rate of an ad hoc network sensing network adopted by the transmission link, and determining a second reliability of the transmission link by using the packet loss rate;
carrying out correlation analysis and data verification on the road infrastructure monitoring data, and calculating to obtain third reliability of the abnormal identification link;
and determining the fourth reliability of the storage link according to the storage backup mode.
In the above scheme, the basic characteristics of the sensor include static characteristics and dynamic characteristics; wherein the static characteristics include at least: measurement range, linearity, hysteresis, repeatability, sensitivity, resolution and temperature stability; the dynamic characteristics include at least: step response and frequency response;
The basic characteristics of the sensor are evaluated through sensor calibration, and the first reliability of the acquisition link is calculated, and the method further comprises the following steps:
selecting corresponding calibration methods for different types of sensors, performing target feature analysis on the sensor types according to the acquired sensor types, recursively traversing the target features to acquire information of the target features obtained by each recursion, and establishing a first set comprising the target features and the corresponding calibration methods according to the acquired information; generating a mapping relation according to the first set, associating each sensor type with a corresponding calibration method, and storing the mapping relation by using a hash table; by utilizing the established mapping relation, a corresponding calibration method is automatically selected, and the calibration method is realized by searching a corresponding item in a mapping relation hash table;
comparing the static characteristics and the dynamic characteristics of the sensor with the data acquired by the sensor according to the corresponding calibration method, and checking whether the static characteristics and the dynamic characteristics of the sensor are in a preset range or not to obtain a checking result aiming at the sensor;
and determining the first reliability of the acquisition link according to the test result.
In the above scheme, determining a packet loss rate of the ad hoc network sensor network adopted in the transmission link, determining a second reliability of the transmission link by using the packet loss rate, further includes:
Determining a network structure of an ad hoc network sensing network adopted by a transmission link;
modeling and simulating the ad hoc network sensing network according to the network structure of the ad hoc network sensing network to obtain a simulation result;
and determining the packet loss rate of the ad hoc network sensing network according to the simulation result, and determining the second reliability of the transmission link, wherein the second reliability is the difference between 100% and the packet loss rate.
In the above scheme, the calculating to obtain the third reliability of the abnormal identification link by performing correlation analysis and data verification on the road infrastructure monitoring data further comprises:
carrying out correlation analysis on road infrastructure monitoring data according to the correlation between the road type characteristics and the sensors; collecting road infrastructure monitoring data and preprocessing; determining the variables of the road infrastructure monitoring data subjected to the correlation analysis, calculating the correlation coefficient between the road infrastructure monitoring data by using the pearson correlation coefficient, and carrying out statistical significance test: interpreting and analyzing relationships between the road infrastructure monitoring data;
according to the correlation analysis result, carrying out data anomaly analysis on the road infrastructure monitoring data, determining the occurrence reason of data anomaly, and screening to obtain real anomaly data;
Comparing the data acquisition and signal processing results in a wireless mode with the data acquisition and signal processing results in a wired mode, and calculating the frequency error and the vibration mode confidence of the data acquisition and signal processing results; when the vibration mode confidence is in the confidence interval, calculating third reliability of the abnormal identification link based on the frequency error, wherein the third reliability is a difference value between 100% and the frequency error; wherein,
wherein Error is freq For frequency error, f Wired wire For wired frequency, f Wireless communication system Is a wireless frequency;
wherein, MAC i Is the vibration confidence, phi i In the form of a matrix of wired modes,to transpose the wired mode matrix, Φ j Is a wireless mode matrix>The wireless mode matrix is transposed;
when the vibration mode confidence is not in the confidence interval, calculating corresponding amplitude attenuation or phase change according to the amplitude or phase of the road infrastructure monitoring data; and according to the amplitude attenuation or the phase change of the road infrastructure monitoring data, the vibration mode confidence is improved to be within the confidence interval by adjusting the amplification factor or the phase difference of the road infrastructure monitoring data.
In the above scheme, determining the fourth reliability of the storage link according to the storage backup condition further includes:
And carrying out multiple backups on the storage links in the road infrastructure monitoring system, and determining the fourth reliability of the storage links to be 100%.
In the above scheme, based on the reliability calculation result of each functional link and the logic relationship of the road infrastructure monitoring, the reliability index of the road infrastructure monitoring system is calculated, and further includes:
according to the logic relation of the road infrastructure monitoring, determining that a plurality of functional links in the road infrastructure monitoring system are in series relation, and determining the reliability index calculation mode of the road infrastructure monitoring system based on the series relation is as follows:
P r ＝P 1 ×P 2 ×P 3 ×P 4
wherein P is r As reliability index, P 1 For the first reliability, P 2 For the second reliability, P 3 For the third reliability, P 4 A fourth reliability;
substituting the reliability calculation results of all the functional links into a reliability index calculation mode to calculate and obtain the reliability index of the road infrastructure monitoring system.
According to another aspect of the present invention, there is provided a road infrastructure monitoring system reliability analysis system, comprising: the system comprises a dividing module, an independent calculating module and a summarizing calculating module; wherein,
the dividing module is used for analyzing the operation mode of the road infrastructure monitoring system, determining the logic relation and the data processing flow of the road infrastructure monitoring process, and dividing the road infrastructure monitoring system into a plurality of functional links according to the logic relation and the data processing flow of the road infrastructure monitoring process; wherein, a plurality of functional links at least include: the device comprises an acquisition link, a transmission link, an abnormality identification link and a storage link;
The independent calculation module is used for respectively carrying out reliability calculation aiming at each functional link to obtain reliability calculation results corresponding to each functional link;
and the summarizing calculation module is used for calculating and obtaining the reliability index of the road infrastructure monitoring system based on the reliability calculation result of each functional link and the logic relation of the road infrastructure monitoring.
According to yet another aspect of the present invention, there is provided a computing device comprising: the device comprises a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface are communicated with each other through the communication bus;
the memory is configured to store at least one executable instruction that causes the processor to perform operations corresponding to the method for reliability analysis of the roadway infrastructure monitoring system as described above.
According to the technical scheme provided by the invention, the operation mode of the road infrastructure monitoring system is analyzed, the logic relation and the data processing flow of the road infrastructure monitoring process are determined, and the road infrastructure monitoring system is divided into a plurality of functional links according to the logic relation and the data processing flow of the road infrastructure monitoring process; wherein, a plurality of functional links at least include: the device comprises an acquisition link, a transmission link, an abnormality identification link and a storage link; reliability calculation is respectively carried out on each functional link, and reliability calculation results corresponding to each functional link are obtained; and calculating to obtain the reliability index of the road infrastructure monitoring system based on the reliability calculation result of each functional link and the logic relation of the road infrastructure monitoring. The reliability index of the whole road infrastructure monitoring system is obtained by functionally dividing the road infrastructure monitoring process and according to the calculated reliability of a plurality of functional links. And according to the function division, the reliability of each function is scientifically obtained from the aspects of basic characteristics of the sensor, the structure and performance of the transmission network, the identification and data storage of abnormal data and the like, the specific links are convenient to maintain, adjust and optimize in a targeted manner, and the reliability index of the quantized road infrastructure monitoring system is further comprehensively obtained, so that monitoring staff can more scientifically maintain the road infrastructure monitoring system, the reliability of the road infrastructure monitoring system is guaranteed, the accuracy of the road infrastructure monitoring data is greatly guaranteed, the safety of the road infrastructure is guaranteed, and the life and property safety of people is protected.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims thereof as well as the appended drawings.
The technical scheme of the invention is further described in detail through the drawings and the embodiments.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:
FIG. 1 shows a flow diagram of a method of reliability analysis of a roadway infrastructure monitoring system, according to one embodiment of the invention;
FIG. 2 illustrates a single sensor data transmission link schematic according to one embodiment of the invention;
FIG. 3 illustrates a schematic diagram of a sensor network data transmission link in accordance with one embodiment of the present invention;
FIG. 4 is a flow chart of a method for determining reliability of an acquisition link of a monitoring system of a road infrastructure according to an embodiment of the invention;
FIG. 5 is a flow chart of a method for determining reliability of a transmission link of a monitoring system of a road infrastructure according to an embodiment of the invention;
FIG. 6 is a flow chart of a method for determining reliability of an anomaly identification link of a monitoring system for a road infrastructure according to an embodiment of the invention;
FIG. 7 is a schematic diagram of a method of reliability analysis of a roadway infrastructure monitoring system in accordance with another embodiment of the present invention;
FIG. 8 shows a block diagram of a road infrastructure monitoring system reliability analysis system according to one embodiment of the invention;
FIG. 9 illustrates a schematic diagram of a computing device, according to an embodiment of the invention.
Detailed Description
The preferred embodiments of the present invention will be described below with reference to the accompanying drawings, it being understood that the preferred embodiments described herein are for illustration and explanation of the present invention only, and are not intended to limit the present invention.
Fig. 1 shows a flow diagram of a method for analyzing reliability of a monitoring system of a road infrastructure according to an embodiment of the invention, the method comprising the steps of:
step S101, analyzing the operation mode of the road infrastructure monitoring system, determining the logic relation and the data processing flow of the road infrastructure monitoring process, and dividing the road infrastructure monitoring system into a plurality of functional links according to the logic relation and the data processing flow of the road infrastructure monitoring process; wherein, a plurality of functional links at least include: the system comprises an acquisition link, a transmission link, an abnormality identification link and a storage link.
Preferably, since the road infrastructure monitoring process is very complex, the reliability of the road infrastructure monitoring system relates to the aspects of sensing, networking, power supply and energy supply, data transmission, storage, processing and the like, and the factors of hardware facilities such as sensors, acquisition instruments, power supply and energy supply devices and the like, networking environments, system software, data processing methods and the like related to the aspects affect the reliability of the road infrastructure monitoring system.
In the process of monitoring the road infrastructure, the transmission link of the data collected by the single sensor is shown in fig. 2, and fig. 2 shows a schematic diagram of the transmission link of the data of the single sensor according to one embodiment of the invention. The road infrastructure monitoring data collected by the sensor are subjected to data anomaly identification after passing through the transmission channel, then are subjected to data storage through the storage equipment, and finally are subjected to data analysis.
Further, the data transmission links of the entire sensor network for monitoring the road infrastructure are shown in fig. 3, and fig. 3 shows a schematic diagram of the data transmission links of the sensor network according to an embodiment of the present invention. The transmission channels through which the data collected by the sensors pass can be connected in parallel, and after the data collected by the sensors are subjected to data anomaly identification, data verification among related data is performed; after the verification is finished, multiple backups of the data are carried out through a plurality of storage devices, and finally data analysis is carried out.
The logic relationship and the data processing flow according to the road infrastructure monitoring process can be sequentially abstracted into the following steps according to the sequence before the data analysis is finally carried out: the road infrastructure monitoring system comprises a data acquisition unit, a data transmission unit, a data processing unit and a data storage unit, and is divided into an acquisition unit, a transmission unit, an abnormality identification unit and a storage unit corresponding to the road infrastructure monitoring system.
Step S102, reliability calculation is carried out on each functional link respectively, and reliability calculation results corresponding to each functional link are obtained.
Specifically, basic characteristics of a sensor are evaluated through sensor calibration, and a first reliability of an acquisition link is calculated;
determining a packet loss rate of an ad hoc network sensing network adopted by the transmission link, and determining a second reliability of the transmission link by using the packet loss rate;
carrying out correlation analysis and data verification on the road infrastructure monitoring data, and calculating to obtain third reliability of the abnormal identification link;
and determining the fourth reliability of the storage link according to the storage backup mode.
Step S103, calculating to obtain the reliability index of the road infrastructure monitoring system based on the reliability calculation result of each functional link and the logic relation of the road infrastructure monitoring.
The transmission link is a series system as a whole; in order to ensure the reliability of data transmission and data storage, the data transmission channel and the storage device are provided with alternative transmission channels and alternative storage devices, namely, the data transmission part and the storage part are both parallel systems. Therefore, the sensor network data transmission link of the road infrastructure monitoring system is a series-parallel hybrid system. And the multiple divided functional links are regarded as a series structure, and if any one of the functional links fails, the functional link becomes a failure path, so that the road infrastructure monitoring system fails. Therefore, the reliability index of the road infrastructure monitoring system is the probability of occurrence of the event that none of the functional links fails. And because the transmission link and the storage link are both in parallel connection, the transmission link can be disabled only when all transmission channels are disabled, and the storage link can be disabled only when all storage devices are disabled.
Accordingly, regarding the acquisition link, the transmission link, the anomaly identification link and the storage link as mutually incompatible events, the road infrastructure monitoring data reliable events can be expressed as:
Wherein,monitoring data-reliable events for road infrastructure, < +.>In order for the acquisition link not to fail,for the event that no failure occurs in the transmission link, +.>For the event that abnormality identification link does not fail, < +.>And the event that the storage link is not invalid is avoided.
The event that the road infrastructure monitoring data is unreliable (the road infrastructure monitoring system fails) can be expressed as:
E＝E 1 ∪E 2 ∪E 3 ∪E 4
wherein E is an unreliable event of road infrastructure monitoring data, E 1 To collect link failure event E 2 For transmission link failure event E 3 For abnormal identification of link failure event, E 4 Is a storage link failure event.
Further, the road infrastructure monitoring system reliability index may be expressed as:
wherein P is r For the reliability index, x is the event of no failure of any functional link.
Preferably, according to the logic relation of the road infrastructure monitoring, the serial relation among a plurality of functional links in the road infrastructure monitoring system is determined, and the reliability index calculation mode of the road infrastructure monitoring system is determined based on the serial relation, wherein the reliability index calculation mode is as follows:
P r ＝P 1 ×P 2 ×P 3 ×P 4
wherein P is r P is the reliability index 1 For the first reliability, P 2 For the second reliability, P 3 For the third reliability, P 4 A fourth reliability;
substituting the reliability calculation results of all the functional links into a reliability index calculation mode to calculate and obtain the reliability index of the road infrastructure monitoring system.
According to the reliability analysis method of the road infrastructure monitoring system provided by the embodiment, the operation mode of the road infrastructure monitoring system is analyzed, the logic relationship and the data processing flow of the road infrastructure monitoring process are determined, and the road infrastructure monitoring system is divided into a plurality of functional links according to the logic relationship and the data processing flow of the road infrastructure monitoring process; wherein, a plurality of functional links at least include: the device comprises an acquisition link, a transmission link, an abnormality identification link and a storage link; reliability calculation is respectively carried out on each functional link, and reliability calculation results corresponding to each functional link are obtained; and calculating to obtain the reliability index of the road infrastructure monitoring system based on the reliability calculation result of each functional link and the logic relation of the road infrastructure monitoring. The method comprises the steps of carrying out functional division on a road infrastructure monitoring process, and scientifically calculating a quantized reliability index of the whole road infrastructure monitoring system according to the calculated reliability of a plurality of functional links and combining logic relations of the functional links. And the reliability of each functional link can be obtained independently according to the functional division, the specific links are convenient to maintain, adjust and optimize in a targeted manner, the road infrastructure monitoring system is more scientifically maintained by monitoring staff, the reliability of the road infrastructure monitoring system is ensured, the accuracy of the road infrastructure monitoring data and the safety of the road infrastructure are greatly ensured, and the life and property safety of people is protected.
Fig. 4 shows a flow chart of a method for determining reliability of an acquisition link of a monitoring system of a road infrastructure according to an embodiment of the invention, as shown in fig. 4, the method comprises the following steps:
step S401, selecting a corresponding calibration method for different types of sensors.
Preferably, the types of sensors applied in the road infrastructure monitoring process include at least: a temperature and humidity sensor, a displacement sensor, a strain sensor and an acceleration sensor;
the different types of sensors have respective corresponding calibration methods, and when the reliability of the sensors used in the acquisition link is determined, the corresponding calibration method is selected for each sensor, and the method specifically comprises the following steps:
(1) Determining the type of the sensor through the model, specification or characteristics of the sensor; the model is an identifier given by a manufacturer and is used for uniquely identifying the model of the sensor, and the sensors of different models generally have different characteristics of working principles, measuring ranges, precision and the like; specification of: the specifications of the sensor are technical parameters and performance indexes of the sensor provided by a manufacturer, including but not limited to a measurement range, measurement accuracy, output signal type, working voltage, working temperature range and the like; the characteristics are as follows: the characteristics of the sensor refer to the characteristics and features of the sensor, and may include physical characteristics, working principles, signal processing modes, applicable environments and the like. For example, the optical sensor may have characteristics of a particular wavelength range and type of photosensitive element;
(2) Establishing a mapping relation between the sensor types and a calibration method: performing target feature analysis on the sensor type according to the acquired sensor type, wherein the target feature comprises a model, a specification or a feature, recursively traversing the target feature, acquiring information of the target feature obtained by recursion each time, and establishing a first set comprising the target feature and a corresponding calibration method according to the acquired information; the method comprises the steps that an ith element pair in a first set is used for storing information obtained by the jth recursion, target features in the ith element at least comprise a model obtained by the jth recursion, values in the ith element at least comprise specifications obtained by the jth recursion, values in the ith element at least comprise features obtained by the jth recursion, i=1, 2, … N, j=1, 2, … N, N is the number of recursions, and i, j and N are positive integers; generating a mapping relation according to the first set, associating each sensor type with a corresponding calibration method, and storing the mapping relation by using a hash table;
(3) By utilizing the established mapping relation, a corresponding calibration method is automatically selected, and the calibration method is realized by searching a corresponding item in a mapping relation hash table;
(4) According to the selected calibration method, corresponding calibration steps and processes are executed, and the sensor is calibrated according to the requirements of the calibration method;
Step S402, comparing the corresponding calibration method with the data acquired by the sensor, and checking whether the static characteristic and the dynamic characteristic of the sensor accord with a preset range or not to obtain a checking result aiming at the sensor.
Preferably, the basic characteristics of the sensor include a static characteristic and a dynamic characteristic, wherein the static characteristic includes at least: measurement range, linearity, hysteresis, repeatability, sensitivity, resolution, temperature stability; the dynamic characteristics include at least: step response and frequency response;
and comparing the data acquired by the sensor with the actual data to be tested, and representing the probability of whether each basic characteristic of the sensor is in a normal range or not according to the comparison result.
For example, for the acceleration sensor, the obtained acceleration data is compared with the actual acceleration data to be tested, and whether each basic characteristic of the acceleration sensor is in a normal range is represented according to the comparison result.
Step S403, determining the first reliability of the acquisition link according to the test result.
Preferably, the probability that each basic feature of the sensor is in a normal range is determined as the first reliability of the acquisition link.
Taking an acceleration sensor as an example, calculating the maximum error rate and the average error rate of acceleration data, and determining the average error rate as a first reliability:
wherein Error is max For maximum error rate, A max For the maximum acceleration obtained in a single test, A min The minimum acceleration value obtained for a single test;
wherein Error is mean For average error rate, A mean The average acceleration obtained for a single test.
According to the method, whether the basic characteristics of the sensors are in the normal range can be scientifically and pertinently judged according to the calibration mode of the sensors of different types, the reliability of the acquisition link is conveniently represented, and the reliability index of the whole road infrastructure monitoring system is further accurately judged; the method ensures that the correct calibration method corresponding to the sensor used in the acquisition link can be selected when the reliability of the sensor is determined. By determining the type, specification or characteristic of the sensor and establishing the mapping relation between the type of the sensor and the calibration method, the accuracy and reliability of calibration can be effectively improved, and the corresponding calibration method can be automatically selected by utilizing the established mapping relation, so that the risk of manually selecting an error calibration method is avoided; therefore, the data acquired by the sensor can be ensured to have higher accuracy and reliability, and a reliable basis is provided for subsequent data processing and analysis.
FIG. 5 is a flow chart of a method for determining reliability of a transmission link of a monitoring system of a road infrastructure according to an embodiment of the invention;
in the road infrastructure monitoring system, the cost of wired transmission is high, the workload is huge, meanwhile, the packet loss phenomenon basically does not exist in the wired transmission, but the packet loss phenomenon exists in the wireless transmission process, so that the transmitted road infrastructure monitoring data is incomplete, and the method is used for calculating the reliability of a transmission link aiming at the ad hoc network sensing network in the wireless transmission.
As shown in fig. 5, the method comprises the steps of:
step S501, determining the network structure of the self-organizing network sensor network adopted in the transmission link.
And step S502, carrying out modeling simulation on the ad hoc network sensing network according to the network structure of the ad hoc network sensing network to obtain a simulation result.
Preferably, based On a software simulation platform NS2 (Network Simulator-Version 2), the self-organizing network sensing network adopted by the transmission module is subjected to theoretical model simulation, and the wireless self-organizing network is subjected to the packet loss rate under three routing protocols of an On-demand plane distance vector AODV (Ad hoc On-demand Distance Vector Routing), a routing protocol Destination node sequence distance vector DSDV (Destination-Sequenced Distance Vector) and data readiness DSR (Data Set Ready).
Step S503, determining the packet loss rate of the ad hoc network sensing network according to the simulation result, and determining the second reliability of the transmission link.
Preferably, the second reliability is a difference between 100% and packet loss rate.
For example, in the simulation result, the packet loss rate in the wireless transmission process is 1%, and the second reliability of the transmission link is 99%.
According to the method, the simulation of the ad hoc network sensing network can be completed based on various routing protocols, the packet loss rate of the transmission link is accurately obtained according to the simulation result, the reliability of the transmission link is calculated, and the reliability index of the whole road infrastructure monitoring system is further accurately judged.
Fig. 6 is a flow chart of a method for determining reliability of an anomaly identification link of a monitoring system for road infrastructure according to an embodiment of the invention, as shown in fig. 6, the method includes the following steps:
step S601, carrying out correlation analysis on road infrastructure monitoring data according to the correlation between the road type characteristics and the sensors; correlation analysis of road infrastructure monitoring data, comprising the steps of:
(1) Collecting road infrastructure monitoring data, and performing data cleaning, abnormal value removal and missing value filling pretreatment; determining road infrastructure monitoring data variables for correlation analysis, wherein the variables comprise environmental data such as atmospheric temperature, humidity and the like, action data such as vehicle axle weight, vehicle speed and the like, and structural response data such as acceleration, displacement, strain and the like; using a scatter plot to visualize the collected road infrastructure monitoring data to observe the distribution and trend of the data;
(2) Calculating a correlation coefficient: calculating a correlation coefficient between road infrastructure monitoring data by using the pearson correlation coefficient, wherein the correlation coefficient measures the strength and the direction of a linear relation between two variables, the value range is-1 to 1, the value range is close to-1, the value range is positive, and the value range is close to 0, the value range is not relevant;
(3) And (3) checking statistical significance: carrying out statistical significance test on the correlation coefficient to determine whether the correlation coefficient has statistical significance, and explaining and analyzing the relation between the road infrastructure monitoring data according to the value of the correlation coefficient and the significance test result; for example, if the correlation coefficient is positive and significant, indicating that two variables are in positive correlation, inferring that an increase in one variable may result in an increase in the other variable.
(4) Repeating the step (2) -the step (3) if a plurality of road infrastructure monitoring data variables need to be subjected to correlation analysis;
preferably, the road infrastructure type includes: bridges, tunnels, slopes and the like, and different road infrastructure types have respective road type characteristics; based on the characteristics of the road infrastructure type, the road infrastructure monitoring data acquired by the sensors at the determined specific positions are in accordance with the structural or environmental rules. Further, in the road infrastructure monitoring data, judging whether the abnormal data acquired by the sensors of the same type accords with a structural or environmental rule, and if the abnormal data does not accord with the structural or environmental rule, judging that the corresponding sensor fails; if the abnormal data is in accordance with the data, it is determined that the cause of the abnormal data is not sensor failure, but structural damage exists.
Taking a bridge as an example, the bridge has the characteristic of symmetry, the road infrastructure monitoring data acquired by the sensors at the symmetrical positions of the bridge are equal or have symmetry, and if the road infrastructure monitoring data acquired by the sensors at the two symmetrical positions are abnormal but have symmetry, the data abnormality is judged not to be caused by sensor failure, but structural damage exists at the symmetrical positions.
The association between the sensors includes: environmental relevance, structural relevance, location relevance, time relevance, etc. The environment relevance refers to that the sensor relevance in the same external environment is larger; structural relevance refers to the fact that sensors located in different subsystems are different in relevance; the position relevance refers to stronger relevance of the sensors on the same structural body; the time relevance refers to stronger relevance of the sensors among the measuring points at the same time and weaker relevance of the sensors among the measuring points at different times.
Step S602, according to the correlation analysis result, carrying out data anomaly analysis on the road infrastructure monitoring data, determining the occurrence reason of data anomaly, and screening to obtain real anomaly data.
Preferably, according to the correlation analysis result, the abnormal data in the road infrastructure monitoring data is analyzed, abnormal data which is not caused by the sensor failure is removed, and real abnormal data is obtained, wherein the real abnormal data is the abnormal data caused by the sensor failure.
Step S603, comparing the data acquisition and signal processing result in a wireless mode with the data acquisition and signal processing result in a wired mode, and calculating the frequency error and the vibration mode confidence of the data acquisition and signal processing result.
Preferably, the modal identification effect is described in terms of frequency error and mode shape confidence, wherein,
wherein Error is freq For frequency error, f Wired wire For wired frequency, f Wireless communication system Is a wireless frequency;
wherein, MAC i Is the vibration confidence, phi i In the form of a matrix of wired modes,to transpose the wired mode matrix, Φ j Is a wireless mode matrix>To transpose the wireless modality matrix.
For example, regarding the strain signal, the front third-order vertical frequency and mode shape mode of the dynamic strain signal identification test model acquired by the DASP (Data Acquisition and signal processing, data Acquisition & Signal Processing) in a wireless manner and the corresponding mode shape mode pair identified by the dynamic strain signal acquired by the DASP in a wired manner are shown in table 1 and table 2; wherein, table 1 is the frequency error identified by the strain signal; table 2 is the vibration mode confidence of strain signal identification;
TABLE 1 frequency error and vibration mode confidence of Strain Signal identification
| Frequency order | 1 st order vertical frequency | 2 nd order vertical frequency | 3 rd order vertical frequency |
| Frequency Error (Error) freq ) | 2.95％ | 0.45％ | 0.52％ |
| Vibration mode confidence (MAC) | 0.972 | 0.985 | 0.984 |
Where MAC is the confidence (Modal Assurance Criterion) between the wired and wireless mode shapes, i.e., the mode confidence.
Step S604, judging whether the vibration mode confidence is in the confidence interval.
Specifically, if the vibration mode confidence is within the confidence interval, step S605 is executed; if not, step S606 is performed.
Preferably, the confidence interval is 95%.
Step S605 calculates a third reliability of the anomaly identification link based on the frequency error, the third reliability being a difference between 100% and the frequency error.
As described above, the vibration mode confidence of the 1 st order vertical vibration mode is 97.2%, greater than 95%, and is within the preset confidence interval, and therefore, the third reliability is calculated by using the maximum value of the frequency error, that is, the third reliability is 100% -2.95% =97.05%.
Step S606, corresponding amplitude attenuation or phase change is calculated according to the amplitude or phase of the road infrastructure monitoring data; and according to the amplitude attenuation or the phase change of the road infrastructure monitoring data, the vibration mode confidence is improved to be within the confidence interval by adjusting the amplification factor or the phase difference of the road infrastructure monitoring data.
According to the method, the abnormal data caused by sensor failure can be screened out from the abnormal data based on the correlation of the monitoring data, the accuracy of the data is improved, the monitoring data is further checked, the third reliability of an abnormal identification link is scientifically calculated according to the frequency error and the vibration mode confidence, and the reliability index of the whole road infrastructure monitoring system is further accurately judged; revealing the association between the variables: the correlation analysis helps to know the relation among monitoring data of different road infrastructures, such as the relation among data of atmospheric temperature, humidity, vehicle axle weight, vehicle speed, acceleration, displacement, strain and the like, and helps to understand the comprehensive condition of the road infrastructures, so that maintenance management and decision making are better carried out; prediction and model establishment: correlation analysis may provide a basis for building a predictive model. If strong correlation exists among the monitoring data of some road infrastructures, the safety conditions of the future road infrastructures are predicted by utilizing the correlation, and reference basis is provided for maintenance management and scientific decision; guiding decisions and optimizing resource allocation: correlation analysis may help to understand causal relationships between the road infrastructure monitoring data. By analysing the correlation coefficients and the significance test results, it can be inferred that an increase in one variable may lead to an increase or decrease in another variable, which is important to the road infrastructure manager, from which decisions can be made and resource allocation optimized; and (3) data quality control: before correlation analysis, the data is subjected to pretreatment steps such as cleaning, outlier removal, missing value filling and the like, so that the accuracy and reliability of analysis are improved, the problem of data quality is found, and the data acquisition and processing method is further improved. In summary, correlation analysis has important implications in the study and application of road infrastructure monitoring data, providing insight and decision support regarding the operational condition of the road infrastructure. In addition, multiple backups are made for the storage links in the road infrastructure monitoring system, and the fourth reliability of the storage links is determined to be 100%.
Fig. 7 shows a schematic diagram of a reliability analysis method of a road infrastructure monitoring system according to another embodiment of the present invention, as shown in fig. 7, wherein,
firstly, sensing road infrastructure monitoring data, performing unit calibration on wireless sensing data, and completing monitoring data calibration and reliability analysis based on a low-power-consumption low-pass filtering technology; then, completing data transmission and networking by an ad hoc network sensing network technology; then, analyzing and processing the collected data by a data anomaly identification method and a monitoring data mutual verification method; and finally, combining the reliability analysis performed in the previous step to obtain the reliability of the road infrastructure monitoring system.
Fig. 8 shows a block diagram of a road infrastructure monitoring system reliability analysis system according to an embodiment of the present invention, as shown in fig. 8, including: a dividing module 801, an independent calculating module 802, and a summary calculating module 803; wherein,
the dividing module 801 is configured to analyze an operation mode of the road infrastructure monitoring system, determine a logic relationship and a data processing flow of the road infrastructure monitoring process, and divide the road infrastructure monitoring system into a plurality of functional links according to the logic relationship and the data processing flow of the road infrastructure monitoring process; wherein, a plurality of functional links at least include: the system comprises an acquisition link, a transmission link, an abnormality identification link and a storage link.
The independent calculation module 802 is configured to perform reliability calculation for each functional link, so as to obtain reliability calculation results corresponding to each functional link.
In particular, the independent calculation module 802, further for,
evaluating the basic characteristics of the sensor through sensor calibration, and calculating to obtain the first reliability of the acquisition link; determining a packet loss rate of an ad hoc network sensing network adopted by the transmission link, and determining a second reliability of the transmission link by using the packet loss rate; carrying out correlation analysis and data verification on the road infrastructure monitoring data, and calculating to obtain third reliability of the abnormal identification link; and determining the fourth reliability of the storage link according to the storage backup condition.
Specifically, in the independent calculation module 802, the basic characteristics of the sensor include static characteristics and dynamic characteristics; wherein the static characteristics include at least: measurement range, linearity, hysteresis, repeatability, sensitivity, resolution and temperature stability; the dynamic characteristics include at least: step response and frequency response; the independent calculation module 802 is further configured to, in response to a request from a user,
selecting corresponding calibration methods for different types of sensors; comparing the static characteristics and the dynamic characteristics of the sensor with the data acquired by the sensor according to the corresponding calibration method, and checking whether the static characteristics and the dynamic characteristics of the sensor are in a preset range or not to obtain a checking result aiming at the sensor; and determining the first reliability of the acquisition link according to the test result.
In particular, the independent calculation module 802, further for,
determining a network structure of an ad hoc network sensing network adopted by a transmission link; modeling and simulating the ad hoc network sensing network according to the network structure of the ad hoc network sensing network to obtain a simulation result; and determining the packet loss rate of the ad hoc network sensing network according to the simulation result, and determining the second reliability of the transmission link, wherein the second reliability is the difference between 100% and the packet loss rate.
In particular, the independent calculation module 802, further for,
carrying out correlation analysis on road infrastructure monitoring data according to the correlation between the road type characteristics and the sensors;
according to the correlation analysis result, carrying out data anomaly analysis on the road infrastructure monitoring data, determining the occurrence reason of data anomaly, and screening to obtain real anomaly data;
comparing the data acquisition and signal processing results in a wireless mode with the data acquisition and signal processing results in a wired mode, and calculating the frequency error and the vibration mode confidence of the data acquisition and signal processing results; when the vibration mode confidence is in the confidence interval, calculating third reliability of the abnormal identification link based on the frequency error, wherein the third reliability is a difference value between 100% and the frequency error; wherein,
Wherein Error is freq For frequency error, f Wired wire For wired frequency, f Wireless communication system Is a wireless frequency;
wherein, MAC i Is the vibration confidence, phi i In the form of a matrix of wired modes,to transpose the wired mode matrix, Φ j Is a wireless mode matrix>The wireless mode matrix is transposed;
when the vibration mode confidence is not in the confidence interval, calculating corresponding amplitude attenuation or phase change according to the amplitude or phase of the road infrastructure monitoring data; and according to the amplitude attenuation or the phase change of the road infrastructure monitoring data, the vibration mode confidence is improved to be within the confidence interval by adjusting the amplification factor or the phase difference of the road infrastructure monitoring data.
In particular, the independent calculation module 802, further for,
and carrying out multiple backups on the storage links in the road infrastructure monitoring system, and determining the fourth reliability of the storage links to be 100%.
The summary calculation module 803 is configured to calculate, based on the reliability calculation result of each functional link and the logic relationship of the road infrastructure monitoring, a reliability index of the road infrastructure monitoring system.
In particular, the summary calculation module 803 is further configured to,
according to the logic relation of the road infrastructure monitoring, determining that a plurality of functional links in the road infrastructure monitoring system are in series relation, and determining the reliability index calculation mode of the road infrastructure monitoring system based on the series relation is as follows:
P r ＝P 1 ×P 2 ×P 3 ×P 4
Wherein P is r P is the reliability index 1 For the first reliability, P 2 For the second reliability, P 3 For the third reliability, P 4 A fourth reliability;
substituting the reliability calculation results of all the functional links into a reliability index calculation mode to calculate and obtain the reliability index of the road infrastructure monitoring system.
According to the reliability analysis system of the road infrastructure monitoring system provided by the embodiment, the operation mode of the road infrastructure monitoring system is analyzed, the logic relationship and the data processing flow of the road infrastructure monitoring process are determined, and the road infrastructure monitoring system is divided into a plurality of functional links according to the logic relationship and the data processing flow of the road infrastructure monitoring process; wherein, a plurality of functional links at least include: the device comprises an acquisition link, a transmission link, an abnormality identification link and a storage link; reliability calculation is respectively carried out on each functional link, and reliability calculation results corresponding to each functional link are obtained; and calculating to obtain the reliability index of the road infrastructure monitoring system based on the reliability calculation result of each functional link and the logic relation of the road infrastructure monitoring. By the reliability analysis system of the road infrastructure monitoring system provided by the embodiment, the road infrastructure monitoring process is functionally divided, and the reliability index of the whole road infrastructure monitoring system is obtained according to the reliability of a plurality of functional links obtained through calculation. According to the function division, the reliability of each function is scientifically obtained from the aspects of basic characteristics of the sensors in the acquisition links, the structure and performance of the transmission network, the identification and data storage of abnormal data and the like, the specific links are convenient to maintain, adjust and optimize in a targeted manner, the reliability index of the road infrastructure monitoring system is further comprehensively obtained, monitoring staff can more scientifically maintain the road infrastructure monitoring system, the reliability of the road infrastructure monitoring system is guaranteed, the accuracy of the road infrastructure monitoring data is greatly guaranteed, the safety of the road infrastructure and the life and property safety of people are greatly guaranteed.
The invention also provides a nonvolatile computer storage medium, wherein the computer storage medium stores at least one executable instruction, and the executable instruction can execute the reliability analysis method of the road infrastructure monitoring system in any method embodiment.
FIG. 9 illustrates a schematic diagram of a computing device, according to an embodiment of the invention, the particular embodiment of the invention not being limited to a particular implementation of the computing device.
As shown in fig. 9, the computing device may include: a processor 902, a communication interface (Communications Interface), a memory 906, and a communication bus 908.
Wherein:
processor 902, communication interface 904, and memory 906 communicate with each other via a communication bus 908.
A communication interface 904 for communicating with network elements of other devices, such as clients or other servers.
The processor 902 is configured to execute the program 910, and may specifically perform relevant steps in the above-described embodiments of the reliability analysis method of the road infrastructure monitoring system.
In particular, the program 910 may include program code including computer operating instructions.
The processor 902 may be a central processing unit, CPU, or a specific integrated circuit ASIC (Applica tion Specific Integrated Circuit), or one or more integrated circuits configured to implement embodiments of the present invention. The one or more processors included by the computing device may be the same type of processor, such as one or more CPUs; but may also be different types of processors such as one or more CPUs and one or more ASICs.
A memory 906 for storing a program 910. Memory 906 may comprise high-speed RAM memory or may also include non-volatile memory (non-volatile memory), such as at least one disk memory.
The program 910 may be specifically configured to cause the processor 902 to perform the method of analyzing reliability of the road infrastructure monitoring system in any of the method embodiments described above. The specific implementation of each step in the procedure 910 may refer to corresponding descriptions in the corresponding steps and units in the above embodiments of the reliability analysis method for the road infrastructure monitoring system, which are not described herein in detail. It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the apparatus and modules described above may refer to corresponding procedure descriptions in the foregoing method embodiments, which are not repeated herein.
The algorithms and displays presented herein are not inherently related to any particular computer, virtual system, or other apparatus. Various general-purpose systems may also be used with the teachings herein. The required structure for a construction of such a system is apparent from the description above. In addition, the present invention is not directed to any particular programming language. It will be appreciated that the teachings of the present invention described herein may be implemented in a variety of programming languages, and the above description of specific languages is provided for disclosure of enablement and best mode of the present invention.
In the description provided herein, numerous specific details are set forth. However, it is understood that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description.
Similarly, it should be appreciated that in the foregoing description of exemplary embodiments of the invention, various features of the invention are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure and aiding in the understanding of one or more of the various inventive aspects. However, the disclosed method should not be construed as reflecting the intention that: i.e., the claimed invention requires more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single foregoing disclosed embodiment. Thus, the claims following the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of this invention.
Those skilled in the art will appreciate that the modules in the apparatus of the embodiments may be adaptively changed and disposed in one or more apparatuses different from the embodiments. The modules or units or components of the embodiments may be combined into one module or unit or component and, furthermore, they may be divided into a plurality of sub-modules or sub-units or sub-components. Any combination of all features disclosed in this specification (including any accompanying claims, abstract and drawings), and all of the processes or units of any method or apparatus so disclosed, may be used in combination, except insofar as at least some of such features and/or processes or units are mutually exclusive. Each feature disclosed in this specification (including any accompanying claims, abstract and drawings), may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise.
Furthermore, those skilled in the art will appreciate that while some embodiments described herein include some features but not others included in other embodiments, combinations of features of different embodiments are meant to be within the scope of the invention and form different embodiments. For example, in the claims, any of the claimed embodiments may be used in any combination.
Various component embodiments of the invention may be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. Those skilled in the art will appreciate that some or all of the functions of some or all of the components in accordance with embodiments of the present invention may be implemented in practice using a microprocessor or Digital Signal Processor (DSP). The present invention can also be implemented as an apparatus or device program (e.g., a computer program and a computer program product) for performing a portion or all of the methods described herein. Such a program embodying the present invention may be stored on a computer readable medium, or may have the form of one or more signals. Such signals may be downloaded from an internet website, provided on a carrier signal, or provided in any other form.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (10)
1. A method for analyzing reliability of a monitoring system of a road infrastructure, comprising:
analyzing the operation mode of the road infrastructure monitoring system, determining the logic relation and the data processing flow of the road infrastructure monitoring process, and dividing the road infrastructure monitoring system into a plurality of functional links according to the logic relation and the data processing flow of the road infrastructure monitoring process;
reliability calculation is respectively carried out on each functional link, and reliability calculation results corresponding to each functional link are obtained;
and calculating to obtain the reliability index of the road infrastructure monitoring system based on the reliability calculation result of each functional link and the logic relation of the road infrastructure monitoring.
2. The method of claim 1, wherein the plurality of functional links comprises at least: the system comprises an acquisition link, a transmission link, an abnormality identification link and a storage link.
3. The method for analyzing the reliability of a road infrastructure monitoring system according to claim 1, wherein the reliability calculation is performed for each functional link, respectively, to obtain a reliability calculation result corresponding to each functional link, further comprising:
evaluating the basic characteristics of the sensor through sensor calibration, and calculating to obtain the first reliability of the acquisition link;
determining a packet loss rate of an ad hoc network sensing network adopted by the transmission link, and determining a second reliability of the transmission link by using the packet loss rate;
carrying out correlation analysis and data verification on the road infrastructure monitoring data, and calculating to obtain third reliability of the abnormal identification link;
and determining the fourth reliability of the storage link according to the storage backup mode.
4. A method of reliability analysis of a road infrastructure monitoring system according to claim 3 wherein the basic characteristics of the sensor include static characteristics and dynamic characteristics; wherein the static characteristics include at least: measurement range, linearity, hysteresis, repeatability, sensitivity, resolution and temperature stability; the dynamic characteristics include at least: step response and frequency response;
the basic characteristics of the sensor are evaluated through sensor calibration, and the first reliability of the acquisition link is calculated, and the method further comprises the following steps:
Selecting corresponding calibration methods for different types of sensors, performing target feature analysis on the sensor types according to the acquired sensor types, recursively traversing the target features to acquire information of the target features obtained by each recursion, and establishing a first set comprising the target features and the corresponding calibration methods according to the acquired information; generating a mapping relation according to the first set, associating each sensor type with a corresponding calibration method, and storing the mapping relation by using a hash table; by utilizing the established mapping relation, a corresponding calibration method is automatically selected, and the calibration method is realized by searching a corresponding item in a mapping relation hash table; comparing the static characteristics and the dynamic characteristics of the sensor with the data acquired by the sensor according to the corresponding calibration method, and checking whether the static characteristics and the dynamic characteristics of the sensor are in a preset range or not to obtain a checking result aiming at the sensor;
and determining the first reliability of the acquisition link according to the test result.
5. The method for analyzing reliability of a road infrastructure monitoring system according to claim 3, wherein determining a packet loss rate of an ad hoc network sensor network used in the transmission link, determining a second reliability of the transmission link using the packet loss rate, further comprises:
Determining a network structure of an ad hoc network sensing network adopted by a transmission link;
modeling and simulating the ad hoc network sensing network according to the network structure of the ad hoc network sensing network to obtain a simulation result;
and determining the packet loss rate of the ad hoc network sensing network according to the simulation result, and determining the second reliability of the transmission link, wherein the second reliability is the difference between 100% and the packet loss rate.
6. The method for analyzing reliability of a road infrastructure monitoring system according to claim 3, wherein the third reliability of the anomaly identification link is calculated by performing correlation analysis and data verification on the road infrastructure monitoring data, further comprising:
carrying out correlation analysis on road infrastructure monitoring data according to the correlation between the road type characteristics and the sensors; collecting road infrastructure monitoring data and preprocessing; determining the variables of the road infrastructure monitoring data subjected to the correlation analysis, calculating the correlation coefficient between the road infrastructure monitoring data by using the pearson correlation coefficient, and carrying out statistical significance test: interpreting and analyzing relationships between the road infrastructure monitoring data; according to the correlation analysis result, carrying out data anomaly analysis on the road infrastructure monitoring data, determining the occurrence reason of data anomaly, and screening to obtain real anomaly data;
Comparing the data acquisition and signal processing results in a wireless mode with the data acquisition and signal processing results in a wired mode, and calculating the frequency error and the vibration mode confidence of the data acquisition and signal processing results; when the vibration mode confidence is in the confidence interval, calculating third reliability of the abnormal identification link based on the frequency error, wherein the third reliability is a difference value between 100% and the frequency error; wherein,
wherein Error is freq For frequency error, f Wired wire For wired frequency, f Wireless communication system Is a wireless frequency;
wherein, MAC i Is the vibration confidence, phi i In the form of a matrix of wired modes,to transpose the wired mode matrix, Φ j Is a wireless mode matrix>The wireless mode matrix is transposed;
when the vibration mode confidence is not in the confidence interval, calculating corresponding amplitude attenuation or phase change according to the amplitude or phase of the road infrastructure monitoring data; and according to the amplitude attenuation or the phase change of the road infrastructure monitoring data, the vibration mode confidence is improved to be within the confidence interval by adjusting the amplification factor or the phase difference of the road infrastructure monitoring data.
7. The method for analyzing reliability of a road infrastructure monitoring system according to claim 3, wherein determining the fourth reliability of the storage link according to the storage backup condition, further comprises:
And carrying out multiple backups on the storage links in the road infrastructure monitoring system, and determining the fourth reliability of the storage links to be 100%.
8. The reliability analysis method of the road infrastructure monitoring system according to claim 1, wherein the reliability index of the road infrastructure monitoring system is calculated based on the reliability calculation result of each functional link and the logic relationship of the road infrastructure monitoring, further comprising:
according to the logic relation of the road infrastructure monitoring, determining that a plurality of functional links in the road infrastructure monitoring system are in series relation, and determining the reliability index calculation mode of the road infrastructure monitoring system based on the series relation is as follows:
P r ＝P 1 ×P 2 ×P 3 ×P 4
wherein P is r As reliability index, P 1 For the first reliability, P 2 For the second reliability, P 3 For the third reliability, P 4 A fourth reliability;
substituting the reliability calculation results of all the functional links into a reliability index calculation mode to calculate and obtain the reliability index of the road infrastructure monitoring system.
9. A system for analyzing reliability of a monitoring system for a road infrastructure, comprising: the system comprises a dividing module, an independent calculating module and a summarizing calculating module; wherein,
The dividing module is used for analyzing the operation mode of the road infrastructure monitoring system, determining the logic relation and the data processing flow of the road infrastructure monitoring process, and dividing the road infrastructure monitoring system into a plurality of functional links according to the logic relation and the data processing flow of the road infrastructure monitoring process; wherein, a plurality of functional links at least include: the device comprises an acquisition link, a transmission link, an abnormality identification link and a storage link;
the independent calculation module is used for respectively carrying out reliability calculation aiming at each functional link to obtain reliability calculation results corresponding to each functional link;
and the summarizing calculation module is used for calculating and obtaining the reliability index of the road infrastructure monitoring system based on the reliability calculation result of each functional link and the logic relation of the road infrastructure monitoring.
10. A computing device, comprising: the device comprises a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface are communicated with each other through the communication bus;
the memory is configured to store at least one executable instruction that causes the processor to perform operations corresponding to the method of reliability analysis of the road infrastructure monitoring system of any of claims 1-8.
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