CN114279554A - Multi-place synchronous self-adaptive performance testing method and system of low-temperature flutter sensor - Google Patents
Multi-place synchronous self-adaptive performance testing method and system of low-temperature flutter sensor Download PDFInfo
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Abstract
The utility model provides a method and a system for testing the multi-place synchronous self-adaptive performance of a low-temperature flutter sensor, which comprises the steps of synchronously acquiring the position environment information of the multi-place flutter sensor; simulating different environments according to the position environment information data of the vibration sensor, and testing the performance of the vibration sensor in different environments; analyzing the performance of the vibration sensor in different environments, and determining the influence relationship of different environmental factors on the performance of the vibration sensor; predicting the performance aging condition of the vibration sensor according to the influence relationship of different environmental factors on the performance of the vibration sensor; and stripping off the entanglement influence of the multiple environmental factors on the performance of the vibration sensor by using a variable control method, and qualitatively and quantitatively analyzing the influence degree of the single environmental factor on the performance of the vibration sensor.
Description
Technical Field
The disclosure belongs to the technical field of power measurement, and particularly relates to a multi-place synchronous self-adaptive performance testing method and system of a low-temperature chatter sensor.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
The sensor is a data source of modern society, with the release of 'notice about giving 2020 national economy of autonomous region and social development plan', the inner Mongolia accelerates the construction of the smart grid, and the sensor has wider application in low-temperature areas such as the inner Mongolia, especially the flutter sensor, and has wide application in the construction, use and maintenance of the smart grid. The inner Mongolia is in a low-temperature environment all the year round, and the lowest temperature recorded historically measured in the inner Mongolia root river city is-58 ℃ through analyzing climate data from establishment of new China, and the lowest temperature all the year round can reach below-50 ℃. Meanwhile, due to the fact that the air saturation vapor pressures at different temperatures are different, the severe temperature change of the inner Mongolia leads to the severe change of the air saturation vapor pressure, and the entanglement change of the relative humidity and the temperature is finally influenced. Meanwhile, the inner Mongolia amplitude member is wide, the altitude of each region is greatly different, and the pressure influencing the performance reduction of the vibration sensor is different from the solar radiation.
The application scene of the vibration sensor is complicated due to various conditions, and the performance of the vibration sensor is affected to a certain extent due to entanglement among various factors, so that the performance of the vibration sensor is attenuated in a low-temperature environment.
Disclosure of Invention
In order to solve the problems, the disclosure provides a method and a system for testing multi-place synchronous self-adaptive performance of a low-temperature flutter sensor, wherein the entanglement influence of multi-environment factors on the performance of the flutter sensor is stripped by using a variable control method, and the influence degree of a single environment factor on the performance of the flutter sensor is qualitatively and quantitatively analyzed; on the basis, the invention also provides a performance prediction model of the vibration sensor, and the aging degree of the vibration sensor in use can be predicted by training the neural network model through test data.
According to some embodiments, a first aspect of the present disclosure provides a method for testing multi-ground synchronous adaptive performance of a low-temperature flutter sensor, which adopts the following technical solutions:
a multi-place synchronous self-adaptive performance testing method for a low-temperature flutter sensor comprises the following steps:
synchronously acquiring position environment information of a plurality of vibration sensors;
simulating different environmental factors according to the position environmental information data of the vibration sensor, and testing the performance of the vibration sensor under different environmental factors;
analyzing the performance of the vibration sensor under different environmental factors, and determining the influence relationship of the different environmental factors on the performance of the vibration sensor;
and predicting the performance aging degree of the vibration sensor according to the influence relationship of different environmental factors on the performance of the vibration sensor.
According to some embodiments, a second aspect of the present disclosure provides a multi-ground synchronous adaptive performance testing system of a low-temperature flutter sensor, which adopts the following technical solutions:
a multi-place synchronous adaptive performance testing system for a cryo-tremor sensor, comprising:
the data acquisition module is configured to synchronously acquire position environment information of the multi-vibration sensor;
the simulation test module is configured to simulate different environmental factors according to the position environmental information data of the vibration sensor and test the performance of the vibration sensor under different environmental factors;
the data processing module is configured to analyze the performance of the vibration sensor under different environmental factors and determine the influence relation of the different environmental factors on the performance of the vibration sensor;
and the aging prediction module is configured to predict the performance aging degree of the vibration sensor according to the influence relation of different environmental factors on the performance of the vibration sensor.
According to some embodiments, a third aspect of the present disclosure provides a computer-readable storage medium.
A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method for multiple simultaneous adaptive performance testing of a cryo-tremor sensor according to the first aspect above.
According to some embodiments, a fourth aspect of the present disclosure provides a computer device.
A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor when executing the program implementing the steps in the method for multiple simultaneous adaptive performance testing of a cryo-tremor sensor according to the first aspect.
Compared with the prior art, the beneficial effect of this disclosure is:
the method comprises the steps of designing a multi-place synchronous single variable testing method for eliminating variable entanglement, predicting the aging condition of a sensor by utilizing neural network self-adaptation, widely acquiring data such as temperature and humidity of a using scene of a flutter sensor by utilizing a low-cost environmental data acquisition module, and summarizing the data to a testing laboratory by utilizing a network high-speed link; the laboratory processes the environmental data, peels off the entanglement in the environmental conditions, and qualitatively and quantitatively analyzes the factors influencing the performance of the flutter sensor.
The method and the device train the neural network model by using the test data, so that the model has good prediction capability on the aging condition of the tremor sensor. Compared with the existing testing method, the method can simultaneously and synchronously test a plurality of areas, reduces the transportation cost of personnel and equipment, utilizes sufficient testing conditions of a laboratory, can strip the mutual entanglement relation of environmental factors, provides sufficient data for establishing an aging model of the vibration sensor, and has good effects on performance testing of the vibration sensor at low temperature and prediction of the aging condition.
Drawings
The accompanying drawings, which are included to provide a further understanding of the disclosure, illustrate embodiments of the disclosure and together with the description serve to explain the disclosure and are not to limit the disclosure.
FIG. 1 is a flow chart of a method for testing the multi-place synchronous adaptive performance of a low-temperature flutter sensor according to a first embodiment of the disclosure;
FIG. 2 is a first level layout of a data collection module in an embodiment of the disclosure;
FIG. 3 is a second level layout of a data acquisition module in an embodiment of the present disclosure;
FIG. 4 is a third level layout of a data acquisition module in an embodiment of the present disclosure;
FIG. 5 is an overall layout of a data acquisition module in an embodiment of the disclosure;
FIG. 6 is a diagram of a manner in which a data acquisition module is installed in an embodiment of the present disclosure;
FIG. 7 is a diagram of a time slot setting relationship in an embodiment of the present disclosure;
FIG. 8 is a block diagram of the internal structure of the experimental box in the embodiment of the present disclosure;
FIG. 9 is a block diagram of an AHP algorithm in an embodiment of the present disclosure;
FIG. 10 is a schematic diagram of a neural network in an embodiment of the present disclosure;
FIG. 11 is a 24-hour internal meteorological data of a place in an embodiment of the present disclosure;
FIG. 12 is a graph of sensor performance degradation within 24 hours of a location in an embodiment of the disclosure;
FIG. 13 is a graph comparing the results of the predictive model with actual values in an embodiment of the disclosure.
The specific implementation mode is as follows:
the present disclosure is further described with reference to the following drawings and examples.
It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the disclosure. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments according to the present disclosure. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, and it should be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof, unless the context clearly indicates otherwise.
In the present disclosure, terms such as "upper", "lower", "left", "right", "front", "rear", "vertical", "horizontal", "side", "bottom", and the like indicate orientations or positional relationships based on those shown in the drawings, and are only relational terms determined for convenience in describing structural relationships of the parts or elements of the present disclosure, and do not refer to any parts or elements of the present disclosure, and are not to be construed as limiting the present disclosure.
The embodiments and features of the embodiments in the present disclosure may be combined with each other without conflict.
Example one
As shown in fig. 1 to 13, the present embodiment provides a method for testing multi-synchronous adaptive performance of a low-temperature flutter sensor, and the present embodiment is illustrated by applying the method to a server, it is understood that the method may also be applied to a terminal, and may also be applied to a system including the terminal and the server, and is implemented by interaction between the terminal and the server. The server may be an independent physical server, a server cluster or a distributed system formed by a plurality of physical servers, or a cloud server providing basic cloud computing services such as a cloud service, a cloud database, cloud computing, a cloud function, cloud storage, a network server, cloud communication, middleware service, a domain name service, a security service CDN, a big data and artificial intelligence platform, and the like. The terminal may be, but is not limited to, a smart phone, a tablet computer, a laptop computer, a desktop computer, a smart speaker, a smart watch, and the like. The terminal and the server may be directly or indirectly connected through wired or wireless communication, and the disclosure is not limited thereto. In this embodiment, the method includes the steps of:
step S100: synchronously acquiring position environment information of a plurality of vibration sensors;
step S200: simulating different environmental factors according to the position environmental information data of the vibration sensor, and testing the performance of the vibration sensor under different environmental factors;
step S300: analyzing the performance of the vibration sensor under different environmental factors, and determining the influence relationship of the different environmental factors on the performance of the vibration sensor;
step S400: and predicting the performance aging degree of the vibration sensor according to the influence relationship of different environmental factors on the performance of the vibration sensor.
In step S100, the position environment information of the multiple tremor sensors is synchronously obtained, specifically:
an original environment data acquisition module is designed according to the size of a deployed position space of the vibration sensor, the environment data acquisition module is deployed, communication of the environment data acquisition module is normal through debugging equipment, and position environment information of the multiple vibration sensors is synchronously acquired.
The external usable space size of the installation position of the vibration sensor needs to be determined, and the communication and power supply mode of the original environment data acquisition module is determined by combining the network coverage condition and the power supply condition, wherein the wireless three-layer design mentioned above is taken as an example. The first layer, as shown in fig. 2, contains primarily cells. The second layer is shown in fig. 3 and mainly includes a main control chip, an NB-IoT module and a matching antenna. The third layer is shown in fig. 4 and is a temperature and humidity sensor, and the temperature and humidity sensor is in contact with the outside to ensure the accuracy of the collected data. The overall structure is shown in fig. 5.
As shown in fig. 6, the data acquisition module and the tremor sensor need to be installed at the same position and angle. After the installation and fixation, technicians need to check the communication condition of the equipment and the laboratory, and the communication between the equipment and the laboratory is ensured. After the installation is finished, a vibration table needs to be installed beside the original environment data acquisition module, the calibrated vibration sensor A with the determined model is tested, and the test result is recorded.
In step S200, simulating different environmental factors according to the position environmental information data of the tremor sensor, and testing the operation data of the tremor sensor under different environmental factors, including:
building a simulated environment test box according to the position environment information of the flutter sensor;
the performance of the flutter sensor under different environmental factors is respectively tested by controlling the sensors with different environmental factors in the test box.
A data center needs to be set in a laboratory, and a receiver receives and stores data of a plurality of original environment data acquisition modules by setting time slots, wherein the time slots are set as shown in fig. 7. Meanwhile, in order to analyze the influence degree of each environmental element, a plurality of simulation boxes need to be arranged in a laboratory, so that variables are controlled, and the environmental variables are free from entanglement, and the four factors of temperature, humidity, pressure and illumination are taken as examples, and the arrangement of the test boxes is shown in fig. 8.
Specifically, before an experiment is carried out, a vibration sensor B which is used for placing the vibration sensor A in the same type and calibration mode in a field environment is required to be installed in a test box provided with a temperature and humidity controller, a pressure regulator and a solar radiation generator, the vibration sensor B is used with a vibration table which is the same as that of the field, the same excitation is applied to the vibration sensor B, if the test results of the sensor A and the sensor B are the same, the data acquisition module placed on the field is considered to work normally, and the acquired data are available.
In order to test the influence of various environmental factors on the performance of the sensor, a plurality of sensors (a flutter sensor C, D, E …) which are the same as and calibrated with the sensor A, B are prepared, different test boxes are built through the combination of four factors of temperature, humidity, pressure, illumination and the like, and the prepared sensors are put into the different test boxes to perform a plurality of performance tests of the sensors, as shown in table 1:
TABLE 1 Performance test chart for vibration sensor under different environmental factors
Wherein, sensor 0000 is the environmental simulation group, will open four controllers and be used for the simulation to the quiver sensor, can test performance parameters such as the drift of zero point, frequency response of obtaining the sensor under this condition. The sensor 0101 is a multivariate simulation suite, in this example there would be 14 simulation suites, each suite would test sensor performance separately. Sensor 1111 is a blank control and will not use the controller to simulate the environmental variables and compare the degradation of the sensor performance under each condition as compared to normal conditions.
In step S300, analyzing the operation data of the tremor sensor under different environmental factors, and determining the influence relationship of the different environmental factors on the performance of the tremor sensor, specifically:
step S301: establishing a three-layer flutter sensor performance AHP analysis model;
step S302: continuously iterating the operation data of the vibration sensor in different environments to determine the weight of each environmental factor; the weight of each environmental factor is the influence relationship of different environmental factors on the performance of the vibration sensor.
As shown in fig. 9, the flutter sensor performance three-layer AHP analysis model includes a data layer, a decision layer, and a target layer.
The target layer is the performance of the sensor, and here, for example, the zero drift is taken as an example, and various factors will cause the performance of the sensor to be reduced.
The decision layer is an index directly influencing the performance of a target layer, namely the sensor, and for example, the aging of an elastic rod, the oxidation of a sensitive element, the aging of a structure and the aging of a material directly influence the performance of the sensor.
The data layer contains data which can be tested in actual use, and the data layer influences variables of the decision layer and then indirectly influences variables of the target layer, wherein the variables comprise environmental variables such as temperature, humidity, air pressure, illumination and the like.
Each lower layer factor affects the upper layer factor, but the transmission weight value needs to be calculated through continuous experiments. And substituting the data obtained by the test in the step S200 into the performance AHP analysis model of the chatter sensor shown in the figure 9, and continuously iterating to obtain the transmission weight of the connected elements of each two adjacent layers.
The data collected through experiments and shown in the table 1 can be used for solving an AHP analysis model of the performance of the flutter sensor. Factors such as temperature, humidity, pressure and illumination of the environment where the sensor is located are brought into C1-C4 in the model shown in FIG. 9, test performances of the sensor such as zero drift, frequency response and the like can be weighted and averaged and then brought into A1 in the model shown in FIG. 9, and iteration can be performed through multiple groups of data to obtain S1 in the AHP analysis model of the performance of the flutter sensorij、SiAnd the like. After the parameters are determined, the model can predict the aging condition of the sensor.
In step S302, determining the weight of each environmental factor by continuously iterating the operation data of the tremor sensor in different environments includes:
step S3021: the test data is normalized.
Aiming at environmental factors such as temperature and the like, in order to ensure that the influence degree of each environmental variable is not influenced by a unit, normalization processing is required, and the processing method comprises the following steps:
t in the formulaiIs a test value of an environmental variable, tMINAnd tMAXMaximum and minimum values of the test values of the environment variable, TiNormalized values for the environmental variables.
The performance indexes of the flutter sensor are numerous, the performance descending range of the sensor needs to be processed for determining, and the n tested performance indexes are normalized by the following formula:
in the formula aiIs the comprehensive performance index of the sensor under the condition,
for the jth test index under this condition,
and
is the extreme value of the test index. The comprehensive performance index a of the sensor under the condition is obtained by normalizing and summing each test itemi。
Step S3022: substituting the AHP model to solve the parameters.
The flutter sensor performance AHP analysis model can analyze the influence of various environmental factors on the comprehensive performance of the sensor, but parameters of the AHP analysis model need to be solved. For the model shown in FIG. 9, where C1-C4 of the data layer are T1-T4 calculated above, A1 of the target layer is a1 calculated above, B1-B4 are intermediate variables, S is Sij，SjWait for the variable to be solved. The transfer function of the model is as follows:
by solving the above equation, the transfer coefficient S can be obtainedij，SjAnd the like.
Specifically, in step S400, predicting the performance aging degree of the tremor sensor according to the influence relationship of different environmental factors on the performance of the tremor sensor includes:
s401: establishing a back propagation neural network;
in particular, using the transfer parameter Sij，SjSetting parameters A in the back propagation neural network model, and establishing the neural network model shown in FIG. 10;
s402: training a backward propagation neural network by utilizing the influence relationship of different environmental factors on the performance of the tremor sensor in the step S300;
specifically, as the parameters calculated by the performance AHP analysis model of the flutter sensor are the calculation results under a fixed environment condition, in order to ensure the universality of the neural network model, a plurality of places of test data are used for training the neural network model.
The performance indexes of various sensors are obtained through the collection of environmental data of multiple places, the normalization processing is carried out, the environmental factors of the temperature are input into the input end of the neural network, and the comprehensive performance of the normalized sensors is used for the calibration of the output end. Through the continuous learning of the neural network, parameters in the model are continuously corrected, so that the model has universality.
And inputting the operating data of the vibration sensor in different environments into the trained vibration sensor performance aging degree prediction model to obtain a final vibration sensor performance aging degree prediction result.
By solving the AHP model in step S300, the relationship between the sensor aging degree and the factors such as temperature, humidity, pressure, and light under the use condition of the tremor sensor a can be obtained.
In order to realize comprehensive prediction under multiple regions and multiple environments, environmental data of multiple regions need to be collected, a backward neural network is used for model training, and finally the aging condition of the sensor can be predicted under multiple environments.
In this embodiment, collected data of temperature, humidity, air pressure, and light in 24 hours of a certain place is used as shown in fig. 11, and the degree of aging of the sensor is tested as shown in fig. 12. A backward neural network is built through MATLAB, model training is performed by using data of the first 12 hours, and prediction and actual values of the model on data of the last 12 hours are shown in fig. 13.
Example two
As shown in fig. 2 to 10, the present embodiment provides a multi-ground synchronous adaptive performance test system of a cryo-tremor sensor, including:
the data acquisition module is configured to synchronously acquire position environment information of the multi-vibration sensor;
the simulation test module is configured to simulate different environmental factors according to the position environmental information data of the vibration sensor and test the performance of the vibration sensor under different environmental factors;
the data processing module is configured to analyze the performance of the vibration sensor under different environmental factors and determine the influence relation of the different environmental factors on the performance of the vibration sensor;
and the aging prediction module is configured to predict the performance aging degree of the vibration sensor according to the influence degree of different environmental factors on the performance of the vibration sensor.
It should be noted here that the data acquisition module, the simulation test module, the data processing module and the aging prediction module correspond to steps S100 to S400 in the first embodiment, and the modules are the same as the corresponding steps in the implementation example and application scenarios, but are not limited to the disclosure in the first embodiment. It should be noted that the modules described above as part of a system may be implemented in a computer system such as a set of computer-executable instructions.
In the foregoing embodiments, the descriptions of the embodiments have different emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
The proposed system can be implemented in other ways. For example, the above-described system embodiments are merely illustrative, and for example, the division of the above-described modules is merely a logical division, and in actual implementation, there may be other divisions, for example, multiple modules may be combined or integrated into another system, or some features may be omitted, or not executed.
Wherein the content of the first and second substances,
1. and a data acquisition module. The module mainly comprises a main control chip, a matched communication chip and a part of sensors capable of testing environmental data, such as sensors for temperature, humidity, air pressure, solar radiation and the like. The module has the characteristics of small size, low cost, high integration level, easiness in installation and the like, has low technical requirements on installation personnel, can be widely deployed in the actual application environment of the vibration sensor, and realizes high-precision acquisition, high-frequency and low-time-delay transmission of environmental data.
2. And simulating a test module. The module mainly comprises a temperature and humidity control box, an air pressure regulator, a solar radiation generator and a peripheral control circuit, and a vibration table is placed in the low-temperature box to test various performances of the vibration sensor. Although the module is high in cost, the adjustability is good, and simulation of various environmental conditions can be achieved through combination of three main devices, namely a control box, a regulator and a generator. Through simulating different environments, the influence degree of different environmental factors on the performance of the vibration sensor can be analyzed, the data obtained through testing can be easily used in subsequent data processing, and the elimination of entanglement among environmental variables is greatly facilitated.
3. And a data processing module. The module mainly comprises an AHP analytic hierarchy process and a back propagation neural network algorithm. The AHP analytic hierarchy process is mainly used for analyzing the influence degree of multi-environment variables, and analyzing the entanglement condition among variables such as temperature, humidity and the like by utilizing the existing single-variable influence model. Obtaining an influence model of the entanglement condition and the univariate;
4. the backward propagation neural network can be trained by data tested by matching with the aging prediction module, and the trained model can predict the performance aging condition of the vibration sensor in use.
The design of the original environment data acquisition module has the following requirements:
1. the module needs to realize the characteristics of small and exquisite structure and high integration level so as to be convenient for installation on the actual installation position of the flutter sensor. For this reason, the module is designed in a multilayer structure, and the integration of components is carried out by using a printed circuit board, so that the module is small and exquisite and has high integration level.
2. The module requires low cost features for installation in a vast number of application scenarios. The main control chip can be selected from a low-performance chip with enough performance, for example, a single chip microcomputer instead of an embedded system, and sensors of temperature, humidity and the like can be selected from a traditional chip with enough precision instead of an advanced MEMS sensor, so that the cost can be greatly reduced.
3. The module also needs to have easy installation features, and not have too high a technical threshold for installers. Therefore, the module is designed in a wireless mode, the installed system distributes identification codes in a unified mode, and installation workers only need to bind the identification codes and installation positions.
For this reason, the original environment data acquisition module will adopt a three-layer design.
The first layer is a battery compartment, and due to the fact that the actual application scene of the flutter sensor is five-door and eight-door, the supply of electric quantity can be difficult to guarantee in partial installation scenes, the installation cost is increased and the complexity of circuit deployment is improved by using wired power supply, the low-power-consumption main control chip is used for carrying out periodic sleep, and the battery power supply can still guarantee the endurance of enough time.
The second layer is a main control chip and a communication chip, the main control chip adopts a low-power consumption singlechip and is assisted with periodic sleep to ensure the continuous endurance of the equipment, the communication chip can use an NB-IoT module, has low power consumption and can be deployed on cellular wireless networks such as 2/3/4G, and the like, and can also be conveniently deployed in the field.
The third layer is sensors such as temperature and humidity, and for guaranteeing the collection precision of environmental data, the sensor needs the direct contact outside, can adopt SMD for the sensor of easy to assemble to link through serial ports and below main control chip, realize the collection to environmental data.
The simulation test module is usually installed in a laboratory, and collects and stores test data sent from various places to perform a simulation test. The simulation test module needs to include the following requirements:
1. the laboratory terminal needs to have larger information throughput, the laboratory terminal is directly connected with the original environment data acquisition modules which are deployed in a large amount, and meanwhile, network delay can be caused by large amount of data transmission. For the information transmission, a time division technology is adopted, after data are packaged, each original environment data acquisition module queues and distributes data, and the flow balance of the data is guaranteed. Meanwhile, data are temporarily stored, and a simulation test is carried out after the data are checked to be correct.
2. The simulation module needs to simulate four typical environment variables, and the laboratory terminal needs to deploy a corresponding simulator. For this reason, the simulation box adopts a temperature and humidity control box, and is matched with an air pressure regulator and a solar radiation generator to realize the simulation of four typical environment variables.
3. In order to make the data obtained by the test easy to be processed subsequently, the variables need to be classified in groups and tested respectively. Therefore, three main devices such as a control box, a regulator and a generator can be combined differently, and tests are carried out under different combinations, so that the performance change conditions under the influence of different environmental factors are obtained.
Therefore, the simulation test module is composed of a time division multiple access data receiving module, a data storage center and a single-multivariable simulation box.
The time division multiple access data receiving module has the main functions of processing data transmitted by a large number of original environment data acquisition modules, and communicating with an upper computer (a simulation test module) at a certain time slot by numbering a lower computer (the original environment data acquisition modules) so as to transmit the acquired environment data. And the sleep is carried out in other time slots, and the low-power-consumption operation is entered. The method can save communication resources, keep a reasonable load of a communication channel, reduce the power consumption condition of the lower computer (the original environment data acquisition module) and prolong the service time.
In order to ensure that the test simulation box can continuously run in the test process without being interrupted by factors such as network delay and the like, the environmental meteorological data are firstly transmitted to a test room through a network link and are stored in a data center after being received by the receiving module, and the subsequent test simulation box directly calls the data of the local data center, so that test interruption caused by test data loss is avoided.
Various meteorological factors in the original environment are entangled with each other and jointly act on the aging of the vibration sensor. Different tests are required to analyze the action effect of a single environmental factor and the entanglement condition among a plurality of environmental variables. By analyzing the superposition of the interaction effect and the independent action effect of the factor A on the factor B, the entanglement between the environmental factors can be analyzed to be jointly promoted or mutually restricted, so that the realization of a subsequent algorithm is facilitated.
The data processing module is a software part and is used for processing data obtained in a simulation test, analyzing the influence degree of each environmental factor on the performance of the flutter sensor and realizing accurate prediction by utilizing a data training model. The module design includes the following requirements:
1. environmental factors are entangled too much, aging of the vibration sensor can be promoted or restricted, and an algorithm needs to be designed for the module to eliminate entanglement among the factors. Therefore, an AHP analytic hierarchy process is used, the possible entanglement relation of each environmental factor is determined by looking up the existing literature, a three-layer AHP analytic model is established, and the weight of each factor in the model is determined by continuously iterating the test data.
2. For the vibration sensor in use, in order to determine whether the vibration sensor has accuracy, the measurement technology is carried out again after the vibration sensor is taken down, and the realization difficulty is high. A prediction model needs to be designed by utilizing the existing test data, and the aging condition of the flutter sensor can be predicted according to the meteorological data of the ground. For this purpose, a back propagation neural network is used, and the model is trained by using the existing test data, so that the model has excellent prediction capability.
Thus, the data processing module contains an AHP hierarchy analysis algorithm.
The AHP analytic hierarchy process comprises a data layer (temperature and humidity and other data), a decision layer (sensor structure, material property and other data), and a target layer (vibration sensor performance). The scale of each factor is analyzed using decision scales by building a consistency matrix. And comparing the model with the existing test data after the model is established, and obtaining the entanglement condition of each factor after the error requirement is met.
The aging prediction module comprises a neural network prediction algorithm.
The neural network prediction algorithm mainly comprises a part of neurons, is used for outputting after being excited by input (temperature, humidity and the like), and outputs through multilayer iteration. And continuously correcting the weight of each propagation path through data training until a reliable neural network model is obtained finally.
In summary, the first and second embodiments have the following advantages:
1. practice thrift manpower and test cost, use low-cost repeatedly usable's environmental data collection system, reduce the equipment transportation and the installation cost of test, and the experimentation is indoor, and security and guarantee nature are high, and the experiment can be repeatedly carried out in order to eliminate the contingency.
2. Factors influencing the performance of the sensor are split in the environment, single variables and partial variables in the sensor can be tested, the strength of the influence degree of different factors on the performance of the sensor is easy to test, and special protection can be achieved when the sensor is protected.
3. The upgrading and maintenance are simple, the system adopts a modular design, the environment data acquisition module is easy to add a novel sensor, a laboratory is also easy to add a novel simulation box, and the measurement of various scene factors can be realized.
EXAMPLE III
The present embodiment provides a computer-readable storage medium, on which a computer program is stored, which when executed by a processor implements the steps in the method for multi-place simultaneous adaptive performance testing of a cryo-tremor sensor as described in the first embodiment above.
Example four
The present embodiment provides a computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of the method for multi-site simultaneous adaptive performance testing of a cryo-tremor sensor according to the first embodiment described above when executing the program.
As will be appreciated by one skilled in the art, embodiments of the present disclosure may be provided as a method, system, or computer program product. Accordingly, the present disclosure may take the form of a hardware embodiment, a software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present disclosure may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, optical storage, and the like) having computer-usable program code embodied therein.
The present disclosure is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the disclosure. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by a computer program, which can be stored in a computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), or the like.
Although the present disclosure has been described with reference to specific embodiments, it should be understood that the scope of the present disclosure is not limited thereto, and those skilled in the art will appreciate that various modifications and changes can be made without departing from the spirit and scope of the present disclosure.
Claims (10)
1. A multi-place synchronous self-adaptive performance testing method of a low-temperature flutter sensor is characterized by comprising the following steps:
synchronously acquiring position environment information of a plurality of vibration sensors;
simulating different environmental factors according to the position environmental information data of the vibration sensor, and testing the performance of the vibration sensor under different environmental factors;
analyzing the performance of the vibration sensor under different environmental factors, and determining the influence relationship of the different environmental factors on the performance of the vibration sensor;
and predicting the performance aging degree of the vibration sensor according to the influence relationship of different environmental factors on the performance of the vibration sensor.
2. The method for testing the multi-place synchronous self-adaptive performance of the low-temperature flutter sensor in claim 1, wherein the step of predicting the performance aging degree of the flutter sensor according to the influence degree of different environmental factors on the performance of the flutter sensor comprises the following steps:
according to the influence relation of different environmental factors on the performance of the vibration sensor and each environmental factor, training a backward propagation neural network to obtain a trained prediction model of the performance aging degree of the vibration sensor;
and inputting the factors under different environments into the trained prediction model of the performance aging degree of the vibration sensor to obtain a final prediction result of the performance aging degree of the vibration sensor.
3. The method for testing the multi-place synchronous self-adaptive performance of the low-temperature flutter sensor according to claim 1, wherein the analyzing the performance of the flutter sensor under different environments to determine the influence relationship of different environmental factors on the performance of the flutter sensor comprises the following steps:
establishing a three-layer flutter sensor performance AHP analysis model;
continuously iterating the operation data of the vibration sensor in different environments to determine the weight of each environmental factor;
the weight of each environmental factor is the influence relationship of different environmental factors on the performance of the vibration sensor.
4. The method as claimed in claim 3, wherein the three-layer AHP analysis model comprises a data layer, a decision layer and a target layer.
5. The method for multi-place synchronous adaptive performance test of a low-temperature flutter sensor according to claim 4, characterized in that the target layer is performance information of the sensor;
the decision layer is index information directly influencing the performance of a target layer, namely the sensor;
the data layers are different environmental factors affecting the performance of the flutter sensor.
6. The method for testing the multi-place synchronous self-adaptive performance of the low-temperature flutter sensor in claim 3, wherein the step of determining the weight value of each environmental factor by continuously iterating the operation data of the flutter sensor under different environments comprises the following steps:
normalizing each environmental factor and performance index of the vibration sensor;
and substituting the processed environmental factors and the performance indexes of the vibration sensor into an AHP analysis model of the performance of the vibration sensor to determine the weight of each environmental factor.
7. The method for testing the multi-place synchronous self-adaptive performance of the low-temperature flutter sensor in claim 1, wherein the simulation of different environmental factors is carried out according to the position environmental information data of the flutter sensor, and the operation data of the flutter sensor under different environmental factors is tested, and the method comprises the following steps:
building a simulated environment test box according to the position environment information of the flutter sensor;
the performance of the flutter sensor under different environmental factors is respectively tested by controlling the sensors with different environmental factors in the test box.
8. A multi-place synchronous self-adaptive performance test system of a low-temperature flutter sensor is characterized by comprising:
the data acquisition module is configured to synchronously acquire position environment information of the multi-vibration sensor;
the simulation test module is configured to simulate different environmental factors according to the position environmental information data of the vibration sensor and test the performance of the vibration sensor under different environmental factors;
the data processing module is configured to analyze the performance of the vibration sensor under different environmental factors and determine the influence relation of the different environmental factors on the performance of the vibration sensor;
and the aging prediction module is configured to predict the performance aging degree of the vibration sensor according to the influence relation of different environmental factors on the performance of the vibration sensor.
9. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method for multi-ground synchronous adaptive performance testing of a cryo-tremor sensor of any of claims 1-7.
10. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the steps in the method for multi-ground synchronous adaptive performance testing of a cryo-tremor sensor of any of claims 1-7 when executing the program.
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