CN116186976A - Verification method and verification system for accuracy of data collected by equipment platform sensor - Google Patents
Verification method and verification system for accuracy of data collected by equipment platform sensor Download PDFInfo
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Abstract
The invention provides a verification method for accuracy of data collected by a sensor of an equipment platform, which comprises the following specific steps of determining the type of the sensor: screening is performed from the data of different objects according to different requirements, and the number, types and requirements of the required sensors are obtained by combining the types. Verifying the correctness of the data collected by the sensor: through simulation analysis and experimental analysis, a certain number of sensors are placed at the positions of performance parameters which can represent the function and performance degradation of the object; and (3) evaluating whether the positions and the number of the sensors are reasonable or not through closed-loop analysis of the test data of the sensors and the real state of the object. The accuracy of the sensor sample data is verified using three sensors at different levels in the object or a mathematically derived model of the system in the object. According to the invention, the accuracy of the data collected by the sensors is verified by different modes of function inheritance, cross verification, redundancy verification and system modeling among the sensors, so that the influence caused by errors or false alarms is avoided.
Description
Technical Field
The invention relates to the technical field of industrial Internet of things application, in particular to a verification method and a verification system for accuracy of data acquisition of an equipment platform sensor.
Background
The sensor is a detection device, can sense the detected information and convert the detected information into an electric signal or other signals through a certain rule to transmit, store and display the acquired data; the sensor has the data acquisition function, and when the sensor has faults such as drift, non-operating condition, etc., the data that gathers can not bring correct effective application, can also wrong mislead operating personnel and maintenance personnel etc..
The method is needed to ensure that the data of the sensor is correct and accurate, and the accuracy of the method is that the data measurement of the sensor is within the error range set by the sensor.
Disclosure of Invention
Aiming at the problems existing in the prior art, the invention provides a verification method for the accuracy of the acquired data of the sensor of the equipment platform, and the accuracy of the acquired data of the sensors on different objects is verified, so that the sensors can better represent the performance parameters of the function and performance degradation of the objects at more specific positions; the accuracy of collected data of the sensors at different positions is verified by utilizing a function inheritance method, a cross verification method, a redundancy verification method or a mathematical deduction model of a system, and the like, so that the influence caused by errors or false alarms of the sensor data is avoided, and the sensors are developed towards the collected and trusted directions.
The invention provides a verification method for accuracy of data collected by a sensor of an equipment platform, which comprises the following specific implementation steps:
s1, determining the type of a sensor: screening data of different objects of the unit, the system and the equipment platform, and obtaining the number, the types and the requirements of the required sensors by combining the types;
s2, verifying the correctness of the acquired data of the sensor, and specifically comprising the following substeps:
s21, placing a certain number of sensors at positions of performance parameters capable of representing the functions and performance degradation of the object through simulation analysis and experimental analysis;
s22, under the functions of monitoring, diagnosing and predicting different objects, performing closed-loop analysis based on the test data of the sensors and the state of the object reaction, and evaluating whether the positions and the number of the sensors are reasonable:
if the sensor acquisition data is within a reasonable range but the function of the object is invalid or the performance of the object is degraded, the positions and the number of the sensors need to be rearranged, and the step S21 is returned and repeated;
if the test data of the sensor is consistent with the state of the object reaction, the positions and the number of the sensors are reasonably arranged, and the step S3 is carried out;
s3, verifying accuracy of data acquired by the sensors by utilizing a plurality of sensors at different levels in the object, wherein the method specifically comprises the following substeps:
s31, if the number of the systems in the object is less than or equal to 3, and each system function is characterized independently and has no characteristic of function feedback, verifying the accuracy of the data acquired by the sensor by adopting a function inheritance method;
s32, if more than 3 systems exist in the object, and the functions of each system are crosslinked and complicated, and the functions of the systems are mutually influenced, verifying the accuracy of the data acquired by the sensor by adopting a cross verification method;
s33, if the object has many-to-one or one-to-many, and the characteristics of the function data are affected by the independent sensor acquisition aiming at function transmission in different systems, verifying the accuracy of the sensor acquisition data by adopting a redundancy verification method;
s4, checking the accuracy of the sensor sampling data according to a mathematical model of the system in the object:
input parameter x of the system 1 And x 2 Respectively inputting the output parameters or the feedback parameters Y into a mathematical model of the system, wherein the expression of the mathematical model is as follows:
wherein k is 1 、k 2 And k 3 Parameters of the mathematical model;
and (3) carrying out difference between the obtained output parameter or feedback parameter and the numerical value acquired by the sensor, if the difference is within the range of the acquisition error of the sensor, acquiring data by the sensor is accurate, and if the difference exceeds the range of the acquisition error of the sensor, acquiring data by the sensor is incorrect.
Preferably, in step S1, the different objects, including units, systems and equipment platforms, the different requirements, including monitoring, diagnosis and health management, the screening conditions are according to the functional data and performance data required by the different objects.
Preferably, in step S21, the simulation analysis includes a circuit simulation analysis and a stress simulation analysis.
Preferably, the accuracy of the sensor sampling data is dependent on the accuracy of the sensor and the sudden failure of the sensor.
Preferably, in step S3, the functional inheritance method and the cross verification method each verify that the acquired data of the third sensor is incorrect by accurately acquiring the data of two sensors of the three sensors, which specifically includes:
if the acquired data of the third sensor is deviated from the acquired data of the first sensor and the second sensor respectively, the accuracy of the third sensor is abnormal, and the acquired data of the third sensor is wrong;
if the third sensor alarms due to the self fault and the comparison result of the first sensor and the second sensor shows that the third sensor is abnormal, the third sensor is electrified again and faults are observed;
if the third sensor does not alarm due to the self-fault, and the comparison result of the first sensor and the second sensor shows that the third sensor is abnormal, the third sensor has a fault.
Preferably, the step S3 and the step S4 are respectively different ways to verify the accuracy of the data collected by the sensor, and are in parallel relationship.
Another aspect of the present invention also provides a verification system for the above verification method for accuracy of data collected by the equipment platform sensor,
the system comprises a sensor type analysis module, a first sensor data verification module, a second sensor data verification module and a sensor data verification module, wherein the sensor type analysis module, the first sensor data verification module, the second sensor data verification module and the sensor data verification module are sequentially in communication connection;
the sensor type analysis module is used for obtaining the number, the type and the requirement of the required sensors according to the data in the database;
the first sensor data verification module is used for evaluating whether the positions and the number of the sensors are reasonable or not;
the second sensor data verification module is used for verifying the accuracy of data acquired by the sensors by using a plurality of sensors at different levels in the object;
the sensor data verification module is used for verifying the accuracy of the sensor sampling data according to a mathematical deduction model of the system in the object.
Preferably, the specific method for verifying the accuracy of the data acquired by the sensor by using a plurality of sensors at different levels in the object by the sensor data verification module is as follows: input parameter x of the system 1 And x 2 Respectively inputting the output parameters or the feedback parameters into a mathematical model of the system, wherein the expression of the mathematical model is as follows:
wherein k is 1 、k 2 And k 3 Parameters of the mathematical model;
and (3) carrying out difference between the obtained output parameter or feedback parameter and the numerical value acquired by the sensor, if the difference is within the range of the acquisition error of the sensor, acquiring data by the sensor is accurate, and if the difference exceeds the range of the acquisition error of the sensor, acquiring data by the sensor is incorrect.
Compared with the prior art, the invention has the following advantages:
the invention obtains clear mechanism of the sensor through modes such as a function inheritance method, a cross verification method, a redundancy verification method and the like among different sensors, namely, the sensor can be verified through a system modeling mode expressed by a mathematical model, and the data accuracy of the sensor is verified, so that the influence caused by errors or false alarms of the sensor data is avoided, the sensor is informed, the sensor is used, the development is more intelligent, the automatic control capability is stronger, the working efficiency is finally improved, the debugging time is shortened, and the misleading condition is reduced.
Drawings
FIG. 1 is a flow chart of a method for verifying accuracy of data collected by a platform sensor of the present invention;
FIG. 2 is a flowchart for verifying the correctness of the sensor acquired data in the accuracy verification method of the sensor acquired data of the equipment platform;
FIG. 3 is a flowchart for verifying accuracy of sensor acquired data in the method for verifying accuracy of sensor acquired data of an equipment platform according to the present invention;
FIG. 4 is a schematic diagram of a functional inheritance method in the accuracy verification method of the data acquired by the sensor of the equipment platform of the invention;
FIG. 5 is a schematic diagram of a cross-validation method in the accuracy validation method of the data collected by the platform sensor of the present invention;
FIG. 6 is a schematic diagram of a redundancy verification method in the accuracy verification method of the data collected by the platform sensor of the present invention;
FIG. 7 is a schematic diagram of a method model for verifying accuracy of data collected by a sensor of an equipment platform according to the present invention;
fig. 8 is a block diagram schematically illustrating the structure of the verification system of the present invention.
Detailed Description
In order to make the technical content, the achieved objects and the effects of the present invention more detailed, the following description is taken in conjunction with the accompanying drawings.
The accuracy verification method for the data collected by the equipment platform sensor is realized by the following steps, as shown in fig. 1:
s1, determining the type of the sensor.
S2, verifying the correctness of the data acquired by the sensor.
S3, verifying the accuracy of data acquired by the sensors by using three sensors at different levels in the object.
In particular, the accuracy of sensor sampling data depends on accuracy issues of the sensor and sudden failures of the sensor.
S4, checking the accuracy of the sensor sampling data according to a mathematical deduction model of the system in the object.
Specifically, step S3 and step S4 are respectively to verify the accuracy of the data collected by the sensor in a parallel relationship by adopting different manners.
Further, the method for determining the sensor type in step S1 is as follows: screening is performed from the data of different objects according to different requirements, and the number, types and requirements of the required sensors are obtained by combining the types. In particular, different objects, including units, systems and equipment platforms, different requirements, including monitoring, diagnosis and health management, are screened for conditions that follow the functional and performance data required by the different objects.
Further, as shown in fig. 2, the method for verifying the correctness of the acquired data of the sensor in step S2 includes,
s21, a certain number of sensors are placed at positions of performance parameters capable of representing the function and performance degradation of the object through simulation analysis and experimental analysis.
Preferably, the simulation analysis comprises circuit simulation analysis and stress simulation analysis, the electronic product is subjected to circuit simulation analysis, and the structural product is subjected to stress simulation analysis.
S22, under the functions of monitoring, diagnosing and predicting different objects, performing closed-loop analysis on the states of the test data of the sensors and the response of the objects, and evaluating whether the positions and the number of the sensors are reasonable or not:
if the function of the object fails and the sensor acquisition data is within a reasonable range, the positions and the number of the sensors need to be rearranged, and the step S21 is repeated;
if the performance of the object is degraded and the performance parameters of the sensor are within a reasonable range, the positions and the number of the sensors need to be rearranged, and the step S21 is repeated;
if the test data of the sensor is consistent with the state of the object reaction, the positions and the number of the sensors are reasonably arranged, and the step S3 is performed.
Further, as shown in fig. 3, the specific steps for verifying the accuracy of the sensor acquired data in step S3 are as follows:
s31, if the number of the systems in the object is less than or equal to 3, and each system function is characterized independently, the function transfer relation of the equipment in the system is simple, and the closed loop transfer characteristic of function feedback is not provided, the accuracy of data collected by the sensor is verified by adopting a function inheritance method.
S32, if the number of the systems in the object is more than 3 and the system cannot be independently represented by the functions of one system, the functions of each system are crosslinked and complicated, the functions of the systems are mutually influenced, and a cross-validation method is adopted to verify the accuracy of the data acquired by the sensor.
S33, if a plurality of systems exist in the object corresponding to one system or one system corresponds to a plurality of systems, and whether the system is one-to-many or one-to-one is characterized in that independent sensors for function transfer are used for acquiring functional data, a redundancy verification method is adopted to verify the accuracy of the acquired data of the sensors.
Further, as shown in fig. 7, the specific steps for verifying the accuracy of the sensor acquired data in step S4 are as follows:
input parameter x of the system 1 And x 2 Respectively inputting the output parameters or the feedback parameters into a mathematical model of the system, wherein the expression of the mathematical model is as follows:
wherein k is 1 、k 2 And k 3 Parameters of the mathematical model.
And (3) carrying out difference between the obtained output parameter or feedback parameter and the numerical value acquired by the sensor, if the difference is within the range of the acquisition error of the sensor, acquiring data by the sensor is accurate, and if the difference is beyond the range of the acquisition error of the sensor, acquiring data by the sensor is incorrect.
In a preferred embodiment of the present invention, the functional inheritance method and the cross-validation method both verify that the acquired data of the third sensor is incorrect by accurately acquiring the data of two sensors of the three sensors, and the specific process is as follows:
if the acquired data of the third sensor is deviated from the acquired data of the first sensor and the second sensor respectively, the accuracy of the third sensor is abnormal, and the acquired data of the third sensor is wrong;
if the third sensor alarms due to the self fault and the comparison result of the first sensor and the second sensor shows that the third sensor is abnormal, the third sensor is electrified again and faults are observed;
if the third sensor does not alarm due to the self-fault, and the comparison result of the first sensor and the second sensor shows that the third sensor is abnormal, the third sensor has a fault.
Specifically, two sensors of the same type are added near the measuring position, wherein any one sensor has larger data deviation from the other two sensors, namely, the sensor with larger deviation is proved to be faulty. Although effective in a certain range, the method increases cost and complex procedures of a test system, so that the method cannot be widely adopted for analyzing and evaluating the accuracy of data.
In another aspect of the present invention, a verification system for the accuracy verification method of the acquired data of the sensor of the equipment platform is provided, as shown in fig. 8, where the system includes a sensor type analysis module 1, a first sensor data verification module 2, a second sensor data verification module 3, and a sensor data verification module 4, and the sensor type analysis module 1, the first sensor data verification module 2, the second sensor data verification module 3, and the sensor data verification module 4 are sequentially connected in a communication manner; the sensor type analysis module 1 is used for obtaining the number, the type and the requirement of the required sensors according to the data in the database; the first sensor data verification module 2 is used for evaluating whether the positions and the number of the sensors are reasonable or not; the second sensor data verification module 3 is used for verifying the accuracy of data acquired by the sensors by using a plurality of sensors at different levels in the object; the sensor data verification module 4 is used for verifying the accuracy of the sensor sampling data according to a mathematical derivation model of the system in the subject.
The method for verifying the accuracy of the acquired data of the equipment platform sensor is further described in the following by combining the embodiment:
s1, determining the type of a sensor: from the consideration of different objects such as units, systems and equipment platforms, the functional data and the performance data required by the different objects are screened according to the requirements of monitoring, diagnosis and health management, different data sets meeting the different levels and different requirements of the object are selected, and the number, the types and the requirements of the required sensors are determined by combining the types and the like.
S2, verifying the correctness of the collected data of the sensor, specifically, whether the installation positions and the quantity of the sensors are correct or not according to the function data and the performance data collected by the unit, the system and the equipment platform.
S21, a certain number of sensors are placed at positions of performance parameters which can represent the function and performance degradation of the object by reference to the past experience or through simulation analysis and experimental analysis.
S22, based on the step S21, according to the monitoring, diagnosing and predicting functions of different objects, through closed-loop analysis of the test data of the sensors and the real state of the objects, whether the positions and the number of the sensors are reasonable or not is evaluated:
if the function of the object fails but the data collected by the sensor is within a reasonable range, the positions and the number of the sensors are not reasonable, readjustment is needed, and the unreasonable state refers to the state that the test data cannot be truly fed back to the object, and the test data cannot be used for fault diagnosis and health management, and the step S21 is repeated.
If the performance of the object is degraded and needs to be degraded, but the performance parameters of the sensors are within a reasonable range, the positions and the number of the sensors are not reasonable, readjustment is needed, and step S21 is repeated.
If the test data of the sensor is consistent with the state of the object reaction, the positions and the number of the sensors are reasonable, and the step S3 is performed.
S3, when a sensor is in a problem, the adopted data are always wrong, and the data without errors have great misleading effect on the subsequent data application, so that wrong guidance can be caused, and wrong decision is caused. Therefore, after the steps of determining the type of the sensor, verifying the correctness of the data and the like are completed, the accuracy of the data acquired by the sensor needs to be verified; three sensors at different levels in an object are utilized to verify the accuracy of data acquired by the sensors, the accuracy of the data acquired by the sensors depends on the accuracy problem of the sensors, the type selection problem is inconsistent with the actual requirements, and sudden faults of the sensors, such as non-working states and drift, exist in common faults.
S31, if the number of the systems in the object is less than or equal to 3, and each system function is characterized independently, the function transfer relation of the equipment in the system is simple, and the closed loop transfer characteristic of function feedback is not provided, the accuracy of data collected by the sensor is verified by adopting a function inheritance method.
In a preferred embodiment of the present invention, as shown in table 1, the equipment platform function inherits the system function, the parameter of the equipment platform function is acquired by the first sensor, the system function inherits the device function, the parameter of the system function is acquired by the second sensor, the parameter of the device function is acquired by the third sensor, and the inaccuracy of the data of each sensor can be determined through the inheritance relationship and the logic relationship between the sensors, so that the accuracy of the other two sensors is verified.
Table 1 functional inheritance relationships and logical relationships
The formulation of the logical relationship can be further expressed in terms of a correlation matrix:
table 2 functional inheritance expression
In this implementation, assuming that the simultaneous failure of two sensors does not occur, by comparing the sensors, it is possible to obtain the failed sensor among the first sensor, the second sensor and the third sensor, and combine the failure reporting of the sensors themselves, and considering that the sensors sometimes fail in false reporting, the relationships among the functions of the equipment, the functions of the system and the functions of the devices are shown in fig. 4.
The equipment platform functions are not only associated with the system functions, but also associated with the functions among a plurality of systems, and the system functions may not only be associated with the equipment functions, so that the association relations are required to be combed in the design process of the equipment platform later to form a mapping table among the functions, and data support is provided for accuracy evaluation of sensor data.
If the data collected by the third sensor is different from the data collected by the first sensor and the second sensor, the accuracy of the third sensor is abnormal, the data collected by the third sensor is inaccurate, and the third sensor cannot be used as input for subsequent data.
If the third sensor alarms due to the self fault and the comparison result of the first sensor and the second sensor shows that the third sensor is abnormal, the fault reported by the third sensor is possibly a false alarm, and the third sensor is powered on again and whether the fault report is eliminated or not is observed.
If the third sensor does not alarm due to the self fault and the comparison result of the first sensor and the second sensor shows that the third sensor is abnormal, the third sensor has a fault, so that the data of the third sensor is inaccurate and cannot be used as the input of the subsequent data.
S32, if the number of the systems in the object is more than 3 and the system cannot be independently represented by the functions of one system, the functions of each system are crosslinked and complicated, the functions of the systems are mutually influenced, and a cross-validation method is adopted to verify the accuracy of the data acquired by the sensor.
In a preferred embodiment of the invention, the cross-validation method has the advantages that the data of the sensors have a cross relation among different systems and different devices, and the cross relation is the relation of transformation, weak correlation, non-mathematical model construction and the like. If the function of a certain system is normal and the function of another system has a cross relation, it can be understood that when the function of the first system fails, the function of the second system fails, and the function of the third system fails, through the influence and discrimination among multiple function transfer, whether each function similar to the first system, the second system and the third system fails can be analyzed, and the cross relation and the logic relation are shown in table 3.
TABLE 3 functional cross-relation of systems
The formulation of the logical relationship can be further expressed in terms of a correlation matrix:
table 4 functional cross-expression of the system
The function cross relation among the systems is generally complicated, and in order to clearly describe the function transfer and the function cross logic relation among the systems, as shown in fig. 5, the first system function can influence whether the second system function is normal or not, and meanwhile, whether the third system function is normal or not can be influenced, all the functions can be detected by corresponding sensors, and when the realization information of any two functions and the other function contradicts, the contradictory sensor data can be obtained to be unreliable and inaccurate.
S33, if a plurality of systems exist in the object corresponding to one system or one system corresponds to a plurality of systems, and whether the system is one-to-many or one-to-one is characterized in that independent sensors for function transfer are used for acquiring functional data, a redundancy verification method is adopted to verify the accuracy of the acquired data of the sensors.
In a preferred embodiment of the present invention, the redundancy verification method deduces whether the data of the sensor redundant to each other is accurate or not through the redundancy relation of the sensor, and whether the data acquisition is abnormal or not due to the occurrence of faults, in this embodiment, the input/output voltage is taken as an example, and the redundancy relation and the logic relation of the sensor function are shown in table 5.
Table 5 functional redundancy method validation data table
The formulation of the logical relationship can be further expressed in terms of a correlation matrix:
table 6 functional redundancy expression
The first input voltage test of the converter is obtained through the first voltage sensor test, the second input voltage test of the converter, the third input voltage test of the converter and the fourth input voltage test of the converter are respectively obtained by the second voltage sensor, the third voltage test and the fourth voltage test of the converter, the data accuracy of the sensor can be checked mutually through the second input voltage test, the third input voltage test and the fourth input voltage test, the logic relationship is shown in table 3, and the specific redundancy schematic diagram is shown in fig. 6.
S4, checking the accuracy of the sensor sampling data according to a mathematical deduction model of the system in the object, and characterizing and observing the data to be measured through the mathematical deduction model.
Input parameter x of the system 1 And x 2 Respectively inputting the output parameters or the feedback parameters into a mathematical model of the system, wherein the expression of the mathematical model is as follows:
wherein k is 1 、k 2 And k 3 Parameters of the mathematical model.
And (3) carrying out difference between the obtained output parameter or feedback parameter and the numerical value acquired by the sensor, if the difference is within the range of the acquisition error of the sensor, acquiring data by the sensor is accurate, and if the difference is beyond the range of the acquisition error of the sensor, acquiring data by the sensor is incorrect.
The above examples are only illustrative of the preferred embodiments of the present invention and are not intended to limit the scope of the present invention, and various modifications and improvements made by those skilled in the art to the technical solution of the present invention should fall within the scope of protection defined by the claims of the present invention without departing from the spirit of the present invention.
Claims (8)
1. The method for verifying the accuracy of the acquired data of the equipment platform sensor is characterized by comprising the following steps of:
s1, determining the type of a sensor: screening data of different objects of the unit, the system and the equipment platform, and obtaining the number, the types and the requirements of the required sensors by combining the types;
s2, verifying the correctness of the acquired data of the sensor, and specifically comprising the following substeps:
s21, placing a certain number of sensors at positions of performance parameters capable of representing the functions and performance degradation of the object through simulation analysis and experimental analysis;
s22, under the functions of monitoring, diagnosing and predicting different objects, performing closed-loop analysis based on the test data of the sensors and the state of the object reaction, and evaluating whether the positions and the number of the sensors are reasonable:
if the sensor acquisition data is within a reasonable range but the function of the object is invalid or the performance of the object is degraded, the positions and the number of the sensors need to be rearranged, and the step S21 is returned and repeated;
if the test data of the sensor is consistent with the state of the object reaction, the positions and the number of the sensors are reasonably arranged, and the step S3 is carried out;
s3, verifying accuracy of data acquired by the sensors by utilizing a plurality of sensors at different levels in the object, wherein the method specifically comprises the following substeps:
s31, if the number of the systems in the object is less than or equal to 3, and each system function is characterized independently and has no characteristic of function feedback, verifying the accuracy of the data acquired by the sensor by adopting a function inheritance method;
s32, if more than 3 systems exist in the object, and the functions of each system are crosslinked and complicated, and the functions of the systems are mutually influenced, verifying the accuracy of the data acquired by the sensor by adopting a cross verification method;
s33, if the object has many-to-one or one-to-many, and the characteristics of the function data are affected by the independent sensor acquisition aiming at function transmission in different systems, verifying the accuracy of the sensor acquisition data by adopting a redundancy verification method;
s4, checking the accuracy of the sensor sampling data according to a mathematical model of the system in the object:
input parameter x of the system 1 And x 2 Respectively inputting the output parameters or the feedback parameters Y into a mathematical model of the system, wherein the expression of the mathematical model is as follows:
wherein k is 1 、k 2 And k 3 Parameters of the mathematical model;
and (3) carrying out difference between the obtained output parameter or feedback parameter and the numerical value acquired by the sensor, if the difference is within the range of the acquisition error of the sensor, acquiring data by the sensor is accurate, and if the difference exceeds the range of the acquisition error of the sensor, acquiring data by the sensor is incorrect.
2. The equipment platform sensor acquisition data accuracy verification method according to claim 1, wherein in step S1, the different requirements, including monitoring, diagnosis and health management, are selected according to the functional data and performance data required by different subjects.
3. The equipment platform sensor acquisition data accuracy verification method according to claim 1, wherein in step S21, the simulation analysis includes a circuit simulation analysis and a stress simulation analysis.
4. The equipment platform sensor acquisition data accuracy verification method of claim 1, wherein the accuracy of the sensor sampling data is dependent on a sensor accuracy problem and a sensor burst failure.
5. The method for verifying accuracy of data collected by sensors on an equipment platform according to claim 1 or 4, wherein in step S3, the functional inheritance method and the cross verification method each verify that the data collected by the third sensor is incorrect by accurately collecting the data from two sensors among the three sensors, and the specific process is as follows:
if the acquired data of the third sensor is deviated from the acquired data of the first sensor and the second sensor respectively, the accuracy of the third sensor is abnormal, and the acquired data of the third sensor is wrong;
if the third sensor alarms due to the self fault and the comparison result of the first sensor and the second sensor shows that the third sensor is abnormal, the third sensor is electrified again and faults are observed;
if the third sensor does not alarm due to the self-fault, and the comparison result of the first sensor and the second sensor shows that the third sensor is abnormal, the third sensor has a fault.
6. The method for verifying accuracy of data collected by a sensor on an equipment platform according to claim 1, wherein the step S3 and the step S4 are respectively different ways to verify accuracy of data collected by the sensor, and are in parallel relation.
7. A verification system for the accuracy verification method of the data collected by the equipment platform sensor according to claim 1, which is characterized in that the verification system comprises the following modules: the sensor type analysis module, the first sensor data verification module, the second sensor data verification module and the sensor data verification module are sequentially in communication connection;
the sensor type analysis module is used for obtaining the number, the type and the requirement of the required sensors according to the data in the database;
the first sensor data verification module is used for evaluating whether the positions and the number of the sensors are reasonable or not;
the second sensor data verification module is used for verifying the accuracy of data acquired by the sensors by using a plurality of sensors at different levels in the object;
the sensor data verification module is used for verifying the accuracy of the sensor sampling data according to a mathematical deduction model of the system in the object.
8. The authentication system of claim 7, wherein the authentication system,
the specific method for verifying the accuracy of the data acquired by the sensor by using a plurality of sensors at different levels in the object by the sensor data verification module is as follows: input parameter x of the system 1 And x 2 Respectively inputting the output parameters or the feedback parameters into a mathematical model of the system, wherein the expression of the mathematical model is as follows:
wherein k is 1 、k 2 And k 3 Parameters of the mathematical model;
and (3) carrying out difference between the obtained output parameter or feedback parameter and the numerical value acquired by the sensor, if the difference is within the range of the acquisition error of the sensor, acquiring data by the sensor is accurate, and if the difference exceeds the range of the acquisition error of the sensor, acquiring data by the sensor is incorrect.
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| CN117250576B (en) * | 2023-11-16 | 2024-01-26 | 苏芯物联技术(南京)有限公司 | Current sensor real-time abnormality detection method based on multidimensional sensing data |
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