CN109813358B - Sensor fault detection method based on redundant coupling signal diagnosis - Google Patents
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Abstract
The invention discloses a sensor fault detection method based on redundant coupling signal diagnosis, which comprises the following steps: 1. establishing a mathematical model among a fault-tolerant matrix, a sensor measurement value and an output vector; 2. initializing and assigning values of all parameters and matrixes; 3. determining a sensor that may have a problem; 4. the malfunctioning sensor is identified. The invention has simple structure, high flexibility and low cost, and can quickly realize the fault detection of the sensor.
Description
Technical Field
The invention belongs to the technical field of measurement and control, and particularly relates to a sensor fault detection method based on redundant coupling signal diagnosis.
Background
When the system fails, the intervention of the redundant configuration component can bear the work of the failed component, thereby reducing the failure time of the system and increasing the reliability of the system, so that the redundant component configuration is sometimes needed to be carried out on the physical quantity to be detected. For redundant components to be configured, such as two or more sensors, the reliability of the performance of each sensor itself also needs to be detected effectively in advance.
Signal coupling phenomena exist in the fields of communication, software, machinery, electronics and the like, and output signals of some force sensors are related to each force/moment component, so that signals to be detected can be obtained only by decoupling each path of output signals, and the difficulty of detecting faulty sensors in engineering application is increased.
Therefore, it is of great significance to design a fault detection method capable of rapidly realizing the sensor through redundant coupling signals.
Disclosure of Invention
The purpose of the invention is as follows: aiming at the defects, the invention provides the sensor fault detection method based on the redundant coupling signal diagnosis, which has the advantages of simple structure, high flexibility and low manufacturing cost, can quickly process the small and medium-scale redundant coupling signals and realizes the fault detection of the sensor.
The technical scheme is as follows: the invention provides a sensor fault detection method based on redundant coupling signal diagnosis, which comprises the following steps:
(1) establishing a mathematical model among a fault-tolerant matrix, a sensor measurement value and an output vector;
(2) carrying out initialization assignment on each parameter and matrix;
(3) judging each sensor to select a sensor with possible problems;
(4) the malfunctioning sensor is identified.
Further, the specific steps of constructing the mathematical model among the fault-tolerant matrix, the sensor measurement value and the output vector in the step (1) are as follows:
Ax＝b
the fault-tolerant matrix A is an m multiplied by n dimensional input matrix set according to actual engineering experience; the sensor measurement value x is an n multiplied by 1 dimensional column vector formed by actual acquisition parameters of a plurality of or various sensors, and each or every sensor reads one parameter each time; b is an m × 1-dimensional output column vector; m is the number of sensors input, and n is the measured value of the sensor signal input.
Further, the parameters and matrices for performing the initialization assignment in step (2) include a fault-tolerant matrix a, a sensor measurement value x, and a fault-tolerant threshold δ.
Further, the specific steps of judging each sensor in the step (3) and selecting a sensor with a possible problem are as follows:
(3.1) comparing the magnitude relation between each element in the output vector b and the set fixed fault-tolerant threshold value delta;
(3.2) find out the sensor number corresponding to possible problems.
Further, the specific step of comparing the magnitude relation between each element in the output vector b and the set fixed fault-tolerant threshold δ in the step (3.1) is as follows: assigning the output column vector b the row element value to be 0 when the row element of the output column vector b is smaller than a set fixed fault-tolerant threshold delta; if the element in the column vector b is larger than the set fixed fault-tolerant threshold delta, no processing is performed.
Further, the specific steps of finding out the sensor number corresponding to the possible problem in the step (3.2) are as follows: and finding out the matrix row of the fault-tolerant matrix A corresponding to the non-0 element of the output vector, wherein the non-0 element value corresponding to the row is the sensor number which is possibly problematic.
Further, the specific steps of identifying the faulty sensor in step (4) are as follows:
(4.1) finding out a matrix row of the fault-tolerant matrix A corresponding to the sensor with the possible problem;
(4.2) fetching the corresponding rows of the output vector, reconstructing the column vector;
(4.3) judging whether the sensor which may have problems is in failure or not, and finally determining the sensor which has the failure.
Further, the specific steps of finally determining the faulty sensor in step (4.3) are as follows: if the column vector constructed in step (4.2) is full rank, the possibly problematic sensor does fail and finally outputs the failed sensor number, whereas if the possibly problematic sensor does not have a failure, the sensor number is not output.
By adopting the technical scheme, the invention has the following beneficial effects:
the invention relates to a sensor fault detection method based on redundant coupling signal diagnosis, which is a data acquisition and analysis system developed by only using hardware resources and a software platform of a computer, has simple structure, high flexibility and low cost, can quickly process medium and small-scale redundant coupling signals, and realizes the fault detection of a sensor.
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FIG. 1 is a flow chart of the present invention.
Detailed Description
The present invention is further illustrated by the following examples, which are intended to be purely exemplary and are not intended to limit the scope of the invention, as various equivalent modifications of the invention will occur to those skilled in the art upon reading the present disclosure and fall within the scope of the appended claims.
As shown in fig. 1: the embodiment of the invention comprises the following steps:
the method comprises the following steps: establishing a mathematical model among a fault-tolerant matrix, a sensor measurement value and an output vector;
the mathematical relationship among the fault-tolerant matrix, the sensor measurement value and the output vector satisfies the following conditions:
Ax＝b (1)
the fault-tolerant matrix A is an m multiplied by n dimensional input matrix set according to actual engineering experience; the sensor measurement value x is an n multiplied by 1 dimensional column vector formed by actual acquisition parameters of a plurality of or various sensors, and each or every sensor reads one parameter each time; b is an m × 1-dimensional output column vector; m is the number of sensors input, and n is the measured value of the sensor signal input. For any 1 or more and k or more and m, ak1x1+ak2x2++aknxn＝bkIf the linear correlation of the formula (1) is required to be satisfied, the parameters in the set fault-tolerant matrix A must satisfy ak1 2+ak2 2++akn 2≠0。
Step two: initializing and assigning values of all parameters and matrixes;
the fault-tolerant matrix A, the sensor measurement value x and the fault-tolerant threshold value delta are respectively as follows:
x＝[7 4 3 1 2 2]T (3)
δ＝0.2 (4)
as can be seen from the expressions (2) and (3), the No. 1 sensor, the No. 3 sensor and the No. 5 sensor have a coupling relationship with each other, and the No. 2 sensor, the No. 4 sensor and the No. 6 sensor have a coupling relationship with each other.
Step three: determining a sensor that may have a problem;
obtaining an m multiplied by 1 column vector b by a set m multiplied by n dimensional fault-tolerant matrix A and an n multiplied by 1 dimensional column vector x, comparing each row element of the column vector b with a set fixed fault-tolerant threshold delta, and if the row element of the column vector b is smaller than the set fixed fault-tolerant threshold delta, assigning the row element value of the column vector b to be 0; if the element in the column vector b is larger than the set fixed fault tolerance threshold delta, no processing is performed.
The column vector b obtained by calculation is shown as formula (5):
b＝[1 0 1 0 0]T (5)
since the fault tolerance threshold δ is 0.2, there is no nonzero value less than the fixed fault tolerance threshold, so the resolved column vector b is not processed.
The non-zero elements of each row of the column vector b correspond to sensor numbers which may have problems, i.e. the fault-tolerant matrix a corresponds to a sequence number of which the row coefficient is not 0. The column vector b exceeding the fault tolerance threshold δ is shown as the first row and the third row by equation (5), and the first row of the column vector b is shown as the sensor numbers 1 and 5 corresponding to the possible problems by equation (2); from equation (2), it can be seen that the third row of the column vector b corresponds to the sensor numbers 1 and 3, which may be problematic.
Step four: the malfunctioning sensor is identified.
The first row of the column vector b corresponds to the sensor numbers 1 and 5 which may have problems, the matrix rows related to the sensor number 1 are the first row and the third row as can be seen from the formula (2), and the column vector formed by the rows where the sensor numbers are located as can be seen from the formula (5)
The formula (2) shows that the matrix rows related to the No. 5 sensor are the first row and the fifth row, and the formula (5) shows that the column vectors formed by the rows are positioned
The third row of the column vector b corresponds to the sensor numbers 1 and 3 which may have problems, the matrix row related to the sensor number 1 is the first row and the third row as can be known from the formula (2), and the column vector formed by the rows in which the sensor numbers are located as can be known from the formula (5)
The matrix rows associated with sensor number 3 are shown in equation (2) as the third and fifth rows, and in equation (5) as the fifth rowColumn vector formed by rows
Sensor number 1 fails because the column vector formed by the matrix rows associated with sensor number 1 is full rank.
Claims (4)
1. A method for detecting sensor faults based on redundant coupled signal diagnostics, comprising the steps of:
(1) establishing a mathematical model among a fault-tolerant matrix, a sensor measurement value and an output column vector;
(2) carrying out initialization assignment on each parameter and matrix;
(3) judging each sensor to select a sensor with possible problems;
(4) confirming a faulty sensor;
the specific steps of judging each sensor in the step (3) and selecting the sensor with possible problems are as follows:
(3.1) comparing the magnitude relation between each element in the output column vector b and the set fixed fault-tolerant threshold value delta;
(3.2) finding out the sensor number corresponding to the possible problem;
the specific steps for confirming the sensor with the fault in the step (4) are as follows:
(4.1) finding out matrix rows of the fault-tolerant matrix A corresponding to the sensors which are possibly in problems;
(4.2) fetching the corresponding rows of the output column vector, reconstructing the column vector;
(4.3) judging whether the sensor which possibly has problems breaks down or not, and finally determining the broken-down sensor;
the specific steps of establishing a mathematical model among the fault-tolerant matrix, the sensor measurement value and the output column vector in the step (1) are as follows:
Ax＝b
the fault-tolerant matrix A is an m multiplied by n dimensional input matrix set according to actual engineering experience; the sensor measurement value x is an n multiplied by 1 dimensional column vector formed by actual acquisition parameters of a plurality of or various sensors, and each or every sensor reads one parameter each time; b is an m × 1-dimensional output column vector; n in the m multiplied by n dimensional input matrix is the number of input sensors, and n in the n multiplied by 1 dimensional column vector is the measured value of the input sensor signal;
and (3) each parameter and matrix subjected to initialization assignment in the step (2) comprise a fault-tolerant matrix A, a sensor measurement value x and a fault-tolerant threshold value delta.
2. The method for detecting sensor faults based on redundant coupled signal diagnosis as claimed in claim 1, wherein the step (3.1) of comparing the magnitude relation between each element in the output column vector b and the set fixed fault tolerance threshold δ is as follows: assigning the output column vector b the row element value to be 0 when the row element of the output column vector b is smaller than a set fixed fault-tolerant threshold delta; if the element in the column vector b is larger than the set fixed fault-tolerant threshold delta, no processing is performed.
3. The method for detecting sensor faults based on redundant coupled signal diagnosis as claimed in claim 2, wherein the specific steps of finding the corresponding possibly problematic sensor number in the step (3.2) are as follows: and finding out the matrix row of the fault-tolerant matrix A corresponding to the non-0 element of the output column vector, wherein the value serial number of the non-0 element corresponding to the row is the sensor serial number possibly having problems.
4. The method for detecting sensor faults based on redundant coupled signal diagnosis as claimed in claim 3, wherein the specific steps of finally determining the faulty sensor in the step (4.3) are as follows: if the column vector constructed in step (4.2) is full rank, the possibly problematic sensor does fail and finally outputs the failed sensor number, whereas if the possibly problematic sensor does not have a failure, the sensor number is not output.
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| CN102183674A (en) * | 2011-03-11 | 2011-09-14 | 东南大学 | Low redundancy and high reliability intelligent speed measuring equipment for ship generator set |
| CN103440418A (en) * | 2013-08-30 | 2013-12-11 | 中南大学 | Multi-sensor active fault-tolerant estimation method based on self-organization Kalman filtering |
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