CN111915858A - Alarm method and system fusing analog quantity and digital quantity related information - Google Patents

Alarm method and system fusing analog quantity and digital quantity related information Download PDF

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CN111915858A
CN111915858A CN202010774350.9A CN202010774350A CN111915858A CN 111915858 A CN111915858 A CN 111915858A CN 202010774350 A CN202010774350 A CN 202010774350A CN 111915858 A CN111915858 A CN 111915858A
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CN111915858B (en
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王建东
肖艳
王振
张超
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Shandong University of Science and Technology
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Abstract

The invention belongs to the technical field of industrial big data analysis, and provides an alarm method and system for fusing analog quantity and digital quantity related information. The alarm method for fusing the analog quantity and digital quantity related information comprises the following steps: acquiring alarm information of at least two sensors for monitoring the same variable in real time; the alarm information monitored by at least one sensor is a digital quantity signal, and the alarm information monitored by at least one sensor is an analog quantity signal; respectively converting alarm information monitored by all sensors into corresponding Gaussian time sequences; quantifying a level of correlation between any two gaussian time series; and (4) screening out the two Gaussian time sequences with the maximum correlation coefficient, fusing the two screened Gaussian time sequences into an alarm message according to the credibility, and converting the alarm message into a corresponding digital quantity signal for alarming.

Description

Alarm method and system fusing analog quantity and digital quantity related information
Technical Field
The invention belongs to the technical field of industrial big data analysis, and particularly relates to an alarm method and system for fusing analog quantity and digital quantity related information.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
The alarm system is a system for monitoring the operation condition of equipment and reminding workers of handling abnormal conditions in time. The inventor finds that when the monitoring equipment operates, single alarm information is often adopted for alarming, but the single information has randomness and uncertainty, so that the alarm information is inaccurate, and the reliability of an alarm system is reduced.
Disclosure of Invention
In order to solve the problems, the invention provides an alarm method and an alarm system for fusing analog quantity and digital quantity related information, wherein alarm information of the same variable is monitored in real time through a plurality of sensors, the correlation of the alarm information is quantized, and a digital quantity signal and an analog quantity signal with the maximum correlation coefficient are fused based on reliability to obtain final alarm information, so that the reliability of the alarm system is improved.
In order to achieve the purpose, the invention adopts the following technical scheme:
the invention provides an alarm method for fusing analog quantity and digital quantity related information.
An alarm method for fusing analog quantity and digital quantity related information comprises the following steps:
acquiring alarm information of at least two sensors for monitoring the same variable in real time; the alarm information monitored by at least one sensor is a digital quantity signal, and the alarm information monitored by at least one sensor is an analog quantity signal;
respectively converting alarm information monitored by all sensors into corresponding Gaussian time sequences;
quantifying a level of correlation between any two gaussian time series;
and (4) screening out the two Gaussian time sequences with the maximum correlation coefficient, fusing the two screened Gaussian time sequences into an alarm message according to the credibility, and converting the alarm message into a corresponding digital quantity signal for alarming.
The second aspect of the invention provides an alarm system for fusing analog quantity and digital quantity related information.
An alarm system fusing information related to analog quantity and digital quantity, comprising:
the alarm signal acquisition module is used for acquiring alarm information of monitoring the same variable by at least two sensors in real time; the alarm information monitored by at least one sensor is a digital quantity signal, and the alarm information monitored by at least one sensor is an analog quantity signal;
the Gaussian time sequence conversion module is used for respectively converting the alarm information monitored by all the sensors into corresponding Gaussian time sequences;
a correlation level quantization module for quantizing a correlation level between any two gaussian time series;
and the alarm information fusion module is used for screening out the two Gaussian time sequences with the maximum correlation coefficient, fusing the two screened Gaussian time sequences into an alarm information according to the credibility and converting the alarm information into a corresponding digital quantity signal for alarming.
A third aspect of the invention 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, implements the steps of the above-mentioned alarm method for fusing information related to analog and digital quantities.
A fourth aspect of the invention provides a computer apparatus.
A computer device, comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps of the alarm method for fusing the information related to the analog quantity and the digital quantity.
Compared with the prior art, the invention has the beneficial effects that:
(1) the invention monitors the alarm information of the same variable in real time through a plurality of sensors, quantifies the correlation of a plurality of pieces of alarm information, and obtains the final alarm information based on the alarm information with higher reliability fusion correlation, thereby improving the reliability of the alarm system.
(2) The invention takes the two Gaussian time sequences with the maximum correlation coefficient screened out based on the credibility fusion as the final alarm information, thereby overcoming the randomness and uncertainty of the single alarm information.
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The accompanying drawings, which are incorporated in and constitute a part of this specification, are included to provide a further understanding of the invention, and are incorporated in and constitute a part of this specification, illustrate exemplary embodiments of the invention and together with the description serve to explain the invention and not to limit the invention.
FIG. 1 is a flow chart of an alarm method for fusing analog quantity and digital quantity related information according to an embodiment of the present invention;
FIG. 2(a) is a schematic diagram of an alarm message monitored by a sensor according to an embodiment of the present invention as a digital signal;
FIG. 2(b) is a Gaussian time sequence corresponding to the digital signal according to the embodiment of the present invention;
FIG. 3(a) is a schematic diagram of process signals and alarm thresholds according to an embodiment of the present invention;
fig. 3(b) shows alarm information ya (t) according to the embodiment of the present invention;
fig. 3(c) is a gaussian time sequence corresponding to the alarm information ya (t) in the embodiment of the present invention;
fig. 3(d) shows alarm information xa (t) according to the embodiment of the present invention;
fig. 3(e) is a gaussian time sequence corresponding to the alarm information xa (t) in the embodiment of the present invention;
FIG. 4(a) is a final Gaussian time series corresponding alarm information according to an embodiment of the present invention;
fig. 4(b) is a digital quantity signal corresponding to the final alarm information according to the embodiment of the present invention.
Detailed Description
The invention is further described with reference to the following figures and examples.
It is to be understood that the following detailed description is exemplary and is intended to provide further explanation of the invention as claimed. 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 invention 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 exemplary embodiments according to the invention. 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.
Example one
Referring to fig. 1, the embodiment provides an alarm method for fusing information related to analog quantity and digital quantity, which includes:
s101: acquiring alarm information of at least two sensors for monitoring the same variable in real time; the alarm information monitored by at least one sensor is a digital quantity signal, and the alarm information monitored by at least one sensor is an analog quantity signal.
S102: and respectively converting alarm information monitored by all the sensors into corresponding Gaussian time sequences.
For a digital quantity signal:
as shown in FIGS. 2(a) -2 (b), the alarm signal Y is extracteda(t) converting the alarm signal into a Gaussian time sequence according to a formula (1) at the starting time and the duration of each alarm;
Figure BDA0002617838310000041
wherein, tjThe beginning time of the jth alarm is h is the bandwidth;
in addition, the selection of h will be on the generated pseudo-time series ya(t) has a great influence. The embodiment will start time t of each alarmsIs determined as tjWill last for a time tdDetermined as h, i.e.: t is tj＝ts，h＝tdTherefore, equation (1) is rewritten as:
Figure BDA0002617838310000051
wherein, ts,jAnd td,jRespectively being an alarm signal Ya(t) the start time and duration of the alarm of the jth (j-1, 2, …, N) occurrence, NyIs an alarm signal Ya(t) number of occurrences of alarms.
For analog quantity signals:
given alarm threshold range a b]The step duration is 0.1, the analog quantity signals are analyzed, and each alarm limit corresponds to a group of alarm signals Xa,i(t), generating n ═ b-a)/0.1 alarm signals to form alarm signal set Xa,:(t)＝{Xa,1(t),Xa,2(t),…,Xa,n(t)}。
Estimating the related delay time according to the following formula, obtaining the actual delay time tau when S is maximum to generate a new alarm signal set Xa,:(t+τ)＝{Xa,1(t+τ),Xa,2(t+τ),…,Xa,n(t+τ)}。
Figure BDA0002617838310000052
Wherein, C: length of alarm signal: n is a radical of1: number of middle '1', N2：Xa,i(t) the number of ` 1 `;
extracting the starting time and the duration time of each alarm signal in the alarm signal set, and converting the alarm signals into a Gaussian time sequence set x according to a formula (3)a,:(t+τ)＝{xa,1(t+τ),xa,2(t+τ),…,xa,n(t+τ)}：
Figure BDA0002617838310000053
S103: the level of correlation between any two gaussian time series is quantified.
In a specific implementation, when the number of sensors exceeds two, the level of quantitative correlation is made between any two resulting gaussian time series.
As shown in FIG. 3(a) -FIG. 3(b)e) Shown is a Gaussian time series x corresponding to any two sensorsa,i(t + τ) and ya(t) is an example:
Figure BDA0002617838310000061
wherein the content of the first and second substances,
Figure BDA0002617838310000069
are respectively xa,i(t) and ya(t) average value; sx，SyAre respectively xa,i(t) and ya(t) standard deviation; n is the data length; r isxyIs a Gaussian-shaped time series xa,i(t + τ) and ya(t) correlation coefficient.
Determining the alarm signal X corresponding to the maximum correlation coefficient found by the method based on the hypothesis test methoda,i(t) with a predetermined warning signal Ya(t) whether there is a correlation.
To examine the original hypothesis H0Rho is 0, and rho is a correlation coefficient; alternative hypothesis H1Rho ≠ 0. According to
Figure BDA0002617838310000062
L represents approximate compliance, corresponding to infinite approach; when the former hypothesis H0When it is established, there are
Figure BDA0002617838310000063
Will be provided with
Figure BDA0002617838310000064
As a test statistic, then for a given significance level α, look up a table of N (0,1) with a threshold value of U1-α/2So that
Figure BDA0002617838310000065
If it is
Figure BDA0002617838310000066
Negative H0The signals are considered to have a correlation therebetween.
S104: and (4) screening out the two Gaussian time sequences with the maximum correlation coefficient, fusing the two screened Gaussian time sequences into an alarm message according to the credibility, and converting the alarm message into a corresponding digital quantity signal for alarming.
In a specific implementation, the measurement system is provided with n sensors, and the n sensors are used for respectively measuring a certain research object. Let the measured value at the moment k of the ith sensor be si(k)＝x+vi(i ═ 1,2, …, n). Where x is the true value of the sampled data, viIs s isiMeasurement noise at time k.
Each sensor measurement is treated as a fuzzy set. According to fuzzy mathematical theory, the closeness between two fuzzy sets can be measured in closeness. The maximum and minimum closeness in fuzzy mathematics is adopted for measurement, and the closeness of the measurement values of the sensor i and the sensor j at the moment k is as follows:
Figure BDA0002617838310000067
and calculating the closeness among the sensors at the moment k, and further forming a reliability matrix:
Figure BDA0002617838310000068
the ith row of the confidence matrix represents the sensor measurement siAnd the mutual support degree between the measured values of other sensors. Mean representation s of row iiThe degree of mutual average support with other sensors, and the variance represents the degree of deviation from other sensors:
Figure BDA0002617838310000071
calculating the weight occupied by the ith sensor measurement value at the moment k, and normalizing the weight:
Figure BDA0002617838310000072
based on credibility data fusion, the method better avoids the influence of subjective factors, thereby more truly depicting the importance degree of each sampling sequence. Therefore, data fusion is carried out by using the credibility, fusion data of two most relevant sensor measurement values at the moment k are obtained through calculation, and fusion data of the whole system are further obtained:
Figure BDA0002617838310000073
wherein x isf(k) The accurate value of each sampling moment; x is the number offAlarm information of the whole sampling moment; n is the total number of samples.
In the embodiment, the alarm signals acquired by the sensor are converted into a Gaussian time sequence according to a Gaussian kernel density function, and if conditions allow, alarm information with certain correlation is fused based on credibility to serve as final alarm information;
the conditions for allowing the alarm information to be fused are as follows:
giving an alarm threshold range [ a: b ] according to historical samples]The stepping time length is 0.1, the collected process signals are analyzed, and each alarm limit corresponds to a group of alarm signals Xa,i(t), generating n ═ (b-a)/0.1 group of alarm signals to form alarm signals;
providing a method for estimating correlation delay between alarm signals to obtain actual delay time, generating a new group of alarm signals, converting the alarm signals into a Gaussian time sequence according to a Gaussian kernel density function, and quantizing the correlation by adopting a Pearson correlation coefficient method;
finding out two groups of alarm information with the maximum correlation coefficient, and fusing the two groups of alarm information into a more accurate alarm signal according to the credibility, wherein the result is shown in figures 4(a) -4 (b);
the following is an application of the method described in this embodiment in a specific example:
all the industrial examples are based on process variables x (t), alarm signal Ya(t) asLow water adding level value of low pressure heater from large power plant and low alarm signal.
(a) Extracting alarm signal Ya(t) the start time and duration of each alarm signal, converting it into a gaussian time series;
(b) analyzing the process signal, x (t) giving an alarm threshold range [ -40: -10 [)]In 0.1 steps, 300 sets of alarm signals are generated. The delay time is estimated and 300 new sets of alarm signals are generated. These 300 sets of alarm signals were then converted into 300 gaussian time series. Finally, the alarm threshold and the alarm signal X corresponding to the maximum correlation coefficient are found through the quantitative correlation level of the Pearson correlation coefficienta(t)；
(c) Obtaining the corresponding alarm signal X when the correlation coefficient is maximum by a hypothesis testing methoda(t) with a predetermined warning signal Ya(t) has a strong correlation. And further fusing a Gaussian time sequence generated by the two alarm signals according to the consistent reliability measure to obtain final alarm information.
Example two
The embodiment provides an alarm system for fusing analog quantity and digital quantity related information, which comprises:
(1) the alarm signal acquisition module is used for acquiring alarm information of monitoring the same variable by at least two sensors in real time; the alarm information monitored by at least one sensor is a digital quantity signal, and the alarm information monitored by at least one sensor is an analog quantity signal.
(2) And the Gaussian time sequence conversion module is used for converting the alarm information monitored by all the sensors into corresponding Gaussian time sequences respectively.
For a digital quantity signal: extracting alarm signal Ya(t) converting the alarm signal into a Gaussian time sequence according to a formula (1) at the starting time and the duration of each alarm;
Figure BDA0002617838310000091
wherein, tjThe beginning time of the jth alarm is h is the bandwidth;
in addition, the selection of h will be on the generated pseudo-time series ya(t) has a great influence. The embodiment will start time t of each alarmsIs determined as tjWill last for a time tdDetermined as h, i.e.: t is tj＝ts，h＝tdTherefore, equation (1) is rewritten as:
Figure BDA0002617838310000092
wherein, ts,jAnd td,jRespectively being an alarm signal Ya(t) the start time and duration of the alarm of the jth (j-1, 2, …, N) occurrence, NyIs an alarm signal Ya(t) number of occurrences of alarms.
For analog quantity signals:
given alarm threshold range a b]The step duration is 0.1, the analog quantity signals are analyzed, and each alarm limit corresponds to a group of alarm signals Xa,i(t), generating n ═ b-a)/0.1 alarm signals to form alarm signal set Xa,:(t)＝{Xa,1(t),Xa,2(t),…,Xa,n(t)}。
Estimating the related delay time according to the following formula, obtaining the actual delay time tau when S is maximum to generate a new alarm signal set Xa,:(t+τ)＝{Xa,1(t+τ),Xa,2(t+τ),…,Xa,n(t+τ)}。
Figure BDA0002617838310000093
Wherein, C: length of alarm signal: n is a radical of1: number of middle '1', N2：Xa,i(t) the number of ` 1 `;
extracting the starting time and the duration time of each alarm signal in the alarm signal set, and converting the alarm signals into a Gaussian time sequence set x according to a formula (3)a,:(t+τ)＝{xa,1(t+τ),xa,2(t+τ),…,xa,n(t+τ)}：
Figure BDA0002617838310000101
(3) A correlation level quantization module for quantizing a correlation level between any two Gaussian-shaped time series.
In a specific implementation, when the number of sensors exceeds two, the level of quantitative correlation is made between any two resulting gaussian time series.
Gaussian time series x corresponding to any two sensorsa,i(t + τ) and ya(t) is an example:
Figure BDA0002617838310000102
wherein the content of the first and second substances,
Figure BDA0002617838310000103
are respectively xa,i(t) and ya(t) average value; sx，SyAre respectively xa,i(t) and ya(t) standard deviation; n is the data length; r isxyIs a Gaussian-shaped time series xa,i(t + τ) and ya(t) correlation coefficient.
Determining the alarm signal X corresponding to the maximum correlation coefficient found by the method based on the hypothesis test methoda,i(t) with a predetermined warning signal Ya(t) whether there is a correlation.
To examine the original hypothesis H0Rho is 0, and rho is a correlation coefficient; alternative hypothesis H1Rho ≠ 0. According to
Figure BDA0002617838310000104
L represents approximate compliance, corresponding to infinite approach; when the former hypothesis H0When it is established, there are
Figure BDA0002617838310000105
Will be provided with
Figure BDA0002617838310000106
As a test statistic, then for a given significance level α, look up a table of N (0,1) with a threshold value of U1-α/2So that
Figure BDA0002617838310000107
If it is
Figure BDA0002617838310000108
Negative H0The signals are considered to have a correlation therebetween.
(4) And the alarm information fusion module is used for screening out the two Gaussian time sequences with the maximum correlation coefficient, fusing the two screened Gaussian time sequences into an alarm information according to the credibility and converting the alarm information into a corresponding digital quantity signal for alarming.
In a specific implementation, the measurement system is provided with n sensors, and the n sensors are used for respectively measuring a certain research object. Let the measured value at the moment k of the ith sensor be si(k)＝x+vi(i ═ 1,2, …, n). Where x is the true value of the sampled data, viIs s isiMeasurement noise at time k.
Each sensor measurement is treated as a fuzzy set. According to fuzzy mathematical theory, the closeness between two fuzzy sets can be measured in closeness. The maximum and minimum closeness in fuzzy mathematics is adopted for measurement, and the closeness of the measurement values of the sensor i and the sensor j at the moment k is as follows:
Figure BDA0002617838310000111
and calculating the closeness among the sensors at the moment k, and further forming a reliability matrix:
Figure BDA0002617838310000112
the ith row of the confidence matrix represents the sensor measurement siMutual offset with other sensor measurementsThe degree of persistence. Mean representation s of row iiThe degree of mutual average support with other sensors, and the variance represents the degree of deviation from other sensors:
Figure BDA0002617838310000113
calculating the weight occupied by the ith sensor measurement value at the moment k, and normalizing the weight:
Figure BDA0002617838310000114
based on credibility data fusion, the method better avoids the influence of subjective factors, thereby more truly depicting the importance degree of each sampling sequence. Therefore, data fusion is carried out by using the credibility, fusion data of two most relevant sensor measurement values at the moment k are obtained through calculation, and fusion data of the whole system are further obtained:
Figure BDA0002617838310000115
wherein x isf(k) The accurate value of each sampling moment; x is the number offAlarm information of the whole sampling moment; n is the total number of samples.
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 alarm method for fusing information related to analog quantity and digital quantity according to the first embodiment.
Example four
The embodiment provides a computer device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps in the alarm method for fusing the information related to the analog quantity and the digital quantity according to the first embodiment.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of a hardware embodiment, a software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention 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 invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. 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.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (10)

1. An alarm method for fusing analog quantity and digital quantity related information is characterized by comprising the following steps:
acquiring alarm information of at least two sensors for monitoring the same variable in real time; the alarm information monitored by at least one sensor is a digital quantity signal, and the alarm information monitored by at least one sensor is an analog quantity signal;
respectively converting alarm information monitored by all sensors into corresponding Gaussian time sequences;
quantifying a level of correlation between any two gaussian time series;
and (4) screening out the two Gaussian time sequences with the maximum correlation coefficient, fusing the two screened Gaussian time sequences into an alarm message according to the credibility, and converting the alarm message into a corresponding digital quantity signal for alarming.
2. The alarm method for fusing the information related to the analog quantity and the digital quantity according to claim 1, wherein when the alarm information monitored by the sensor is a digital quantity signal, the digital quantity signal is converted into a gaussian time series according to a gaussian kernel density function.
3. The alarm method for fusing the information related to the analog quantity and the digital quantity as claimed in claim 1, wherein when the alarm information monitored by the sensor is an analog quantity signal, the process of converting the analog quantity signal into a gaussian time series comprises the following steps:
giving an analog quantity signal alarm threshold range and stepping duration to generate a plurality of groups of analog quantity signals;
and estimating the correlation delay time between the analog quantity signals, obtaining all groups of analog quantity signals containing the actual delay time and converting the analog quantity signals into Gaussian time sequences.
4. The alarm method for fusing analog quantity and digital quantity related information according to claim 3, wherein all the sets of analog quantity signals containing the actual delay time are converted into corresponding Gaussian-shaped time series according to a Gaussian kernel density function.
5. The alarm method for fusing analog quantity and digital quantity related information according to claim 1, wherein a pearson correlation coefficient method is used to quantify the correlation level between any two gaussian time series.
6. The alarm method for fusing analog quantity and digital quantity related information according to claim 1, wherein it is determined whether one of the gaussian time series corresponding to the selected maximum correlation coefficient has a correlation with another gaussian time series given in advance by a hypothesis test method.
7. The alarm method for fusing the information related to the analog quantity and the digital quantity as claimed in claim 1, wherein the two screened Gaussian time sequences are respectively multiplied by the weight occupied by the measured value of the corresponding sensor and then accumulated to obtain fused alarm information; the weight occupied by the sensor measurement value is a normalized value of the ratio of the mean value and the corresponding variance of the mutual support degree of the corresponding sensor measurement value and other sensors.
8. An alarm system fusing information related to analog quantity and digital quantity, comprising:
the alarm signal acquisition module is used for acquiring alarm information of monitoring the same variable by at least two sensors in real time; the alarm information monitored by at least one sensor is a digital quantity signal, and the alarm information monitored by at least one sensor is an analog quantity signal;
the Gaussian time sequence conversion module is used for respectively converting the alarm information monitored by all the sensors into corresponding Gaussian time sequences;
a correlation level quantization module for quantizing a correlation level between any two gaussian time series;
and the alarm information fusion module is used for screening out the two Gaussian time sequences with the maximum correlation coefficient, fusing the two screened Gaussian time sequences into an alarm information according to the credibility and converting the alarm information into a corresponding digital quantity signal for alarming.
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 alarm method of fusing analog-quantity-related information and digital-quantity-related information according to any one of claims 1 to 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 fusing information relating to analog and digital quantities according to any one of claims 1 to 7 when executing the program.
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