CN111178554B - Equipment health management method, system and radar - Google Patents

Equipment health management method, system and radar Download PDF

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CN111178554B
CN111178554B CN201911320291.1A CN201911320291A CN111178554B CN 111178554 B CN111178554 B CN 111178554B CN 201911320291 A CN201911320291 A CN 201911320291A CN 111178554 B CN111178554 B CN 111178554B
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equipment
state
component
temperature
score
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CN111178554A (en
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高心军
蔡红维
彭飞
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Beijing Institute of Radio Measurement
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/20—Administration of product repair or maintenance
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/40—Means for monitoring or calibrating
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
    • G06Q50/04—Manufacturing
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/30—Computing systems specially adapted for manufacturing
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S10/00—Systems supporting electrical power generation, transmission or distribution
    • Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications

Abstract

The application relates to a device health management method, a system and a radar, which are characterized in that firstly, a pre-output mode set is determined according to the mapping relation between each component of a device and each corresponding fault mode, then, the actual corresponding relation is obtained after the actual output state of the device is obtained and the pre-output mode in the pre-output mode set is compared with the pre-output mode, on one hand, the corresponding fault mode and the fault component can be accurately judged according to the actual corresponding relation, and maintenance personnel can conveniently maintain the device; on the other hand, the residual service life of the equipment can be determined according to the actual output state, so that maintenance personnel can know the health condition of the equipment in real time conveniently, that is, the reasonable health management of the equipment is realized by establishing a model of the correlation between the pre-output mode set and the actual output state.

Description

Equipment health management method, system and radar
Technical Field
The present application relates to the field of device management, and in particular, to a device health management method, system, and radar.
Background
In order to adapt to the comprehensive guarantee requirement of radar equipment, the defects of the traditional regular after-the-fact maintenance guarantee mode are changed, the quality and efficiency of equipment guarantee are improved, an advanced testing, maintenance and management technology is put forward in the United states at the end of the 20 th century, namely fault prediction and health state management (Prognostics and Health Management, PHM), various information acquired by a monitoring system in real time is utilized, the current state of the whole equipment is evaluated through an intelligent algorithm, and the radar system fault can be effectively predicted through monitoring various indexes just like physical examination of a human body. The health management is a comprehensive fault detection, isolation, prediction and state management control technology, which can effectively improve the task reliability of radar work, but in the current research, the technical architecture related to the health management is more, the research related to a model algorithm is less, some devices such as the health state and fault information of the radar are huge and disordered, some information can be difficult to quantify, some information can be useless data, and the rationality of carrying out health management on the radar system is lower just because of the lack of a reasonable health management model.
Therefore, how to propose a model to reasonably manage health of a device is a technical problem to be solved in the industry.
Disclosure of Invention
The application aims to solve the technical problem of providing a device health management method, a device health management system and a radar aiming at the defects of the prior art.
The technical scheme of the equipment health management method, the system and the radar is as follows:
s1, acquiring each fault mode of equipment, establishing a mapping relation between each component of the equipment and each corresponding fault mode, and determining different pre-output modes of the equipment according to each mapping relation, and recording the different pre-output modes as a pre-output mode set;
s2, acquiring an actual output state of the equipment, obtaining a mapping relation corresponding to the actual output state according to the pre-output mode set, marking the mapping relation as an actual corresponding relation, and determining a corresponding fault mode and a fault assembly according to the actual corresponding relation or determining the residual life of the equipment according to the actual output state.
The equipment health management method has the beneficial effects that:
firstly, determining a pre-output mode set according to the mapping relation between each component of the equipment and each corresponding fault mode, and then comparing the pre-output mode set with the pre-output mode in the pre-output mode set to obtain an actual corresponding relation by acquiring the actual output state of the equipment; on the other hand, the residual service life of the equipment can be determined according to the actual output state, so that maintenance personnel can know the health condition of the equipment in real time conveniently, that is, the application extracts useful information in the whole service life period of the equipment by establishing a model of correlation between the pre-output mode set and the actual output state, evaluates and predicts the service state of the equipment and provides maintenance and guarantee decisions, lays a foundation for the reliability of the equipment, and realizes reasonable health management of the equipment.
The technical scheme of the equipment health management system is as follows:
the system comprises a pre-establishment module and a prediction module;
the pre-establishing module acquires each fault mode of the equipment, establishes a mapping relation between each component of the equipment and each corresponding fault mode, and determines different pre-output modes of the equipment according to each mapping relation to be recorded as a pre-output mode set;
the prediction module obtains the actual output state of the equipment, obtains a mapping relation corresponding to the actual output state according to the pre-output mode set, marks the mapping relation as an actual corresponding relation, and determines a corresponding fault mode and a fault component according to the actual corresponding relation or determines the residual life of the equipment according to the actual output state.
The equipment health management system has the beneficial effects that:
firstly, a pre-establishing module establishes a mapping relation between each component of the equipment and each corresponding fault mode, a pre-output mode set is determined, then an actual corresponding relation is obtained after the actual output state of the equipment is obtained and is compared with the pre-output modes in the pre-output mode set, on one hand, the corresponding fault modes and the fault components can be accurately judged according to the actual corresponding relation, and maintenance personnel can conveniently maintain the equipment; on the other hand, the residual service life of the equipment can be determined according to the actual output state, so that maintenance personnel can know the health condition of the equipment in real time conveniently, that is, the application extracts useful information in the whole service life period of the equipment by establishing a model of correlation between the pre-output mode set and the actual output state, evaluates and predicts the service state of the equipment and provides maintenance and guarantee decisions, lays a foundation for the reliability of the equipment, and realizes reasonable health management of the equipment.
The technical scheme of the radar of the application is as follows: the device health management system comprises a control chip, wherein the control chip is used for executing the device health management method according to any one of the above.
The beneficial effects of the radar of the application are that: the control chip firstly obtains the mapping relation between each component of the radar and each corresponding fault mode, determines a pre-output mode set, and then obtains an actual corresponding relation after comparing the actual output state of the device with the pre-output modes in the pre-output mode set, on one hand, the corresponding fault modes and the fault components can be accurately judged according to the actual corresponding relation, and maintenance personnel can conveniently maintain the radar; on the other hand, the residual life of the radar can be determined according to the actual output state, so that maintenance personnel can know the health condition of the equipment in real time.
Drawings
Fig. 1 is a schematic flow chart of a device health management method according to an embodiment of the present application;
FIG. 2 is a schematic diagram of an impact level framework of a subsystem;
FIG. 3 is a fitted curve of the fitting equation;
FIG. 4 is a schematic diagram illustrating a configuration of an apparatus health management system according to an embodiment of the present application;
Detailed Description
As shown in fig. 1, a device health management method according to an embodiment of the present application includes the following steps:
s1, acquiring each fault mode of equipment, establishing a mapping relation between each component of the equipment and each corresponding fault mode, and determining different pre-output modes of the equipment according to each mapping relation, and recording the different pre-output modes as a pre-output mode set;
s2, acquiring an actual output state of the equipment, obtaining a mapping relation corresponding to the actual output state according to the pre-output mode set, marking the mapping relation as an actual corresponding relation, and determining a corresponding fault mode and a fault assembly according to the actual corresponding relation or determining the residual life of the equipment according to the actual output state.
Firstly, determining a pre-output mode set according to the mapping relation between each component of the equipment and each corresponding fault mode, and then comparing the pre-output mode set with the pre-output mode in the pre-output mode set to obtain an actual corresponding relation by acquiring the actual output state of the equipment; on the other hand, the residual service life of the equipment can be determined according to the actual output state, so that maintenance personnel can know the health condition of the equipment in real time conveniently, that is, the application extracts useful information in the whole service life period of the equipment by establishing a model of correlation between the pre-output mode set and the actual output state, evaluates and predicts the service state of the equipment and provides maintenance and guarantee decisions, lays a foundation for the reliability of the equipment, and realizes reasonable health management of the equipment.
Preferably, in the above technical solution, the establishing the mapping relationship specifically includes the following steps:
acquiring the temperature and state of an ith component of the equipment and expressing the ith component b by a first formula i The corresponding relation between the first formula and the corresponding fault mode is as follows:
wherein x is i，1 Indicating the temperature of the ith component, x i，2 Representing the state of the ith component, x i，1 And x i，2 The value of (1) is 0 or 1, (0, 0) indicates that the ith component is in a normal state, (1, 0) indicates that the temperature of the ith component exceeds the standard, (0, 1) indicates that the ith component is in a fault state, (1, 1) indicates that the ith component is in a fault state and the temperature exceeds the standard, and i is a positive integer;
s11, establishing a second formula:bringing the first formula into the second formula yields:
wherein b i Representing the output value of the ith component, (x) i，1 ，x i，2 ) And b i The relation between the i-th component and the corresponding fault mode;
s12, repeatedly executing S10 to S11, and determining the mapping relation between each component of the equipment and each corresponding fault mode. And establishing a mapping relation between each component of the equipment and each corresponding fault mode through mathematical modeling.
Taking a radar subsystem as an example, the following details are described: the subsystem comprises 29 components, the output values of which are respectively marked as b 1 ，b 2 ，...b i ，...b 29 The D matrix of a subsystem can be output according to an established radar subsystem testability model, a general fault diagnosis inference engine based on testability modeling, namely a multi-signal flow model is utilized, the finally formed diagnosis positioning output is 64 fault modes, and the 64 fault modes are expressed as: a= { a 1 ，a 2 ，...a k ...，a 64 And }, wherein a k =0 or a k ＝1，a k Represents the kth failure mode, among which 64 failure modes a can be set 11 、a 13 、a 17 、a 19 、a 22 、a 24 、a 27 、a 29 、a 32 、a 33 、a 34 、a 35 、a 37 、a 40 、a 42 、a 47 、a 51 、a 53 、a 56 、a 59 、a 61 A total of 21 failure modes are temperature, in detail:
the remaining 43 failure modes are states, in detail:
this yields a first formula:
the first formula is then brought into the second formula,
the specific meaning of the second formula is: when b i When=1, it means that the ith component is normal, when b i When=2, the temperature of the i-th component exceeds the standard, and when the i-th component b i When=5, it indicates that the i-th component has failed.
In addition, the discriminant delta=x can be used i1 or x i2 +x i2 Then (0, 0) corresponds to Δ=0, (1, 0) corresponds to Δ=1, (0, 1) and (1, 1) both correspond to Δ=2, where:
and further giving output values of all the components, specifically:
first, the corresponding relation between each component and each failure mode is obtained, and in detail: the first component is a first power divider, the input of which is dependent on a 1 And is in a state where x 1，1 ＝0，x 1，2 ＝a 1 Therefore, the corresponding relationship is
The second component is a power module whose input is dependent on a 2 、a 4 And all are in state, at this time x 2，1 ＝0，x 2，2 ＝max{a 2 ，a 4 Then its corresponding relationship is
The third component is a second power divider whose input is dependent on a 3 And is in a state where x 3，1 ＝0，x 3，2 ＝a 3 Its corresponding relationship is
The fourth component is a first power amplifier source module, and the input is based on a 5 And is in a state where x 4，1 ＝0，x 4，2 ＝a 5 Its corresponding relationship is
The fifth component is a second power amplifier source module, and the input is based on a 6 And is in a state where x 5，1 ＝0，x 5，2 ＝a 6 Its corresponding relationship is
The sixth component is the reference frequency component, the input is dependent on a 7 、a 8 、a 9 、a 10 、a 11 Wherein a is 7 、a 8 、a 9 、a 10 In the state of a 11 At the temperature of x 6，1 ＝a 11 ，x 6，2 ＝max{a 7 ，a 8 ，a 9 ，a 10 And the corresponding relation is:
the seventh component is a fine stepping component whose input is dependent on a 12 、a 13 Wherein a is 12 In the state of a 13 At the temperature of x 7，1 ＝a 13 ，x 7，2 ＝a 12 The corresponding relationship is:
the eighth component is a fine step spread spectrum component whose input is dependent on a 14 、a 15 、a 16 、a 17 Wherein a is 14 、a 15 、a 16 In the state of a 17 At the temperature of x 8，1 ＝a 17 ，x 8，2 ＝max{a 14 ，a 15 ，a 16 And the corresponding relation is:
the ninth component is the first control component, the input of which is dependent on a 18 、a 19 Wherein a is 18 In the state of a 19 At the temperature of x 9，1 ＝a 19 ，x 9，2 ＝a 18 The corresponding relationship is:
the tenth component is a frequency spreading component whose input is dependent on a 20 、a 21 、a 22 Wherein a is 20 、a 21 In the state of a 22 At the temperature of x 10，1 ＝a 22 ，x 10，2 ＝max{a 20 ，a 21 And the corresponding relation is:
the eleventh component is a frequency synthesis component whose input is dependent on a 23 、a 24 Wherein a is 23 In the state of the device, the device is in a state,a 24 at the temperature of x 11，1 ＝a 24 ，x 11，2 ＝a 23 The corresponding relationship is:
the twelfth component is a frequency-spread-spectrum component whose input is dependent on a 25 、a 26 、a 27 Wherein a is 25 、a 26 In the state of a 27 At the temperature of x 1 ＝a 27 ，x 2 ＝max{a 25 ，a 26 And the corresponding relation is:
the thirteenth component is a wideband frequency spreading component whose input is dependent on a 28 、a 29 Wherein a is 28 In the state of a 29 At the temperature of x 13，1 ＝a 29 ，x 13，2 ＝a 28 The corresponding relationship is:
the fourteenth component is a wideband waveform component whose input is dependent on a 30 、a 31 、a 32 Wherein a is 30 、a 31 In the state of a 32 At the temperature of x 14，1 ＝a 32 ，x 14，2 ＝max{a 30 ，a 31 And the corresponding relation is:
the fifteenth component is a transceiver correction component, the input of which is dependent on a 33 And is the temperature at which x 15，1 ＝a 33 ，x 15，2 =0, then its correspondence is:
the sixteenth component is the first data transmission component, and its input is determined by a 34 And is the temperature at which x 16，1 ＝a 34 ，x 16，2 =0, then its correspondence is:
the seventeenth component is a second data transmission component whose input is dependent on a 35 And is the temperature at which x 17，1 ＝a 35 ，x 17，2 =0, then its correspondence is:
the eighteenth component is a second control component whose input is dependent on a 36 、a 37 Wherein a is 36 In the state of a 37 At the temperature of x 18，1 ＝a 37 ，x 18，2 ＝a 36 The corresponding relationship is:
the nineteenth component is a second wideband waveform component whose input is dependent on a 38 、a 39 、a 40 Wherein a is 38 、a 39 In the state of a 40 At the temperature of x 19，1 ＝a 40 ，x 19，2 ＝max{a 38 ，a 39 And the corresponding relation is:
the twentieth component is a second wideband frequency-spreading componentIts input depends on a 41 、a 42 Wherein a is 41 In the state of a 42 At the temperature of x 20，1 ＝a 42 ，x 20，2 ＝a 41 The corresponding relationship is:
the twenty-first component is a second reference frequency component whose input is dependent on a 43 、a 44 、a 45 、a 46 、a 47 Wherein a is 43 、a 44 、a 45 、a 46 In the state of a 47 At the temperature of x 21，1 ＝a 47 ，x 21，2 ＝max{a 43 ，a 44 ，a 45 ，a 46 And the corresponding relation is:
the twenty-second component is a second fine step-wise frequency spreading component, the input of which depends on a 48 、a 49 、a 50 、a 51 Wherein a is 48 、a 49 、a 50 In the state of a 51 At the temperature of x 22，1 ＝a 51 ，x 22，2 ＝max{a 48 ，a 49 ，a 50 And the corresponding relation is:
the twenty-third component is a second fine stepping component, the input of which depends on a 52 、a 53 Wherein a is 52 In the state of a 53 At the temperature of x 23，1 ＝a 53 ，x 23，2 ＝a 52 The corresponding relationship is:
the twenty-fourth component is a second frequency-spreading component whose input is dependent on a 54 、a 55 、a 56 Wherein a is 54 、a 55 In the state of a 56 At the temperature of x 24，1 ＝a 56 ，x 24，2 ＝max{a 54 ，a 55 And the corresponding relation is:
the twenty-fifth component is a second frequency-spread-spectrum component whose input is dependent on a 57 、a 58 、a 59 Wherein a is 57 、a 58 In the state of a 59 At the temperature of x 25，1 ＝a 59 ，x 25，2 ＝max{a 57 ，a 58 And the corresponding relation is:
the twenty-sixth component is a second frequency synthesis component whose input is dependent on a 60 、a 61 Wherein a is 60 In the state of a 61 At the temperature of x 26，1 ＝a 61 ，x 26，2 ＝a 60 The corresponding relationship is:
the twenty-seventh component is a clock amplification component whose input is dependent on a 62 And is in a state where x 27，1 ＝0，x 27，2 ＝a 62 And the corresponding relation is as follows:
the twenty eighth component is a two local oscillation amplifying component, the input of which is dependent on a 63 And is in a state where x 28，1 ＝0，x 28，2 ＝a 63 The corresponding relationship is:
the twenty-ninth component is a local oscillation amplifying component, the input of which is dependent on a 64 And is in a state where x 29，1 ＝0，x 29，2 ＝a 64 The corresponding relationship is:
and respectively bringing the corresponding relations into a second formula:
the method comprises the following steps:
if use b 1 、b 3 The output values of the two power dividers are represented, and three combinations are respectively formed on the assumption that the power dividers do not form any combination and the combination structure mode of the subsystem is combed, wherein the first combination is { b } 2 ，b 6 ，b 7 ，b 8 ，b 9 ，b 10 ，b 11 ，b 12 ，b 13 ，b 14 ，b 15 ，b 16 Total of 12 components, b i =1, 2,5, and the corresponding discriminant delta is set 1 ＝max{b 2 ，b 6 ，b 7 ，b 8 ，b 9 ，b 10 ，b 11 ，b 12 ，b 13 ，b 14 ，b 15 ，b 16 The output of the first combination is:
wherein the second combination is { b } 17 ，b 18 ，b 19 ，b 20 ，b 21 ，b 22 ，b 23 ，b 24 ，b 25 ，b 26 Total of 10 components, where b i =1, 2,5, and the corresponding discriminant delta is set 2 ＝max{b 17 ，b 18 ，b 19 ，b 20 ，b 21 ，b 22 ，b 23 ，b 24 ，b 25 ，b 26 The output of the second combination is:
wherein the third combination is { b } 4 ，b 5 ，b 27 ，b 28 ，b 29 Total of 5 components, where b i =1, 5, set the corresponding discriminant delta 3 ＝max{b 4 ，b 5 ，b 27 ，b 28 ，b 29 The output of the third combination is:
according to the components of the subsystem and the corresponding failure modes, the subsystem can be divided into 4 parts, namely a perfect set, two functional sets and a non-influencing performance set, wherein the perfect set is denoted by A1, the two functional sets are denoted by A2 and A3 respectively, the non-influencing performance set is denoted by A4, as shown in figure 2, A1, A2, A3 and A4 form an influence level framework of the subsystem, the output values of the sets are 1,2 and 5, and the output values of the A1, A2, A3 and A4 are respectively marked as A 1 、A 2 、A 3 And A 4 The method comprises the steps of carrying out a first treatment on the surface of the Marked as A e =1, 2,5, wherein e is 1-4; presetting the influence level frame outputs 1,2,3, 4, 5 respectively representing the system shapeThe state is as follows: health, early warning, attention, deterioration and shutdown, namely determining different pre-output modes of the subsystem to be health, early warning, attention, deterioration and shutdown, which are respectively represented by 1,2,3, 4 and 5, wherein the health can be indicated by green, the early warning can be indicated by yellow, the attention can be indicated by orange, the deterioration can be indicated by pink, and the shutdown can be indicated by red;
as can be seen from FIG. 2, the outputs of the subsystem add up to 3 4 The case of =81, specifically:
1) If A 1 When=5, the output value of the system is 5, which is 3 3 =27 cases;
2) If A 1 =1 or a 1 When=2, continue to judge a 2 And A 3 In detail:
2.1 If A) 2 +A 3 10, the output value of the system is 5, 2×3=6 cases in total;
2.2 If A) 2 +A 3 =6 or a 2 +A 3 The output value of the subsystem is 4 for a total of 2×4×3=24 cases, =7;
2.3 If A) 2 +A 3 And (4) continuing to judge A 4 In detail:
2.3.1 If A) 2 +A 3 =3 or a 2 +A 3 =4, orIn the case of A 4 =1 or a 4 2, the output value of the subsystem is 2, and there are 7×2=14 cases; if A 4 =5, the output value of the subsystem is 3, for a total of 7 cases;
2.3.2 If (1)Then, when A 4 When=1, the output value of the subsystem is 1, and the total number is 1; when A is 4 When=2, the output value of the subsystem is 2, and 1 case is taken as a total; when A is 4 When=5, the output value of the subsystem is 3, and 1 case is altogether;
counting the above cases, and when the output value of the subsystem is 5, totally 27+6=33 cases; when the output value of the subsystem is 4, 24 situations are totally considered; when the output value of the subsystem is 3, 7+1=8 cases are shared; when the output value of the subsystem is 2, 14+1=15 cases are totally used; the subsystem output value is 1,1 case is shared, and the total is 81 cases;
if the actual output value of the subsystem is 5, the actual output state of the subsystem is obtained, and at the moment, A is present 1 =5 orThe mapping relation corresponding to the actual output state, namely the actual corresponding relation, is obtained from the pre-output mode set, then the component with the fault is found, and the corresponding fault mode is further found.
If the actual output value of the subsystem is 4, then there isOr->Or->Or->The mapping relation corresponding to the actual output state, namely the actual corresponding relation, is obtained from the pre-output mode set, then the component with the fault is found, and the corresponding fault mode is further found.
Preferably, in the above technical solution, a health status score of the device is obtained, where the health status score includes a service time score, a guarantee capability score, and a performance status score of the device;
wherein the length of service scoreWherein X represents a full life cycle, X 1 Representing the length of service, alpha represents the service coefficient, Y 1 A full score value representing the length of service score; />
The support ability scoreWherein Y is 2 A full score representing the security capability score, M representing the spare part type, L j Indicating the number of spare parts of the j-th type, N j Represents the consumption number of the j-th spare parts, and N is more than or equal to 0 j ≤L j ，M、L j 、N j And j are integers;
and obtaining the power value of the equipment, and obtaining the performance state score in a segmentation mode according to different temperatures. After the actual output state of the device is obtained, the maintenance personnel can further know the actual situation in the actual output state through the health status score.
The actual output state of the health state of the traditional equipment is only two modes of normal state and fault state, and green and red are used for prompting maintenance personnel respectively, but the degree of the normal state and the degree of the fault state are difficult to quantify, so that the health state score of the equipment is introduced, and specifically comprises the service time score, the guarantee capability score and the performance state score of the equipment, the service time score of the equipment is converted according to the service start-up time in the whole life cycle of the equipment, and the full value of the service time score can be set to be 50 points, namely Y 1 =50, also can set Y 1 =70 or Y 1 100, etc., and a full score value Y of the length of service score 1 The device can be set according to actual conditions, the service time of the device is more than 1 hour, the whole service life period X of the device is reduced by 1 hour, and so on, in some devices, such as a radar, the service time of the radar is considered and then the whole service life period X of the device is weighted according to GJB4384-2002, wherein the method comprises the following steps:
1) In the region with better environmental conditions in the north of Yangtze river, the service coefficient alpha is 1.5;
2) The service coefficient alpha is 1.35 in the south of the Yangtze river and in the north coast of the Yangtze river (the banded region 20 km away from the coastline) and in the island region;
3) The service coefficient alpha is 1.2 in the coastal region of the south of Yangtze river and in the mountain and desert region with severe inland environmental conditions;
4) In tropical island regions, the service coefficient alpha is 1.
The full life cycle X of the radar can be converted according to different service coefficients alpha.
For example, when the full value of the length of service score is set to 50 points, Y 1 =50, full life cycle X40000 hours, length of service X 1 The length of service score for the device is:
wherein, the security capability score is rated according to the residual number of spare parts of the equipment, the satisfaction probability of the spare parts is mainly rated, the available percentage is displayed, and the full-scale value Y of the security capability score 2 50, 100, etc., can be determined according to actual conditions, and meanwhile, the power-on time of equipment, the fault occurrence probability of spare parts, the turnover time of the spare parts, etc. can be considered while the satisfaction probability is considered.
The performance state score of the obtaining device is specifically:
assuming that the existing data of a certain device are counted, the variation range of the power value is 950-1250 mW, the value of the power attenuation is 0-10 dB, and the variation range of the temperature is-40-70 ℃, then: when the power value exceeds 1250mW, the performance state score is set to 0, the performance state corresponding to the starting position of the power value at each temperature is set to be the full value of the performance state score, and the full value is marked as Y 3 I.e. Y 3 A full value representing a performance state score, wherein Y 3 =100, also Y can be set 3 =70 or Y 3 =50, etc., can be set according to actual conditions, and is herein denoted by Y 3 Further to the description of =100, if different temperatures are segmented, for example, if temperature-40+.t+.25, the start data p0= -0.2308t+996.7692 of the power value is set, if temperatureWhen T is 25-70, the initial data p0=0.8667t+969.3333 of the power value is set, then:
1) When the temperature is-40.ltoreq.T.ltoreq.25, if the power value p of the apparatus is not within the range of [996.7692-0.2308T,1250]When the range of the performance state is within the interval range, the performance state score can be set to be 0; if the power value p of the device is within the range of [996.7692-0.2308T,1250]Within the interval of (2), then performance state scoring
2) If the power value p of the apparatus is not within the range of [969.3333+0.8667T,1250 ] when the temperature is 25.ltoreq.T.ltoreq.70]If the power value p of the device is within the interval range, the performance state score can be set to 0, if the power value p of the device is within the range of [969.3333+0.8667T,1250]Within the interval, the performance status scores
Further to the above examples, when the subsystem output is 1,2,3, the actual temperature and power values may be incorporated as described above, and the health status score of the subsystem may be further given, for example, if the system output is 3, the performance status score of the corresponding health status score may be accurately calculated at a time between 40 and 60 minutes, and if the calculated performance status score is 42 minutes, the maintenance personnel may prepare the corresponding spare parts for maintenance and replacement, and if the calculated performance status score is 60 minutes, the maintenance personnel may not be urgent for maintenance.
Preferably, in the above technical solution, determining the remaining lifetime of the device according to the actual output state specifically includes the following steps:
s20, supplementing power values of the equipment at different temperatures based on a dynamic prediction model of an interpolation theory, and obtaining a corresponding final working temperature extremum according to preset cut-off output power;
s21, bringing the actual temperature and the final working temperature extreme value into a fitting equation of temperature along with time respectively: t=0.0299T 2 -2.2420T+33.1209 minLet t be 1 And t 2 The residual life is t 2 -t 1 Wherein T represents a temperature value.
The residual life of the equipment can be accurately predicted by a dynamic prediction model based on interpolation theory and a fitting equation, wherein a fitting curve of the fitting equation is shown in fig. 3.
Continuing to explain by using the above example, when the output value of the subsystem is 2, after calculating the health state score, the remaining life of the subsystem can be further predicted, the dynamic prediction model based on the interpolation theory supplements the power values at different temperatures mainly according to the interpolation information calculated by statistics, the corresponding final working temperature extremum is found out through the change of the power values, the cut-off output power is 1250mW, and 25 is less than or equal to T is less than or equal to 70, when the actual power value exceeds 1250mW, specifically, the fault occurs:
first, the actual temperature is marked as T 1 Then t 1 ＝0.0299T 1 2 -2.2420T 1 +33.1209 where T 1 ≥37.4916；
The final operating temperature extremum is then marked as T 2 Wherein, the method comprises the steps of, wherein,calculating t according to the fitting equation 2 ＝0.0299T 2 2 -2.2420T 2 +33.1209；
Finally, according to t=t 2 -t 1 The remaining lifetime t is obtained.
The dynamic prediction model of the interpolation theory can be understood as: as shown in table 1 below:
table 1:
t1 to T12 in Table 1 represent temperatures, the minimum value of the power value at T1 temperature is 969.3333+0.8667T1, and the maximum value of the power value is 1250mW, i.e., P in Table 1 1T1 ＝969.3333+0.8667T1，P 12T1 =1250 mW, at which time the corresponding time at temperature T1 is T 1 ＝0.0299T1 2 -2.2420t1+33.1209, when the temperature reached 323.8337 ℃, the device would fail, i.e. t12= 323.8337 ℃, while P 12T1 Let us now assume that the actual power value P acquired at temperature T1 is between [969.3333+0.8667T,1250 ]]When the attenuation is 5dB, P is set 6T1 P is =P, then P 6T7 =1250 mW, finding the temperature corresponding to the failure of the equipment as T7, and obtaining the time T when the equipment stops working from T7 2 ＝0.0299T7 2 -2.2420T7+33.1209, finally defined by t 2 -t 1 The remaining life of the device can be calculated.
Further elaboration follows with the above examples: the power value P and the actual temperature of the subsystem are obtained to actually calculate the performance state score, and the power value P and the actual temperature of the equipment are used for explanation:
when the actual temperature is 20 ℃, the power value is changed to be [1001.4, 1250 ]]If the power value p=994 mW of the device, the performance state score y 3 =0, if the power value p=1179 mW of the device, a performance state score y is obtained 3 ＝28.5582。
If the actual temperature is +50℃, the power value range considered at this time is [1012.7, 1250 ]]If the value x=1003 is given, then a score of 0 is easily given; if the power value p=1003 mW of the device, the performance state score y 3 =0, if the power value p=1179 mW of the device, a performance state score y is obtained 3 ＝29.9159。
The remaining life of the subsystem may also be predicted based on the above. For example, consider the temperature t= +50 ℃, if the power value x=1179, the calculated performance state score 29.9159 minutes; the remaining life was further calculated to be 261.9311 seconds.
As shown in fig. 4, a device health management system 200 according to an embodiment of the present application includes a pre-establishment module 210 and a prediction module 220; the pre-establishment module 210 obtains each failure mode of the device, establishes a mapping relation between each component of the device and each corresponding failure mode, and determines different pre-output modes of the device according to each mapping relation, and marks the different pre-output modes as a pre-output mode set; the prediction module 220 obtains an actual output state of the device, obtains a mapping relationship corresponding to the actual output state according to the pre-output mode set, marks the mapping relationship as an actual corresponding relationship, and determines a corresponding fault mode and a fault component according to the actual corresponding relationship, or determines a remaining life of the device according to the actual output state.
Firstly, a pre-establishing module 210 establishes a mapping relation between each component of the device and each corresponding fault mode, determines a pre-output mode set, and then obtains an actual corresponding relation by obtaining an actual output state of the device and comparing the actual output state with the pre-output modes in the pre-output mode set, on one hand, the corresponding fault modes and the fault components can be accurately judged according to the actual corresponding relation, so that maintenance personnel can conveniently maintain the device; on the other hand, the residual service life of the equipment can be determined according to the actual output state, so that maintenance personnel can know the health condition of the equipment in real time conveniently, that is, the application extracts useful information in the whole service life period of the equipment by establishing a model of correlation between the pre-output mode set and the actual output state, evaluates and predicts the service state of the equipment and provides maintenance and guarantee decisions, lays a foundation for the reliability of the equipment, and realizes reasonable health management of the equipment.
Preferably, in the above technical solution, the method further includes: the pre-establishment module 210 obtains the temperature and state of the ith component of the device and expresses the ith component b with a first formula i The corresponding relation between the first formula and the corresponding fault mode is as follows:
wherein x is i，1 Indicating the temperature of the ith component, x i，2 Representing the state of the ith component, x i，1 And x i，2 The value of (1) is 0 or 1, (0, 0) indicates that the ith component is in a normal state, (1, 0) indicates that the temperature of the ith component exceeds the standard, (0, 1) indicates that the ith component is in a fault state, (1, 1) indicates that the ith component is in a fault stateThe temperature exceeds the standard in a state, i is a positive integer;
establishing a second formula:bringing the first formula into the second formula yields:
wherein b i Representing the output value of the ith component, (x) i，1 ，x i，2 ) And b i The relation between the i-th component and the corresponding fault mode;
by analogy, the pre-establishment module 210 determines a mapping between components of the device and respective failure modes. And establishing a mapping relation between each component of the equipment and each corresponding fault mode through mathematical modeling.
Preferably, in the above calculation scheme, the system further comprises a scoring module, wherein the scoring module obtains a health status score of the equipment, and the health status score comprises a service time score, a guarantee capability score and a performance status score of the equipment;
wherein the length of service scoreWherein X represents the service time, X 1 Representing the length of service, alpha represents the service coefficient, Y 1 A full score value representing the length of service score;
the support ability scoreWherein Y is 2 A full score representing the security capability score, M representing the spare part type, L j Indicating the number of spare parts of the j-th type, N j Represents the consumption number of the j-th spare parts, and N is more than or equal to 0 j ≤L j ，M、L j 、N j And j are integers;
and obtaining the power value of the equipment, and obtaining the performance state score in a segmentation mode according to different temperatures.
After the actual output state of the device is obtained, the maintenance personnel can further know the actual situation in the actual output state through the health status score.
Preferably, in the above technical solution, the method further includes: the prediction module 220 supplements power values of the device at different temperatures based on a dynamic prediction model of an interpolation theory, obtains a corresponding final working temperature extremum according to a preset cut-off output power, and brings the actual temperature and the final working temperature extremum into a fitting equation of temperature along with time respectively: t=0.0299T 2 -2.2420T+33.1209, giving t respectively 1 And t 2 The residual life is t 2 -t 1 Wherein T represents a temperature value. The residual life of the equipment can be accurately predicted by a dynamic prediction model and a fitting equation based on an interpolation theory.
The steps for implementing the corresponding functions by the parameters and the unit modules in the device health management system 200 according to the present application are referred to the parameters and the steps in the embodiments of the device health management method according to the present application, and are not described herein.
The radar of the application comprises a control chip, wherein the control chip is used for executing the equipment health management method.
The control chip firstly obtains the mapping relation between each component of the radar and each corresponding fault mode, determines a pre-output mode set, and then obtains an actual corresponding relation after comparing the actual output state of the device with the pre-output modes in the pre-output mode set, on one hand, the corresponding fault modes and the fault components can be accurately judged according to the actual corresponding relation, and maintenance personnel can conveniently maintain the radar; on the other hand, the residual life of the radar can be determined according to the actual output state, so that maintenance personnel can know the health condition of equipment conveniently.
In the present disclosure, the terms "first," "second," and "second" are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implying a number of technical features being indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include at least one such feature. In the description of the present application, the meaning of "plurality" means at least two, for example, two, three, etc., unless specifically defined otherwise.
In the description of the present specification, a description referring to terms "one embodiment," "some embodiments," "examples," "specific examples," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present application. In this specification, schematic representations of the above terms are not necessarily directed to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, the different embodiments or examples described in this specification and the features of the different embodiments or examples may be combined and combined by those skilled in the art without contradiction.
While embodiments of the present application have been shown and described above, it will be understood that the above embodiments are illustrative and not to be construed as limiting the application, and that variations, modifications, alternatives and variations may be made to the above embodiments by one of ordinary skill in the art within the scope of the application.

Claims (5)

1. A method for device health management, comprising the steps of:
s1, acquiring each fault mode of equipment, establishing a mapping relation between each component of the equipment and each corresponding fault mode, and determining different pre-output modes of the equipment according to each mapping relation, and recording the different pre-output modes as a pre-output mode set;
s2, acquiring an actual output state of the equipment, obtaining a mapping relation corresponding to the actual output state according to the pre-output mode set, marking the mapping relation as an actual corresponding relation, and determining a corresponding fault mode and a fault assembly according to the actual corresponding relation or determining the residual life of the equipment according to the actual output state;
the mapping relation establishment specifically comprises the following steps:
s10, acquiring the temperature and the state of an ith component of the equipment, and expressing the ith component b by a first formula i The corresponding relation between the first formula and the corresponding fault mode is as follows:
wherein x is i，1 Indicating the temperature of the ith component, x i，2 Representing the state of the ith component, x i，1 And x i，2 The value of (1) is 0 or 1, (0, 0) indicates that the ith component is in a normal state, (1, 0) indicates that the temperature of the ith component exceeds the standard, (0, 1) indicates that the ith component is in a fault state, (1, 1) indicates that the ith component is in a fault state and the temperature exceeds the standard, and i is a positive integer;
s11, establishing a second formula:bringing the first formula into the second formula yields:
wherein b i Representing the output value of the ith component, (x) i，1 ,x i，2 ) And b i The relation between the i-th component and the corresponding fault mode;
s12, repeatedly executing S10 to S11, and determining the mapping relation between each component of the equipment and each corresponding fault mode;
further comprises: acquiring health status scores of the equipment, wherein the health status scores comprise service time scores, guarantee capability scores and performance status scores of the equipment;
wherein the length of service scoreWherein X represents a full life cycle, X 1 Representing the length of service, alpha represents the service coefficient, Y 1 A full score value representing the length of service score;
the support ability scoreWherein Y is 2 A full score representing the security capability score, M representing the spare part type, L j Indicating the number of spare parts of the j-th type, N j Represents the consumption number of the j-th spare parts, and N is more than or equal to 0 j ≤L j ，M、L j 、N j And j are integers;
and obtaining the power value of the equipment, and obtaining the performance state score in a segmentation mode according to different temperatures.
2. The device health management method according to claim 1, wherein determining the remaining lifetime of the device based on the actual output status comprises the steps of:
s20, supplementing power values of the equipment at different temperatures based on a dynamic prediction model of an interpolation theory, and obtaining a corresponding final working temperature extremum according to preset cut-off output power;
s21, bringing the actual temperature and the final working temperature extreme value into a fitting equation of temperature along with time respectively: t=0.0299T 2 -2.2420T+33.1209, giving t respectively 1 And t 2 The residual life is t 2 -t 1 Wherein T represents a temperature value, T 1 ＝0.0299T 1 2 -2.2420T 1 +33.1209，t 2 ＝0.0299T 2 2 -2.2420T 2 +33.1209，T 1 Indicating the actual temperature T 2 Representing the final operating temperature limit.
3. The equipment health management system is characterized by comprising a pre-establishment module and a prediction module;
the pre-establishing module acquires each fault mode of the equipment, establishes a mapping relation between each component of the equipment and each corresponding fault mode, and determines different pre-output modes of the equipment according to each mapping relation to be recorded as a pre-output mode set;
the prediction module obtains the actual output state of the equipment, obtains a mapping relation corresponding to the actual output state according to the pre-output mode set, marks the mapping relation as an actual corresponding relation, and determines a corresponding fault mode and a fault component according to the actual corresponding relation or determines the residual life of the equipment according to the actual output state;
further comprises: the pre-establishment module obtains the temperature and the state of the ith component of the equipment and expresses the ith component b by a first formula i The corresponding relation between the first formula and the corresponding fault mode is as follows:
wherein x is i，1 Indicating the temperature of the ith component, x i，2 Representing the state of the ith component, x i，1 And x i，2 The value of (1) is 0 or 1, (0, 0) indicates that the ith component is in a normal state, (1, 0) indicates that the temperature of the ith component exceeds the standard, (0, 1) indicates that the ith component is in a fault state, (1, 1) indicates that the ith component is in a fault state and the temperature exceeds the standard, and i is a positive integer;
establishing a second formula:bringing the first formula into the second formula yields:
wherein, the liquid crystal display device comprises a liquid crystal display device,b i representing the output value of the ith component, (x) i，1 ,x i，2 ) And b i The relation between the i-th component and the corresponding fault mode;
by analogy, the pre-establishment module determines a mapping relationship between each component of the device and each corresponding failure mode;
the system further comprises a scoring module, wherein the scoring module acquires health status scores of the equipment, and the health status scores comprise a service time score, a guarantee capability score and a performance status score of the equipment;
wherein the length of service scoreWherein X represents a full life cycle, X 1 Representing the length of service, alpha represents the service coefficient, Y 1 A full score value representing the length of service score;
the support ability scoreWherein Y is 2 A full score representing the security capability score, M representing the spare part type, L j Indicating the number of spare parts of the j-th type, N j Represents the consumption number of the j-th spare parts, and N is more than or equal to 0 j ≤L j ，M、L j 、N j And j are integers;
and obtaining the power value of the equipment, and obtaining the performance state score in a segmentation mode according to different temperatures.
4. A device health management system according to claim 3, further comprising: the prediction module supplements power values of the equipment at different temperatures based on a dynamic prediction model of an interpolation theory, obtains a corresponding final working temperature extremum according to preset cut-off output power, and brings the actual temperature and the final working temperature extremum into a fitting equation of temperature along with time respectively: t=0.0299T 2 -2.2420T+33.1209, giving t respectively 1 And t 2 The residual life is t 2 -t 1 Wherein T represents a temperature value, T 1 ＝0.0299T 1 2 -2.2420T 1 +33.1209，t 2 ＝0.0299T 2 2 -2.2420T 2 +33.1209，T 1 Indicating the actual temperature T 2 Representing the final operating temperature limit.
5. A radar comprising a control chip, characterized in that the control chip is adapted to perform a device health management method according to claim 1 or 2.
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