CN111178554A - Equipment health management method and system and radar - Google Patents

Equipment health management method and system and radar Download PDF

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CN111178554A
CN111178554A CN201911320291.1A CN201911320291A CN111178554A CN 111178554 A CN111178554 A CN 111178554A CN 201911320291 A CN201911320291 A CN 201911320291A CN 111178554 A CN111178554 A CN 111178554A
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equipment
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state
component
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CN111178554B (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 invention relates to a method, a system and a radar for equipment health management, which are characterized in that firstly, a pre-output mode set is determined according to the mapping relation between each component of equipment and each corresponding fault mode, then the actual output state of the equipment is obtained, and the actual corresponding relation is obtained after the actual output state of the equipment is compared with the pre-output modes in the pre-output mode set, on one hand, the corresponding fault mode and the corresponding fault component can be accurately judged according to the actual corresponding relation, so that maintenance personnel can conveniently maintain the equipment; on the other hand, the remaining service life of the equipment can be determined according to the actual output state, so that maintenance personnel can conveniently know the health condition of the equipment in real time, namely, 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 and system and radar
Technical Field
The invention relates to the field of equipment management, in particular to an equipment health management method, an equipment health management system and a radar.
Background
In order to meet the comprehensive guarantee requirement of radar equipment, change the defects of the traditional periodic after-repair guarantee mode and improve the quality and efficiency of equipment guarantee, an advanced testing, maintaining and managing technology, namely fault Prediction and Health Management (PHM), is provided in the United states at the end of the 20 th century, 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 fault of a radar system can be effectively predicted just like physical examination of a human body through monitoring various indexes. However, in the current research, the technical architecture related to the health management is more, the research related to the model algorithm is less, the health state and fault information of some equipment such as the radar are huge and disordered, some information is difficult to quantify, some information is useless, and just because of the absence of a reasonable health management model, the rationality of the health management of the radar system is low.
Therefore, how to provide a model to reasonably and healthily manage equipment is a technical problem to be solved urgently in the industry.
Disclosure of Invention
The invention provides a method and a system for equipment health management and a radar, aiming at the defects of the prior art.
The invention discloses a device health management method, a system and a radar, and the technical scheme is as follows:
s1, acquiring each fault mode of the equipment, establishing a mapping relation between each component of the equipment and each corresponding fault mode, determining different pre-output modes of the equipment according to each mapping relation, and recording as a pre-output mode set;
and S2, acquiring the actual output state of the equipment, acquiring a mapping relation corresponding to the actual output state according to the pre-output mode set, recording the mapping relation as an actual corresponding relation, and determining a corresponding fault mode and a fault component 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 following beneficial effects:
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 obtaining an actual corresponding relation after comparing the actual output state of the equipment with the pre-output modes in the pre-output mode set, on one hand, the corresponding fault mode and the fault component can be accurately judged according to the actual corresponding relation, so that maintenance personnel can conveniently maintain; on the other hand, the residual life of the equipment can be determined according to the actual output state, so that maintenance personnel can conveniently know the health condition of the equipment in real time, namely, the method extracts useful information in the whole life cycle of the equipment by establishing a model in which the pre-output mode set and the actual output state are correlated, evaluates and predicts the service state of the equipment and provides maintenance guarantee decisions, lays a foundation for the reliability of the equipment, and realizes reasonable health management on the equipment.
The technical scheme of the equipment health management system is as follows:
the device comprises a pre-establishing module and a predicting 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, determines different pre-output modes of the equipment according to each mapping relation, and records the different pre-output modes as a pre-output mode set;
and the prediction module acquires the actual output state of the equipment, acquires a mapping relation corresponding to the actual output state according to the pre-output mode set, records 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 following beneficial effects:
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 output state of the equipment is obtained, and the actual output state is compared with the pre-output modes in the pre-output mode set to obtain an actual corresponding relation, on one hand, the corresponding fault mode and the corresponding fault component can be accurately judged according to the actual corresponding relation, and maintenance personnel can conveniently maintain the fault mode; on the other hand, the residual life of the equipment can be determined according to the actual output state, so that maintenance personnel can conveniently know the health condition of the equipment in real time, namely, the method extracts useful information in the whole life cycle of the equipment by establishing a model in which the pre-output mode set and the actual output state are correlated, evaluates and predicts the service state of the equipment and provides maintenance guarantee decisions, lays a foundation for the reliability of the equipment, and realizes reasonable health management on the equipment.
The technical scheme of the radar of the invention 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.
The radar of the invention has the beneficial effects 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 equipment with the pre-output modes in the pre-output mode set, on one hand, the corresponding fault mode and the fault component can be accurately judged according to the actual corresponding relation, so that maintenance personnel can conveniently maintain; on the other hand, the remaining life of the radar can be determined according to the actual output state, and maintenance personnel can conveniently know the health condition of the equipment in real time.
Drawings
Fig. 1 is a schematic flow chart of a method for managing health of a device according to an embodiment of the present invention;
FIG. 2 is a diagram of an impact level framework for a subsystem;
FIG. 3 is a fitted curve of a fitted equation;
FIG. 4 is a schematic structural diagram of an apparatus health management system according to an embodiment of the present invention;
Detailed Description
As shown in fig. 1, a method for managing health of a device according to an embodiment of the present invention includes the following steps:
s1, acquiring each fault mode of the equipment, establishing a mapping relation between each component of the equipment and each corresponding fault mode, determining different pre-output modes of the equipment according to each mapping relation, and recording as a pre-output mode set;
and S2, acquiring the actual output state of the equipment, acquiring a mapping relation corresponding to the actual output state according to the pre-output mode set, recording the mapping relation as an actual corresponding relation, and determining a corresponding fault mode and a fault component 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 obtaining an actual corresponding relation after comparing the actual output state of the equipment with the pre-output modes in the pre-output mode set, on one hand, the corresponding fault mode and the fault component can be accurately judged according to the actual corresponding relation, so that maintenance personnel can conveniently maintain; on the other hand, the residual life of the equipment can be determined according to the actual output state, so that maintenance personnel can conveniently know the health condition of the equipment in real time, namely, the method extracts useful information in the whole life cycle of the equipment by establishing a model in which the pre-output mode set and the actual output state are correlated, evaluates and predicts the service state of the equipment and provides maintenance guarantee decisions, lays a foundation for the reliability of the equipment, and realizes reasonable health management on the equipment.
Preferably, in the above technical solution, the establishing of the mapping relationship specifically includes the following steps:
obtaining the temperature and state of the ith component of the device using a first algorithmFormula (I) represents the i-th component biAnd the corresponding relation between the first formula and the corresponding failure mode, wherein the first formula is as follows:
Figure BDA0002326955270000041
wherein x isi，1Denotes the temperature, x, of the i-th componenti，2Indicating the state of the i-th component, xi，1And xi，2The 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 the fault state and the temperature exceeds the standard, and i is a positive integer;
s11, establishing a second formula:
Figure BDA0002326955270000051
substituting the first formula into the second formula to obtain:
Figure BDA0002326955270000052
wherein, biRepresents the output value of the ith component, (x)i，1，xi，2) And biThe relationship between the components is the mapping relationship between the ith component and the corresponding failure mode;
and S12, repeatedly executing S10 to S11, and determining the mapping relation between each component of the equipment and each corresponding failure mode. And establishing a mapping relation between each component of the equipment and each corresponding fault mode through mathematical modeling.
Wherein, taking a certain subsystem of the radar as an example, the detailed explanation is carried out: the subsystem comprises 29 components, the output values of which are respectively marked b1，b2，...bi，...b29The D matrix of a certain subsystem of the radar can be output according to an established testability model of the subsystem, and finally, the diagnosis positioning output is 64 fault modes by utilizing a universal fault diagnosis inference machine based on testability modeling, namely a multi-signal flow model, wherein the 64 fault modes are expressed as follows: a ═ a1，a2，...ak...，a64In which ak0 or ak＝1，akIndicating the k-th failure mode, and among the 64 failure modes, a may be set11、a13、a17、a19、a22、a24、a27、a29、a32、a33、a34、a35、a37、a40、a42、a47、a51、a53、a56、a59、a61A total of 21 failure modes are temperature, in detail:
Figure BDA0002326955270000053
the remaining 43 failure modes are states, in detail:
Figure BDA0002326955270000054
this yields the first formula:
Figure BDA0002326955270000061
then substituting the first formula into the second formula,
Figure BDA0002326955270000062
the specific meaning of the second formula is: when b isiWhen 1, the i-th component is normal, and when b is normaliWhen the temperature of the ith module exceeds the standard, the temperature of the ith module is higher than the standard when the temperature of the ith module is 2iWhen the value is 5, the i-th component is indicated to be in failure.
In addition, the discrimination quantity Δ ═ x can be usedi1or xi2+xi2Then (0,0) corresponds to Δ ═ 0, (1,0) corresponds to Δ ═ 1, (0,1) and (1,1) both correspond to Δ ═ 2, when:
Figure BDA0002326955270000063
and then, the output values of the components are given, specifically:
firstly, obtaining the corresponding relation between each component and each fault mode, and in detail: the first component being a first power divider whose input is dependent on a1And is in a state, at which x1，1＝0，x1，2＝a1Therefore, the corresponding relationship is
Figure BDA0002326955270000064
The second component being a power supply module, the input of which is dependent on a2、a4And are all states, at which time x2，1＝0，x2，2＝max{a2，a4The corresponding relationship is
Figure BDA0002326955270000065
The third component being a second power divider whose input is dependent on a3And is in a state, at which x3，1＝0，x3，2＝a3The corresponding relationship is
Figure BDA0002326955270000066
The fourth component is a first power amplifier power supply module, and the input of the fourth component is determined by a5And is in a state, at which x4，1＝0，x4，2＝a5If the corresponding relationship is
Figure BDA0002326955270000067
The fifth component is a second power amplifier power supply module, and the input of the fifth component is determined by a6And is in a state, at which x5，1＝0，x5，2＝a6If the corresponding relationship is
Figure BDA0002326955270000071
The sixth component being a reference frequency component, the input being dependent on a7、a8、a9、a10、a11Wherein a is7、a8、a9、a10Is in a state of11Is the temperature at this time x6，1＝a11，x6，2＝max{a7，a8，a9，a10The corresponding relationship is:
Figure BDA0002326955270000072
the seventh component being a fine-stepping component whose input is dependent on a12、a13Wherein a is12Is in a state of13Is the temperature at this time x7，1＝a13，x7，2＝a12Then, the corresponding relationship is:
Figure BDA0002326955270000073
the eighth element being a fine step-spread element whose input is dependent on a14、a15、a16、a17Wherein a is14、a15、a16Is in a state of17Is the temperature at this time x8，1＝a17，x8，2＝max{a14，a15，a16The corresponding relationship is:
Figure BDA0002326955270000074
the ninth component being a first control component whose input is dependent on a18、a19Wherein a is18Is in a state of19Is the temperature at this time x9，1＝a19，x9，2＝a18Then, the corresponding relationship is:
Figure BDA0002326955270000075
a tenth element being a spreading element, the input of which is dependent on a20、a21、a22Wherein a is20、a21Is in a state of22Is the temperature at this time x10，1＝a22，x10，2＝max{a20，a21The corresponding relationship is:
Figure BDA0002326955270000081
the eleventh element being a frequency synthesizing element whose input depends on a23、a24Wherein a is23Is in a state of24Is the temperature at this time x11，1＝a24，x11，2＝a23Then, the corresponding relationship is:
Figure BDA0002326955270000082
a twelfth element being a spread-spectrum-spread-spectrum element, the input of which is dependent on a25、a26、a27Wherein a is25、a26Is in a state of27Is the temperature at this time x1＝a27，x2＝max{a25，a26The corresponding relationship is:
Figure BDA0002326955270000083
a thirteenth component is a wideband spreading component, the input of which is dependent on a28、a29Wherein a is28Is in a state of29Is the temperature at this time x13，1＝a29，x13，2＝a28Then, the corresponding relationship is:
Figure BDA0002326955270000084
a fourteenth element being a broadband waveform element, the input of which is dependent on a30、a31、a32Wherein a is30、a31Is in a state of32Is the temperature at this time x14，1＝a32，x14，2＝max{a30，a31The corresponding relationship is:
Figure BDA0002326955270000085
a fifteenth element is a transmit-receive correction element whose input is dependent on a33And is temperature, at this time x15，1＝a33，x15，2If 0, the corresponding relationship is:
Figure BDA0002326955270000086
the sixteenth element being a first data-transfer element whose input is dependent on a34And is temperature, at this time x16，1＝a34，x16，2If 0, the corresponding relationship is:
Figure BDA0002326955270000091
a seventeenth element being a second digital transmission element whose input is dependent on a35And is temperature, at this time x17，1＝a35，x17，2If 0, the corresponding relationship is:
Figure BDA0002326955270000092
the eighteenth element being a second control element whose input is dependent on a36、a37Wherein a is36Is in a state of37Is the temperature at this time x18，1＝a37，x18，2＝a36Then, the corresponding relationship is:
Figure BDA0002326955270000093
a nineteenth component is a second broadband waveform component, the input of which is dependent on a38、a39、a40Wherein a is38、a39Is in a state of40Is temperatureAt this time x19，1＝a40，x19，2＝max{a38，a39The corresponding relationship is:
Figure BDA0002326955270000094
the twentieth component being a second wideband spreading component, the input of which is dependent on a41、a42Wherein a is41Is in a state of42Is the temperature at this time x20，1＝a42，x20，2＝a41Then, the corresponding relationship is:
Figure BDA0002326955270000095
the twenty-first component being a second reference frequency component, the input of which is dependent on a43、a44、a45、a46、a47Wherein a is43、a44、a45、a46Is in a state of47Is the temperature at this time x21，1＝a47，x21，2＝max{a43，a44，a45，a46The corresponding relationship is:
Figure BDA0002326955270000101
the second twelfth element being a second fine step spread spectrum element whose input is dependent on a48、a49、a50、a51Wherein a is48、a49、a50Is in a state of51Is the temperature at this time x22，1＝a51，x22，2＝max{a48，a49，a50The corresponding relationship is:
Figure BDA0002326955270000102
the twenty-third component is the second fine stepAssembly, the input of which depends on a52、a53Wherein a is52Is in a state of53Is the temperature at this time x23，1＝a53，x23，2＝a52Then, the corresponding relationship is:
Figure BDA0002326955270000103
a twenty-fourth component is a second spread spectrum component, the input of which is dependent on a54、a55、a56Wherein a is54、a55Is in a state of56Is the temperature at this time x24，1＝a56，x24，2＝max{a54，a55The corresponding relationship is:
Figure BDA0002326955270000104
a twenty-fifth element being a second spread-spectrum element whose input is dependent on a57、a58、a59Wherein a is57、a58Is in a state of59Is the temperature at this time x25，1＝a59，x25，2＝max{a57，a58The corresponding relationship is:
Figure BDA0002326955270000105
a twenty-sixth element being a second frequency synthesizing element whose input is dependent on a60、a61Wherein a is60Is in a state of61Is the temperature at this time x26，1＝a61，x26，2＝a60Then, the corresponding relationship is:
Figure BDA0002326955270000111
a twenty-seventh element being a clock amplifying element, the input of which is dependent on a62And is in a state at this timex27，1＝0，x27，2＝a62And, the corresponding relationship is:
Figure BDA0002326955270000112
the twenty-eighth block being a two-local oscillator amplification block whose input is dependent on a63And is in a state, at which x28，1＝0，x28，2＝a63Then, the corresponding relationship is:
Figure BDA0002326955270000113
the twenty-ninth element being a local oscillator amplifying element, the input of which is dependent on a64And is in a state, at which x29，1＝0，x29，2＝a64Then, the corresponding relationship is:
Figure BDA0002326955270000114
and respectively substituting the corresponding relations into a second formula:
Figure BDA0002326955270000115
obtaining:
Figure BDA0002326955270000116
Figure BDA0002326955270000117
Figure BDA0002326955270000118
Figure BDA0002326955270000119
Figure BDA0002326955270000121
Figure BDA0002326955270000122
Figure BDA0002326955270000123
Figure BDA0002326955270000124
Figure BDA0002326955270000125
Figure BDA0002326955270000126
Figure BDA0002326955270000127
if using b1、b3The output values of the two power dividers are expressed, because the power dividers do not form any combination, and the combination structure mode of combing the power dividers is assumed, three combinations are respectively formed, wherein the first combination is { b }2，b6，b7，b8，b9，b10，b11，b12，b13，b14，b15，b16In total, is composed of 12 components, where bi1, 2, 5, a corresponding discrimination amount Δ is set1＝max{b2，b6，b7，b8，b9，b10，b11，b12，b13，b14，b15，b16And the output of the first combination is:
Figure BDA0002326955270000128
wherein the second combination is { b17，b18，b19，b20，b21，b22，b23，b24，b25，b26In total, is composed of 10 components, where bi1, 2, 5, a corresponding discrimination amount Δ is set2＝max{b17，b18，b19，b20，b21，b22，b23，b24，b25，b26And the output of the second combination is:
Figure BDA0002326955270000131
wherein the third combination is { b4，b5，b27，b28，b29In total, is composed of 5 components, where bi1, 5, setting the corresponding discrimination quantity delta3＝max{b4，b5，b27，b28，b29And the output of the third combination is:
Figure BDA0002326955270000132
the subsystem can be divided into 4 parts according to the components of the subsystem and the corresponding failure modes, wherein the good set is represented by A1, the two function sets are represented by A2 and A3, and the non-affecting performance set is represented by A4, and A1, A2, A3 and A4 form an affecting level frame of the subsystem, the output values of the sets are 1, 2 and 5, and the output values of A1, A2, A3 and A4 are labeled A41、A2、A3And A4(ii) a Is marked as Ae1, 2 and 5, wherein, e is more than or equal to 1 and less than or equal to 4; the impact level framework outputs 1, 2, 3, 4, and 5 are preset to represent the system states as follows: health, early warning, attention, deterioration and shutdown, namely determining different pre-output modes of the subsystem as health, early warning, attention, deterioration and shutdown respectively1.2, 3, 4 and 5, wherein health can be prompted by green, early warning can be prompted by yellow, attention can be prompted by orange, deterioration can be prompted by pink, and shutdown can be prompted by red;
as can be seen from FIG. 2, the outputs of the subsystems share 34As 81 cases, specifically:
1) if A is1When the output value is 5, the output value of the system is 5, and the total output value is 3327 cases are defined;
2) if A is11 or A1When the value is 2, the judgment of A is continued2And A3In detail:
2.1) if A2+A3The output value of the system is 5, and 2 × 3 is 6 cases;
2.2) if A2+A36 or A2+A3When the output value of the subsystem is 4, the total output value is 2 × 4 × 3 or 24;
2.3) if A2+A3If not more than 4, continue to judge A4In detail:
2.3.1) if A2+A3Either of 3 and A2+A34 or
Figure BDA0002326955270000141
When, if A41 or A4When the output value of the subsystem is 2, the output value of the subsystem is 7 × 2, and 14 cases are total; if A4If the output value of the subsystem is 5, the output value of the subsystem is 3, and 7 cases are total;
2.3.2) if
Figure BDA0002326955270000142
Then, when A4When the output value is 1, the output value of the subsystem is 1, and 1 condition is total; when A is4When the output value is 2, the output value of the subsystem is 2, and 1 case is total; when A is4When the output value is 5, the output value of the subsystem is 3, and 1 case is total;
counting the above cases, when the subsystem output value is 5, the total number of cases is 27+ 6-33; when the subsystem output value is 4, there are 24 cases in total; when the subsystem output value is 3, 7+1 is 8 cases in total; when the subsystem output value is 2, 14+1 is 15 cases in total; the subsystem output value is 1 in total, and the total is 81;
if the actual output value of the subsystem is 5, the actual output state of the subsystem is obtained, and A exists at the moment1Either 5 or
Figure BDA0002326955270000143
That is, the mapping relationship corresponding to the actual output state, i.e. the actual corresponding relationship, is obtained from the pre-output mode set, and then the failed component is found, and the corresponding failure mode is further found.
If the actual output value of the subsystem is 4, there is
Figure BDA0002326955270000144
Or
Figure BDA0002326955270000145
Or
Figure BDA0002326955270000146
Or
Figure BDA0002326955270000147
That is, the mapping relationship corresponding to the actual output state, i.e. the actual corresponding relationship, is obtained from the pre-output mode set, and then the failed component is found, and the corresponding failure 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 time of service score
Figure BDA0002326955270000151
Wherein X represents the full life cycle, X1representing the time of service, α representing the service coefficient, Y1A full score value representing the time-of-service score;
the ability to safeguard score
Figure BDA0002326955270000152
Wherein, Y2A full score value representing the security capability score, M represents a spare part type, LjDenotes the number of jth spare parts, NjRepresents the consumption number of the jth spare part, and is more than or equal to 0 and less than or equal to Nj≤Lj，M、Lj、NjAnd j are integers;
and acquiring the power value of the equipment, and obtaining the performance state score in a segmented manner according to different temperatures. After the actual output state of the equipment is obtained, maintenance personnel can further know the actual situation of the actual output state through the health state score.
The actual output state of the health state of the traditional equipment only has two modes of a normal state and a fault state, and the green state and the red state are respectively used for prompting maintenance personnel, but the degrees of the normal state and the fault state are difficult to quantify, so the health state score of the equipment is introduced, the service time score, the guarantee capability score and the performance state score of the equipment are specifically included, the service time score of the equipment is converted according to the service time in the whole life cycle of the equipment, and the full-service score of the service time score can be set to be 50 minutes, namely Y1Y may also be set at 50170 or Y 1100, etc. and the full value Y of the service time score1The setting can be made according to the actual situation, if the device is in service for more than 1 hour, the full life cycle X of the device is reduced by 1 hour, and so on, in some devices, such as a radar, during the service, the service place of the radar is considered and then the full life cycle X is weighted, which is specifically as follows according to the GJB 4384-2002:
1) in areas with better environmental conditions in the north of the Yangtze river, the service coefficient α is 1.5;
2) the service coefficient alpha is 1.35 in the regions of coastal areas (strip-shaped areas 20 kilometers from the coastline) and islands in the south of the Yangtze river and the north of the Yangtze river;
3) the service coefficient alpha is 1.2 in the regions of south coast of Yangtze river and high mountains and deserts with severe inland environmental conditions;
4) in tropical sea island regions, the service coefficient α is 1.
the full life cycle X of the radar can be converted according to different service coefficients alpha.
For example, when the full score of the service time score is set to 50 points, Y150, the whole life cycle X is 40000 hours, the service time X1Then the service time of the equipment is scored as:
Figure BDA0002326955270000161
wherein, the guarantee ability score is evaluated according to the residual number of the spare parts of the equipment, the satisfaction probability of the spare parts is mainly evaluated, the available percentage is displayed, and the full score Y of the guarantee ability score is2Which may be 50, 100, etc., may be determined according to actual conditions, and while considering the satisfaction probability, may also consider factors such as power-up time of the equipment, failure occurrence probability of the spare parts, and turnaround time of the spare parts.
The obtaining of the performance state score of the device specifically includes:
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 be 0, the performance state corresponding to the initial position of the power value at each temperature is set to be the full score of the performance state score and is marked as Y3I.e. Y3Full score representing performance status score, where Y 3100, Y may also be provided370 or Y3It may be set to 50 or the like according to the actual situation, and Y is used here3Continuing with the explanation at 100, if different temperatures are segmented, for example, if a temperature of-40 ≦ T ≦ 25, the power value start data P0 is set at-0.2308T +996.7692, and if a temperature of 25 ≦ T ≦ 70, the power value start data P0 is set at 0.8667T +969.3333, then:
1) when the temperature is more than or equal to-40 and less than or equal to 25, if the power value p of the equipment is not in the range of 996.7692-0.2308T,1250]within the interval range of (a), the performance status score at this time can be set to 0; if the power value p of the equipment is [996.7692-0.2308T, 1250]Within the interval of (3), then the performance status score is given
Figure BDA0002326955270000162
2) When the temperature is more than or equal to 25 and less than or equal to 70, 1250 if the power value p of the equipment is not in [969.3333+0.8667T]When the power value p is within the interval, the performance status score at this time is set to 0, and if the power value p of the equipment is [969.3333+0.8667T, 1250%]Within the interval, the performance status is scored
Figure BDA0002326955270000163
As further illustrated by the above example, when the output value of the subsystem is 1, 2, or 3, the actual temperature and power value may be taken in according to the above contents, and the health status score of the subsystem may be further provided, for example, if the output value of the system is 3, the performance status score of the corresponding health status score is between 40 and 60, at this time, the performance status score may be accurately calculated, if the calculated performance status score is 42, the maintenance personnel may prepare the corresponding spare part for maintenance and replacement, and if the calculated performance status score is 60, the maintenance personnel may not be urgently required to perform maintenance.
Preferably, in the above technical solution, determining the remaining life 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 extreme value according to preset cut-off output power;
s21, respectively substituting the actual temperature and the final working temperature extreme value into a fitting equation of the temperature along with the time: t is 0.0299T2-2.2420T +33.1209 yielding T, respectively1And t2The residual life is t2-t1Where T represents a temperature value.
The residual life of the equipment can be accurately predicted by a dynamic prediction model based on an 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 score of the health state, the remaining life of the subsystem can be further predicted, the dynamic prediction model based on the interpolation theory mainly supplements power values at different temperatures according to the interpolation information calculated by statistics, finds out the corresponding final working temperature extreme value through the change of the power value, the cut-off output power is 1250mW, and T is more than or equal to 25 and less than or equal to 70, and when the actual power value exceeds 1250mW, a fault occurs, specifically:
first, the actual temperature is marked as T1Then t is1＝0.0299T1 2-2.2420T1+33.1209 where T1≥37.4916；
The final operating temperature limit is then labeled T2Wherein, in the step (A),
Figure BDA0002326955270000171
calculating t according to fitting equation2＝0.0299T2 2-2.2420T2+33.1209；
Finally, according to t ═ t2-t1The remaining life t is obtained.
Wherein, the dynamic prediction model of the interpolation theory can be understood as: as shown in table 1 below:
table 1:
Figure BDA0002326955270000181
t1 to T12 in Table 1 indicate temperatures, the minimum value of the power values at T1 is 969.3333+0.8667T1, and the maximum value of the power values is 1250mW, i.e. P in Table 11T1＝969.3333+0.8667T1，P12T11250mW, the corresponding time at T1 temperature is T1＝0.0299T122.2420T1+33.1209, the device will fail when the temperature reaches 323.8337 ℃, i.e. T12 ═ 323.8337 ℃, and P12T11250mW, it is now assumed that the power value P actually collected at T1 is between[969.3333+0.8667T，1250]P is set at a value of 5dB without attenuation6T1When P is equal to P, then P6T71250mW, finding the temperature T7 corresponding to the failure of the equipment, and obtaining the time T when the equipment stops working from T72＝0.0299T72-2.2420T7+33.1209, finally by T2-t1The remaining life of the device can be calculated.
Further elaboration follows with the above example: the performance state score can only be actually solved by acquiring the power value P and the actual temperature of the subsystem, and the power value P and the actual temperature of the equipment are explained as follows:
when the actual temperature is 20 ℃, the variation range of the power value is [1001.4, 1250 ]]If the power value P of the equipment is 994mW, the performance state score y3If the power value P of the equipment is 1179mW, the performance status score y is obtained3＝28.5582。
If the actual temperature is +50 ℃, the power value range considered at this time is [1012.7, 1250 ]]If the given value x is 1003, it is easy to give a score of 0; if the power value P of the equipment is 1003mW, the performance state score y3If the power value P of the equipment is 1179mW, the performance status score y is obtained3＝29.9159。
The remaining life of the subsystem may also be predicted based on the above. For example, if the power value x is 1179, considering the temperature T +50 ℃, the calculated performance status score is 29.9159 points; the remaining life was further calculated to be 261.9311 seconds.
As shown in fig. 4, an apparatus health management system 200 according to an embodiment of the present invention includes a pre-establishing module 210 and a predicting module 220; the pre-establishing module 210 obtains each failure mode of the device, establishes a mapping relationship between each component of the device and each corresponding failure mode, determines different pre-output modes of the device according to each mapping relationship, and records 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, records the mapping relationship as an actual corresponding relationship, and determines a corresponding failure mode and a failure component according to the actual corresponding relationship, or determines the remaining life of the device according to the actual output state.
Firstly, the pre-establishing module 210 establishes a mapping relationship between each component of the device and each corresponding failure mode, determines a pre-output mode set, and then obtains an actual corresponding relationship 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, so that on one hand, the corresponding failure modes and the failure components can be accurately judged according to the actual corresponding relationship, and maintenance personnel can conveniently maintain the failure modes; on the other hand, the residual life of the equipment can be determined according to the actual output state, so that maintenance personnel can conveniently know the health condition of the equipment in real time, namely, the method extracts useful information in the whole life cycle of the equipment by establishing a model in which the pre-output mode set and the actual output state are correlated, evaluates and predicts the service state of the equipment and provides maintenance guarantee decisions, lays a foundation for the reliability of the equipment, and realizes reasonable health management on the equipment.
Preferably, in the above technical solution, the method further comprises: the pre-establishment module 210 obtains the temperature and the state of the ith component of the device, and expresses the ith component b by a first formulaiAnd the corresponding relation between the first formula and the corresponding failure mode, wherein the first formula is as follows:
Figure BDA0002326955270000191
wherein x isi，1Denotes the temperature, x, of the i-th componenti，2Indicating the state of the i-th component, xi，1And xi，2The 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 the fault state and the temperature exceeds the standard, and i is a positive integer;
establishing a second formula:
Figure BDA0002326955270000201
the first oneSubstituting the formula into the second formula yields:
Figure BDA0002326955270000202
wherein, biRepresents the output value of the ith component, (x)i，1，xi，2) And biThe relationship between the components is the mapping relationship between the ith component and the corresponding failure 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 calculation method further includes a scoring module, where the scoring module obtains a health status score of the device, and the health status score includes a service time score, a guarantee capability score, and a performance status score of the device;
wherein the time of service score
Figure BDA0002326955270000203
Wherein X represents the required service time, X1representing the time of service, α representing the service coefficient, Y1A full score value representing the time-of-service score;
the ability to safeguard score
Figure BDA0002326955270000204
Wherein, Y2A full score value representing the security capability score, M represents a spare part type, LjDenotes the number of jth spare parts, NjRepresents the consumption number of the jth spare part, and is more than or equal to 0 and less than or equal to Nj≤Lj，M、Lj、NjAnd j are integers;
and acquiring the power value of the equipment, and obtaining the performance state score in a segmented manner according to different temperatures.
After the actual output state of the equipment is obtained, maintenance personnel can further know the actual situation of the actual output state through the health state score.
Preferably, in the above technical solution, the method further comprises: the prediction module 220 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 extreme value according to a preset cut-off output power, and brings the actual temperature and the final working temperature extreme value into a fitting equation of the temperature along with time respectively: t is 0.0299T2-2.2420T +33.1209 yielding T, respectively1And t2The residual life is t2-t1Where T represents a temperature value. The residual service life of the equipment can be accurately predicted by a dynamic prediction model and a fitting equation based on an interpolation theory.
The above steps for realizing the corresponding functions of each parameter and each unit module in the device health management system 200 according to the present invention may refer to each parameter and step in the above embodiment of the device health management method, which are not described herein again.
The radar of the invention comprises a control chip, and 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 equipment with the pre-output modes in the pre-output mode set, on one hand, the corresponding fault mode and the fault component can be accurately judged according to the actual corresponding relation, so that maintenance personnel can conveniently maintain; on the other hand, the remaining 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 conveniently.
In the present invention, the terms "first", "second" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present invention, "a plurality" means at least two, e.g., two, three, etc., unless specifically limited otherwise.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean 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 invention. In this specification, the schematic representations of the terms used above are not necessarily intended to refer 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, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention, and that variations, modifications, substitutions and alterations can be made to the above embodiments by those of ordinary skill in the art within the scope of the present invention.

Claims (9)

1. A device health management method is characterized by comprising the following steps:
s1, acquiring each fault mode of the equipment, establishing a mapping relation between each component of the equipment and each corresponding fault mode, determining different pre-output modes of the equipment according to each mapping relation, and recording as a pre-output mode set;
and S2, acquiring the actual output state of the equipment, acquiring a mapping relation corresponding to the actual output state according to the pre-output mode set, recording the mapping relation as an actual corresponding relation, and determining a corresponding fault mode and a fault component according to the actual corresponding relation, or determining the residual life of the equipment according to the actual output state.
2. The device health management method according to claim 1, wherein establishing the mapping relationship specifically comprises the steps of:
s10, acquiring the temperature and state of the ith component of the equipment, and expressing the ith component b by a first formulaiAnd the corresponding relation between the first formula and the corresponding failure mode, wherein the first formula is as follows:
Figure FDA0002326955260000011
wherein x isi，1Denotes the temperature, x, of the i-th componenti，2Indicating the state of the i-th component, xi，1And xi，2The 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 the fault state and the temperature exceeds the standard, and i is a positive integer;
s11, establishing a second formula:
Figure FDA0002326955260000012
substituting the first formula into the second formula to obtain:
Figure FDA0002326955260000013
wherein, biRepresents the output value of the ith component, (x)i，1,xi，2) And biThe relationship between the components is the mapping relationship between the ith component and the corresponding failure mode;
and S12, repeatedly executing S10 to S11, and determining the mapping relation between each component of the equipment and each corresponding failure mode.
3. The device health management method of claim 2, further comprising: acquiring a health state score of the equipment, wherein the health state score comprises a service time score, a guarantee capability score and a performance state score of the equipment;
wherein the time of service score
Figure FDA0002326955260000021
Wherein X represents the full life cycle, X1representing the time of service, α representing the service coefficient, Y1A full score value representing the time-of-service score;
the ability to safeguard score
Figure FDA0002326955260000022
Wherein, Y2A full score value representing the security capability score, M represents a spare part type, LjDenotes the number of jth spare parts, NjRepresents the consumption number of the jth spare part, and is more than or equal to 0 and less than or equal to Nj≤Lj，M、Lj、NjAnd j are integers;
and acquiring the power value of the equipment, and obtaining the performance state score in a segmented manner according to different temperatures.
4. The method according to claim 3, wherein determining the remaining life of the device based on the actual output status specifically comprises:
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 extreme value according to preset cut-off output power;
s21, respectively substituting the actual temperature and the final working temperature extreme value into a fitting equation of the temperature along with the time: t is 0.0299T2-2.2420T +33.1209 yielding T, respectively1And t2The residual life is t2-t1Where T represents a temperature value.
5. The equipment health management method is characterized by comprising a pre-establishing module and a predicting 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, determines different pre-output modes of the equipment according to each mapping relation, and records the different pre-output modes as a pre-output mode set;
and the prediction module acquires the actual output state of the equipment, acquires a mapping relation corresponding to the actual output state according to the pre-output mode set, records 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.
6. The device health management method of claim 5, further comprising: the pre-establishing module obtains the temperature and the state of the ith component of the equipment and uses a first formula to represent the ith component biAnd the corresponding relation between the first formula and the corresponding failure mode, wherein the first formula is as follows:
Figure FDA0002326955260000031
wherein x isi，1Denotes the temperature, x, of the i-th componenti，2Indicating the state of the i-th component, xi，1And xi，2The 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 the fault state and the temperature exceeds the standard, and i is a positive integer;
establishing a second formula:
Figure FDA0002326955260000032
substituting the first formula into the second formula to obtain:
Figure FDA0002326955260000033
wherein, biRepresents the output value of the ith component, (x)i，1,xi，2) And biThe relationship between the components is the mapping relationship between the ith component and the corresponding failure mode;
by analogy, the pre-establishment module determines a mapping relationship between each component of the device and each corresponding failure mode.
7. The equipment health management method according to claim 6, further comprising 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 time of service score
Figure FDA0002326955260000041
Wherein X represents the full life cycle, X1representing the time of service, α representing the service coefficient, Y1A full score value representing the time-of-service score;
the ability to safeguard score
Figure FDA0002326955260000042
Wherein, Y2A full score value representing the security capability score, M represents a spare part type, LjDenotes the number of jth spare parts, NjRepresents the consumption number of the jth spare part, and is more than or equal to 0 and less than or equal to Nj≤Lj，M、Lj、NjAnd j are integers;
and acquiring the power value of the equipment, and obtaining the performance state score in a segmented manner according to different temperatures.
8. The device health management method of claim 7, 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 extreme value according to preset cut-off output power, and respectively brings the actual temperature and the final working temperature extreme value into a fitting equation of the temperature along with time:
t＝0.0299T2-2.2420T +33.1209 yielding T, respectively1And t2The residual life is t2-t1Where T represents a temperature value.
9. A radar comprising a control chip, wherein the control chip is configured to perform the method for health management of a device according to any one of claims 1 to 4.
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