CN114355185A - Operation management and control system for intelligent switch - Google Patents
Operation management and control system for intelligent switch Download PDFInfo
- Publication number
- CN114355185A CN114355185A CN202210032158.1A CN202210032158A CN114355185A CN 114355185 A CN114355185 A CN 114355185A CN 202210032158 A CN202210032158 A CN 202210032158A CN 114355185 A CN114355185 A CN 114355185A
- Authority
- CN
- China
- Prior art keywords
- switch
- real
- intelligent switch
- time
- value
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Withdrawn
Links
- 238000001514 detection method Methods 0.000 claims abstract description 66
- 238000000034 method Methods 0.000 claims abstract description 48
- 238000004458 analytical method Methods 0.000 claims description 118
- 238000011156 evaluation Methods 0.000 claims description 29
- 238000011897 real-time detection Methods 0.000 claims description 29
- 230000007613 environmental effect Effects 0.000 claims description 26
- 230000002159 abnormal effect Effects 0.000 claims description 11
- 238000010223 real-time analysis Methods 0.000 claims description 7
- 230000002093 peripheral effect Effects 0.000 claims description 6
- 230000000630 rising effect Effects 0.000 claims description 6
- 230000006854 communication Effects 0.000 claims description 3
- 238000004891 communication Methods 0.000 claims description 3
- 230000005611 electricity Effects 0.000 abstract description 4
- 238000007726 management method Methods 0.000 description 5
- 238000012423 maintenance Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000007175 bidirectional communication Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000003891 environmental analysis Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000008054 signal transmission Effects 0.000 description 1
- 229920000638 styrene acrylonitrile Polymers 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
Images
Abstract
The invention discloses an operation control system for an intelligent switch, which relates to the technical field of intelligent switch control, solves the technical problem that the intelligent switch in the prior art cannot be controlled in real time in the operation process, detects the operation of the intelligent switch and controls the operation according to the detection result, ensures the operation efficiency of the intelligent switch, reduces the fault risk of the intelligent switch, improves the power utilization safety performance and simultaneously increases the use quality of a user; the real-time operation of the intelligent switch is detected, the real-time operation state of the intelligent switch is judged, the detection accuracy of the intelligent switch is improved, and the condition that the operation detection of the intelligent switch has faults, so that the operation efficiency of the intelligent switch is reduced, and the electricity utilization risk of a user is increased; the fault prediction is carried out on the intelligent switch corresponding to the real-time operation normal signal, so that the fault risk in the operation process of the intelligent switch is reduced, and the stability of the qualified operation of the intelligent switch is improved.
Description
Technical Field
The invention relates to the technical field of intelligent switch control, in particular to an operation control system for an intelligent switch.
Background
The intelligent switch is a unit which utilizes the combination and programming of a control panel and an electronic component to realize the control of the intelligent switch of the circuit; the intelligent switch makes storage management possible in different environments, reduces the cost of SAM, provides extensibility and scalability to the large number of existing storage area networks, and is still in the stage of evolution, perhaps not an ideal solution for small businesses, or cannot be changed instantly in SANs as one would like;
however, in the prior art, the intelligent switch cannot be managed and controlled in real time in the operation process, and the operation performance of the intelligent switch can be accurately judged through real-time detection, fault prediction and environmental analysis, so that the intelligent switch cannot be accurately scheduled, and the intelligent switch resources cannot be evenly distributed;
in view of the above technical drawbacks, a solution is proposed.
Disclosure of Invention
The invention aims to solve the problems and provides an operation control system for an intelligent switch, which detects the operation of the intelligent switch and controls the operation according to the detection result, thereby ensuring the operation efficiency of the intelligent switch, reducing the fault risk of the intelligent switch, improving the power utilization safety performance and simultaneously increasing the use quality of users; the real-time operation of the intelligent switch is detected, the real-time operation state of the intelligent switch is judged, the detection accuracy of the intelligent switch is improved, and the condition that the operation detection of the intelligent switch has faults, so that the operation efficiency of the intelligent switch is reduced, and the electricity utilization risk of a user is increased; the fault prediction is carried out on the intelligent switch corresponding to the real-time operation normal signal, so that the fault risk in the operation process of the intelligent switch is reduced, and the stability of the qualified operation of the intelligent switch is improved.
The purpose of the invention can be realized by the following technical scheme:
an operation control system for an intelligent switch comprises an intelligent switch control platform, wherein a server is arranged in the intelligent switch control platform, and the server is in communication connection with a real-time detection analysis unit, a fault prediction analysis unit, an environment detection analysis unit and an operation evaluation analysis unit;
the intelligent switch control platform is used for detecting the operation of the intelligent switch and controlling the operation according to the detection result, the server generates a real-time detection analysis signal and sends the real-time detection analysis signal to the real-time detection analysis unit, and the real-time operation of the intelligent switch is detected through the real-time detection analysis unit; generating a real-time operation abnormal signal or a real-time operation normal signal through detection; the server generates a fault prediction analysis signal and sends the fault prediction analysis signal to a fault prediction analysis unit, and the fault prediction analysis unit carries out fault prediction on the intelligent switch corresponding to the real-time operation normal signal; generating a high risk fault signal or a low risk fault signal through fault prediction; the server generates an environment detection analysis signal and sends the environment detection analysis signal to the environment detection analysis unit, and the environment detection analysis unit carries out environment detection analysis on a fault prediction object corresponding to the low-risk fault signal; acquiring an environment-influenced switch and a non-environment-influenced switch through environment detection and analysis; the server generates an operation evaluation analysis signal and sends the operation evaluation analysis signal to the operation evaluation analysis unit, and the operation evaluation analysis unit carries out operation evaluation analysis on the environment-influenced switch and the non-environment-influenced switch.
As a preferred embodiment of the present invention, the real-time detection and analysis process of the real-time detection and analysis unit is as follows:
acquiring data of the intelligent switch which runs in real time, setting a mark i corresponding to the intelligent switch, wherein the mark i is a natural number larger than 1, acquiring a temperature value of the intelligent switch and a real-time rising speed of the temperature value corresponding to the intelligent switch in the real-time running process, and marking the temperature value of the intelligent switch and the real-time rising speed of the temperature value corresponding to the intelligent switch in the real-time running process as WDZi and SSDi respectively; acquiring a numerical value that the noise decibel value generated by the intelligent switch is higher than the peripheral environment decibel value in the real-time operation process, and marking the numerical value that the noise decibel value generated by the intelligent switch is higher than the peripheral environment decibel value in the real-time operation process as GFBi;
the real-time running intelligent switch detection analysis coefficient Xi is obtained through analysis, and the real-time running intelligent switch detection analysis coefficient Xi is compared with a real-time detection analysis coefficient threshold value:
if the real-time running intelligent switch detection analysis coefficient Xi exceeds the real-time detection analysis coefficient threshold value, judging that the corresponding intelligent switch is unqualified in real-time running detection, generating a real-time running abnormal signal and sending the real-time running abnormal signal and the number of the corresponding intelligent switch to a server; and if the detection and analysis coefficient Xi of the intelligent switch which operates in real time does not exceed the threshold value of the detection and analysis coefficient of the real time, judging that the real-time operation detection of the corresponding intelligent switch is qualified, generating a normal signal of the real-time operation, and sending the normal signal of the real-time operation and the number of the corresponding intelligent switch to the server.
As a preferred embodiment of the present invention, the failure prediction analysis process of the failure prediction analysis unit is as follows:
the method comprises the following steps of marking an intelligent switch corresponding to a real-time operation normal signal as a fault prediction object, carrying out data acquisition on the fault prediction object, acquiring a voltage peak value passed by the fault prediction object in an operation process and a frequency continuously operated with the voltage peak value, and comparing the voltage peak value passed by the fault prediction object in the operation process and the frequency continuously operated with the voltage peak value with a voltage peak value threshold value and a voltage peak value operation frequency threshold value respectively:
if the voltage peak value passed by the fault prediction object in the operation process exceeds the voltage peak value threshold value, or the frequency continuously operated with the voltage peak value exceeds the frequency threshold value operated with the voltage peak value, judging that the corresponding fault prediction object has a high fault risk, generating a high-risk fault signal and sending the high-risk fault signal and the number of the corresponding fault prediction object to the server; if the voltage peak value passed by the fault prediction object in the operation process does not exceed the voltage peak value threshold value and the frequency continuously operated with the voltage peak value does not exceed the frequency threshold value operated with the voltage peak value, determining that the corresponding fault prediction object has a low fault risk, generating a low-risk fault signal and sending the low-risk fault signal and the number of the corresponding fault prediction object to the server.
As a preferred embodiment of the present invention, the environment detection analysis process of the environment detection analysis unit is as follows:
acquiring data of a fault prediction object corresponding to the low-risk fault signal, acquiring a floating value corresponding to the difference value between the operating temperature and the ambient temperature of the fault prediction object and the difference between the floating speed corresponding to the operating temperature and the floating speed of the ambient temperature, and comparing the floating value corresponding to the difference value between the operating temperature and the ambient temperature of the fault prediction object and the difference between the floating speed corresponding to the operating temperature and the floating speed of the ambient temperature with a difference floating value threshold value and a floating speed difference threshold value respectively:
if the difference value of the operation temperature of the fault prediction object and the ambient temperature is larger than the difference value floating value threshold value correspondingly, or the difference value of the floating speed of the corresponding operation temperature and the floating speed of the ambient temperature is larger than the floating speed difference value threshold value, judging that the corresponding fault prediction object has environmental influence during operation, marking the corresponding fault prediction object as an environmental influence switch, generating an environmental influence signal and sending the environmental influence signal and the serial number of the environmental influence switch to the server together; if the floating value corresponding to the difference value between the operation temperature of the fault prediction object and the ambient temperature does not exceed the difference floating value threshold value, and the difference between the floating speed corresponding to the operation temperature and the floating speed corresponding to the ambient temperature does not exceed the floating speed difference value threshold value, it is judged that no environmental influence exists in the operation of the corresponding fault prediction object, the corresponding fault prediction object is marked as a non-environmental-influence switch, an environmental non-influence signal is generated, and the environmental non-influence signal and the serial number of the non-environmental-influence switch are sent to the server together.
As a preferred embodiment of the present invention, the operation evaluation analysis process of the operation evaluation analysis unit is as follows:
uniformly marking the environment-influenced switch and the non-environment-influenced switch as switches to be evaluated, collecting the operation voltage peak value and the continuous operation longest time of the switches to be evaluated, and respectively comparing the operation voltage peak value and the continuous operation longest time of the switches to be evaluated with an operation voltage peak value threshold value and a longest time threshold value:
if the operating voltage peak value of the switch to be evaluated exceeds the operating voltage peak value threshold value, or the longest duration of continuous operation exceeds the longest duration threshold value, judging that the operating performance of the corresponding switch to be evaluated is high-quality, and if the corresponding switch to be evaluated is an environment-influenced switch, marking the corresponding environment-influenced switch as a high-quality operating switch; if the corresponding switch to be evaluated is a non-environment-influenced switch, marking the corresponding environment-influenced switch as a qualified operation switch;
if the operation voltage peak value of the switch to be evaluated does not exceed the operation voltage peak value threshold value and the longest time length of continuous operation does not exceed the longest time length threshold value, judging that the operation performance of the corresponding switch to be evaluated is ordinary, and if the corresponding switch to be evaluated is an environment-influenced switch, marking the corresponding environment-influenced switch as a normal operation switch; if the corresponding switch to be evaluated is a non-environment-influenced switch, marking the corresponding environment-influenced switch as a low-quality operation switch; and sending the high-quality operation switch, the qualified operation switch, the normal operation switch and the low-quality operation switch to a server together.
Compared with the prior art, the invention has the beneficial effects that:
1. according to the intelligent switch, the operation of the intelligent switch is detected and controlled according to the detection result, so that the operation efficiency of the intelligent switch is ensured, the fault risk of the intelligent switch is reduced, the electricity safety performance is improved, and the use quality of a user is improved; the real-time operation of the intelligent switch is detected, the real-time operation state of the intelligent switch is judged, the detection accuracy of the intelligent switch is improved, and the condition that the operation detection of the intelligent switch has faults, so that the operation efficiency of the intelligent switch is reduced, and the electricity utilization risk of a user is increased; the fault prediction is carried out on the intelligent switch corresponding to the real-time operation normal signal, so that the fault risk in the operation process of the intelligent switch is reduced, and the qualified operation stability of the intelligent switch is improved;
2. according to the intelligent switch control method, the environment detection analysis is carried out on the fault prediction object corresponding to the low-risk fault signal, and the influence of the environment on the switch operation in the operation process of the corresponding fault prediction object is judged, so that the accuracy of intelligent switch control is improved; the operating performance of the intelligent switch is accurately judged, the control of the performance of the intelligent switch is improved, reasonable distribution of the intelligent switch is facilitated, and the operating efficiency of the intelligent switch is enhanced.
Drawings
In order to facilitate understanding for those skilled in the art, the present invention will be further described with reference to the accompanying drawings.
Fig. 1 is a schematic block diagram of an operation management and control system for an intelligent switch according to the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the following embodiments, and it should be understood that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, an operation control system for an intelligent switch includes an intelligent switch control platform, a server is disposed in the intelligent switch control platform, and the server is connected with a real-time detection and analysis unit, a fault prediction and analysis unit, an environment detection and analysis unit, and an operation evaluation and analysis unit in a communication manner, wherein the server is connected with the real-time detection and analysis unit, the fault prediction and analysis unit, the environment detection and analysis unit, and the operation evaluation and analysis unit in a bidirectional communication manner;
the intelligent switch management and control platform is used for detecting the operation of intelligent switch and managing and controlling according to the testing result, ensure the operating efficiency of intelligent switch, the trouble risk of intelligent switch has been reduced, the quality of use that has increased the user when having improved the power consumption security performance, the server generates real-time detection analysis signal and sends real-time detection analysis signal to real-time detection analysis unit, real-time detection analysis unit is used for detecting the real-time operation of intelligent switch, judge the real-time running state of intelligent switch, the accuracy that the intelligent switch detected has been improved, prevent that intelligent switch operation from detecting to have trouble, the operating efficiency that leads to intelligent switch reduces the power consumption risk that has increased the user, concrete real-time detection analytic process is as follows:
acquiring data of the intelligent switch which runs in real time, setting a mark i corresponding to the intelligent switch, wherein the mark i is a natural number larger than 1, acquiring a temperature value of the intelligent switch and a real-time rising speed of the temperature value corresponding to the intelligent switch in the real-time running process, and marking the temperature value of the intelligent switch and the real-time rising speed of the temperature value corresponding to the intelligent switch in the real-time running process as WDZi and SSDi respectively; acquiring a numerical value that the noise decibel value generated by the intelligent switch is higher than the peripheral environment decibel value in the real-time operation process, and marking the numerical value that the noise decibel value generated by the intelligent switch is higher than the peripheral environment decibel value in the real-time operation process as GFBi;
by the formula Xi ═ e (WDZi × a1+ SSDi × a2+ GFBi × a3)a1+a2+a3Acquiring an intelligent switch detection analysis coefficient Xi running in real time, wherein a1, a2 and a3 are all preset proportionality coefficients, a1 is greater than a2 is greater than a3 is greater than 0, and e is a natural constant;
comparing the real-time running intelligent switch detection analysis coefficient Xi with a real-time detection analysis coefficient threshold value:
if the real-time running intelligent switch detection analysis coefficient Xi exceeds the real-time detection analysis coefficient threshold value, judging that the corresponding intelligent switch is unqualified in real-time running detection, generating a real-time running abnormal signal and sending the real-time running abnormal signal and the number of the corresponding intelligent switch to a server; if the detection and analysis coefficient Xi of the intelligent switch which operates in real time does not exceed the threshold value of the detection and analysis coefficient of real time, judging that the real-time operation detection of the corresponding intelligent switch is qualified, generating a normal signal of real-time operation, and sending the normal signal of real-time operation and the number of the corresponding intelligent switch to a server;
after the server receives the abnormal signal of real-time operation, the operation that will correspond intelligent switch is interrupted and will correspond intelligent switch and overhaul the maintenance, the influence of intelligent switch abnormal operation to the user power consumption has been reduced, after the server received the normal signal of real-time operation, generate the failure prediction analysis signal and with failure prediction analysis signal transmission to failure prediction analysis unit, failure prediction analysis unit is used for carrying out the failure prediction to the intelligent switch that the normal signal of real-time operation corresponds, the trouble risk in the intelligence switch operation process has been reduced, the stability of the qualified operation of intelligent switch has been improved, concrete failure prediction analysis process is as follows:
the method comprises the following steps of marking an intelligent switch corresponding to a real-time operation normal signal as a fault prediction object, carrying out data acquisition on the fault prediction object, acquiring a voltage peak value passed by the fault prediction object in an operation process and a frequency continuously operated with the voltage peak value, and comparing the voltage peak value passed by the fault prediction object in the operation process and the frequency continuously operated with the voltage peak value with a voltage peak value threshold value and a voltage peak value operation frequency threshold value respectively:
if the voltage peak value passed by the fault prediction object in the operation process exceeds the voltage peak value threshold value, or the frequency continuously operated with the voltage peak value exceeds the frequency threshold value operated with the voltage peak value, judging that the corresponding fault prediction object has a high fault risk, generating a high-risk fault signal and sending the high-risk fault signal and the number of the corresponding fault prediction object to the server; if the voltage peak value passed by the fault prediction object in the operation process does not exceed the voltage peak value threshold value and the frequency continuously operating at the voltage peak value does not exceed the frequency threshold value operating at the voltage peak value, judging that the corresponding fault prediction object has a low fault risk, generating a low-risk fault signal and sending the low-risk fault signal and the number of the corresponding fault prediction object to the server;
after receiving the high-risk fault signal, the server carries out real-time maintenance and overhaul on the corresponding fault prediction object; after the server receives the low risk fault signal, generate environment detection analysis signal and send environment detection analysis signal to environment detection analysis unit, environment detection analysis unit is used for corresponding the failure prediction object to low risk fault signal and carries out environment detection analysis, judges the influence of environment to the switch operation in the corresponding failure prediction object operation process to the improvement is to the precision of intelligent switch management and control, and concrete environment detection analysis process is as follows:
acquiring data of a fault prediction object corresponding to the low-risk fault signal, acquiring a floating value corresponding to the difference value between the operating temperature and the ambient temperature of the fault prediction object and the difference between the floating speed corresponding to the operating temperature and the floating speed of the ambient temperature, and comparing the floating value corresponding to the difference value between the operating temperature and the ambient temperature of the fault prediction object and the difference between the floating speed corresponding to the operating temperature and the floating speed of the ambient temperature with a difference floating value threshold value and a floating speed difference threshold value respectively:
if the difference value of the operation temperature of the fault prediction object and the ambient temperature is larger than the difference value floating value threshold value correspondingly, or the difference value of the floating speed of the corresponding operation temperature and the floating speed of the ambient temperature is larger than the floating speed difference value threshold value, judging that the corresponding fault prediction object has environmental influence during operation, marking the corresponding fault prediction object as an environmental influence switch, generating an environmental influence signal and sending the environmental influence signal and the serial number of the environmental influence switch to the server together; if the floating value corresponding to the difference value between the operation temperature of the fault prediction object and the ambient temperature does not exceed the difference floating value threshold value, and the difference between the floating speed corresponding to the operation temperature and the floating speed corresponding to the ambient temperature does not exceed the floating speed difference value threshold value, judging that the corresponding fault prediction object does not have environmental influence in operation, marking the corresponding fault prediction object as a non-environmental influence switch, generating an environmental non-influence signal and sending the environmental non-influence signal and the serial number of the non-environmental influence switch to the server;
the server generates operation evaluation analysis signals and sends the operation evaluation analysis signals to the operation evaluation analysis unit, the operation evaluation analysis unit is used for carrying out operation evaluation analysis on the environment-influenced switch and the non-environment-influenced switch, the operation performance of the intelligent switch is accurately judged, the control of the performance of the intelligent switch is improved, the reasonable distribution of the intelligent switch is facilitated, the operation efficiency of the intelligent switch is enhanced, and the specific operation evaluation analysis process is as follows:
uniformly marking the environment-influenced switch and the non-environment-influenced switch as switches to be evaluated, collecting the operation voltage peak value and the continuous operation longest time of the switches to be evaluated, and respectively comparing the operation voltage peak value and the continuous operation longest time of the switches to be evaluated with an operation voltage peak value threshold value and a longest time threshold value:
if the operating voltage peak value of the switch to be evaluated exceeds the operating voltage peak value threshold value, or the longest duration of continuous operation exceeds the longest duration threshold value, judging that the operating performance of the corresponding switch to be evaluated is high-quality, and if the corresponding switch to be evaluated is an environment-influenced switch, marking the corresponding environment-influenced switch as a high-quality operating switch; if the corresponding switch to be evaluated is a non-environment-influenced switch, marking the corresponding environment-influenced switch as a qualified operation switch;
if the operation voltage peak value of the switch to be evaluated does not exceed the operation voltage peak value threshold value and the longest time length of continuous operation does not exceed the longest time length threshold value, judging that the operation performance of the corresponding switch to be evaluated is ordinary, and if the corresponding switch to be evaluated is an environment-influenced switch, marking the corresponding environment-influenced switch as a normal operation switch; if the corresponding switch to be evaluated is a non-environment-influenced switch, marking the corresponding environment-influenced switch as a low-quality operation switch;
sending the high-quality operation switch, the qualified operation switch, the normal operation switch and the low-quality operation switch to a server together; the server receives the high-quality operation switch, the qualified operation switch, the normal operation switch and the low-quality operation switch, and then real-time scheduling distribution is carried out according to the type of the intelligent switch, and the high-quality operation switch, the qualified operation switch, the normal operation switch and the low-quality operation switch are classified according to the operation efficiency, so that the efficiency of the high-quality operation switch is optimal, the qualified operation switch and the normal operation switch can be influenced by the environment and can normally operate, and the low-quality operation switch shows that the efficiency can be reduced under the influence of the environment.
The formulas are obtained by acquiring a large amount of data and performing software simulation, and the coefficients in the formulas are set by the technicians in the field according to actual conditions;
when the intelligent switch is used, the operation of the intelligent switch is detected through the intelligent switch control platform, the intelligent switch is controlled according to a detection result, and the real-time operation of the intelligent switch is detected through the real-time detection and analysis unit; generating a real-time operation abnormal signal or a real-time operation normal signal through detection; performing fault prediction on the intelligent switch corresponding to the real-time operation normal signal through a fault prediction analysis unit; generating a high risk fault signal or a low risk fault signal through fault prediction; performing environment detection analysis on a fault prediction object corresponding to the low-risk fault signal through an environment detection analysis unit; acquiring an environment-influenced switch and a non-environment-influenced switch through environment detection and analysis; the server generates an operation evaluation analysis signal and sends the operation evaluation analysis signal to the operation evaluation analysis unit, and the operation evaluation analysis unit carries out operation evaluation analysis on the environment-influenced switch and the non-environment-influenced switch.
The preferred embodiments of the invention disclosed above are intended to be illustrative only. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise forms disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best utilize the invention. The invention is limited only by the claims and their full scope and equivalents.
Claims (5)
1. An operation control system for an intelligent switch is characterized by comprising an intelligent switch control platform, wherein a server is arranged in the intelligent switch control platform, and the server is in communication connection with a real-time detection analysis unit, a fault prediction analysis unit, an environment detection analysis unit and an operation evaluation analysis unit;
the intelligent switch control platform is used for detecting the operation of the intelligent switch and controlling the operation according to the detection result, the server generates a real-time detection analysis signal and sends the real-time detection analysis signal to the real-time detection analysis unit, and the real-time operation of the intelligent switch is detected through the real-time detection analysis unit; generating a real-time operation abnormal signal or a real-time operation normal signal through detection; the server generates a fault prediction analysis signal and sends the fault prediction analysis signal to a fault prediction analysis unit, and the fault prediction analysis unit carries out fault prediction on the intelligent switch corresponding to the real-time operation normal signal; generating a high risk fault signal or a low risk fault signal through fault prediction; the server generates an environment detection analysis signal and sends the environment detection analysis signal to the environment detection analysis unit, and the environment detection analysis unit carries out environment detection analysis on a fault prediction object corresponding to the low-risk fault signal; acquiring an environment-influenced switch and a non-environment-influenced switch through environment detection and analysis; the server generates an operation evaluation analysis signal and sends the operation evaluation analysis signal to the operation evaluation analysis unit, and the operation evaluation analysis unit carries out operation evaluation analysis on the environment-influenced switch and the non-environment-influenced switch.
2. The operation control system for the intelligent switch according to claim 1, wherein the real-time detection and analysis process of the real-time detection and analysis unit is as follows:
acquiring data of the intelligent switch which runs in real time, setting a mark i corresponding to the intelligent switch, wherein the mark i is a natural number larger than 1, acquiring a temperature value of the intelligent switch and a real-time rising speed of the temperature value corresponding to the intelligent switch in the real-time running process, and marking the temperature value of the intelligent switch and the real-time rising speed of the temperature value corresponding to the intelligent switch in the real-time running process as WDZi and SSDi respectively; acquiring a numerical value that the noise decibel value generated by the intelligent switch is higher than the peripheral environment decibel value in the real-time operation process, and marking the numerical value that the noise decibel value generated by the intelligent switch is higher than the peripheral environment decibel value in the real-time operation process as GFBi;
the real-time running intelligent switch detection analysis coefficient Xi is obtained through analysis, and the real-time running intelligent switch detection analysis coefficient Xi is compared with a real-time detection analysis coefficient threshold value:
if the real-time running intelligent switch detection analysis coefficient Xi exceeds the real-time detection analysis coefficient threshold value, judging that the corresponding intelligent switch is unqualified in real-time running detection, generating a real-time running abnormal signal and sending the real-time running abnormal signal and the number of the corresponding intelligent switch to a server; and if the detection and analysis coefficient Xi of the intelligent switch which operates in real time does not exceed the threshold value of the detection and analysis coefficient of the real time, judging that the real-time operation detection of the corresponding intelligent switch is qualified, generating a normal signal of the real-time operation, and sending the normal signal of the real-time operation and the number of the corresponding intelligent switch to the server.
3. The operation control system for the intelligent switch according to claim 1, wherein the failure prediction analysis process of the failure prediction analysis unit is as follows:
the method comprises the following steps of marking an intelligent switch corresponding to a real-time operation normal signal as a fault prediction object, carrying out data acquisition on the fault prediction object, acquiring a voltage peak value passed by the fault prediction object in an operation process and a frequency continuously operated with the voltage peak value, and comparing the voltage peak value passed by the fault prediction object in the operation process and the frequency continuously operated with the voltage peak value with a voltage peak value threshold value and a voltage peak value operation frequency threshold value respectively:
if the voltage peak value passed by the fault prediction object in the operation process exceeds the voltage peak value threshold value, or the frequency continuously operated with the voltage peak value exceeds the frequency threshold value operated with the voltage peak value, judging that the corresponding fault prediction object has a high fault risk, generating a high-risk fault signal and sending the high-risk fault signal and the number of the corresponding fault prediction object to the server; if the voltage peak value passed by the fault prediction object in the operation process does not exceed the voltage peak value threshold value and the frequency continuously operated with the voltage peak value does not exceed the frequency threshold value operated with the voltage peak value, determining that the corresponding fault prediction object has a low fault risk, generating a low-risk fault signal and sending the low-risk fault signal and the number of the corresponding fault prediction object to the server.
4. The operation control system for the intelligent switch according to claim 1, wherein the environment detection analysis process of the environment detection analysis unit is as follows:
acquiring data of a fault prediction object corresponding to the low-risk fault signal, acquiring a floating value corresponding to the difference value between the operating temperature and the ambient temperature of the fault prediction object and the difference between the floating speed corresponding to the operating temperature and the floating speed of the ambient temperature, and comparing the floating value corresponding to the difference value between the operating temperature and the ambient temperature of the fault prediction object and the difference between the floating speed corresponding to the operating temperature and the floating speed of the ambient temperature with a difference floating value threshold value and a floating speed difference threshold value respectively:
if the difference value of the operation temperature of the fault prediction object and the ambient temperature is larger than the difference value floating value threshold value correspondingly, or the difference value of the floating speed of the corresponding operation temperature and the floating speed of the ambient temperature is larger than the floating speed difference value threshold value, judging that the corresponding fault prediction object has environmental influence during operation, marking the corresponding fault prediction object as an environmental influence switch, generating an environmental influence signal and sending the environmental influence signal and the serial number of the environmental influence switch to the server together; if the floating value corresponding to the difference value between the operation temperature of the fault prediction object and the ambient temperature does not exceed the difference floating value threshold value, and the difference between the floating speed corresponding to the operation temperature and the floating speed corresponding to the ambient temperature does not exceed the floating speed difference value threshold value, it is judged that no environmental influence exists in the operation of the corresponding fault prediction object, the corresponding fault prediction object is marked as a non-environmental-influence switch, an environmental non-influence signal is generated, and the environmental non-influence signal and the serial number of the non-environmental-influence switch are sent to the server together.
5. The operation control system for the intelligent switch according to claim 1, wherein the operation evaluation analysis process of the operation evaluation analysis unit is as follows:
uniformly marking the environment-influenced switch and the non-environment-influenced switch as switches to be evaluated, collecting the operation voltage peak value and the continuous operation longest time of the switches to be evaluated, and respectively comparing the operation voltage peak value and the continuous operation longest time of the switches to be evaluated with an operation voltage peak value threshold value and a longest time threshold value:
if the operating voltage peak value of the switch to be evaluated exceeds the operating voltage peak value threshold value, or the longest duration of continuous operation exceeds the longest duration threshold value, judging that the operating performance of the corresponding switch to be evaluated is high-quality, and if the corresponding switch to be evaluated is an environment-influenced switch, marking the corresponding environment-influenced switch as a high-quality operating switch; if the corresponding switch to be evaluated is a non-environment-influenced switch, marking the corresponding environment-influenced switch as a qualified operation switch;
if the operation voltage peak value of the switch to be evaluated does not exceed the operation voltage peak value threshold value and the longest time length of continuous operation does not exceed the longest time length threshold value, judging that the operation performance of the corresponding switch to be evaluated is ordinary, and if the corresponding switch to be evaluated is an environment-influenced switch, marking the corresponding environment-influenced switch as a normal operation switch; if the corresponding switch to be evaluated is a non-environment-influenced switch, marking the corresponding environment-influenced switch as a low-quality operation switch; and sending the high-quality operation switch, the qualified operation switch, the normal operation switch and the low-quality operation switch to a server together.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210032158.1A CN114355185A (en) | 2022-01-12 | 2022-01-12 | Operation management and control system for intelligent switch |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210032158.1A CN114355185A (en) | 2022-01-12 | 2022-01-12 | Operation management and control system for intelligent switch |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN114355185A true CN114355185A (en) | 2022-04-15 |
Family
ID=81108287
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210032158.1A Withdrawn CN114355185A (en) | 2022-01-12 | 2022-01-12 | Operation management and control system for intelligent switch |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114355185A (en) |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114628016A (en) * | 2022-05-17 | 2022-06-14 | 西南医科大学附属医院 | Laparoscope surgical instrument operation fault prediction system based on big data |
| CN114665611A (en) * | 2022-05-25 | 2022-06-24 | 融科能源系统(广东)有限公司 | Power distribution cabinet operation intelligent monitoring management system based on data analysis |
| CN115957447A (en) * | 2022-12-29 | 2023-04-14 | 安徽猫头鹰科技有限公司 | Operation detection system for calibrated light instrument |
| CN117110746A (en) * | 2023-08-25 | 2023-11-24 | 安徽中科源起科技有限公司 | Super station fault location detection management system based on cloud platform |
-
2022
- 2022-01-12 CN CN202210032158.1A patent/CN114355185A/en not_active Withdrawn
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114628016A (en) * | 2022-05-17 | 2022-06-14 | 西南医科大学附属医院 | Laparoscope surgical instrument operation fault prediction system based on big data |
| CN114665611A (en) * | 2022-05-25 | 2022-06-24 | 融科能源系统(广东)有限公司 | Power distribution cabinet operation intelligent monitoring management system based on data analysis |
| CN114665611B (en) * | 2022-05-25 | 2022-07-29 | 融科能源系统(广东)有限公司 | Power distribution cabinet operation intelligent monitoring management system based on data analysis |
| CN115957447A (en) * | 2022-12-29 | 2023-04-14 | 安徽猫头鹰科技有限公司 | Operation detection system for calibrated light instrument |
| CN115957447B (en) * | 2022-12-29 | 2023-08-08 | 安徽猫头鹰科技有限公司 | Operation detection system for calibratable light feeding instrument |
| CN117110746A (en) * | 2023-08-25 | 2023-11-24 | 安徽中科源起科技有限公司 | Super station fault location detection management system based on cloud platform |
| CN117110746B (en) * | 2023-08-25 | 2024-03-12 | 安徽中科源起科技有限公司 | Super station fault location detection management system based on cloud platform |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN114355185A (en) | Operation management and control system for intelligent switch | |
| CN114498942B (en) | Transformer monitoring management system based on big data analysis | |
| CN110212645B (en) | Power consumption information acquisition terminal power failure event reporting method and device | |
| CN114819415B (en) | Power equipment fault prediction system based on data analysis | |
| CN114826989A (en) | Communication equipment operation monitoring and predicting system based on big data | |
| CN112436888B (en) | Method, device, equipment and medium for adjusting value of selected key attribute of optical module | |
| CN114123512B (en) | High tension switchgear remote control system based on it is intelligent | |
| CN113325308B (en) | Power supply fault detection method for data center | |
| CN103227662A (en) | Safety detection method and system of electric power communication equipment based on state control | |
| CN115473331B (en) | Digital twin power grid electricity consumption monitoring system based on dynamic modeling | |
| CN204206183U (en) | A kind of system of testing smart machine luminous power receiving sensitivity | |
| CN116885716A (en) | Edge calculation-based low-voltage distribution network power quality situation awareness method and system | |
| CN117031381B (en) | Fault detection system and method of power supply detection equipment | |
| CN115834325A (en) | SD-WAN-oriented network hardware operation management system | |
| CN115907731A (en) | Big data-based electric power operation and maintenance management system | |
| CN113644711B (en) | Management system for wireless charging of interactive mobile phone | |
| CN204882837U (en) | Electric power DC power supply module's ageing monitored control system | |
| CN112751421A (en) | Digital computing enhanced high-reliability low-voltage power distribution safety monitoring system | |
| CN115425734B (en) | Operation and maintenance box with automatic energy-saving operation program | |
| CN115829166B (en) | Equipment selection optimizing system based on efficient machine room | |
| CN112468346B (en) | Equipment monitoring and early warning visualization system based on simple network management protocol | |
| CN112986673B (en) | Electric heating metering method and electric heating meter | |
| CN116545124B (en) | Digital intelligent switch cabinet comprehensive monitoring system | |
| CN104092301A (en) | Remote centralized online monitoring system and method for storage battery of power distribution equipment | |
| CN215870906U (en) | Digital computing enhanced high-reliability low-voltage power distribution safety monitoring system |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| WW01 | Invention patent application withdrawn after publication | ||
| WW01 | Invention patent application withdrawn after publication |
Application publication date: 20220415 |