CN116320832A - Monitoring equipment fault monitoring method and device - Google Patents
Monitoring equipment fault monitoring method and device Download PDFInfo
- Publication number
- CN116320832A CN116320832A CN202310582750.3A CN202310582750A CN116320832A CN 116320832 A CN116320832 A CN 116320832A CN 202310582750 A CN202310582750 A CN 202310582750A CN 116320832 A CN116320832 A CN 116320832A
- Authority
- CN
- China
- Prior art keywords
- fault
- monitoring
- monitoring equipment
- equipment
- information
- 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.)
- Granted
Links
- 238000012544 monitoring process Methods 0.000 title claims abstract description 260
- 238000000034 method Methods 0.000 title claims abstract description 37
- 238000004458 analytical method Methods 0.000 claims abstract description 39
- 238000001514 detection method Methods 0.000 claims abstract description 17
- 230000002159 abnormal effect Effects 0.000 claims abstract description 13
- 238000012806 monitoring device Methods 0.000 claims description 22
- 238000012549 training Methods 0.000 claims description 17
- 238000012545 processing Methods 0.000 claims description 8
- 230000002093 peripheral effect Effects 0.000 claims description 7
- 238000000605 extraction Methods 0.000 claims description 5
- 238000011418 maintenance treatment Methods 0.000 claims description 4
- 238000012423 maintenance Methods 0.000 abstract description 2
- 238000011282 treatment Methods 0.000 description 6
- 230000005540 biological transmission Effects 0.000 description 4
- 238000004364 calculation method Methods 0.000 description 3
- 230000007613 environmental effect Effects 0.000 description 3
- 230000009286 beneficial effect Effects 0.000 description 2
- 230000002349 favourable effect Effects 0.000 description 2
- 238000007689 inspection Methods 0.000 description 2
- 238000007792 addition Methods 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 238000013135 deep learning Methods 0.000 description 1
- 230000001419 dependent effect Effects 0.000 description 1
- 238000003745 diagnosis Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 239000013307 optical fiber Substances 0.000 description 1
- 230000001681 protective effect Effects 0.000 description 1
- 238000000926 separation method Methods 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 1
Images
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04Q—SELECTING
- H04Q9/00—Arrangements in telecontrol or telemetry systems for selectively calling a substation from a main station, in which substation desired apparatus is selected for applying a control signal thereto or for obtaining measured values therefrom
-
- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/18—Status alarms
- G08B21/182—Level alarms, e.g. alarms responsive to variables exceeding a threshold
-
- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B31/00—Predictive alarm systems characterised by extrapolation or other computation using updated historic data
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N7/00—Television systems
- H04N7/18—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04Q—SELECTING
- H04Q2209/00—Arrangements in telecontrol or telemetry systems
- H04Q2209/80—Arrangements in the sub-station, i.e. sensing device
Landscapes
- Engineering & Computer Science (AREA)
- Signal Processing (AREA)
- Computing Systems (AREA)
- Computer Networks & Wireless Communication (AREA)
- Business, Economics & Management (AREA)
- Emergency Management (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Medical Informatics (AREA)
- Multimedia (AREA)
- Testing And Monitoring For Control Systems (AREA)
Abstract
The invention relates to the technical field of monitoring equipment detection, and particularly discloses a monitoring equipment fault monitoring method, which comprises the following steps: acquiring surrounding information environment parameters of the monitoring equipment and operation parameters of the monitoring equipment, and generating a fault monitoring strategy according to the operation parameters of the monitoring equipment; analyzing a fault monitoring strategy to judge whether the fault coefficient of the monitoring equipment is abnormal or not: if yes, judging whether the fault coefficient belongs to a preset threshold range; if yes, a first fault early warning signal is generated; if not, generating a second fault early warning signal and powering off; if not, judging that the monitoring equipment is normal; acquiring associated fault information of the monitoring equipment according to the first fault early warning signal result; performing equipment fault operation through the associated fault information analysis result; by setting and analyzing the fault monitoring strategy, the accurate detection of the influence factors of the surrounding environment of the monitoring equipment on the faults of the monitoring equipment is ensured, and the fault maintenance analysis speed of the monitoring equipment is improved.
Description
Technical Field
The invention relates to the technical field of monitoring equipment detection, in particular to a monitoring equipment fault monitoring method and device.
Background
The monitoring equipment generally comprises a front-end equipment and a rear-end equipment, the front-end equipment and the rear-end equipment have various construction modes, the connection between the front-end equipment and the rear-end equipment (also can be called a transmission system) can be realized through various modes such as cables, optical fibers or microwaves, the front-end equipment generally comprises a camera, a manual or electric lens, a cradle head, a protective cover, a monitor, an alarm detector, a multifunctional decoder and the like, and the rear-end equipment comprises various control equipment; other parts such as display, record and the like are included.
The monitoring device mainly performs a transmission process of monitoring information through a transmission system, for example, a transmission server is responsible for moving data between devices on a network; when the fault of the monitoring equipment occurs, the performance of the equipment is reduced by the light weight, the service life is shortened, and the equipment is destroyed by the heavy weight, so that the fault detection and diagnosis technology plays an important role in timely and accurately finding out the fault and predicting the fault if necessary, and ensuring that the equipment system always keeps high-efficiency, safe and reliable operation during the working period.
In the existing monitoring equipment fault monitoring process, the hardware condition of the front-end detection equipment is usually required to be pre-detected and monitored to reduce the generation probability of equipment faults, but for the actual condition, the situation of predicting the occurrence of faults of the hardware equipment in the actual monitoring process is easy to realize, and the influence of the surrounding environment except the equipment, in which the hardware equipment is in the condition, is usually fuzzy; in addition, after the equipment software is in a problem, operators with abundant experience are required to be invited to predict and judge the failure cause, and the process influences the detection efficiency of monitoring the failure of the monitoring equipment and the overhaul speed of the equipment to a certain extent.
Disclosure of Invention
The invention aims to provide a monitoring equipment fault monitoring method and device, which solve the following technical problems:
how to ensure the accurate detection of the influence factors of the surrounding environment of the monitoring equipment on the faults of the monitoring equipment and improve the fault maintenance analysis speed of the monitoring equipment.
The aim of the invention can be achieved by the following technical scheme:
a method of monitoring equipment failure, the method comprising:
step one, acquiring surrounding information environment parameters of monitoring equipment and operation parameters of the monitoring equipment, and generating a fault monitoring strategy according to the operation parameters of the monitoring equipment;
the monitoring device operating parameters include: high current signal parameterStrong voltage signal parameter->Network operation speed adjustment parameter->;
Analyzing a fault monitoring strategy to judge whether the fault coefficient of the monitoring equipment is abnormal or not:
if yes, judging whether the fault coefficient belongs to a preset threshold range;
if yes, a first fault early warning signal is generated;
if not, generating a second fault early warning signal and powering off;
if not, judging that the monitoring equipment is normal;
step three, acquiring the associated fault information of the monitoring equipment according to the first fault early warning signal result;
and fourthly, performing equipment fault operation through the analysis result of the associated fault information.
The fault monitoring strategy is generated in the following way:
by the formulaCalculating fault coefficient->Acquiring a fault monitoring strategy according to the fault coefficient;
wherein ,、/>respectively a strong current signal parameter weight coefficient and a strong voltage signalParameter weight coefficient,/->、、/>And the standard parameters are respectively a strong current signal standard parameter, a strong voltage signal standard parameter and a network operation speed adjustment standard parameter.
The ambient information environment parameters include working humidity parametersBy detecting the working humidity of the monitoring equipment, the peripheral electric leakage condition can be conveniently checked, and the electric safety of the hardware equipment is ensured.
Preferably, the fault coefficients in the fault monitoring strategy areAnd a preset failure coefficient standard threshold value->AndAlignment is carried out, and 0 </o-></>:
if it is≤/>≤/>Judging that the monitoring equipment is abnormal, generating a first fault early warning signal, and further detecting the working humidity of the monitoring equipment;
if it is>/>And judging that the monitoring equipment is abnormal, generating a second fault early warning signal, and performing power-off maintenance treatment.
Preferably, the step of obtaining the associated fault information includes:
Preferably, the difference is determinedAnd a preset threshold-> and />Alignment is carried out, and 0 </o-></>:
if it is≤/>Judging that the fault is related to the working humidity, but the influence is not great, and continuing to operate;
if it is</>≤/>Judging that the working humidity mainly influences the faults of the monitoring equipment, and carrying out fault early warning and overhauling;
if it is>/>And the working humidity seriously affects the faults of the monitoring equipment, and the fault alarm and the power failure are carried out.
Preferably, the device failure operation includes:
acquiring operation information of monitoring equipment and surrounding environment state information;
judging whether the fault type of the monitoring equipment is related to the surrounding environment state information according to the analysis result of the associated fault information:
if yes, training according to the operation information set of the historical monitoring equipment and the historical surrounding environment related fault information set to obtain a monitoring fault related model;
if not, training according to the information set of the historical monitoring equipment to obtain a monitoring fault model;
and inputting the operation information set of the monitoring equipment and the related fault information set of the surrounding environment state acquired in real time according to the training result to acquire the final processing result of the monitoring equipment faults.
A monitoring equipment fault monitoring device of a monitoring equipment fault monitoring method comprises:
the equipment information acquisition module is used for acquiring the operation parameters of the monitoring equipment and comprises the following components:
the video extraction unit is used for identifying and extracting the ambient humidity information of the monitoring equipment;
the power detection unit is used for monitoring the peripheral power operation condition information of the monitoring equipment;
the network monitoring unit is used for monitoring network operation state information of the monitoring equipment;
the fault analysis module is used for carrying out monitoring equipment state analysis according to the fault monitoring strategy and obtaining a fault early warning signal;
and the fault alarm module is used for acquiring the associated fault information of the monitoring equipment according to the fault early warning signal result and carrying out fault information alarm.
The invention has the beneficial effects that: the state of the monitoring equipment is accurately judged through a fault monitoring strategy, early warning signal analysis is facilitated, the fault early warning signal is analyzed, the influence of the related fault information is judged according to the analysis result, the judgment of the fault related information is beneficial to detecting the service life of the monitoring equipment by the surrounding environment, analyzing, predicting and early warning the fault problem, preventing the fault from happening in advance, and guaranteeing the service life of the monitoring equipment; the associated fault information is analyzed, steps of predicting and judging the associated faults by workers with abundant experience are reduced through the analysis of the associated fault information, and complex operations of on-site inspection and data adjustment are reduced through direct analysis, so that the analysis rate of the associated faults is improved rapidly, and the analysis efficiency is improved remarkably.
Of course, it is not necessary for any one product to practice the invention to achieve all of the advantages set forth above at the same time.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed for the description of the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a fault monitoring method for a monitoring device according to the present invention;
fig. 2 is a block diagram of a fault monitoring device module of a monitoring apparatus according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, a method for monitoring faults of a monitoring device includes:
step one, acquiring surrounding information environment parameters of monitoring equipment and operation parameters of the monitoring equipment, and generating a fault monitoring strategy according to the operation parameters of the monitoring equipment;
monitoring equipment operating parameters includes: high current signal parameterStrong voltage signal parameter->Network operation speed adjustment parameter->;
Analyzing a fault monitoring strategy to judge whether the fault coefficient of the monitoring equipment is abnormal or not:
if yes, judging whether the fault coefficient belongs to a preset threshold range;
if yes, a first fault early warning signal is generated;
if not, generating a second fault early warning signal and powering off;
if not, judging that the monitoring equipment is normal;
step three, acquiring the associated fault information of the monitoring equipment according to the first fault early warning signal result;
and fourthly, performing equipment fault operation through the analysis result of the associated fault information.
Through the technical scheme: because the hardware condition of the front-end detection equipment is usually required to be pre-detected and monitored in the existing monitoring equipment fault monitoring process, the generation probability of equipment faults is reduced, but for the actual condition, the situation of predicting the faults of the hardware equipment in the actual monitoring process is easy to realize, and the influence of the surrounding environment except the equipment, in which the hardware equipment is in the condition, is usually fuzzy; in addition, after the equipment software is in a problem, operators with abundant experience are required to be invited to predict and judge the failure cause, and the process influences the detection efficiency of monitoring the failure of the monitoring equipment and the overhaul speed of the equipment to a certain extent.
In order to solve the technical problems, specifically, firstly, acquiring the surrounding information environment parameters of the monitoring equipment and the operation parameters of the monitoring equipment, generating a fault monitoring strategy according to the operation parameters of the monitoring equipment, and generally, the influence of the surrounding environment on the monitoring equipment in the detection process of the monitoring equipment is easy to ignore except the problems in the specification and the quality of the equipment, and through the past experience, the surrounding environment types which cause the faults of the monitoring equipment are summarized in the detection process of the monitoring equipment, and setting the operation factors affecting the monitoring equipment, wherein the method comprises the following steps: the equipment current, voltage, network operation speed and the like, and the operation parameters of the monitoring equipment are obtained through analysis and data statistics, and specifically comprise: high current signal parameterStrong voltage signal parameter->Network operation speed adjustment parametersThe method comprises the steps of carrying out a first treatment on the surface of the Predicting the fault influence of the monitoring equipment according to the change of the operation parameters of the monitoring equipment; and generating a fault monitoring strategy by analyzing the operation parameters of the monitoring equipment.
Then, analyzing the fault monitoring strategy to judge whether the fault coefficient of the monitoring equipment is abnormal or not: if yes, judging whether the fault coefficient belongs to a preset threshold range; if yes, a first fault early warning signal is generated; if not, generating a second fault early warning signal and powering off; if not, judging that the monitoring equipment is normal; in order to ensure accurate acquisition of fault signals, accurately judging the state of the monitoring equipment by analyzing a fault monitoring strategy, wherein the specific state of the monitoring equipment is obtained according to the size of a fault coefficient acquired by the fault monitoring strategy; then, according to the result of the first fault early warning signal, the related fault information of the monitoring equipment is obtained, the working humidity of the monitoring equipment is further detected by utilizing the first fault early warning signal generated in the fault monitoring strategy in the process of monitoring data, namely, the related fault information is judged according to the analysis result, then the equipment fault operation is carried out by utilizing the analysis result of the related fault information, the judgment of the fault problem of the monitoring equipment can be directly detected or intuitively judged by checking hardware equipment through the data, the influence of the surrounding environment in the operation of the monitoring equipment on the service life of the monitoring equipment and the fault prediction is larger, the fault problem analysis and early warning of the monitoring equipment are facilitated by judging the related fault information, the fault problem is prevented from happening, and the service life of the monitoring equipment is ensured; finally, acquiring the associated fault information of the monitoring equipment according to the first fault early warning signal result, wherein the following is needed: and acquiring the surrounding environment information parameters of the same time period through the equipment information monitoring process after the first fault early-warning signal is generated according to the fault coefficient result by a device fault detection strategy of a period of time, so as to acquire and analyze the associated fault information.
The step of analyzing through the associated fault information reduces the steps of off-line manual fault analysis and detection, and the complex operation of on-site inspection and data adjustment and separation is reduced through direct analysis, so that the associated fault analysis rate is improved rapidly, and the analysis efficiency is improved remarkably.
Preferably, the fault monitoring policy is generated in the following manner:
by the formulaCalculating fault coefficient->Acquiring a fault monitoring strategy according to the fault coefficient;
wherein ,、/>respectively a strong current signal parameter weight coefficient and a strong voltage signal parameter weight coefficient, +.>、、/>And the standard parameters are respectively a strong current signal standard parameter, a strong voltage signal standard parameter and a network operation speed adjustment standard parameter.
Through the technical scheme: the fault monitoring strategy is obtained by specifically analyzing the faults of the surrounding environment of the equipment, so that the faults of the monitoring equipment are predicted, and the faults are specifically predicted by a formulaCalculating fault coefficient->Failure coefficient->The method is used for judging the state of the monitoring equipment so as to judge whether the current surrounding environment information has influence on the fault of the monitoring equipment; and obtaining a fault monitoring strategy according to the fault coefficient, wherein the specific judging process of the fault monitoring strategy is embodied as follows.
wherein ,、/>the weight coefficients are respectively a strong current signal parameter weight coefficient and a strong voltage signal parameter weight coefficient, the weight coefficients are selected according to the influence degree of the strong current signal and the strong voltage signal on the fault of the monitoring equipment,/>、/>、respectively, strong current signal standard parameter, strong voltage signal standard parameter and network operation speed regulation standard parameter,/->、、/>Is set according to the standard data size required by the normal operation of the equipment in the existing monitoring equipment database.
Preferably, the ambient information environmental parameter comprises an operating humidity parameterThe working humidity of the monitoring equipment is detected, so that the peripheral electric leakage condition is conveniently checked, and the electric safety of the hardware equipment is ensured.
Through the technical scheme: the factors that the surrounding information environment parameters are influenced are many, the influence of the surrounding environment of the state power on of the monitoring equipment is considered, particularly the influence of the environment working humidity on the operation of the monitoring equipment is considered, whether the periphery of the monitoring equipment is leaked or not is ensured to be checked by detecting the working humidity, and the power consumption of hardware equipment and the personal safety of management staff are ensured.
As an embodiment of the present invention, specifically, the fault coefficient in the fault monitoring strategyAnd a preset failure coefficient standard threshold value->Is->Performing comparison, 0 </o-></>:
if it is≤/>≤/>Judging that the monitoring equipment is abnormal, generating a fault early warning signal, and further detecting the working humidity of the monitoring equipment;
if it is>/>And judging that the monitoring equipment is abnormal, generating a fault early warning signal, and performing power-off maintenance treatment.
Through the technical scheme: the fault monitoring strategy is judged by the fault coefficientThe comparison is carried out, the state of the monitoring equipment is judged, and particularly, the fault coefficient in the fault monitoring strategy is judged>And a preset failure coefficient standard threshold value->Is->Performing comparison, 0 </o-></>Judging: if->Less than->Judging that the monitoring equipment is normal, and not performing other processing; if->Belonging to the standard threshold->Is->Within (i.e.)>≤/>≤/>Judging that the monitoring equipment is abnormal, generating a fault early warning signal, and further detecting the working humidity condition of the monitoring equipment; if->>/>And judging that the monitoring equipment is abnormal, generating a fault early warning signal, and performing power-off maintenance treatment.
As one embodiment of the present invention, specifically, the step of acquiring the associated failure information includes:
Through the technical scheme: in order to further analyze the relevant faults of the monitoring equipment, firstly, acquiring real-time working humidity parameters through the monitoring equipmentTime-dependent curveLine->The method comprises the steps of carrying out a first treatment on the surface of the The real-time operating humidity parameter here->The air state measuring instrument is obtained by using the existing air state measuring instrument, is not limited to the existing air detector or air humidity detector in the market, and is parameterized according to the influence degree of the existing air humidity change on equipment and instruments; then, the preset working humidity parameter is acquired>Standard curve over time>The method comprises the steps of carrying out a first treatment on the surface of the Preset working humidity parameter->The working humidity change value of a certain degree of faults of the monitoring equipment is counted in the historical database, wherein the measured working humidity value is obtained by parameterizing according to the probability degree of faults of the monitoring equipment, and the change curve of the measured data parameter in a period of time>The method comprises the steps of carrying out a first treatment on the surface of the Finally, will->And->Built in the same coordinate system, calculate +.> and />Is>Anddifference of->The method comprises the steps of carrying out a first treatment on the surface of the Due to difference->The relation between the monitoring device and the working humidity and the influence degree thereof can be judged to a certain extent by the difference value +.>The relation and the relation degree between the working humidity can be obtained by analyzing the size of the water level meter, so that the next step of fault prediction and judgment can be conveniently carried out.
As an embodiment of the present invention, specifically, the difference value is judgedAnd a preset threshold-> and />Alignment is carried out, and 0 </o-></>:
if it is≤/>Judging that the fault is related to the working humidity, but the influence is not great, and continuing to operate;
if it is</>≤/>Judging that the working humidity mainly influences the faults of the monitoring equipment, and carrying out fault early warning and overhauling;
if it is>/>If the working humidity seriously affects the fault of the monitoring equipment, carrying out fault report if +.>≥/>And (3) further judging: if->≤/>Judging that the fault is related to the working humidity, but the influence is not great, and continuing to operate; if-></>≤/>Judging that the working humidity mainly influences the faults of the monitoring equipment, and carrying out fault early warning and overhauling; if->>/>The working humidity seriously affects the faults of the monitoring equipment, and the fault alarm and the power failure are carried out; by +.>The judgment of the working environment is favorable for analyzing and timely early warning the conditions of the surrounding environment of the monitoring equipment, and particularly, the early warning and timely power-off of the working humidity conditions ensure the safety of the monitoring equipment of the working environment and the safety of staff.
Preferably, the device failure operation includes:
acquiring operation information of monitoring equipment and surrounding environment state information;
judging whether the fault type of the monitoring equipment is related to the surrounding environment state information according to the analysis result of the associated fault information:
if yes, training according to the operation information set of the historical monitoring equipment and the historical surrounding environment related fault information set to obtain a monitoring fault related model;
if not, training according to the information set of the historical monitoring equipment to obtain a monitoring fault model;
and inputting the operation information set of the monitoring equipment and the related fault information set of the surrounding environment state acquired in real time according to the training result to acquire the final processing result of the monitoring equipment faults.
Through the technical scheme: the device fault operation is favorable for analyzing according to the actual condition of the monitoring device, and the fault analysis result matched with the monitoring device fault is obtained, and the specific device fault operation comprises the following steps: acquiring operation information of monitoring equipment and surrounding environment state information; then, judging whether the fault type of the monitoring equipment is related to surrounding environment state information or not according to the analysis result of the associated fault information; if yes, training according to the operation information set of the historical monitoring equipment and the historical surrounding environment related fault information set to obtain a monitoring fault related model; and if not, training according to the information set of the historical monitoring equipment to obtain a monitoring fault model.
The monitoring fault correlation model and the monitoring fault model are the results of performing data set processing and surrounding environment correlation data set processing obtained through history and modeling training through a large amount of history empirical data statistics in monitoring faults of monitoring equipment, and are assumed to be trained, which means that the model performs well in a training set and a testing set and does not have fitting and under fitting conditions; the model training can be based on the existing model training method, and is not limited to a deep learning method and the like; inputting a monitoring equipment operation information set and a surrounding environment state association fault information set which are obtained in real time according to the training results to obtain a final processing result of the monitoring equipment faults; the operation information set of the monitoring equipment and the related fault information set of the surrounding environment state are subjected to parameterization, and the parameterization is a parameter result obtained by performing data calculation according to the surrounding environment fault data duty ratio and the importance degree occupied by the fault analysis of the whole monitoring equipment.
Wherein, the surrounding environment fault data refer to five outdoor environment parameters including: the method comprises the steps of obtaining the proportion of equipment fault influence through training analysis according to five environmental parameters, judging the proportion of the obtained humidity parameter (with the largest influence on monitoring equipment faults) to the five environmental parameters, and obtaining the surrounding environment fault data proportion according to the proportion; the importance of failure analysis of the whole monitoring equipment refers to three parameters affecting the operation of the monitoring equipment, namely, parameters of strong current signalsStrong voltage signal parameter->Network operation speed adjustment parameter->The method comprises the steps of carrying out a first treatment on the surface of the And according to the parameter values obtained by the three parameters on the dynamic results of the fault coefficient analysis of the equipment, carrying out data calculation on the parameter result monitoring fault model obtained by carrying out data calculation according to the surrounding environment fault data duty ratio and the importance degree occupied by the fault analysis of the whole monitoring equipment to obtain a monitoring fault correlation model.
Referring to fig. 2, the monitoring device fault monitoring apparatus of the monitoring device fault monitoring method specifically includes:
the equipment information acquisition module is used for acquiring the operation parameters of the monitoring equipment and comprises the following components:
the video extraction unit is used for identifying and extracting the ambient humidity information of the monitoring equipment;
the power detection unit is used for monitoring the peripheral power operation condition information of the monitoring equipment;
the network monitoring unit is used for monitoring network operation state information of the monitoring equipment;
the fault analysis module is used for carrying out monitoring equipment state analysis according to a fault monitoring strategy and obtaining a fault early warning signal;
and the fault alarm module is used for acquiring the associated fault information of the monitoring equipment according to the fault early warning signal result and carrying out fault information alarm.
Through the technical scheme: in this embodiment, by setting a monitoring device fault monitoring device of a monitoring device fault monitoring method, the monitoring device fault monitoring device specifically includes: the system comprises an environment information acquisition module, a fault analysis module and a fault alarm module, wherein the environment information acquisition module is used for acquiring surrounding information environment parameters; the environment information acquisition module specifically comprises a video extraction unit, a video processing unit and a control unit, wherein the video extraction unit is used for identifying and extracting the ambient environment humidity information of the monitoring equipment and extracting the ambient humidity information data; the power detection unit is used for monitoring the peripheral power operation condition information of the monitoring equipment and comprises acquiring current, voltage related data and the like of the equipment; the network monitoring unit is used for monitoring the network operation state information of the monitoring equipment and acquiring the network operation speed; the fault analysis module is used for carrying out monitoring equipment state analysis according to a fault monitoring strategy to obtain a fault early warning signal; the fault alarm module is used for acquiring the associated fault information of the monitoring equipment according to the fault early warning signal result and carrying out fault information alarm.
The foregoing is merely illustrative and explanatory of the principles of the invention, as various modifications and additions may be made to the specific embodiments described, or similar thereto, by those skilled in the art, without departing from the principles of the invention or beyond the scope of the appended claims.
Claims (6)
1. A method of monitoring equipment failure, the method comprising:
step one, acquiring surrounding information environment parameters of monitoring equipment and operation parameters of the monitoring equipment, and generating a fault monitoring strategy according to the operation parameters of the monitoring equipment;
the monitoring device operating parameters include: high current signal parameterStrong voltage signal parameter->Network operation speed adjustment parameter->;
Analyzing a fault monitoring strategy to judge whether the fault coefficient of the monitoring equipment is abnormal or not:
if yes, judging whether the fault coefficient belongs to a preset threshold range;
if yes, a first fault early warning signal is generated;
if not, generating a second fault early warning signal and powering off;
if not, judging that the monitoring equipment is normal;
step three, acquiring the associated fault information of the monitoring equipment according to the first fault early warning signal result;
step four, performing equipment fault operation through the analysis result of the associated fault information;
the fault monitoring strategy is generated in the following way:
by the formulaCalculating fault coefficient->Acquiring a fault monitoring strategy according to the fault coefficient;
wherein ,、/>respectively a strong current signal parameter weight coefficient and a strong voltage signal parameter weight coefficient, +.>、/>、The method comprises the steps of respectively adjusting standard parameters of strong current signals, strong voltage signals and network operation speed;
2. A method of monitoring a fault in a monitoring device according to claim 1, wherein the fault coefficients in the fault monitoring strategy areAnd a preset failure coefficient standard threshold value->Is->Alignment is carried out, and 0 </o-></>:
if it is≤/>≤/>Judging that the monitoring equipment is abnormal, generating a first fault early warning signal, and further detecting the working humidity of the monitoring equipment;
3. The method for monitoring a fault of a monitoring device according to claim 1, wherein the step of obtaining the associated fault information includes:
4. A monitoring device failure monitoring method according to claim 3Characterized in that the difference value is judgedAnd a preset threshold-> and />Alignment is carried out, and 0 </o-></>:
if it is≤/>Judging that the fault is related to the working humidity, but the influence is not great, and continuing to operate;
if it is</>≤/>Judging that the working humidity mainly influences the faults of the monitoring equipment, and carrying out fault early warning and overhauling;
5. A method of monitoring for equipment failure according to claim 1, wherein the equipment failure operation comprises:
acquiring operation information of monitoring equipment and surrounding environment state information;
judging whether the fault type of the monitoring equipment is related to the surrounding environment state information according to the analysis result of the associated fault information:
if yes, training according to the operation information set of the historical monitoring equipment and the historical surrounding environment related fault information set to obtain a monitoring fault related model;
if not, training according to the information set of the historical monitoring equipment to obtain a monitoring fault model;
and inputting the operation information set of the monitoring equipment and the related fault information set of the surrounding environment state acquired in real time according to the training result to acquire the final processing result of the monitoring equipment faults.
6. A monitoring device failure monitoring apparatus based on the monitoring device failure monitoring method according to any one of claims 1 to 5, characterized by comprising:
the equipment information acquisition module is used for acquiring the operation parameters of the monitoring equipment and comprises the following components:
the video extraction unit is used for identifying and extracting the ambient humidity information of the monitoring equipment;
the power detection unit is used for monitoring the peripheral power operation condition information of the monitoring equipment;
the network monitoring unit is used for monitoring network operation state information of the monitoring equipment;
the fault analysis module is used for carrying out monitoring equipment state analysis according to the fault monitoring strategy and obtaining a fault early warning signal;
and the fault alarm module is used for acquiring the associated fault information of the monitoring equipment according to the fault early warning signal result and carrying out fault information alarm.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202310582750.3A CN116320832B (en) | 2023-05-23 | 2023-05-23 | Monitoring equipment fault monitoring method and device |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202310582750.3A CN116320832B (en) | 2023-05-23 | 2023-05-23 | Monitoring equipment fault monitoring method and device |
Publications (2)
Publication Number | Publication Date |
---|---|
CN116320832A true CN116320832A (en) | 2023-06-23 |
CN116320832B CN116320832B (en) | 2023-08-15 |
Family
ID=86815343
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN202310582750.3A Active CN116320832B (en) | 2023-05-23 | 2023-05-23 | Monitoring equipment fault monitoring method and device |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN116320832B (en) |
Cited By (9)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN117291582A (en) * | 2023-11-27 | 2023-12-26 | 合肥宝康自动化系统有限公司 | Industrial production interconnection monitoring system based on data analysis |
CN117332233A (en) * | 2023-10-07 | 2024-01-02 | 江苏丰昌机电科技有限公司 | Intelligent maintenance system for motor |
CN117406048A (en) * | 2023-12-15 | 2024-01-16 | 国网山西省电力公司太原供电公司 | Transformer discharge fault diagnosis method and device |
CN117472629A (en) * | 2023-11-02 | 2024-01-30 | 兰州航空职业技术学院 | Multi-fault diagnosis method and system for electronic information system |
CN117478681A (en) * | 2023-12-26 | 2024-01-30 | 常州指尖互动网络科技有限公司 | Recursive server state monitoring method based on edge calculation |
CN117499621A (en) * | 2024-01-02 | 2024-02-02 | 中移(苏州)软件技术有限公司 | Detection method, device, equipment and medium of video acquisition equipment |
CN117576879A (en) * | 2024-01-17 | 2024-02-20 | 兰陵城投矿业有限公司 | Detection and early warning method and system for mine transportation equipment |
CN117829811A (en) * | 2023-12-29 | 2024-04-05 | 江苏天合清特电气有限公司 | Equipment monitoring method, device and related system |
CN118368793A (en) * | 2024-06-20 | 2024-07-19 | 无锡照明股份有限公司 | Fault alarm method and system based on intelligent street lamp state monitoring |
Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20110181295A1 (en) * | 2010-01-22 | 2011-07-28 | Livewire Test Labs, Inc. | Fault detection using combined reflectometry and electronic parameter measurement |
CN106124949A (en) * | 2016-08-30 | 2016-11-16 | 国网山东省电力公司济南供电公司 | A kind of based on thermal infrared imaging technology to insulator breakdown on-line monitoring method |
CN110430709A (en) * | 2019-07-23 | 2019-11-08 | 合肥康尔信电力系统有限公司 | Diesel-generator set control system |
US20210208648A1 (en) * | 2020-01-08 | 2021-07-08 | Cypress Semiconductor Corporation | Dynamic power throttling based on system conditions in usb type-c power delivery (usb-c/pd) ecosystem |
CN114859177A (en) * | 2022-05-17 | 2022-08-05 | 云南电网有限责任公司临沧供电局 | Fault finding system and method based on split-phase switch |
-
2023
- 2023-05-23 CN CN202310582750.3A patent/CN116320832B/en active Active
Patent Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20110181295A1 (en) * | 2010-01-22 | 2011-07-28 | Livewire Test Labs, Inc. | Fault detection using combined reflectometry and electronic parameter measurement |
CN106124949A (en) * | 2016-08-30 | 2016-11-16 | 国网山东省电力公司济南供电公司 | A kind of based on thermal infrared imaging technology to insulator breakdown on-line monitoring method |
CN110430709A (en) * | 2019-07-23 | 2019-11-08 | 合肥康尔信电力系统有限公司 | Diesel-generator set control system |
US20210208648A1 (en) * | 2020-01-08 | 2021-07-08 | Cypress Semiconductor Corporation | Dynamic power throttling based on system conditions in usb type-c power delivery (usb-c/pd) ecosystem |
CN114859177A (en) * | 2022-05-17 | 2022-08-05 | 云南电网有限责任公司临沧供电局 | Fault finding system and method based on split-phase switch |
Non-Patent Citations (2)
Title |
---|
李建成: "《针对电牵引采煤机的状态监测与 故障识别逻辑的研究》", 《创新与实践》, vol. 25, no. 6 * |
王晟: "基于ZigBee 网络和视频监控的 电力设备故障监测与诊断", 《机械设计与制造工程》, vol. 49, no. 12 * |
Cited By (16)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN117332233A (en) * | 2023-10-07 | 2024-01-02 | 江苏丰昌机电科技有限公司 | Intelligent maintenance system for motor |
CN117332233B (en) * | 2023-10-07 | 2024-05-31 | 江苏丰昌机电科技有限公司 | Intelligent maintenance system for motor |
CN117472629A (en) * | 2023-11-02 | 2024-01-30 | 兰州航空职业技术学院 | Multi-fault diagnosis method and system for electronic information system |
CN117472629B (en) * | 2023-11-02 | 2024-05-28 | 兰州航空职业技术学院 | Multi-fault diagnosis method and system for electronic information system |
CN117291582A (en) * | 2023-11-27 | 2023-12-26 | 合肥宝康自动化系统有限公司 | Industrial production interconnection monitoring system based on data analysis |
CN117291582B (en) * | 2023-11-27 | 2024-03-29 | 合肥宝康自动化系统有限公司 | Industrial production interconnection monitoring system based on data analysis |
CN117406048A (en) * | 2023-12-15 | 2024-01-16 | 国网山西省电力公司太原供电公司 | Transformer discharge fault diagnosis method and device |
CN117406048B (en) * | 2023-12-15 | 2024-02-27 | 国网山西省电力公司太原供电公司 | Transformer discharge fault diagnosis method and device |
CN117478681B (en) * | 2023-12-26 | 2024-03-08 | 常州指尖互动网络科技有限公司 | Recursive server state monitoring method based on edge calculation |
CN117478681A (en) * | 2023-12-26 | 2024-01-30 | 常州指尖互动网络科技有限公司 | Recursive server state monitoring method based on edge calculation |
CN117829811A (en) * | 2023-12-29 | 2024-04-05 | 江苏天合清特电气有限公司 | Equipment monitoring method, device and related system |
CN117499621B (en) * | 2024-01-02 | 2024-04-09 | 中移(苏州)软件技术有限公司 | Detection method, device, equipment and medium of video acquisition equipment |
CN117499621A (en) * | 2024-01-02 | 2024-02-02 | 中移(苏州)软件技术有限公司 | Detection method, device, equipment and medium of video acquisition equipment |
CN117576879A (en) * | 2024-01-17 | 2024-02-20 | 兰陵城投矿业有限公司 | Detection and early warning method and system for mine transportation equipment |
CN117576879B (en) * | 2024-01-17 | 2024-04-16 | 兰陵城投矿业有限公司 | Detection and early warning method and system for mine transportation equipment |
CN118368793A (en) * | 2024-06-20 | 2024-07-19 | 无锡照明股份有限公司 | Fault alarm method and system based on intelligent street lamp state monitoring |
Also Published As
Publication number | Publication date |
---|---|
CN116320832B (en) | 2023-08-15 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN116320832B (en) | Monitoring equipment fault monitoring method and device | |
CN116660669B (en) | Power equipment fault on-line monitoring system and method | |
CN114793019A (en) | Secondary equipment visual supervision system based on big data analysis | |
CN115559890B (en) | Water pump unit operation fault prediction adjustment method and system | |
CN117808456B (en) | Equipment fault early warning method and device based on intelligent operation management | |
CN117406026A (en) | Power distribution network fault detection method suitable for distributed power supply | |
CN106228472A (en) | A kind of substation equipment intelligent patrol detection failure analysis methods | |
CN110688774A (en) | Power grid fault simulation deduction system and method | |
CN118152784B (en) | Modularized substation equipment data feature extraction method | |
CN114255784A (en) | Substation equipment fault diagnosis method based on voiceprint recognition and related device | |
CN113177646A (en) | Power distribution equipment online monitoring method and system based on self-adaptive edge proxy | |
CN117038048B (en) | Remote fault processing method and system for medical instrument | |
CN117937768B (en) | Intelligent electrical cabinet remote monitoring system | |
CN117423225A (en) | Disaster remote sensing early warning system based on high-speed railway operation | |
CN117791876A (en) | Substation equipment operation state monitoring method and abnormal control system | |
CN117791869B (en) | Data online monitoring method and system based on intelligent power distribution cabinet | |
CN118309644A (en) | Pipeline pump operation flow monitoring method and system based on digital twin | |
CN111878323B (en) | Wind generating set fault early warning method based on frequency spectrum autocorrelation function | |
CN117373478A (en) | Voiceprint recognition system for transformer | |
CN111638416A (en) | Fault monitoring device and method for power distribution cabinet of power distribution room | |
CN116566839A (en) | Communication resource quality evaluation system for power enterprises | |
CN114264902A (en) | Method and system for monitoring working state of lightning protection box, electronic equipment and storage medium | |
CN117168865B (en) | Electromechanical device protection system | |
CN117493129B (en) | Operating power monitoring system of computer control equipment | |
CN118197589B (en) | Real-time monitoring optimization method and equipment for medical care equipment |
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 | ||
GR01 | Patent grant | ||
GR01 | Patent grant |