CN115495315A - Fault early warning system of large-scale medical equipment - Google Patents
Fault early warning system of large-scale medical equipment Download PDFInfo
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Abstract
The invention discloses a fault early warning system of large-scale medical equipment, which relates to the technical field of fault early warning and solves the technical problems that the fault type cannot be accurately corresponded and whether the fault can be controllably analyzed in the prior art, the fault of an analysis object is subjected to influence analysis, the fault influence factor of the analysis object is judged, the maintenance efficiency of the fault of the analysis object is improved, meanwhile, the accuracy of the fault early warning of the analysis object is improved, and the influence brought by the fault corresponding equipment is reduced to the maximum extent; analyzing and evaluating according to the real-time fault of the analysis object, and judging the influence of the fault on the analysis object corresponding to the real-time operation process of the analysis object, so that the early warning accuracy of the analysis object is improved, and the working efficiency and the maintenance efficiency of the analysis object are ensured; and carrying out real-time fault early warning on the corresponding analysis object, and carrying out real-time prediction on the running state of the analysis object, so that the fault monitoring strength of the analysis object is improved, and the accuracy of fault prediction is ensured.
Description
Technical Field
The invention relates to the technical field of fault early warning, in particular to a fault early warning system of large-scale medical equipment.
Background
Medical equipment refers to instruments, devices, appliances, materials or other items used alone or in combination in the human body, and also includes required software. The medical equipment is the most basic element of medical treatment, scientific research, teaching, institutions and clinical discipline work, namely professional medical equipment and household medical equipment. With the development of technology, the variety of medical devices is increasing, and the use failure of the medical devices is increasing, so that the medical device failure early warning has also become a part of the operation of the medical devices.
However, in the prior art, during the fault early warning process of the medical equipment, the type of the fault and whether the fault is controllable cannot be accurately analyzed, and meanwhile, the early warning parameters corresponding to the fault cannot be acquired, so that the accuracy of the fault early warning is reduced, and the operating efficiency of the medical equipment is affected.
Disclosure of Invention
The invention aims to solve the problems, and provides a fault early warning system of large-scale medical equipment, which analyzes the influence of the fault of an analysis object, judges the fault influence factors of the analysis object, improves the maintenance efficiency of the fault of the analysis object, is beneficial to improving the accuracy of the fault early warning of the analysis object, and reduces the influence of the fault corresponding to the equipment to the maximum extent; and analyzing and evaluating according to the real-time fault of the analysis object, and judging the influence of the fault on the analysis object corresponding to the real-time operation process of the analysis object, thereby improving the early warning accuracy of the analysis object and ensuring the working efficiency and the maintenance efficiency of the analysis object.
The purpose of the invention can be realized by the following technical scheme:
the utility model provides a fault early warning system of large-scale medical equipment, includes the server, server communication connection:
the equipment risk analysis unit is used for analyzing the operation risk of the medical equipment, judging the operation risk type of the medical equipment, marking the medical equipment as an analysis object, acquiring a historical operation section of the analysis object, acquiring a fault time period of the analysis object according to the operation fault occurrence moment of the analysis object, dividing the fault into a physical risk type, a clinical risk type and a maintenance risk type through fault time period analysis, formulating an optimal solution according to the historical solution process of the fault type, executing a corresponding optimal solution when the corresponding fault type occurs, and optimizing the optimal solution according to real-time execution; then sending the fault type and the corresponding optimal solution in the fault time period of the analysis object to a server;
the fault influence analysis unit is used for carrying out influence analysis on the fault of the analysis object, judging fault influence factors of the analysis object, obtaining the confirmed fixing response parameters of each type of fault through analysis, and sending the parameters to the server after binding the parameters;
the fault analysis and evaluation unit is used for carrying out fault analysis and evaluation on the analysis object, dividing each type of fault into a controllable fault and a non-controllable fault through analysis, acquiring an early warning factor of the controllable fault and a non-early warning factor of the non-controllable fault, and sending the early warning factors to the server;
and the fault real-time early warning unit is used for carrying out real-time fault early warning on the corresponding analysis object, generating a fault early warning signal and a safety signal through analysis, and sending the fault early warning signal and the safety signal to the server.
In a preferred embodiment of the present invention, the operation of the facility risk analysis unit is as follows:
acquiring a fault type of an analysis object, analyzing the fault type of the analysis object, and if the fault of the analysis object is an inherent defect of the equipment per se under the limitation of the prior art or an unpredictable and uncontrollable potential risk exists in the use process of the equipment, marking the corresponding fault type as a physical risk type; if the failure of the analysis object is the deviation of the equipment operation setting parameters or the corresponding operation process error of the equipment operation, marking the corresponding failure type as a clinical risk type; and if the fault of the analysis object is that the setting of the daily maintenance period is not met or the routine maintenance flow is not qualified, marking the corresponding fault type as a maintenance risk type.
As a preferred embodiment of the present invention, the operation of the fault influence analysis unit is as follows:
acquiring operation parameters of an analysis object which floats after a fault occurs in a fault time period of the analysis object, and marking the corresponding floating operation parameters as preset influence parameters;
acquiring the floating frequency of the preset influence parameters in the fault event section of the same type of faults of the analysis object and the probability of the faults of the analysis object when the preset influence parameters float, and comparing the frequency with a floating frequency threshold value and a fault probability threshold value respectively:
if the frequency of floating of the preset influence parameters in the fault event section of the same type of faults of the analysis object exceeds a floating frequency threshold value, or the probability of the faults of the analysis object exceeds a fault probability threshold value when the preset influence parameters float, marking the preset influence parameters of the current type of faults of the analysis object as determined influence parameters, binding the determined influence parameters with corresponding fault types, and sending the bound determined influence parameters and the corresponding fault types to a server together;
if the frequency of the fluctuation of the preset influence parameters in the fault event section of the same type of faults of the analysis object does not exceed the fluctuation frequency threshold value, and the probability of the faults of the analysis object does not exceed the fault probability threshold value when the preset influence parameters fluctuate, the preset influence parameters of the current type of faults of the analysis object are marked as undetermined influence parameters, the undetermined influence parameters and the corresponding fault types are bound, and the bound undetermined influence parameters and the corresponding fault types are sent to a server together.
In a preferred embodiment of the present invention, the operation of the failure analysis and evaluation unit is as follows:
collecting a failure occurrence probability reduction value after determining the influence factor management and control in the operation process of an analysis object, determining the corresponding failure resolution probability of the influence factor management and control after the failure occurs, and comparing the probability reduction value with a probability reduction value threshold value and a failure resolution probability threshold value respectively:
if the failure occurrence probability reduction value exceeds the probability reduction value threshold value after the influence factor management and control is determined in the operation process of the analysis object, or the failure solving probability corresponding to the influence factor management and control is determined to exceed the failure solving probability threshold value after the failure occurs, the corresponding failure of the analysis object is judged to be controllable, the corresponding failure is marked as a controllable failure, and the corresponding determination influence factor of the controllable failure is marked as a pre-warning factor; if the probability reduction value of the fault after the control of the influence factors is determined not to exceed the probability reduction value threshold value in the operation process of the analysis object, and the probability of the corresponding fault solution of the control of the influence factors is determined not to exceed the probability threshold value of the fault solution after the fault occurs, the corresponding fault of the analysis object is judged to be uncontrollable, the corresponding fault is marked as an uncontrollable fault, and the corresponding determined influence factor of the uncontrollable fault is marked as an uncontrollable early warning factor.
As a preferred embodiment of the present invention, the operation process of the real-time fault warning unit is as follows:
acquiring the floating frequency of the analysis object corresponding to the early warning factor and the floating span of the corresponding early warning factor, and comparing the floating frequency of the analysis object corresponding to the early warning factor and the floating span of the corresponding early warning factor with a floating frequency threshold value and a floating span threshold value respectively:
if the floating frequency of the analysis object corresponding to the early warning factor exceeds the floating frequency threshold value or the floating span of the analysis object corresponding to the early warning factor exceeds the floating span threshold value, judging that the fault prediction of the analysis object is fault high-risk generation, generating a fault early warning signal and sending the fault early warning signal and the fault type corresponding to the early warning factor to a server;
and if the floating frequency of the analysis object corresponding to the early warning factor does not exceed the floating frequency threshold value and the floating span corresponding to the early warning factor does not exceed the floating span threshold value, judging that the fault prediction of the analysis object is fault low-risk generation, generating a safety signal and sending the safety signal to the server.
Compared with the prior art, the invention has the beneficial effects that:
1. according to the invention, the operation risk of the medical equipment is analyzed, and the operation risk type of the medical equipment is judged, so that the efficiency of medical equipment supervision is improved, the early warning accuracy of the medical equipment is increased, meanwhile, the fault type of the medical equipment is accurately obtained, the fault maintenance efficiency of the medical equipment is improved, and the occurrence probability of abnormal maintenance direction is reduced; the method has the advantages that the fault of the analysis object is subjected to influence analysis, the fault influence factor of the analysis object is judged, the maintenance efficiency of the fault of the analysis object is improved, meanwhile, the accuracy of fault early warning of the analysis object is improved, and the influence of the fault corresponding equipment is reduced to the maximum extent;
2. according to the method, analysis and evaluation are carried out according to the real-time faults of the analysis object, and the influence of the faults on the analysis object corresponding to the real-time operation process of the analysis object is judged, so that the early warning accuracy of the analysis object is improved, and the working efficiency and the maintenance efficiency of the analysis object are ensured; the method has the advantages that real-time fault early warning is carried out on the corresponding analysis object, the running state of the analysis object is predicted in real time, the fault monitoring strength of the analysis object is improved, the accuracy of fault prediction is guaranteed, the working efficiency of the analysis object is improved, and the influence caused by the fault of the analysis object is reduced.
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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 a fault early warning system of a large medical device 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, a fault early warning system of a large-scale medical device includes a server, the server is in communication connection with a device risk analysis unit, a fault influence analysis unit, a fault analysis and evaluation unit and a fault real-time early warning unit, wherein the server is in bidirectional communication connection with the device risk analysis unit, the fault influence analysis unit, the fault analysis and evaluation unit and the fault real-time early warning unit;
the server generates an equipment risk analysis signal and sends the equipment risk analysis signal to the equipment risk analysis unit, the equipment risk analysis unit analyzes the operation risk of the medical equipment after receiving the equipment risk analysis signal, and judges the operation risk type of the medical equipment, so that the efficiency of monitoring the medical equipment is improved, the accuracy of early warning of the medical equipment is increased, meanwhile, the fault type of the medical equipment is accurately obtained, the fault maintenance efficiency of the medical equipment is improved, and the occurrence probability of abnormal maintenance direction is reduced;
marking the medical equipment as an analysis object, setting a mark i as a natural number larger than 1, collecting a historical operation segment of the analysis object, and acquiring a fault time period of the analysis object according to the occurrence moment of an operation fault of the analysis object;
acquiring a fault type of an analysis object, analyzing the fault type of the analysis object, and if the fault of the analysis object is an inherent defect of the equipment itself under the limitation of the prior art or an unpredictable and uncontrollable potential risk exists in the use process of the equipment, marking the corresponding fault type as a physical risk type, such as: the insulativity of equipment is reduced, the power distribution operation of a power grid is unstable or the external temperature and humidity are high;
if the fault of the analysis object is the deviation of the equipment operation setting parameter or the corresponding operation flow error of the equipment operation, marking the corresponding fault type as a clinical risk type, such as the deviation of the equipment parameter setting corresponding to the medical staff and the execution sequence error of the operation flow;
if the failure of the analysis object is that the setting of the daily maintenance period is not met or the execution of the daily maintenance process is not qualified, marking the corresponding failure type as a maintenance risk type, such as the maintenance period of the medical equipment floats or the execution efficiency in the maintenance process is not qualified;
an optimal solution is formulated according to the historical solution process of the fault type, the corresponding optimal solution is executed when the corresponding fault type occurs, and the optimal solution is optimized according to real-time execution; then, the fault type and the corresponding optimal solution in the fault time period of the analysis object are sent to a server; the server receives the fault type and the corresponding optimal solution and monitors the medical equipment in real time;
the server generates a fault influence analysis signal and sends the fault influence analysis signal to the fault influence analysis unit, and after the fault influence analysis unit receives the fault influence analysis signal, the fault influence analysis unit analyzes the influence of the fault of the analysis object, judges fault influence factors of the analysis object, improves the maintenance efficiency of the fault of the analysis object, is beneficial to improving the accuracy of fault early warning of the analysis object, and reduces the influence of the fault corresponding to the equipment to the maximum extent;
acquiring operation parameters of the analysis object which float after a fault occurs in a fault time period of the analysis object, marking the corresponding floating operation parameters as preset influence parameters, and expressing the operation parameters as relevant operation parameters of medical equipment such as operation duration, equipment voltage and current values and the like;
acquiring the floating frequency of the preset influence parameters in the fault event section of the same type of faults of the analysis object and the probability of the faults of the analysis object when the preset influence parameters float, and comparing the floating frequency of the preset influence parameters in the fault event section of the same type of faults of the analysis object and the probability of the faults of the analysis object when the preset influence parameters float with a floating frequency threshold value and a fault probability threshold value respectively:
if the frequency of floating of the preset influence parameters in the fault event section of the same type of fault of the analysis object exceeds a floating frequency threshold value, or the probability of the fault of the analysis object exceeds a fault probability threshold value when the preset influence parameters float, marking the preset influence parameters of the current type of fault of the analysis object as determined influence parameters, binding the determined influence parameters with corresponding fault types, and sending the bound determined influence parameters and the corresponding fault types to a server;
if the frequency of floating of the preset influence parameters in the fault event section of the same type of faults of the analysis object does not exceed the floating frequency threshold value and the probability of the faults of the analysis object does not exceed the fault probability threshold value when the preset influence parameters float, marking the preset influence parameters of the current type of faults of the analysis object as undetermined influence parameters, binding the undetermined influence parameters with corresponding fault types, and sending the bound undetermined influence parameters and the corresponding fault types to a server together;
the server generates a fault analysis evaluation signal and sends the fault analysis evaluation signal to the fault analysis evaluation unit, and the fault analysis evaluation unit carries out fault analysis evaluation on an analysis object after receiving the fault analysis evaluation signal, carries out analysis evaluation according to the real-time fault of the analysis object and judges the influence of the fault on the analysis object corresponding to the real-time operation process of the analysis object, so that the early warning accuracy of the analysis object is improved, and the working efficiency and the maintenance efficiency of the analysis object are ensured;
collecting a failure occurrence probability reduction value after determining the influence factor management and control in the operation process of the analysis object, determining a failure resolution probability corresponding to the influence factor management and control after the failure occurs, and comparing the failure occurrence probability reduction value after determining the influence factor management and control in the operation process of the analysis object and determining the failure resolution probability corresponding to the influence factor management and control after the failure occurs with a probability reduction value threshold and a failure resolution probability threshold respectively:
if the failure occurrence probability reduction value exceeds the probability reduction value threshold value after the influence factor management and control is determined in the operation process of the analysis object, or the failure solving probability corresponding to the influence factor management and control is determined to exceed the failure solving probability threshold value after the failure occurs, the corresponding failure of the analysis object is judged to be controllable, the corresponding failure is marked as a controllable failure, and the corresponding determination influence factor of the controllable failure is marked as a pre-warning factor; if the probability reduction value of the fault after the control of the influence factors is determined not to exceed the probability reduction value threshold value in the operation process of the analysis object, and the probability of the corresponding fault solution of the control of the influence factors is determined not to exceed the probability threshold value of the fault solution after the fault occurs, the corresponding fault of the analysis object is judged to be uncontrollable, the corresponding fault is marked as an uncontrollable fault, and the corresponding determined influence factor of the uncontrollable fault is marked as an uncontrollable early warning factor;
the server generates a fault real-time early warning signal and sends the fault real-time early warning signal to the fault real-time early warning unit, and the fault real-time early warning unit carries out real-time fault early warning on a corresponding analysis object after receiving the fault real-time early warning signal, carries out real-time prediction on the running state of the analysis object, improves the fault monitoring strength of the analysis object, ensures the accuracy of fault prediction, is beneficial to improving the working efficiency of the analysis object and reducing the influence caused by the fault of the analysis object;
acquiring the floating frequency of the early warning factor corresponding to the analysis object and the floating span of the early warning factor corresponding to the analysis object, and comparing the floating frequency of the early warning factor corresponding to the analysis object and the floating span of the early warning factor corresponding to the analysis object with a floating frequency threshold and a floating span threshold respectively:
if the floating frequency of the early-warning factors corresponding to the analysis object exceeds the floating frequency threshold value or the floating span of the early-warning factors exceeds the floating span threshold value, judging that the fault prediction of the analysis object is fault high-risk generation, generating fault early-warning signals and sending the fault early-warning signals and fault types corresponding to the early-warning factors to a server, and after receiving the fault early-warning signals and the fault types corresponding to the early-warning factors, the server controls the corresponding early-warning factors and manages and controls the related influence parameters of the corresponding types of faults;
and if the floating frequency of the analysis object corresponding to the early warning factor does not exceed the floating frequency threshold value and the floating span corresponding to the early warning factor does not exceed the floating span threshold value, judging that the fault prediction of the analysis object is fault low-risk generation, generating a safety signal and sending the safety signal to the server.
When the medical equipment failure analysis system is used, the operation risk of the medical equipment is analyzed through the equipment risk analysis unit, the operation risk type of the medical equipment is judged, the medical equipment is marked as an analysis object, a historical operation section of the analysis object is acquired, the failure time period of the analysis object is acquired according to the operation failure occurrence moment of the analysis object, the failure is divided into a physical risk type, a clinical risk type and a maintenance risk type through the failure time period analysis, an optimal solution is formulated according to the historical solution process of the failure type, a corresponding optimal solution is executed when the corresponding failure type occurs, and the optimal solution is optimized according to the real-time execution; then sending the fault type and the corresponding optimal solution in the fault time period of the analysis object to a server; the method comprises the steps that a fault influence analysis unit is used for carrying out influence analysis on faults of an analysis object, judging fault influence factors of the analysis object, obtaining the confirmed response parameters of various types of faults through analysis, binding the parameters and sending the parameters to a server; fault analysis and evaluation are carried out on an analysis object through a fault analysis and evaluation unit, each type of fault is divided into a controllable fault and a non-controllable fault through analysis, and an early warning factor of the controllable fault and a non-early warning factor of the non-controllable fault are obtained and sent to a server; and carrying out real-time fault early warning on the corresponding analysis object through the fault real-time early warning unit, generating a fault early warning signal and a safety signal through analysis, and sending the fault early warning signal and the safety signal to the server.
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. The utility model provides a fault early warning system of large-scale medical equipment which characterized in that, includes the server, server communication connection:
the equipment risk analysis unit is used for analyzing the operation risk of the medical equipment, judging the operation risk type of the medical equipment, marking the medical equipment as an analysis object, acquiring a historical operation section of the analysis object, acquiring a fault time period of the analysis object according to the operation fault occurrence moment of the analysis object, dividing the fault into a physical risk type, a clinical risk type and a maintenance risk type through fault time period analysis, formulating an optimal solution according to the historical solution process of the fault type, executing a corresponding optimal solution when the corresponding fault type occurs, and optimizing the optimal solution according to real-time execution; then sending the fault type and the corresponding optimal solution in the fault time period of the analysis object to a server;
the fault influence analysis unit is used for carrying out influence analysis on the fault of the analysis object, judging the fault influence factors of the analysis object, obtaining the confirmed fixing response parameters of each type of fault through analysis, binding the parameters and sending the parameters to the server;
the fault analysis and evaluation unit is used for carrying out fault analysis and evaluation on the analysis object, dividing each type of fault into a controllable fault and a non-controllable fault through analysis, acquiring an early warning factor of the controllable fault and a non-early warning factor of the non-controllable fault, and sending the early warning factors to the server;
and the fault real-time early warning unit is used for carrying out real-time fault early warning on the corresponding analysis object, generating a fault early warning signal and a safety signal through analysis, and sending the fault early warning signal and the safety signal to the server.
2. The system of claim 1, wherein the equipment risk analysis unit operates as follows:
acquiring a fault type of an analysis object, analyzing the fault type of the analysis object, and if the fault of the analysis object is an inherent defect of the equipment under the limitation of the prior art or an unpredictable and uncontrollable potential risk of the equipment in the use process, marking the corresponding fault type as a physical risk type; if the failure of the analysis object is the deviation of the equipment operation setting parameters or the corresponding operation process error of the equipment operation, marking the corresponding failure type as a clinical risk type; and if the fault of the analysis object is that the setting of the daily maintenance period is not met or the routine maintenance flow is not qualified, marking the corresponding fault type as a maintenance risk type.
3. The system of claim 1, wherein the operation of the failure analysis unit is as follows:
acquiring operation parameters of an analysis object which floats after a fault occurs in a fault time period of the analysis object, and marking the corresponding floating operation parameters as preset influence parameters;
acquiring the floating frequency of preset influence parameters in a fault event section of the same type of faults of an analysis object and the probability of the faults of the analysis object when the preset influence parameters float, and comparing the frequency with a floating frequency threshold and a fault probability threshold respectively:
if the frequency of floating of the preset influence parameters in the fault event section of the same type of faults of the analysis object exceeds a floating frequency threshold value, or the probability of the faults of the analysis object exceeds a fault probability threshold value when the preset influence parameters float, marking the preset influence parameters of the current type of faults of the analysis object as determined influence parameters, binding the determined influence parameters with corresponding fault types, and sending the bound determined influence parameters and the corresponding fault types to a server together;
if the frequency of the fluctuation of the preset influence parameters in the fault event section of the same type of faults of the analysis object does not exceed the fluctuation frequency threshold value, and the probability of the faults of the analysis object does not exceed the fault probability threshold value when the preset influence parameters fluctuate, the preset influence parameters of the current type of faults of the analysis object are marked as undetermined influence parameters, the undetermined influence parameters and the corresponding fault types are bound, and the bound undetermined influence parameters and the corresponding fault types are sent to a server together.
4. The system of claim 1, wherein the failure analysis and evaluation unit operates as follows:
collecting a failure occurrence probability reduction value after determining the influence factor management and control in the operation process of an analysis object, determining the corresponding failure resolution probability of the influence factor management and control after the failure occurs, and comparing the probability reduction value with a probability reduction value threshold value and a failure resolution probability threshold value respectively:
if the probability reduction value of the fault occurrence exceeds the probability reduction value threshold value after the influence factor management and control is determined in the operation process of the analysis object, or the probability of the fault resolution corresponding to the influence factor management and control is determined to exceed the probability threshold value of the fault resolution after the fault occurs, the corresponding fault of the analysis object is judged to be controllable, the corresponding fault is marked as a controllable fault, and the corresponding determination influence factor of the controllable fault is marked as a pre-warning factor; if the probability reduction value of the fault after the control of the influence factors is determined not to exceed the probability reduction value threshold value in the operation process of the analysis object, and the probability of the corresponding fault solution of the control of the influence factors is determined not to exceed the probability threshold value of the fault solution after the fault occurs, the corresponding fault of the analysis object is judged to be uncontrollable, the corresponding fault is marked as an uncontrollable fault, and the corresponding determined influence factor of the uncontrollable fault is marked as an uncontrollable early warning factor.
5. The system of claim 1, wherein the real-time fault pre-warning unit operates as follows:
acquiring the floating frequency of the analysis object corresponding to the early warning factor and the floating span of the corresponding early warning factor, and comparing the floating frequency of the analysis object corresponding to the early warning factor and the floating span of the corresponding early warning factor with a floating frequency threshold value and a floating span threshold value respectively:
if the floating frequency of the analysis object corresponding to the early warning factor exceeds the floating frequency threshold value or the floating span of the analysis object corresponding to the early warning factor exceeds the floating span threshold value, judging that the fault prediction of the analysis object is fault high-risk generation, generating a fault early warning signal and sending the fault early warning signal and the fault type corresponding to the early warning factor to a server;
and if the floating frequency of the analysis object corresponding to the early warning factor does not exceed the floating frequency threshold value and the floating span corresponding to the early warning factor does not exceed the floating span threshold value, judging that the fault prediction of the analysis object is fault low-risk generation, generating a safety signal and sending the safety signal to the server.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN116449809A (en) * | 2023-06-16 | 2023-07-18 | 成都瀚辰光翼生物工程有限公司 | Fault processing method and device, electronic equipment and storage medium |
| CN117670315A (en) * | 2024-01-31 | 2024-03-08 | 天科新能源有限责任公司 | Semi-solid battery recycling management system based on big data |
| CN117854698A (en) * | 2024-03-05 | 2024-04-09 | 四川大象医疗科技有限公司 | Online early warning method and device for nuclear magnetic equipment, electronic equipment and storage medium |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN116449809A (en) * | 2023-06-16 | 2023-07-18 | 成都瀚辰光翼生物工程有限公司 | Fault processing method and device, electronic equipment and storage medium |
| CN116449809B (en) * | 2023-06-16 | 2023-09-05 | 成都瀚辰光翼生物工程有限公司 | Fault processing method and device, electronic equipment and storage medium |
| CN117670315A (en) * | 2024-01-31 | 2024-03-08 | 天科新能源有限责任公司 | Semi-solid battery recycling management system based on big data |
| CN117670315B (en) * | 2024-01-31 | 2024-04-26 | 天科新能源有限责任公司 | Semi-solid battery recycling management system based on big data |
| CN117854698A (en) * | 2024-03-05 | 2024-04-09 | 四川大象医疗科技有限公司 | Online early warning method and device for nuclear magnetic equipment, electronic equipment and storage medium |
| CN117854698B (en) * | 2024-03-05 | 2024-05-10 | 四川大象医疗科技有限公司 | Online early warning method and device for nuclear magnetic equipment, electronic equipment and storage medium |
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