CN116736027A - Equipment fault early warning system for medical self-service terminal - Google Patents
Equipment fault early warning system for medical self-service terminal Download PDFInfo
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Abstract
The invention discloses an equipment fault early warning system for a medical self-service terminal, which is used for solving the problems that the existing equipment fault early warning system cannot accurately classify the severity of the faults, potential faults cannot be warned, and the equipment damage is easy to influence the working efficiency of a hospital.
Description
Technical Field
The invention relates to the technical field of equipment fault early warning of medical self-service terminals, in particular to an equipment fault early warning system for a medical self-service terminal.
Background
The medical self-service terminal equipment is generally composed of a human-computer interface, is self-service equipment of a hospital, is operated by a user according to equipment prompts, and is intelligent equipment designed for a waiting team length of a large hospital with long queuing and registering time.
The system can conveniently provide various services for patients, meets the information inquiry requirements of the patients on self-help registration, self-help reservation, self-help recharging, self-help payment and the like of hospitals, but frequently encounters some common faults in the use process, such as system faults, network anomalies, circuit faults and the like, the hospitals often arrange detection personnel to periodically inspect or carry out fault reporting treatment through the faults of the patients in use, the mode can not realize timely early warning notification, the medical self-help terminal equipment can be always in a fault waiting state, inconvenience is caused to the patients, and meanwhile, maintenance personnel generally carry out one-by-one investigation according to an overhaul manual to determine the fault condition when the equipment breaks down, so that the detection mode is single and one-sided, and the consumed time is longer, so that the quality and efficiency of medical work are seriously influenced;
in order to solve the above-mentioned defect, a technical scheme is provided.
Disclosure of Invention
The invention aims to solve the problems that in the existing method for early warning the equipment faults of the medical self-service terminal, the severity of the faults in the running state of the equipment of the medical self-service terminal cannot be classified, and the potential faults in the running state of the equipment cannot be timely early-warning notification, so that the equipment damage affects the working quality and efficiency of a hospital, and provides the equipment fault early-warning system for the medical self-service terminal.
The aim of the invention can be achieved by the following technical scheme:
the invention relates to a device fault early warning system for a medical self-service terminal, which comprises a server, wherein the server is in communication connection with a data acquisition unit, a device system running state early warning unit, a network running state early warning unit, an electric power running state early warning unit, a fault analysis feedback unit, an automatic obstacle removing unit, an interference obstacle removing unit and a display platform;
the data acquisition unit is used for acquiring equipment system operation state information, network operation state information and power operation state information of the medical self-service terminal equipment and respectively transmitting the equipment system operation state information, the network operation state information and the power operation state information to the equipment system operation state early warning unit, the network operation state early warning unit and the power operation state early warning unit through the server;
the equipment system running state early warning unit is used for receiving the equipment system running state information, analyzing and processing the equipment system running state, obtaining a severe fault signal, a moderate fault signal and a mild fault signal according to the equipment system running state information, and sending the severe fault signal, the moderate fault signal and the mild fault signal to the fault analysis feedback unit;
the network operation state early warning unit is used for receiving the network operation state information, analyzing and processing the network operation state, obtaining a network fault risk signal and a network potential fault risk signal according to the network operation state information, and sending the network fault risk signal and the network potential fault risk signal to the fault analysis feedback unit;
the power running state early warning unit is used for receiving the power running state information, analyzing and processing the power running state, obtaining a power running abnormal signal according to the power running state information, and sending the power running abnormal signal to the fault analysis feedback unit;
the fault analysis feedback unit is used for triggering corresponding fault early warning instructions according to the received equipment system fault type judging signals, network fault type judging signals and power operation abnormal signals respectively and sending the fault early warning instructions to the automatic fault clearing unit or the interference fault clearing unit;
and the automatic obstacle removing unit or the intervention obstacle removing unit performs corresponding automatic operation processing or personnel intervention operation processing according to the received corresponding fault early warning instruction, and displays and notifies the result on a display platform.
Further, the specific operation process of the equipment system running state analysis processing is as follows:
monitoring hardware fault information of each time point in equipment system running state information in a period of time, wherein the hardware fault information comprises a heat value, a wear degree and a use load value, and respectively calibrating the heat value, the wear degree and the use load value into wa, ma and qa according to a formula:obtaining a hardware damage degree coefficient, wherein i represents each time monitoring point in a period of time, i=1, 2,3 … … n, n is a positive integer greater than zero, and ++>、/>And->Weight coefficients expressed as a heat value, a wear degree and a usage load value, respectively, and +.>＞/>＞/>；
Taking time as an abscissa and a hardware damage degree coefficient as an ordinate, establishing a two-dimensional dynamic coordinate system of the hardware damage degree according to the time and drawing the calculated hardware damage degree coefficient on the two-dimensional dynamic coordinate system of the hardware damage degree in a period of time in a dot curve construction mode, thereby obtaining a waveform curve of the hardware damage degree coefficient;
all inflection points of the waveform curve of the hardware damage degree coefficient are obtained and recorded as i, i=1, 2,3 … … n1, n1 are contained in n, and all the inflection points of the waveform curve of the hardware damage degree coefficient are countedThe number of points, according to the formula:obtaining the number of times of hardware faults;
monitoring software fault information of each time point in the running state information of the equipment system in a period of time, wherein the software fault information comprises system breakdown times and software flashing back times, and respectively calibrating the system breakdown times and the software flashing back times into ty and ry according to a formula:obtaining a software damage degree coefficient->And->Weight coefficients expressed as the number of system crashes and the number of software flashing backs, respectively, and +.>＜/>；
Setting a software damage degree threshold, comparing and analyzing a software damage degree coefficient with the software damage degree threshold, judging a software running state as a fault state when the software damage degree coefficient is larger than or equal to the software damage degree threshold, counting the times of occurrence of the fault state, and carrying out summation calculation according to a formula:obtaining the software failure times, wherein +_>Indicating the point in time when the software operation has failed over a period of time,/->=1, 2,3 … … n2, and n2 is included in n;
device for acquiring medical self-service terminalThe hardware failure times and the software failure times in the system running state information are respectively calibrated into HP and KP according to the formula:obtaining a device system operation fault value HK, wherein +.>And->Weight coefficients expressed as number of hardware failures and number of software failures, respectively, and +.>＞/>；
Three fault gradient comparison intervals of the equipment system operation fault value are set, namely a first gradient fault interval zvq1, a second gradient fault interval zvq and a third gradient fault interval zvq3, and zvq 1=zvq2=2/>zvq3, where zvq1 > zvq2 > zvq3, +.>Representing a multiple of the gradient;
when the equipment system operation fault value is in a preset first gradient fault interval zvq1, a severe fault signal is generated, when the equipment system operation fault value is in a preset second gradient fault interval zvq2, a moderate fault signal is generated, and when the equipment system operation fault value is in a preset third gradient fault interval zvq, a slight fault signal is generated.
Further, the specific operation process of the network operation state analysis processing is as follows:
monitoring network transmissions in network operational status information over a period of timeThe speed value, the network attack frequency and the static induction degree value are calibrated as wcs, bgs and jys according to the formula:obtaining a network operation risk value WM, wherein u1, u2 and u3 are respectively represented as weight coefficients of a network transmission rate value, attack times and an electrostatic induction degree value, and u1 is more than u2 and more than u3;
setting a network operation risk threshold, comparing and analyzing the network operation risk value with the network operation risk threshold, generating a network risk fault signal when the network operation risk value is larger than the network operation risk threshold, and generating a network potential risk fault signal when the network operation risk value is equal to or smaller than the network operation risk threshold.
Further, the specific operation procedure of the power running state analysis processing is as follows:
monitoring the power supply value, the temperature value and the humidity value in the power running state information within a period of time, and calibrating the power supply value, the temperature value and the humidity value as light i 、wcv i And scu i According to the formula:obtaining an electric power running value DZ, wherein ght i 、wcv i And scu i The influence factors respectively representing the power supply value, the temperature value and the humidity value, and e3 > e2 > e1, ght * 、wcv * And scu * Respectively representing an initial power supply value, an initial temperature value and an initial humidity value;
and setting the power operation threshold value as DZQ, comparing and analyzing the power operation value with the power operation threshold value, and generating a power operation abnormal signal when the power operation value is greater than or equal to the power operation threshold value.
Further, the specific operation process of the medical self-service terminal device for analysis and judgment of the operation abnormality is as follows:
when a severe fault signal or a moderate fault signal is captured, triggering an R1 fault early warning instruction and sending the R1 fault early warning instruction to an intervention obstacle removing unit;
when the light fault signal is captured, triggering a V1 fault early warning instruction and sending the V1 fault early warning instruction to an automatic obstacle removing unit;
when a network fault risk signal is captured, triggering an R2 fault early warning instruction, and sending the R2 fault early warning instruction to an interference obstacle removing unit;
when a potential fault risk signal of the network is captured, triggering a V2 fault early warning instruction and sending the V2 fault early warning instruction to an automatic obstacle removing unit;
according to the triggered power operation abnormal signal, firstly, calling a power supply value in the power operation state information, substituting the power supply value into an abnormal power supply comparison interval for comparison and analysis, triggering a power supply fault early warning instruction when the power supply value is in a preset abnormal power supply comparison interval, and sending the power supply fault early warning instruction to an intervention obstacle removing unit;
when the power supply value is not in a preset abnormal power supply comparison interval, the temperature in the power running state information is called, the temperature is compared and analyzed with a temperature threshold value, and when the temperature is greater than or less than the preset temperature threshold value, a temperature fault early warning instruction is triggered and sent to an automatic obstacle avoidance unit;
and when the temperature is equal to a preset temperature threshold value, the humidity in the power running state information is called, the humidity is compared and analyzed with the humidity threshold value, and when the humidity is greater than the preset humidity threshold value, a humidity fault early warning instruction is triggered and sent to the automatic obstacle removing unit.
Further, the specific operation steps of the corresponding automatic operation process are as follows:
according to the received V1 fault early warning instruction, performing automatic restarting operation on the equipment in the set time period B, and performing display notification on a display platform;
according to the received V2 fault early warning instruction, the operation system is updated and automatically encrypted in a set D time period, and display notification is carried out on a display platform;
counting down the circuit cut-off in a set F time period according to the received temperature fault early warning instruction, performing temperature regulation and control operation, and displaying and notifying on a display platform;
and counting down the circuit cut-off in a set F time period according to the received humidity fault early warning instruction, performing humidity regulation operation, and displaying and informing on a display platform.
Further, the corresponding personnel intervention operation treatment comprises the following specific operation steps:
according to the received R1 fault early warning instruction, a maintainer is assigned to go to maintenance or replacement operation in a set time period A, and display notification is carried out on a display platform;
according to the received R2 fault early warning instruction, invoking a network operation risk value in the current time period, carrying out matching analysis on the network operation risk value and a network operation state early warning level table stored in a cloud database, thereby obtaining early warning network fault risk level data, wherein each obtained network operation risk value corresponds to one early warning network fault risk level data, carrying out corresponding maintenance operation in a set C time period according to the obtained network fault risk level data to be early warned, and carrying out display notification on a display platform;
and immediately and automatically cutting off the power supply according to the received power failure early warning instruction, assigning maintenance personnel to go to maintenance in a set E time period, and displaying a notice on a display platform.
Compared with the prior art, the invention has the beneficial effects that:
according to the invention, by means of calculating, processing, comparing and duty ratio analyzing and other methods on the relevant parameters of the equipment system operation state information, the network operation state information and the electric power operation state information of the medical self-service terminal equipment, the equipment system operation fault value, the network operation risk value and the electric power operation value are analyzed, and the judgment and analysis on the operation state of the medical self-service terminal equipment are realized by utilizing the threshold comparison and the gradient interval comparison methods, so that a powerful data foundation is laid for comprehensively and timely early warning when the medical self-service terminal equipment fails;
the received abnormal signals are comprehensively analyzed, corresponding fault early warning instructions are triggered and respectively sent to the automatic obstacle removing unit and the intervention obstacle removing unit, and corresponding early warning operation measures are formulated on the basis of the fault early warning instructions, so that comprehensive and timely early warning notification is realized when the medical self-service terminal equipment fails.
Drawings
For the convenience of those skilled in the art, the present invention will be further described with reference to the accompanying drawings;
fig. 1 is a general block diagram of the system of the present invention.
Detailed Description
The technical solutions of the present invention will be clearly and completely described in connection with the embodiments, and it is obvious that the described embodiments 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.
As shown in fig. 1, the equipment fault early warning system for the medical self-service terminal comprises a server, wherein the server is in communication connection with a data acquisition unit, an equipment system running state early warning unit, a network running state early warning unit, an electric power running state early warning unit, a fault analysis feedback unit, an automatic obstacle removing unit, an interference obstacle removing unit and a display platform;
the data acquisition unit is used for acquiring equipment system operation state information, network operation state information and power operation state information of the medical self-service terminal equipment and respectively transmitting the equipment system operation state information, the network operation state information and the power operation state information to the equipment system operation state early warning unit, the network operation state early warning unit and the power operation state early warning unit through the server;
when the equipment system running state early warning unit receives the equipment system running state information, analyzing and processing the equipment system running state, and the specific operation process is as follows:
monitoring hardware fault information of each time point in equipment system running state information in a period of time, wherein the hardware fault information comprises a heat value, a wear degree and a use load value, and respectively calibrating the heat value, the wear degree and the use load value into wa, ma and qa according to a formula:obtaining a hardware damage degree coefficient, wherein i represents each time monitoring point in a period of time, i=1, 2,3 … … n, n is a positive integer greater than zero, and ++>、/>And->Weight coefficients expressed as a heat value, a wear degree and a usage load value, respectively, and +.>＞/>＞/>The weight coefficient is used for balancing the duty ratio weight of each item of data in formula calculation, so that the accuracy of a calculation result is promoted;
it should be noted that, the heat value refers to the temperature generated by the hardware failure caused by the operation of the equipment system, the wear degree refers to the ratio of the working time of the equipment system to the rated working time in unit time, and the load value refers to the ratio of the number of detected current anomalies of the equipment system to the total number of detected current anomalies in unit time;
taking time as an abscissa and a hardware damage degree coefficient as an ordinate, establishing a two-dimensional dynamic coordinate system of the hardware damage degree according to the time and drawing the calculated hardware damage degree coefficient on the two-dimensional dynamic coordinate system of the hardware damage degree in a period of time in a dot curve construction mode, thereby obtaining a waveform curve of the hardware damage degree coefficient;
all inflection points of the waveform curve of the hardware damage degree coefficient are obtained and recorded as i, i=1, 2,3 … … n1, n1 are contained in n, and the occurrence of the waveform curve of the hardware damage degree coefficient is countedThe number of inflection points is calculated according to the formula:obtaining the number of times of hardware faults;
monitoring software fault information of each time point in the running state information of the equipment system in a period of time, wherein the software fault information comprises system breakdown times and software flashing back times, and respectively calibrating the system breakdown times and the software flashing back times into ty and ry according to a formula:obtaining a software damage degree coefficient->And->Weight coefficients expressed as the number of system crashes and the number of software flashing backs, respectively, and +.>＜/>The weight coefficient is used for balancing the duty ratio weight of each item of data in formula calculation, so that the accuracy of a calculation result is promoted;
setting a software damage degree threshold, comparing and analyzing a software damage degree coefficient with the software damage degree threshold, judging a software running state as a fault state when the software damage degree coefficient is larger than or equal to the software damage degree threshold, counting the times of occurrence of the fault state, and carrying out summation calculation according to a formula:obtaining the software failure times, wherein +_>Indicating the point in time when the software operation has failed over a period of time,/->=1, 2,3 … … n2, and n2 is included in n;
acquiring the hardware fault times and the software fault times in the equipment system running state information of the medical self-service terminal, respectively calibrating the hardware fault times and the software fault times as HP and KP, and according to the formula:obtaining a device system operation fault value HK, wherein +.>And->Weight coefficients expressed as number of hardware failures and number of software failures, respectively, and +.>＞/>The weight coefficient is used for balancing the duty ratio weight of each item of data in formula calculation, so that the accuracy of a calculation result is promoted;
three fault gradient comparison intervals of the equipment system operation fault value are set, namely a first gradient fault interval zvq1, a second gradient fault interval zvq and a third gradient fault interval zvq3, and zvq 1=zvq2=2/>zvq3, where zvq1 > zvq2 > zvq3, +.>Represents the multiple of the gradient, and->Setting specific values of (2) by a person skilled in the art in a specific medical self-service terminal equipment fault instance;
when the equipment system operation fault value is in a preset first gradient fault interval zvq1, a severe fault signal is generated, when the equipment system operation fault value is in a preset second gradient fault interval zvq2, a moderate fault signal is generated, and when the equipment system operation fault value is in a preset third gradient fault interval zvq, a slight fault signal is generated;
the generated severe fault signals, medium fault signals and light fault signals are sent to a fault analysis feedback unit;
the fault analysis feedback unit analyzes the abnormal operation of the equipment system according to the received equipment system fault type judging signal, wherein the equipment system fault type judging signal comprises a severe fault signal, a moderate fault signal and a mild fault signal, and the specific operation process is as follows:
when a severe fault signal or a moderate fault signal is captured, triggering an R1 fault early warning instruction, sending the R1 fault early warning instruction to an interference obstacle removing unit, and assigning maintenance personnel to carry out maintenance or replacement operation in a set A time period by the interference obstacle removing unit according to the received R1 fault early warning instruction, and displaying a notice on a display platform;
when a mild fault signal is captured, triggering a V1 fault early warning instruction, sending the V1 fault early warning instruction to an automatic obstacle removing unit, and carrying out automatic restarting operation of equipment in a set time period B by the automatic obstacle removing unit according to the received V1 fault early warning instruction and carrying out display notification on a display platform;
when an R1 fault early warning instruction occurs, the severity of the fault occurring in the operation of the equipment system is greater than that of the fault occurring in the operation of the equipment system, the A time period and the B time period represent preset time periods, and the A time period is smaller than the B time period;
when the network operation state early warning unit receives the network operation state information, the network operation state analysis processing is carried out, and the specific operation process is as follows:
monitoring a network transmission rate value, network attack times and static induction degree value in network running state information within a period of time, and calibrating the network transmission rate value, the network attack times and the static induction degree value as wcs, bgs and jys according to the formula:obtaining a network operation risk value WM, wherein u1, u2 and u3 are respectively represented as weight coefficients of a network transmission rate value, attack times and an electrostatic induction degree value, and u1 is more than u2 and more than u3, and the weight coefficients are used for balancing the duty ratio weights of various data in formula calculation, so that the accuracy of a calculation result is promoted;
it should be noted that the network transmission rate value represents the data exchange capability of the hub, and is defined as S by acquiring the number of lost data packets and the transmitted data sets in the test over a period of time Lost the And S is Hair brush The duty ratio of the two data is calculated according to the formulaObtaining a network transmission speed value, wherein the network attack frequency represents the number of times of attack in running of the network in a period of time, the static induction degree value represents the speed of influencing the running speed of the network, the static force at each time point in running of the network in a period of time is monitored, the static force at each time point in running of the network in a period of time is calculated to obtain an average static force, and the static force at each time point in running of the network in a period of time and the average static force are calculated to obtain a static induction degree value jys;
setting a network operation risk threshold value as WMA, comparing and analyzing the network operation risk value with the network operation risk threshold value, generating a network risk fault signal when the network operation risk value is larger than the network operation risk threshold value, and generating a network potential risk fault signal when the network operation risk value is equal to or smaller than the network operation risk threshold value;
the generated network fault risk signals and the generated network potential fault risk signals are sent to a fault analysis feedback unit;
the fault analysis feedback unit analyzes network operation abnormality according to the received network fault type judgment signal, wherein the network fault type judgment signal comprises a network fault risk signal and a network potential fault risk signal, and the specific operation process is as follows:
when a network fault risk signal is captured, triggering an R2 fault early warning instruction, and sending the R2 fault early warning instruction to an interference obstacle removing unit;
the intervention obstacle removing unit invokes a network operation risk value in the current time period according to the received R2 fault early warning instruction, performs matching analysis on the network operation risk value and a network operation state early warning level table stored in a cloud database, so as to obtain early warning network fault risk level data, each obtained network operation risk value corresponds to one early warning network fault risk level data, performs corresponding maintenance in a set C time period according to the early warning network fault risk level data, and performs display notification on a display platform;
when a potential fault risk signal of the network is captured, triggering a V2 fault early warning instruction, sending the V2 fault early warning instruction to an automatic obstacle removing unit, and carrying out operation system updating and automatic encryption in a set D time period by the automatic obstacle removing unit according to the received V2 fault early warning instruction, and carrying out display notification on a display platform;
it should be noted that, when the R2 fault early warning command occurs, the severity of the risk of occurrence of the network operation is greater than that of the V2 fault early warning command, the C time period and the D time period represent preset time periods, and the C time period is smaller than the D time period;
when the power running state early warning unit receives the power running state information, the power running state analysis processing is performed, and the specific operation process is as follows:
monitoring the power supply value, the temperature value and the humidity value in the power running state information within a period of time, and calibrating the power supply value, the temperature value and the humidity value as light i 、wcv i And scu i According to the formula:obtaining an electric power running value DZ, wherein e1, e2 and e3 respectively represent the influencing factors of a power supply value, a temperature value and a humidity value, and e3 is more than e2 is more than e1 and is more than right * 、wcv * And scu * Respectively representing an initial power supply value, an initial temperature value and an initial humidity value;
the power supply value represents the power consumption required by the medical self-service terminal equipment during operation, the temperature value represents the internal temperature of the medical self-service terminal equipment during operation and the external environment temperature of the medical self-service terminal equipment, the two values are taken for summation and calculation, and the humidity value represents the external environment humidity of the medical self-service terminal equipment;
setting an electric power operation threshold value as DZQ, comparing and analyzing the electric power operation value with the electric power operation threshold value, generating an electric power operation abnormal signal when the electric power operation value is larger than or equal to the electric power operation threshold value, and generating an electric power operation normal signal when the electric power operation value is smaller than the electric power operation threshold value;
the generated power operation abnormality signal is sent to a fault analysis feedback unit for power operation abnormality analysis, and the specific operation process is as follows:
according to the triggered power operation abnormal signal, firstly, a power supply value in the power operation state information is called, the power supply value is substituted into an abnormal power supply comparison interval for comparison and analysis, when the power supply value is in the preset abnormal power supply comparison interval, a power supply fault early warning instruction is triggered, the power supply fault early warning instruction is sent to an interference barrier removal unit, fault early warning feedback operation is carried out on an abnormal power supply in the power operation state information, specifically, automatic power supply cutting operation is triggered, maintenance personnel are assigned to go to overhaul in a set E time period, and display notification is carried out on a display platform;
when the power supply value is not in a preset abnormal power supply comparison interval, the temperature in the power running state information is called, the temperature is compared and analyzed with a temperature threshold value, when the temperature is larger than or smaller than the preset temperature threshold value, a temperature fault early warning instruction is triggered, the temperature fault early warning instruction is sent to an automatic obstacle removing unit, fault early warning feedback operation is carried out on the abnormal temperature in the power running state information, specifically, circuit breaking and countdown are carried out in a set F time period, temperature regulation operation is carried out, and display notification is carried out on a display platform;
when the temperature is equal to a preset temperature threshold value, the humidity in the power running state information is called, the humidity is compared and analyzed with the humidity threshold value, when the humidity is greater than the preset humidity threshold value, a humidity fault early warning instruction is triggered, the humidity fault early warning instruction is sent to an automatic obstacle removing unit, fault early warning feedback operation is carried out on abnormal humidity in the power running state information, specifically, circuit switching-off countdown is carried out in a set G time period, humidity regulation operation is carried out, and display notification is carried out on a display platform.
The preferred embodiments of the invention disclosed above are intended only to assist in the explanation of the invention. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise form 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 understand and utilize the invention. The invention is limited only by the claims and the full scope and equivalents thereof.
Claims (7)
1. The equipment fault early warning system for the medical self-service terminal comprises a server, a data acquisition unit and a display platform, and is characterized by further comprising an equipment system running state early warning unit, a network running state early warning unit, an electric power running state early warning unit, a fault analysis feedback unit, an automatic obstacle removing unit and an intervention obstacle removing unit;
the data acquisition unit is used for acquiring equipment system operation state information, network operation state information and power operation state information of the medical self-service terminal equipment and respectively transmitting the equipment system operation state information, the network operation state information and the power operation state information to the equipment system operation state early warning unit, the network operation state early warning unit and the power operation state early warning unit through the server;
the equipment system running state early warning unit is used for receiving the equipment system running state information, analyzing and processing the equipment system running state, obtaining a severe fault signal, a moderate fault signal and a mild fault signal according to the equipment system running state information, and sending the severe fault signal, the moderate fault signal and the mild fault signal to the fault analysis feedback unit;
the network operation state early warning unit is used for receiving the network operation state information, analyzing and processing the network operation state, obtaining a network fault risk signal and a network potential fault risk signal according to the network operation state information, and sending the network fault risk signal and the network potential fault risk signal to the fault analysis feedback unit;
the power running state early warning unit is used for receiving the power running state information, analyzing and processing the power running state, obtaining a power running abnormal signal according to the power running state information, and sending the power running abnormal signal to the fault analysis feedback unit;
the fault analysis feedback unit is used for triggering corresponding fault early warning instructions according to the received equipment system fault type judging signals, network fault type judging signals and power operation abnormal signals respectively and sending the fault early warning instructions to the automatic fault clearing unit or the interference fault clearing unit;
and the automatic obstacle removing unit or the intervention obstacle removing unit performs corresponding automatic operation processing or personnel intervention operation processing according to the received corresponding fault early warning instruction, and displays and notifies the result on a display platform.
2. The equipment failure early warning system for the medical self-service terminal according to claim 1, wherein the analysis processing of the running state of the equipment system is performed, and the specific operation process is as follows:
monitoring hardware fault information of each time point in the running state information of the equipment system within a period of time, wherein the hardware fault information comprises a heat value, a wear degree and a use load value, and performing calculation processing to obtain a hardware damage degree coefficient;
taking time as an abscissa, taking a hardware damage degree coefficient as an ordinate, establishing a two-dimensional dynamic coordinate system of the hardware damage degree according to the time, drawing the calculated hardware damage degree coefficient on the two-dimensional dynamic coordinate system of the hardware damage degree in a period of time in a way of constructing a description curve, thereby obtaining a waveform curve of the hardware damage degree coefficient, obtaining all inflection points of the waveform curve of the hardware damage degree coefficient, counting the number of all inflection points of the waveform curve of the hardware damage degree coefficient, and obtaining the number of hardware faults according to calculation processing;
monitoring software fault information of each time point in the running state information of the equipment system within a period of time, wherein the software fault information comprises system breakdown times and software flashing back times, and performing calculation processing to obtain a software damage degree coefficient;
comparing and analyzing the software damage degree coefficient with a software damage degree threshold, judging the running state of the software as a fault state when the software damage degree coefficient is larger than or equal to the software damage degree threshold, counting the times of occurrence of the fault state, and summing up to obtain the times of the software fault;
acquiring the number of hardware faults and the number of software faults in the equipment system running state information of the medical self-service terminal, and calculating and processing to obtain an equipment system running fault value;
setting three fault gradient comparison intervals of the equipment system operation fault value, namely a first gradient fault interval, a second gradient fault interval and a third gradient fault interval;
and when the operation fault value of the equipment system is in a preset first gradient fault interval, generating a severe fault signal, when the operation fault value of the equipment system is in a preset second gradient fault interval, generating a moderate fault signal, and when the operation fault value of the equipment system is in a preset third gradient fault interval, generating a mild fault signal.
3. The equipment failure early warning system for a medical self-service terminal according to claim 1, wherein the analysis processing of the network operation state is performed, and the specific operation process is as follows:
monitoring a network transmission rate value, network attack times and an electrostatic induction degree value in network operation state information within a period of time, and performing calculation processing to obtain a network operation risk value;
setting a network operation risk threshold, comparing and analyzing the network operation risk value with the network operation risk threshold, generating a network risk fault signal when the network operation risk value is larger than the network operation risk threshold, and generating a network potential risk fault signal when the network operation risk value is equal to or smaller than the network operation risk threshold.
4. The equipment failure early warning system for a medical self-service terminal according to claim 1, wherein the power running state analysis processing is performed, and the specific operation process is as follows:
monitoring a power supply value, a temperature value and a humidity value in the power running state information within a period of time, and performing calculation processing to obtain a power running value;
and comparing and analyzing the electric power operation value with an electric power operation threshold value, and generating an electric power operation abnormal signal when the electric power operation value is greater than or equal to the electric power operation threshold value.
5. The equipment failure early warning system for a medical self-service terminal according to claim 1, wherein the operation abnormality analysis determination of the medical self-service terminal equipment is performed, and the specific operation process is as follows:
when a severe fault signal or a moderate fault signal is captured, triggering an R1 fault early warning instruction and sending the R1 fault early warning instruction to an intervention obstacle removing unit;
when the light fault signal is captured, triggering a V1 fault early warning instruction and sending the V1 fault early warning instruction to an automatic obstacle removing unit;
when a network fault risk signal is captured, triggering an R2 fault early warning instruction, and sending the R2 fault early warning instruction to an interference obstacle removing unit;
when a potential fault risk signal of the network is captured, triggering a V2 fault early warning instruction and sending the V2 fault early warning instruction to an automatic obstacle removing unit;
according to the triggered power operation abnormal signal, firstly, calling a power supply value in the power operation state information, substituting the power supply value into an abnormal power supply comparison interval for comparison and analysis, triggering a power supply fault early warning instruction when the power supply value is in a preset abnormal power supply comparison interval, and sending the power supply fault early warning instruction to an intervention obstacle removing unit;
when the power supply value is not in a preset abnormal power supply comparison interval, the temperature in the power running state information is called, the temperature is compared and analyzed with a temperature threshold value, and when the temperature is greater than or less than the preset temperature threshold value, a temperature fault early warning instruction is triggered and sent to an automatic obstacle avoidance unit;
and when the temperature is equal to a preset temperature threshold value, the humidity in the power running state information is called, the humidity is compared and analyzed with the humidity threshold value, and when the humidity is greater than the preset humidity threshold value, a humidity fault early warning instruction is triggered and sent to the automatic obstacle removing unit.
6. The equipment failure early warning system for a medical self-service terminal according to claim 1, wherein the corresponding automatic operation processing is performed, and the specific operation steps are as follows:
according to the received V1 fault early warning instruction, performing automatic restarting operation on the equipment in the set time period B, and performing display notification on a display platform;
according to the received V2 fault early warning instruction, the operation system is updated and automatically encrypted in a set D time period, and display notification is carried out on a display platform;
counting down the circuit cut-off in a set F time period according to the received temperature fault early warning instruction, performing temperature regulation and control operation, and displaying and notifying on a display platform;
and counting down the cut-off circuit in the set G time period according to the received humidity fault early warning instruction, performing humidity regulation and control operation, and displaying and informing on a display platform.
7. The equipment failure early warning system for a medical self-service terminal according to claim 1, wherein the corresponding personnel intervention operation process is performed, and the specific operation steps are as follows:
according to the received R1 fault early warning instruction, a maintainer is assigned to go to maintenance or replacement operation in a set time period A, and display notification is carried out on a display platform;
according to the received R2 fault early warning instruction, invoking a network operation risk value in the current time period, carrying out matching analysis on the network operation risk value and a network operation state early warning level table stored in a cloud database, thereby obtaining early warning network fault risk level data, wherein each obtained network operation risk value corresponds to one early warning network fault risk level data, carrying out corresponding maintenance operation in a set C time period according to the obtained network fault risk level data to be early warned, and carrying out display notification on a display platform;
and immediately and automatically cutting off the power supply according to the received power failure early warning instruction, assigning maintenance personnel to go to maintenance in a set E time period, and displaying a notice on a display platform.
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