CN117497160A - Medical equipment fault prediction and maintenance system based on intelligent sensing technology - Google Patents

Medical equipment fault prediction and maintenance system based on intelligent sensing technology Download PDF

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Publication number
CN117497160A
CN117497160A CN202311291451.0A CN202311291451A CN117497160A CN 117497160 A CN117497160 A CN 117497160A CN 202311291451 A CN202311291451 A CN 202311291451A CN 117497160 A CN117497160 A CN 117497160A
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maintenance
circuit monitoring
server
sensor
equipment
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Inventor
戴琼
刘赤岩
马海燕
姜进
周珏
袁家长
徐凡
王照顺
邬涌
朱肖凯
骆梦莲
石玮
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Huangshi Aikang Hospital Co ltd
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Huangshi Aikang Hospital Co ltd
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    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H40/00—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
    • G16H40/40—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management of medical equipment or devices, e.g. scheduling maintenance or upgrades
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01H—MEASUREMENT OF MECHANICAL VIBRATIONS OR ULTRASONIC, SONIC OR INFRASONIC WAVES
    • G01H1/00—Measuring characteristics of vibrations in solids by using direct conduction to the detector
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/20—Administration of product repair or maintenance
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising
    • G06Q30/0278—Product appraisal

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  • Business, Economics & Management (AREA)
  • Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • General Business, Economics & Management (AREA)
  • Physics & Mathematics (AREA)
  • Health & Medical Sciences (AREA)
  • Strategic Management (AREA)
  • Entrepreneurship & Innovation (AREA)
  • Biomedical Technology (AREA)
  • Finance (AREA)
  • Human Resources & Organizations (AREA)
  • Economics (AREA)
  • Development Economics (AREA)
  • Marketing (AREA)
  • Accounting & Taxation (AREA)
  • Theoretical Computer Science (AREA)
  • Medical Informatics (AREA)
  • Tourism & Hospitality (AREA)
  • Epidemiology (AREA)
  • General Health & Medical Sciences (AREA)
  • Quality & Reliability (AREA)
  • Operations Research (AREA)
  • Primary Health Care (AREA)
  • Public Health (AREA)
  • Game Theory and Decision Science (AREA)
  • Measuring And Recording Apparatus For Diagnosis (AREA)

Abstract

The invention discloses a medical equipment fault prediction and maintenance system based on an intelligent sensing technology in the field of equipment fault prediction, which comprises a surface detection sensor, a circuit monitoring sensor and a server, wherein the surface detection sensor is used for detecting the faults of equipment; the surface detection sensor comprises crystal mud, a plurality of sensors are uniformly distributed in the crystal mud, each sensor comprises a vibration sensor and an LED lamp, and the sensors are connected in parallel through thin wires; the circuit monitoring sensor comprises a voltage sensor and a wireless module, wherein the wireless module is used for sending the detected voltage value to the server; the server is used for collecting voltage value data sent by the circuit monitoring sensor, and the server can detect that the voltage detected by the circuit monitoring sensor is in a stable range and send out an alarm when the voltage exceeds the stable range. By adopting the technical scheme of the invention, the aging judgment can be carried out through the vibration distribution of the surface of the equipment.

Description

Medical equipment fault prediction and maintenance system based on intelligent sensing technology
Technical Field
The invention belongs to the field of equipment fault prediction, and particularly relates to a medical equipment fault prediction and maintenance system based on an intelligent sensing technology.
Background
Medical devices are the most fundamental components of medical, scientific, institutional and clinical discipline work, such as positron emission tomography/X-ray computer tomography devices. However, once the medical equipment fails, the whole workflow depending on the medical equipment is terminated, so that serious economic loss is caused, and more importantly, the safety of a patient is possibly threatened, so that the prediction of the failure of the medical equipment is very important.
To address the above issues, patent publication No. CN108898238A discloses a medical device fault prediction system and related methods, apparatuses, and devices, including: collecting real-time state data, real-time fault state data and index data of medical equipment; acquiring a current feature vector set Sn according to the real-time state data, the real-time fault state data and the index data; inputting the current feature vector set Sn into a latest medical equipment fault prediction network, and outputting a first fault prediction probability Pn; outputting a second fault prediction probability Nn through Monte Carlo tree search; and taking the matching degree of the first fault prediction probability Pn and the second fault prediction probability Nn as a training target, wherein the matching degree of the first fault prediction probability Pn and the real-time fault state data in the input next feature vector set Sn+1 reaches a first preset value.
According to the medical equipment fault prediction system, the related method, the related device and the related equipment, the faults are analyzed by collecting the real-time state data, the real-time fault state data and the index data, but besides an internal program, various parts of the equipment are aged, so that the equipment gradually breaks down.
Disclosure of Invention
In order to solve the problem that equipment aging is difficult to detect and faults are caused in the prior art, the invention aims to provide a medical equipment failure prediction and maintenance system based on an intelligent sensing technology, and aging judgment can be carried out through equipment surface vibration distribution.
In order to achieve the above object, the technical scheme of the present invention is as follows: the medical equipment fault prediction and maintenance system based on the intelligent sensing technology comprises a surface detection sensor, a circuit monitoring sensor and a server;
the surface detection sensor comprises crystal mud, a plurality of sensors are uniformly distributed in the crystal mud, each sensor comprises a vibration sensor and an LED lamp, and the sensors are connected in parallel through thin wires;
the circuit monitoring sensor comprises a voltage sensor and a wireless module, wherein the wireless module is used for sending the detected voltage value to the server;
the server is used for collecting voltage value data sent by the circuit monitoring sensor, and the server can detect that the voltage detected by the circuit monitoring sensor is in a stable range and send out an alarm when the voltage exceeds the stable range.
After the scheme is adopted, the following beneficial effects are realized: the surface detection sensor is used for detecting vibration distribution of the equipment so as to judge whether the equipment is aged or not, and crystal mud can flow like liquid and enter a gap or deform along with the shape of the equipment, so that the inductor can cover the surface of the equipment. When the device is in operation, the vibration sensor can change the resistance due to vibration, so that the brightness of the LED lamp is changed. The light intensity represents the vibration distribution to determine if the device has aged.
The circuit monitoring sensor detects voltages on two sides of the electronic element, so that the electronic element is damaged quickly under abnormal voltages, and meanwhile, the detected voltages after the electronic element is damaged are abnormal. By means of the circuit inside the voltage monitoring device, faults can be predicted by means of voltage changes and fault locations can be located.
Compared with the prior art, the surface detection sensor can enter a gap or deform along with the shape of equipment in a crystal mud wrapping mode, and is attached to the appearance of the equipment for detection; whether equipment is aged or worn or not is judged by detecting vibration distribution, so that faults are predicted in terms of physical structure.
Further, a fault maintenance system based on the intelligent sensing technology-based medical device fault prediction system of claim 1;
and a circuit monitoring database is arranged in the server, and the equipment code of the circuit monitoring sensor in the circuit monitoring database is bound with the monitored electronic element model field.
The beneficial effects are that: the maintenance personnel can prepare the electronic element in advance according to the circuit monitoring sensor giving out the alarm, so that the maintenance personnel can directly replace the electronic element in the subsequent maintenance process, maintenance materials are not required to be prepared after checking, and the number of times that the maintenance personnel goes to the site is reduced.
Further, the server is further used for storing maintenance feedback information by maintenance personnel, wherein the maintenance feedback information comprises maintenance time, damaged parts, equipment codes of the circuit monitoring sensor for detecting abnormality, maintenance difficulty rating, maintenance personnel mobile phone numbers, maintenance time consumption and tool and instrument types; when the circuit monitoring sensor detects that the voltage exceeds the stable range, a maintenance request is sent to maintenance personnel, and all maintenance feedback information related to equipment codes of the circuit monitoring sensor is included in the maintenance request.
The beneficial effects are that: the maintenance feedback information can record maintenance information, and is convenient for a manager to select maintenance personnel or collect the maintenance information. Maintenance personnel can use the maintenance feedback information as a reference to carry out maintenance, so that the judgment or operation of the maintenance personnel is quickened.
Further, the maintenance difficulty rating includes a very easy rating that does not require specialized skills and tools.
The beneficial effects are that: the maintenance instruction can be completed without professional skills and tools, the failure of the medical instrument can affect the examination or treatment of a patient, and the manager can conduct maintenance through guiding through telephone communication, so that the equipment can operate as soon as possible, and meanwhile, the waste of maintenance resources is reduced.
Further, the equipment code of the circuit monitoring sensor in the circuit monitoring database is also bound with the geographic position information of the circuit monitoring sensor;
when a plurality of geographic position circuit monitoring sensors detect that the voltage exceeds a stable range, the server can schedule an optimal route for maintenance personnel according to the distribution of the geographic positions.
The beneficial effects are that: through arranging reasonable route, make maintenance personal can once only accomplish the maintenance to many places equipment, practice thrift unnecessary journey, make full use of maintenance personal's time.
Further, the server stores volume and weight data of various tool and instruments, when a plurality of geographic position circuit monitoring sensors detect that the voltage exceeds a stable range, the server can call the tool and instrument types in maintenance feedback information related to equipment codes of the circuit monitoring sensors, calculate the volume and weight of the tool and instrument needed to be carried by maintenance personnel, and when the volume and weight of the tool and instrument are overlarge, disassemble an optimal route into a departure route carrying a proper amount of tool and instrument for a plurality of times.
The beneficial effects are that: the majority of repairs are performed with tools, and too many tools are involved in a route that is too heavy to be a burden. By recording the volume and weight data of the tool equipment, the tool carrying quantity of one route is reasonably controlled, and the burden of maintenance personnel is reduced.
Further, the server reads the maintenance feedback information and generates a spare part list, parts in the spare part list are all high-frequency damaged parts, and the normal spare part holding number is calculated according to the damage frequency.
The beneficial effects are that: according to the maintenance feedback information, the damage rate of the parts is high, part of the parts need to be shipped from a manufacturer, the logistics time is too long, and the detection or treatment of patients is delayed. Therefore, the parts with high damage rate are counted, and the stored parts are used for standby, so that the parts can be quickly replaced after being damaged.
Further, the normal spare parts holding number of the spare parts table is multiplied by a part price coefficient, the part price coefficient of the low part price is larger than 1, and the part price coefficient of the high part price is smaller than 1.
The beneficial effects are that: the cost of storing the parts is too high due to the excessive price of the parts, the amount of money consumed is large, and the maintenance cost is too high. Therefore, the price coefficient of the parts is introduced, the reserve quantity of each high-price part is reduced, and the reserve quantity of the low-price part is increased. The operation and maintenance cost is reduced, and meanwhile, the probability that low-price part reserves are consumed for a short time is reduced.
Drawings
FIG. 1 is a schematic diagram of an embodiment of the present invention.
FIG. 2 is a schematic diagram of a surface detection sensor
Detailed Description
The following is a further detailed description of the embodiments:
reference numerals in the drawings of the specification include: 1 of crystal mud, 2 of an LED lamp and 3 of a vibration sensor.
Example 1
An example is substantially as shown in figures 1 and 2:
the medical equipment fault prediction system based on the intelligent sensing technology comprises a surface detection sensor, a circuit monitoring sensor and a server, wherein the model of the server is NF5280M5;
the surface detection sensor comprises crystal mud 1, a plurality of sensors are uniformly distributed in the crystal mud 1, each sensor comprises a vibration sensor 3 and an LED lamp 2, the model of the vibration sensor 3 is SW-420, the model of the LED lamp 2 is HJ-FGEJG, and the sensors are connected in parallel through thin wires;
the circuit monitoring sensor comprises a voltage sensor and a wireless module, wherein the model of the voltage sensor is xc30729, the model of the wireless module is AX200, and the wireless module is used for sending the detected voltage value to the server;
the server is used for collecting voltage value data sent by the circuit monitoring sensor, and the server can detect that the voltage detected by the circuit monitoring sensor is in a stable range and send out an alarm when the voltage exceeds the stable range.
The specific implementation process is as follows: the surface detection sensor is used for detecting vibration distribution of equipment so as to judge whether the equipment is aged or not, and the crystal mud 1 can flow like liquid and enter a gap or deform along with the shape of the equipment, so that the inductor can cover the surface of the equipment. When the device is in operation, the vibration sensor 3 changes resistance due to vibration, and the brightness of the LED lamp 2 is changed. The light intensity represents the vibration distribution to determine if the device has aged.
The circuit monitoring sensor detects voltages on two sides of the electronic element, so that the electronic element is damaged quickly under abnormal voltages, and meanwhile, the detected voltages after the electronic element is damaged are abnormal. By means of the circuit inside the voltage monitoring device, faults can be predicted by means of voltage changes and fault locations can be located.
The surface detection sensor can enter a gap or deform along with the shape of equipment through the wrapping form of crystal mud 1, and is attached to the appearance of the equipment for detection; whether equipment is aged or worn or not is judged by detecting vibration distribution, so that faults are predicted in terms of physical structure.
Example two
The difference from the above embodiment is that: a fault maintenance system based on the intelligent sensing technology-based medical device fault prediction system of claim 1;
and a circuit monitoring database is arranged in the server, and the equipment code of the circuit monitoring sensor in the circuit monitoring database is bound with the monitored electronic element model field.
The specific implementation process is as follows: the maintenance personnel can prepare the electronic element in advance according to the circuit monitoring sensor giving out the alarm, so that the maintenance personnel can directly replace the electronic element in the subsequent maintenance process, maintenance materials are not required to be prepared after checking, and the number of times that the maintenance personnel goes to the site is reduced.
Example III
The difference from the above embodiment is that: the server is also used for storing maintenance feedback information by maintenance personnel, wherein the maintenance feedback information comprises maintenance time, damaged parts, equipment codes of the circuit monitoring sensor for detecting abnormality, maintenance difficulty rating, maintenance personnel mobile phone numbers, maintenance time consumption and tool and instrument types; when the circuit monitoring sensor detects that the voltage exceeds the stable range, a maintenance request is sent to maintenance personnel, and all maintenance feedback information related to equipment codes of the circuit monitoring sensor is included in the maintenance request.
The specific implementation process is as follows: the maintenance feedback information can record maintenance information, and is convenient for a manager to select maintenance personnel or collect the maintenance information. Maintenance personnel can use the maintenance feedback information as a reference to carry out maintenance, so that the judgment or operation of the maintenance personnel is quickened.
Example IV
The difference from the above embodiment is that: maintenance difficulty ratings include extremely easy ratings that do not require specialized skills and tools.
The specific implementation process is as follows: the maintenance instruction can be completed without professional skills and tools, the failure of the medical instrument can affect the examination or treatment of a patient, and the manager can conduct maintenance through guiding through telephone communication, so that the equipment can operate as soon as possible, and meanwhile, the waste of maintenance resources is reduced.
Example five
The difference from the above embodiment is that: the equipment code of the circuit monitoring sensor in the circuit monitoring database is also bound with the geographic position information of the circuit monitoring sensor;
when a plurality of geographic position circuit monitoring sensors detect that the voltage exceeds a stable range, the server can schedule an optimal route for maintenance personnel according to the distribution of the geographic positions.
The specific implementation process is as follows: through arranging reasonable route, make maintenance personal can once only accomplish the maintenance to many places equipment, practice thrift unnecessary journey, make full use of maintenance personal's time.
Example six
The difference from the above embodiment is that: the server stores the volume and weight data of various tool and instruments, when a plurality of geographic position circuit monitoring sensors detect that the voltage exceeds a stable range, the server can call the tool and instrument types in maintenance feedback information related to equipment codes of the circuit monitoring sensors, calculate the volume and weight of the tool and instrument needed to be carried by maintenance personnel, and when the volume and weight of the tool and instrument are overlarge, disassemble an optimal route into a departure route carrying a proper amount of tool and instrument for a plurality of times.
The specific implementation process is as follows: the majority of repairs are performed with tools, and too many tools are involved in a route that is too heavy to be a burden. By recording the volume and weight data of the tool equipment, the tool carrying quantity of one route is reasonably controlled, and the burden of maintenance personnel is reduced.
Example seven
The difference from the above embodiment is that: the server reads the maintenance feedback information and generates a spare part list, parts in the spare part list are all high-frequency damaged parts, and the normal spare part holding number is calculated according to the damage frequency.
The specific implementation process is as follows: according to the maintenance feedback information, the damage rate of the parts is high, part of the parts need to be shipped from a manufacturer, the logistics time is too long, and the detection or treatment of patients is delayed. Therefore, the parts with high damage rate are counted, and the stored parts are used for standby, so that the parts can be quickly replaced after being damaged.
Example eight
The difference from the above embodiment is that: the normal spare parts holding number of the spare parts table is multiplied by a part price coefficient, the part price coefficient of low part price is more than 1, and the part price coefficient of high part price is less than 1.
The specific implementation process is as follows: the cost of storing the parts is too high due to the excessive price of the parts, the amount of money consumed is large, and the maintenance cost is too high. Therefore, the price coefficient of the parts is introduced, the reserve quantity of each high-price part is reduced, and the reserve quantity of the low-price part is increased. The operation and maintenance cost is reduced, and meanwhile, the probability that low-price part reserves are consumed for a short time is reduced.
The foregoing is merely an embodiment of the present invention, and a specific structure and characteristics of common knowledge in the art, which are well known in the scheme, are not described herein, so that a person of ordinary skill in the art knows all the prior art in the application day or before the priority date of the present invention, and can know all the prior art in the field, and have the capability of applying the conventional experimental means before the date, so that a person of ordinary skill in the art can complete and implement the present embodiment in combination with his own capability in the light of the present application, and some typical known structures or known methods should not be an obstacle for a person of ordinary skill in the art to implement the present application. It should be noted that modifications and improvements can be made by those skilled in the art without departing from the structure of the present invention, and these should also be considered as the scope of the present invention, which does not affect the effect of the implementation of the present invention and the utility of the patent. The protection scope of the present application shall be subject to the content of the claims, and the description of the specific embodiments and the like in the specification can be used for explaining the content of the claims.

Claims (8)

1. Medical equipment fault prediction system based on intelligent sensing technology, its characterized in that: the system comprises a surface detection sensor, a circuit monitoring sensor and a server;
the surface detection sensor comprises crystal mud, a plurality of sensors are uniformly distributed in the crystal mud, each sensor comprises a vibration sensor and an LED lamp, and the sensors are connected in parallel through thin wires;
the circuit monitoring sensor comprises a voltage sensor and a wireless module, wherein the wireless module is used for sending the detected voltage value to the server;
the server is used for collecting voltage value data sent by the circuit monitoring sensor, and the server can detect that the voltage detected by the circuit monitoring sensor is in a stable range and send out an alarm when the voltage exceeds the stable range.
2. Medical equipment fault maintenance system based on intelligent sensing technology, its characterized in that: a fault maintenance system based on the intelligent sensing technology-based medical device fault prediction system of claim 1;
and a circuit monitoring database is arranged in the server, and the equipment code of the circuit monitoring sensor in the circuit monitoring database is bound with the monitored electronic element model field.
3. The intelligent sensing technology-based medical device fault maintenance system of claim 2, wherein: the server is also used for storing maintenance feedback information by maintenance personnel, wherein the maintenance feedback information comprises maintenance time, damaged parts, equipment codes of the circuit monitoring sensor for detecting abnormality, maintenance difficulty rating, maintenance personnel mobile phone numbers, maintenance time consumption and tool and instrument types; when the circuit monitoring sensor detects that the voltage exceeds the stable range, a maintenance request is sent to maintenance personnel, and all maintenance feedback information related to equipment codes of the circuit monitoring sensor is included in the maintenance request.
4. The intelligent sensing technology-based medical device fault maintenance system of claim 3, wherein: maintenance difficulty ratings include extremely easy ratings that do not require specialized skills and tools.
5. The intelligent sensing technology-based medical device fault maintenance system of claim 4, wherein: the equipment code of the circuit monitoring sensor in the circuit monitoring database is also bound with the geographic position information of the circuit monitoring sensor;
when a plurality of geographic position circuit monitoring sensors detect that the voltage exceeds a stable range, the server can schedule an optimal route for maintenance personnel according to the distribution of the geographic positions.
6. The intelligent sensing technology-based medical device fault maintenance system of claim 5, wherein: the server stores the volume and weight data of various tool and instruments, when a plurality of geographic position circuit monitoring sensors detect that the voltage exceeds a stable range, the server can call the tool and instrument types in maintenance feedback information related to equipment codes of the circuit monitoring sensors, calculate the volume and weight of the tool and instrument needed to be carried by maintenance personnel, and when the volume and weight of the tool and instrument are overlarge, disassemble an optimal route into a departure route carrying a proper amount of tool and instrument for a plurality of times.
7. The intelligent sensing technology-based medical device fault maintenance system of claim 6, wherein: the server reads the maintenance feedback information and generates a spare part list, parts in the spare part list are all high-frequency damaged parts, and the normal spare part holding number is calculated according to the damage frequency.
8. The intelligent sensing technology-based medical device fault maintenance system of claim 7, wherein: the normal spare parts holding number of the spare parts table is multiplied by a part price coefficient, the part price coefficient of low part price is more than 1, and the part price coefficient of high part price is less than 1.
CN202311291451.0A 2023-10-08 2023-10-08 Medical equipment fault prediction and maintenance system based on intelligent sensing technology Withdrawn CN117497160A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202311291451.0A CN117497160A (en) 2023-10-08 2023-10-08 Medical equipment fault prediction and maintenance system based on intelligent sensing technology

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202311291451.0A CN117497160A (en) 2023-10-08 2023-10-08 Medical equipment fault prediction and maintenance system based on intelligent sensing technology

Publications (1)

Publication Number Publication Date
CN117497160A true CN117497160A (en) 2024-02-02

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CN202311291451.0A Withdrawn CN117497160A (en) 2023-10-08 2023-10-08 Medical equipment fault prediction and maintenance system based on intelligent sensing technology

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Application publication date: 20240202