Production instrument safety management system and method based on big data
By using big data analysis and intelligent settings for irradiation intensity, the problem of unreasonable irradiation intensity in ultraviolet disinfection has been solved, improving disinfection reliability and equipment lifespan.
Patent Information
- Application Number
- CN202511757553.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-11-27
- Publication Date
- 2026-04-21
- Estimated Expiration
- Not applicable · inactive patent
AI Technical Summary
In the current medical device disinfection process, the intensity of ultraviolet irradiation is artificially set, which is unreasonable, cannot effectively inactivate viruses, and may accelerate the aging of devices, affecting the reliability of disinfection and service life.
Based on big data analysis of the historical records and monitoring videos of ultraviolet disinfection devices, the reliability of calibration points and operators is extracted. Combined with pollution source detection, the degree of equipment contamination is calculated, and a reasonable irradiation intensity is intelligently set.
It improves the reliability of medical device disinfection, reduces device aging caused by unreasonable irradiation intensity, and enhances disinfection effect and service life.
Smart Images
Figure CN121905455A_ABST
Abstract
Description
[0001] This invention relates to the field of big data technology, specifically to a production machinery safety management system and method based on big data. Background Technology
[0002] The medical devices produced are mainly used for diagnosing, treating, alleviating diseases, or supporting human anatomy. They are typically used in healthcare institutions, doctors' offices, home care, and other healthcare environments. They are the core support for ensuring the accuracy of medical diagnosis, the effectiveness of treatment, and the safety of care, and are also an indispensable key medical resource for maintaining public health. To avoid cross-infection and cut off the infection route, medical devices need to be disinfected with ultraviolet light promptly after use. However, the irradiation intensity for disinfecting medical devices is usually set manually. Due to human subjectivity, unreasonable irradiation intensity may occur. Some viruses require a certain irradiation intensity to be eliminated, and even if the irradiation time is extended, they cannot be completely inactivated. On the other hand, excessive irradiation intensity will accelerate the aging of medical device materials and reduce their service life. Therefore, if the irradiation intensity can be reasonably set according to the actual use of medical devices, the reliability of medical device disinfection can be effectively improved. Summary of the Invention
[0003] The purpose of this invention is to provide a production machinery safety management system and method based on big data, so as to solve the problems raised in the prior art.
[0004] To solve the above-mentioned technical problems, the present invention provides the following technical solution: The big data-based method for safety management of production equipment includes the following steps: Retrieve historical disinfection records from the ultraviolet disinfection device, extract the corresponding medical devices and disinfection times from the disinfection records, retrieve historical surveillance videos, analyze the movement of medical devices in the medical department, and extract calibration points from the medical devices. Extract the operators corresponding to the disinfection records, and obtain the reliability of the disinfection records based on the operators' operating permissions and shift times; measure the change in bacterial density at the calibration point before and after disinfection to obtain the bacterial residue rate; The target records in the disinfection log are judged and extracted based on a combination of reliability, bacterial residue rate, and disinfection duration. A three-dimensional model of the medical department is established to obtain all pollution sources within the department. Bacterial detection is performed at the source release points of the pollution sources to obtain the pollution intensity of each pollution source. The location of the corresponding medical devices during use is monitored in real time. Based on the pollution intensity, the location of the medical devices, and the location of the pollution sources, the degree of pollution of the medical devices is calculated. The medical device that needs to be disinfected is selected as the device to be tested. The monitoring footage of the device to be tested during use is retrieved to obtain the current level of contamination. The irradiation intensity corresponding to the target record is extracted, and the irradiation intensity for disinfection of the device to be tested is intelligently set according to the level of contamination.
[0005] Preferably, extracting calibration points from a medical device includes the following steps: Retrieve the historical disinfection records of the ultraviolet disinfection device, extract the medical device X and disinfection time T1 corresponding to a certain disinfection record, obtain the previous disinfection time T0 of medical device X, and retrieve the monitoring segment between disinfection time T0 and disinfection time T1. Medical device X performs its function by contacting the ROI (Region of Interest). The region R of medical device X within the monitoring segment is obtained. X And the ROI region in the monitoring segment, region R ROI , will region R X With region R ROI Let the moment of the first contact be t1. Starting from time t1, search for the region R. X With region R ROI The moment of first separation is designated as t2. Several image frames are extracted from time t1 and time t2. Extract several location points on medical device X, and set the initial target value of each location point to 0; obtain region R in a certain image frame F. X With region R ROI Overlapping region R F , will be in region R F Increment the target value of the location point within the region by 1; if it is not within region R... F The target value of the location point within remains unchanged; the region R in several image frames is obtained. X With region R ROI The overlapping areas are identified, and the final target value for each location point is obtained. The location point with the largest final target value is then used as the calibration point.
[0006] Preferably, the target record in the disinfection record is identified and extracted, including the following steps: Extract the operator P and disinfection time T corresponding to a disinfection record G. If the operator P has the authority to use the disinfection device to disinfect the medical device, the first confidence level of the operator P is set to 1. If the operator P does not have the authority to use the disinfection device to disinfect the medical device, the first confidence level of the operator P is set to 0. Obtain the shift time of operator P. If the disinfection time T falls within the shift time, set the second confidence level of operator P to 1. If the disinfection time T does not fall within the shift time, extract the end time S1 of the previous shift and the start time S2 of the next shift to obtain the target duration: D = min(T - S1, S2 - T). Calculate the second confidence level of operator P as e. -D Multiply the first confidence level by the second confidence level to obtain the reliability of the disinfection record G; The target duration D is the minimum of the duration between the end time of the previous shift S1 and the disinfection time T, and the duration between the disinfection time T and the start time of the next shift S2. A larger target duration D indicates a lower second reliability of operator P. Therefore, in this scheme, formula e can be used. -D As a second level of credibility, the first level of credibility is multiplied by the second level of credibility to obtain the reliability. The reliability value ranges from 0 to 1. The higher the reliability, the more reliable the disinfection record G information. By combining the reliability, bacterial residue rate and disinfection time, a reliable target record can be obtained.
[0007] Obtain the bacterial density B1 before disinfection and the bacterial density B2 after disinfection at the calibration point location, and obtain the bacterial residue rate: B2 / B1; if the reliability of the disinfection record G is greater than the preset reliability threshold, the bacterial residue rate is less than the preset ratio threshold, and the disinfection duration is greater than the preset duration threshold, then the disinfection record G is taken as the target record, and all target records are extracted.
[0008] Preferably, calculating the degree of contamination of a medical device includes the following steps: A 3D model of the medical department was created, and all pollution sources within the department were identified and labeled in the 3D model. Bacterial detection was performed at the source release points of the pollution sources to obtain the bacterial density and number of bacterial species for each pollution source. The maximum bacterial density M was then extracted. max and the maximum number of bacterial species N max The pollution intensity of one of the pollution sources s is obtained as: C s =W M ×M s / M max +W N ×N s / N max Among them, W M W is the bacterial density weight. N M represents the weight of the number of bacterial species. s N represents the bacterial density of pollution source s. s Let s be the number of bacterial species in pollution source s, and then the pollution intensity of each pollution source can be obtained; The location of a medical device Y corresponding to a target record during use is monitored in real time. If there is no source of pollution within a radius of r around the medical device Y at a certain moment, the pollution value V of the medical device Y at that moment is set to 0. If there are pollution sources within a radius of r around the device at a certain moment, based on the condition that the smaller the distance to the pollution source, the larger the pollution weight, the pollution weight of each pollution source is obtained. Based on the pollution weight and pollution intensity of each pollution source, the pollution value V of the medical device Y at a certain moment is obtained; thus, the pollution degree of the medical device Y is obtained as follows: Where Z is the number of time points, and V i Let be the contamination value of medical device Y at time i.
[0009] Preferably, the intelligent setting of the irradiation intensity for disinfecting the instruments to be tested includes the following steps: Obtain the previous disinfection time of the device Q to be tested, retrieve the monitoring segment of the time period between the previous disinfection time and the current time, calculate the contamination value of the device Q at each time moment, and obtain the current contamination level L of the device Q. Q ; Based on the current contamination level L of the device Q to be tested Q If the instrument Q to be tested needs to be disinfected, then the contamination level of the medical instrument must be no less than the contamination level L. Q The target records (since the extraction conditions for the target records include a bacterial residue rate less than a preset ratio threshold, the disinfection results of the medical devices in the target records are all qualified), and the minimum irradiation intensity among them is used as the irradiation intensity for disinfecting the device Q to be tested (the minimum irradiation intensity is to prevent excessive irradiation intensity from accelerating the aging of medical device materials and reducing service life). Based on the analysis of historical disinfection records according to this invention, and by comprehensively considering calibration points and contamination sources, a reasonable irradiation intensity is set for the device Q to be tested, which helps to improve the reliability of medical device disinfection and reduce problems caused by unreasonable disinfection irradiation intensity.
[0010] Based on the contamination level of each medical device corresponding to the target record, those with a contamination level not less than contamination level L are selected. Q The minimum irradiation intensity recorded in the target record is used as the irradiation intensity for disinfecting the instrument Q to be tested.
[0011] The production equipment safety management system based on big data includes a calibration point extraction module, a target record extraction module, a contamination degree calculation module, and an irradiation intensity setting module. Calibration point extraction module: used to retrieve historical disinfection records of ultraviolet disinfection devices, extract the medical devices and disinfection time corresponding to the disinfection records, retrieve historical monitoring videos, analyze the movement of medical devices in the medical department, and extract calibration points in the medical devices. Target record extraction module: used to extract the operators corresponding to disinfection records, and obtain the reliability of disinfection records based on the operators' operating permissions and shift time; measure the change in bacterial density at the calibration point before and after disinfection to obtain the bacterial residue rate; and judge and extract target records in disinfection records by combining reliability, bacterial residue rate and disinfection time. The contamination level calculation module is used to build a 3D model of the medical department, acquire all contamination sources within the medical department, perform bacterial detection on the source release points of contamination sources, and obtain the contamination intensity of each contamination source; it also monitors the location of the corresponding medical devices in real time during use, and calculates the contamination level of the medical devices based on the contamination intensity, the location of the medical devices, and the location of the contamination sources. Irradiation intensity setting module: This module selects the medical device to be disinfected as the device to be tested, retrieves monitoring footage of the device during its use to obtain its current level of contamination, extracts the irradiation intensity corresponding to the target record, and intelligently sets the irradiation intensity for disinfection based on the contamination level of the device.
[0012] Preferably, the calibration point extraction module includes an image frame extraction unit and a calibration point extraction unit; Image frame extraction unit: used to retrieve historical disinfection records of the ultraviolet disinfection device, extract the medical device and disinfection time corresponding to a certain disinfection record, and obtain the corresponding monitoring segment; obtain the area of the medical device in the monitoring segment, as well as the area of the ROI area in the monitoring segment, and extract several image frames; Calibration point extraction unit: used to extract several location points on the medical device, set the initial target value of each location point to 0; based on several image frames, obtain the final target value of each location point, and take the location point with the largest final target value as the calibration point.
[0013] Preferably, the pollution degree calculation module includes a pollution intensity calculation unit and a pollution degree calculation unit; Pollution intensity calculation unit: used to obtain the bacterial density and number of bacterial species for each pollution source, extract the maximum bacterial density and the maximum number of bacterial species, and obtain the pollution intensity of each pollution source; Pollution level calculation unit: used to monitor the location of a medical device corresponding to a target record in real time during use, and to obtain the pollution level of the medical device based on the pollution intensity and location of each pollution source.
[0014] Compared with existing technologies, the beneficial effects of this invention are as follows: This invention provides a production equipment safety management system and method based on big data, including: retrieving historical disinfection records of ultraviolet disinfection devices, retrieving monitoring videos, analyzing the movement of medical devices, and extracting calibration points from the medical devices; extracting the operators of the disinfection records and obtaining the reliability of the disinfection records; obtaining the bacterial residue rate of the calibration points; judging and extracting target records from the disinfection records; acquiring the pollution sources in the medical department, obtaining the pollution intensity of each pollution source, and calculating the pollution degree of the medical devices; acquiring the device to be tested and calculating the current pollution degree, and intelligently setting the irradiation intensity of the device to be tested according to the irradiation intensity of the target record. This invention, by analyzing historical disinfection records and combining calibration points and pollution sources, sets reasonable irradiation intensities, which helps to improve the reliability of medical device disinfection and reduce problems caused by unreasonable disinfection irradiation intensities. Attached Figure Description
[0015] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0016] Figure 1 This is a flowchart illustrating the production equipment safety management method based on big data according to the present invention. Detailed Implementation
[0017] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0018] Example: Figure 1 As shown, this invention provides a technical solution for production equipment safety management based on big data, including the following steps: (1) Retrieve the historical disinfection records of the ultraviolet disinfection device, extract the medical devices and disinfection time corresponding to the disinfection records, retrieve the historical monitoring videos, analyze the movement of medical devices in the medical department, and extract the calibration points in the medical devices.
[0019] Retrieve the historical disinfection records of the ultraviolet disinfection device, extract the medical device X and disinfection time T1 corresponding to a certain disinfection record, obtain the previous disinfection time T0 of medical device X, and retrieve the monitoring segment between disinfection time T0 and disinfection time T1. Medical device X performs its function by contacting the ROI (Region of Interest). The region R of medical device X within the monitoring segment is obtained. X And the ROI region in the monitoring segment, region R ROI , will region R X With region R ROI Let the moment of the first contact be t1. Starting from time t1, search for the region R. X With region R ROI The moment of first separation is designated as t2. Several image frames are extracted from time t1 and time t2. Medical devices manufactured for use in medical departments fall into various categories. For example, when the medical device is forceps, the ROI (Region of Interest) it contacts may include sterile gauze, sutures, or patient body parts. When the medical device is a scalpel, the ROI it contacts may include surgical incision areas or diseased tissue areas. These medical devices need direct contact with the ROI to function, therefore monitoring the bacterial density at the contact points is necessary. This solution establishes calibration points; for example, the calibration point for forceps is the forceps tip, and for a scalpel, it is the blade. Monitoring the bacteria at these calibration points is crucial. These calibration points are key verification points on the medical device used to determine the effectiveness of disinfection. The specific steps for extracting the calibration points are as follows: Extract several location points on medical device X, and set the initial target value of each location point to 0; obtain region R in a certain image frame F. X With region R ROI Overlapping region R F , will be in region R F Increment the target value of the location point within the region by 1; if it is not within region R... F The target value of the location point within remains unchanged; the region R in several image frames is obtained. X With region R ROI The overlapping areas are identified, and the final target value for each location point is obtained. The location point with the largest final target value is then used as the calibration point.
[0020] (2) Extract the operators corresponding to the disinfection records, and obtain the reliability of the disinfection records based on the operators' operating permissions and shift time; measure the change in bacterial density at the calibration point before and after disinfection to obtain the bacterial residue rate; The target records in the disinfection log are judged and extracted based on a combination of reliability, bacterial residue rate, and disinfection duration.
[0021] Extract the operator P and disinfection time T corresponding to a disinfection record G. If the operator P has the authority to use the disinfection device to disinfect the medical device, the first confidence level of the operator P is set to 1. If the operator P does not have the authority to use the disinfection device to disinfect the medical device, the first confidence level of the operator P is set to 0. Obtain the shift time of operator P. If the disinfection time T falls within the shift time, set the second confidence level of operator P to 1. If the disinfection time T does not fall within the shift time, extract the end time S1 of the previous shift and the start time S2 of the next shift to obtain the target duration: D = min(T - S1, S2 - T). Calculate the second confidence level of operator P as e. -D Multiply the first confidence level by the second confidence level to obtain the reliability of the disinfection record G; The target duration D is the minimum of the duration between the end time of the previous shift S1 and the disinfection time T, and the duration between the disinfection time T and the start time of the next shift S2. A larger target duration D indicates a lower second reliability of operator P. Therefore, in this scheme, formula e can be used. -D As a second level of credibility, the first level of credibility is multiplied by the second level of credibility to obtain the reliability. The reliability value ranges from 0 to 1. The higher the reliability, the more reliable the disinfection record G information. By combining the reliability, bacterial residue rate and disinfection time, a reliable target record can be obtained.
[0022] Obtain the bacterial density B1 before disinfection and the bacterial density B2 after disinfection at the calibration point location, and obtain the bacterial residue rate: B2 / B1; if the reliability of the disinfection record G is greater than the preset reliability threshold, the bacterial residue rate is less than the preset ratio threshold, and the disinfection duration is greater than the preset duration threshold, then the disinfection record G is taken as the target record, and all target records are extracted.
[0023] (3) Establish a three-dimensional model of the medical department, obtain all pollution sources in the medical department, conduct bacterial detection on the source release point of the pollution source, and obtain the pollution intensity of each pollution source; monitor the location of the corresponding medical device in real time during use, and calculate the pollution degree of the medical device based on the pollution intensity, the location of the medical device and the location of the pollution source.
[0024] A 3D model of the medical department was created, and all pollution sources within the department were identified and labeled in the 3D model. Bacterial detection was performed at the source release points of the pollution sources to obtain the bacterial density and number of bacterial species for each pollution source. The maximum bacterial density M was then extracted. max and the maximum number of bacterial species N max The pollution intensity of one of the pollution sources s is obtained as: C s =W M ×M s / M max +W N ×N s / N max Among them, W M W is the bacterial density weight. N M represents the weight of the number of bacterial species. sN represents the bacterial density of pollution source s. s Let s be the number of bacterial species in pollution source s, and then the pollution intensity of each pollution source can be obtained; the higher the bacterial density and the more bacterial species, the higher the pollution intensity of the pollution source.
[0025] The location of a medical device Y corresponding to a target record during use is monitored in real time. If there is no source of pollution within a radius of r around the medical device Y at a certain moment, the pollution value V of the medical device Y at that moment is set to 0. If there are pollution sources within a radius of r around the device at a certain moment, based on the condition that the smaller the distance to the pollution source, the larger the pollution weight, the pollution weight of each pollution source is obtained. Based on the pollution weight and pollution intensity of each pollution source, the pollution value V of the medical device Y at a certain moment is obtained; thus, the pollution degree of the medical device Y is obtained as follows: Where Z is the number of time points, and V i Let be the contamination value of medical device Y at time i.
[0026] In this scheme, the sum of the pollution weights of each pollution source is 1. The formula is y = 1 - e^(-1 / 2). -x When x takes the value x>0, y takes the value 0 to 1, and y increases as x increases. Therefore, in this scheme, the more time points there are, the greater the contamination value at each time point, indicating that the bacterial residue on the medical device is more serious, and the degree of contamination of the medical device Y is also greater.
[0027] (4) Take the medical device that needs to be disinfected as the device to be tested, retrieve the monitoring segment of the device to be tested during use, and obtain the current degree of contamination of the device to be tested; extract the irradiation intensity corresponding to the target record, and intelligently set the irradiation intensity for disinfection of the device to be tested according to the degree of contamination of the device to be tested.
[0028] Obtain the previous disinfection time of the device Q to be tested, retrieve the monitoring segment of the time period between the previous disinfection time and the current time, calculate the contamination value of the device Q at each time moment, and obtain the current contamination level L of the device Q. Q ; Based on the current contamination level L of the device Q to be tested Q If the instrument Q to be tested needs to be disinfected, then the contamination level of the medical instrument must be no less than the contamination level L. QThe target records (since the extraction conditions for the target records include a bacterial residue rate less than a preset ratio threshold, the disinfection results of the medical devices in the target records are all qualified), and the minimum irradiation intensity among them is used as the irradiation intensity for disinfecting the device Q to be tested (the minimum irradiation intensity is to prevent excessive irradiation intensity from accelerating the aging of medical device materials and reducing service life). Based on the analysis of historical disinfection records according to this invention, and by comprehensively considering calibration points and contamination sources, a reasonable irradiation intensity is set for the device Q to be tested, which helps to improve the reliability of medical device disinfection and reduce problems caused by unreasonable disinfection irradiation intensity.
[0029] Based on the contamination level of each medical device corresponding to the target record, those with a contamination level not less than contamination level L are selected. Q The minimum irradiation intensity recorded in the target record is used as the irradiation intensity for disinfecting the instrument Q to be tested.
[0030] This embodiment also provides a production equipment safety management system based on big data, including a calibration point extraction module, a target record extraction module, a contamination degree calculation module, and an irradiation intensity setting module. The calibration point extraction module includes an image frame extraction unit and a calibration point extraction unit, and the contamination degree calculation module includes a contamination intensity calculation unit and a contamination degree calculation unit. When the system executes the computer program, it implements the above-mentioned production equipment safety management method based on big data. Since the production equipment safety management method based on big data has been described in detail above, it will not be repeated here.
[0031] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. Furthermore, specific embodiments have been described above. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps described in the claims can be performed in a different order than that shown in the embodiments and still achieve the desired result. Additionally, the processes depicted in the drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.
[0032] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.
[0033] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.
Claims
1. A production machinery safety management method based on big data, characterized in that, Includes the following steps: Retrieve historical disinfection records from the ultraviolet disinfection device, extract the corresponding medical devices and disinfection times from the disinfection records, retrieve historical surveillance videos, analyze the movement of medical devices in the medical department, and extract calibration points from the medical devices. Extract the operators corresponding to the disinfection records, and obtain the reliability of the disinfection records based on the operators' operating permissions and shift times; measure the change in bacterial density at the calibration point before and after disinfection to obtain the bacterial residue rate; The target records in the disinfection log are judged and extracted based on a combination of reliability, bacterial residue rate, and disinfection duration. A three-dimensional model of the medical department is established to obtain all pollution sources within the department. Bacterial detection is performed at the source release points of the pollution sources to obtain the pollution intensity of each pollution source. The location of the corresponding medical devices during use is monitored in real time. Based on the pollution intensity, the location of the medical devices, and the location of the pollution sources, the degree of pollution of the medical devices is calculated. The medical device that needs to be disinfected is selected as the device to be tested. The monitoring footage of the device to be tested during use is retrieved to obtain the current level of contamination. The irradiation intensity corresponding to the target record is extracted, and the irradiation intensity for disinfection of the device to be tested is intelligently set according to the level of contamination.
2. The production equipment safety management method based on big data according to claim 1, characterized in that, Extracting calibration points from medical devices includes the following steps: Retrieve the historical disinfection records of the ultraviolet disinfection device, extract the medical device X and disinfection time T1 corresponding to a certain disinfection record, obtain the previous disinfection time T0 of medical device X, and retrieve the monitoring segment between disinfection time T0 and disinfection time T1. Medical device X performs its function by contacting the ROI (Region of Interest). The region R of medical device X within the monitoring segment is obtained. X And the ROI region in the monitoring segment, region R ROI , will region R X With region R ROI Let the moment of the first contact be t1. Starting from time t1, search for the region R. X With region R ROI The moment of first separation is taken as t2. Several image frames are extracted from time t1 and time t2. Extract several location points on medical device X, and set the initial target value of each location point to 0; obtain region R in a certain image frame F. X With region R ROI Overlapping region R F , will be in region R F Increment the target value of the location point within the region by 1; if it is not within region R... F The target value of the location point within remains unchanged; the region R in several image frames is obtained. X With region R ROI The overlapping areas are identified, and the final target value for each location point is obtained. The location point with the largest final target value is then used as the calibration point.
3. The production equipment safety management method based on big data according to claim 1, characterized in that, The process of identifying and extracting target records from disinfection logs includes the following steps: Extract the operator P and disinfection time T corresponding to a disinfection record G. If the operator P has the authority to use the disinfection device to disinfect the medical device, the first confidence level of the operator P is set to 1. If the operator P does not have the authority to use the disinfection device to disinfect the medical device, the first confidence level of the operator P is set to 0. Obtain the shift time of operator P. If the disinfection time T is within the shift time, set the second confidence level of operator P to 1. If the disinfection time T is not within the shift time, extract the end time S1 of the previous shift and the start time S2 of the next shift to obtain the target duration: D = min(T - S1, S2 - T). Calculate the second confidence level of operator P as e. -D Multiply the first confidence level by the second confidence level to obtain the reliability of the disinfection record G; Obtain the bacterial density B1 before disinfection and the bacterial density B2 after disinfection at the calibration point location, and obtain the bacterial residue rate: B2 / B1; if the reliability of the disinfection record G is greater than the preset reliability threshold, the bacterial residue rate is less than the preset ratio threshold, and the disinfection time is greater than the preset time threshold, then the disinfection record G is taken as the target record, and all target records are extracted.
4. The production machinery safety management method based on big data according to claim 1, characterized in that, Calculating the degree of contamination of medical devices includes the following steps: A 3D model of the medical department was created, and all pollution sources within the department were identified and labeled in the 3D model. Bacterial detection was performed at the source release points of the pollution sources to obtain the bacterial density and number of bacterial species for each pollution source. The maximum bacterial density M was then extracted. max and the maximum number of bacterial species N max The pollution intensity of one of the pollution sources s is obtained as follows: C s =W M ×M s / M max +W N ×N s / N max Among them, W M W is the bacterial density weight. N M represents the weight of the number of bacterial species. s N represents the bacterial density of pollution source s. s Let s be the number of bacterial species in pollution source s, and then the pollution intensity of each pollution source can be obtained; Real-time monitoring of the location of medical device Y corresponding to a target record during use; if there is no source of contamination within a radius of r around medical device Y at a certain moment, then the contamination value V of medical device Y at that moment is taken as 0. If there are pollution sources within a radius of r around a certain moment, based on the condition that the smaller the distance to the pollution source, the greater the pollution weight, the pollution weight of each pollution source is obtained. Based on the pollution weight and pollution intensity of each pollution source, the pollution value V of medical device Y at that moment is obtained; thus, the pollution degree of medical device Y is obtained as follows: Where Z is the number of time points, and V i Let be the contamination value of medical device Y at time i.
5. The production machinery safety management method based on big data according to claim 4, characterized in that, The intelligent setting of the irradiation intensity for disinfecting the instruments to be tested includes the following steps: Obtain the previous disinfection time of the device Q to be tested, retrieve the monitoring segment of the time period between the previous disinfection time and the current time, calculate the contamination value of the device Q at each time moment, and obtain the current contamination level L of the device Q to be tested. Q ; Based on the contamination level of each medical device corresponding to the target record, those with a contamination level not less than contamination level L are selected. Q The minimum irradiation intensity recorded in the target record is used as the irradiation intensity for disinfecting the instrument Q to be tested.
6. A production equipment safety management system, used to execute the production equipment safety management method based on big data as described in any one of claims 1-5, characterized in that, The system includes a calibration point extraction module, a target record extraction module, a pollution degree calculation module, and an irradiation intensity setting module; Calibration point extraction module: used to retrieve historical disinfection records of ultraviolet disinfection devices, extract the medical devices and disinfection time corresponding to the disinfection records, retrieve historical monitoring videos, analyze the movement of medical devices in the medical department, and extract calibration points in the medical devices. Target record extraction module: used to extract the operators corresponding to disinfection records, and obtain the reliability of disinfection records based on the operators' operating permissions and shift time; measure the change in bacterial density at the calibration point before and after disinfection to obtain the bacterial residue rate; and judge and extract target records in disinfection records by combining reliability, bacterial residue rate and disinfection time. The contamination level calculation module is used to build a 3D model of the medical department, acquire all contamination sources within the medical department, perform bacterial detection on the source release points of contamination sources, and obtain the contamination intensity of each contamination source; it also monitors the location of the corresponding medical devices during use in real time, and calculates the contamination level of the medical devices based on the contamination intensity, the location of the medical devices, and the location of the contamination sources. Irradiation intensity setting module: This module selects the medical device to be disinfected as the device to be tested, retrieves monitoring footage of the device during its use to obtain its current level of contamination, extracts the irradiation intensity corresponding to the target record, and intelligently sets the irradiation intensity for disinfection based on the contamination level of the device.
7. The production machinery safety management system according to claim 6, characterized in that, The calibration point extraction module includes an image frame extraction unit and a calibration point extraction unit; Image frame extraction unit: used to retrieve historical disinfection records of the ultraviolet disinfection device, extract the medical device and disinfection time corresponding to a certain disinfection record, and obtain the corresponding monitoring segment; obtain the area of the medical device in the monitoring segment, as well as the area of the ROI region in the monitoring segment, and extract several image frames; Calibration point extraction unit: used to extract several location points on the medical device, set the initial target value of each location point to 0; based on the several image frames, obtain the final target value of each location point, and take the location point with the largest final target value as the calibration point.
8. The production machinery safety management system according to claim 6, characterized in that, The pollution level calculation module includes a pollution intensity calculation unit and a pollution level calculation unit; Pollution intensity calculation unit: used to obtain the bacterial density and number of bacterial species for each pollution source, extract the maximum bacterial density and the maximum number of bacterial species, and obtain the pollution intensity of each pollution source; Pollution level calculation unit: used to monitor the location of a medical device corresponding to a target record in real time during use, and to obtain the pollution level of the medical device based on the pollution intensity and location of each pollution source.