Shared scientific research instrument real-time supervision system based on wireless network

Abstract

The invention relates to a shared scientific research instrument real-time supervision system based on a wireless network, which is applied to a scientific research instrument management device, a control terminal and a plurality of edge terminals are arranged in the device, and the edge terminals correspond to equipment terminals. The system comprises an application approval module used for performing approval based on a device application request of a user to obtain an approval result; the priority evaluation module is used for evaluating the priority of the user according to the grade of the user and the emergency degree of the application project when the approval result is approval; the equipment scheduling module is used for making an equipment scheduling decision according to the priority and the real-time equipment data to obtain a scheduling result; and the real-time supervision module is used for acquiring the use condition of the equipment in real time through the edge terminal and generating supervision reminding information when the use condition of the equipment is different from the scheduling result. According to the system, real-time monitoring and intelligent scheduling of the equipment are realized through the wireless network and the edge terminal, and the use efficiency of the equipment and reasonable configuration of scientific research resources are improved.

Description

Technical Field

[0001] The invention belongs to the field of computer and communication technology, and in particular relates to a real-time monitoring system for shared scientific research instruments based on a wireless network. Background Art

[0002] In the field of scientific research, with the advancement of science and technology and the increasing popularity of the concept of resource sharing, the management and use of scientific research instruments are gradually transforming towards intelligence and efficiency. As an important scientific research resource, the sharing and reasonable scheduling of scientific research instruments are of great significance to scientific research efficiency and resource utilization. However, most traditional scientific research instrument management methods rely on manual approval and simple appointment queuing systems, lacking effective supervision of the real-time status of the equipment. After the user submits the equipment application, the administrator approves it based on the equipment's idleness and the applicant's needs, but often cannot grasp the real-time use status and fault conditions of the equipment and other key information. This method has problems such as long approval cycle and unreasonable allocation of equipment resources. Especially in high-demand or emergency projects, traditional methods often cannot respond flexibly, resulting in the impact on scientific research work, and the efficiency and reliability of equipment use are difficult to guarantee. Summary of the invention

[0003] Based on this, it is necessary to address the above-mentioned technical problems. The purpose of the present invention is to provide an efficient and intelligent real-time supervision system for shared scientific research instruments, which aims to monitor and dispatch scientific research instruments in real time to optimize the resource allocation and utilization efficiency of the equipment, thereby improving the utilization rate of scientific research instruments, reducing resource waste and improving scientific research efficiency.

[0004] In a first aspect, the present application provides a real-time monitoring system for shared scientific research instruments based on a wireless network, characterized in that it is applied to a scientific research instrument management device, in which a control terminal and a plurality of edge terminals are provided, and the edge terminals correspond to the device terminals; the control terminal and the edge terminals communicate via a wireless network;

[0005] The system includes:

[0006] The application approval module is used to approve the device application request based on the user and obtain the approval result. The approval result is used to indicate whether the device application request meets the device use conditions; the device application request includes the type of device applied for, the application usage time and the user identity information;

[0007] The priority assessment module is used to assess the user's priority based on the user's level and the urgency of the application project when the approval result is approved;

[0008] The equipment scheduling module is used to make equipment scheduling decisions based on priority and real-time equipment data to obtain scheduling results; real-time equipment data includes equipment usage information, usage rate, failure frequency, equipment maintenance history and user ratings;

[0009] The real-time monitoring module is used to obtain the equipment usage status in real time through the edge terminal, and generate monitoring reminder information when there is a difference between the equipment usage status and the scheduling result. The equipment usage status includes whether the equipment is turned on and the identity information of the equipment user.

[0010] In one embodiment, the device scheduling module includes:

[0011] A data normalization subunit is used to normalize the priority and the real-time data of the device to obtain normalized data;

[0012] A feature construction subunit is used to construct cross features according to normalized data, wherein the cross features include priority use demand and equipment health stability index;

[0013] The model building subunit is used to build an intelligent scheduling model based on cross-features, scheduling objectives and constraints. The scheduling objectives include maximizing equipment utilization, minimizing user waiting time, maximizing satisfaction of high-priority user needs and ensuring healthy operation of equipment.

[0014] The model solving subunit is used to solve the intelligent scheduling model based on reinforcement learning to obtain the scheduling result.

[0015] In one embodiment, the scheduling target is calculated by the following formula:

[0016]

[0017] Among them, U max Indicates the maximum value of equipment utilization, n indicates the total number of equipment, R i represents the utilization rate of the i-th device, T i represents the available time of the i-th device within the scheduling time period, W min represents the minimum waiting time of users, m represents the number of waiting users, W j represents the waiting time of the jth user, S max represents the maximum value of the satisfaction of high-priority users’ needs, l represents the number of high-priority users, P k represents the priority of the kth high-priority user, A k Indicates the satisfaction degree of the kth high-priority user’s needs, such as whether the user obtains the right to use the device within the expected time. min Indicates the minimum value for ensuring healthy operation of the equipment, H i Represents the health stability index of the i-th device.

[0018] In one of the embodiments, the edge terminal is further configured with a sensor, and the sensor is used to obtain device working data;

[0019] The system also includes a fault warning module for:

[0020] Receive device working data acquired by the edge terminal;

[0021] Build a fault detection model based on the random forest algorithm at the edge terminal;

[0022] Input the equipment working data into the fault detection model to perform fault detection and obtain fault warning information, which includes equipment number, fault type, and fault location;

[0023] The fault warning information is sent to the control terminal, and the fault warning information is used to instruct the control terminal to optimize the scheduling result according to the fault warning information to obtain the optimized scheduling result.

[0024] In one embodiment, the system further includes a sharing evaluation module for obtaining scientific research results after the user uses the device, and the scientific research results include the completion status of the scientific research project;

[0025] Used to calculate maintenance status indicators based on the historical usage of the equipment; historical usage includes failure frequency, equipment maintenance duration, and equipment maintenance cost;

[0026] It is used to calculate the comprehensive score of equipment sharing based on scientific research results, maintenance status indicators and user feedback. The comprehensive score of equipment sharing is used to manage equipment.

[0027] In one of the embodiments, the system further includes an equipment layout optimization module for obtaining a laboratory space model and an equipment model;

[0028] It is used to simulate different layouts of the equipment model in the laboratory space model and evaluate the different layouts to obtain evaluation indicators, including space adaptability evaluation results, operation process consistency evaluation results and equipment utilization efficiency evaluation results;

[0029] Used to select the optimal equipment layout solution based on evaluation indicators.

[0030] In one embodiment, the calculation formula of the operation process consistency evaluation result is:

[0031]

[0032] Among them, C op (t) represents the consistency score of the operation process under layout t, w ij represents the operation coherence weight between device i and device j, n represents the total number of devices, d ij (t) represents the distance between device i and device j under layout t, and t represents the number of the device layout, which is used to distinguish different device layout schemes.

[0033] In a second aspect, the present invention also provides a real-time monitoring method for shared scientific research instruments based on a wireless network, which is applied to a scientific research instrument management device, wherein a control terminal and a plurality of edge terminals are provided in the scientific research instrument management device, and the edge terminals correspond to the device terminals; the control terminal and the edge terminals communicate via a wireless network;

[0034] Methods include:

[0035] Approval is performed based on the user's device application request to obtain an approval result, which is used to indicate whether the device application request meets the device use conditions; the device application request includes the type of device applied for, the application usage duration, and the user identity information;

[0036] When the approval result is approved, the user's priority is evaluated based on the user's level and the urgency of the application project;

[0037] Make equipment scheduling decisions based on priority and real-time equipment data to obtain scheduling results; real-time equipment data includes equipment usage information, usage rate, failure frequency, equipment maintenance history, and user ratings;

[0038] The device usage status is obtained in real time through the edge terminal. The device usage status includes whether the device is turned on and the identity information of the device user.

[0039] In a third aspect, the present invention further provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps of the real-time monitoring system for shared scientific research instruments of any one of the first aspects are implemented.

[0040] In a fourth aspect, the present invention further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the real-time monitoring system for shared scientific research instruments of any one of the first aspects.

[0041] The above-mentioned real-time monitoring system, method, computer equipment and storage medium for shared scientific research instruments based on a wireless network, through the application approval module, approves the equipment application request submitted by the user, and evaluates whether the equipment application meets the use conditions, thereby ensuring the reasonable allocation of equipment resources. The equipment application request includes the equipment type, usage time and user identity information. The approval result is used to determine whether the application is approved, thereby providing a basis for equipment scheduling. After approval, the system evaluates the user's usage priority according to the user's level and the urgency of the application project through the priority evaluation module to ensure that high-priority needs can be met in a timely manner.

[0042] Secondly, based on the real-time data and priority of the equipment, the equipment scheduling module can make scientific equipment scheduling decisions. The scheduling results comprehensively consider key data such as equipment usage information, usage rate, failure frequency, equipment maintenance history, and user ratings to achieve optimal utilization of equipment resources. The real-time supervision module obtains the equipment usage status in real time through the edge terminal, monitors whether the equipment is operating normally, and compares the difference between the actual equipment usage and the scheduling results. When the equipment does not operate according to the scheduling results, the system will promptly generate supervision reminder information to notify relevant personnel to intervene.

[0043] Compared with traditional scientific research instrument management systems, this system can accurately grasp the use of equipment and perform dynamic scheduling through wireless network technology and real-time data feedback. And through the system's priority evaluation and scheduling decision-making mechanism, it ensures the efficient use of equipment resources and reduces scientific research delays caused by improper equipment use or unreasonable resource allocation. Through the intelligent monitoring and difference reminder functions of the real-time supervision module, the system effectively improves the transparency and response speed of equipment management, which not only improves the utilization efficiency of scientific research resources, but also enhances the intelligent level of equipment management. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the related technologies, the drawings required for use in the embodiments or the related technical descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0045] Figure 1 A schematic diagram of a real-time monitoring system for shared scientific research instruments based on a wireless network is provided as an exemplary embodiment of the present invention;

[0046] Figure 2 A flow chart of a real-time monitoring method for shared scientific research instruments based on a wireless network is provided as an exemplary embodiment of the present invention. DETAILED DESCRIPTION

[0047] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0048] In one embodiment, Figure 1As shown, a real-time monitoring system for shared scientific research instruments based on a wireless network is provided. This embodiment takes the application of the system to a scientific research instrument management device as an example. The scientific research instrument management device is provided with a control terminal and multiple edge terminals. The edge terminal corresponds to the device terminal, and the control terminal and the edge terminal communicate through a wireless network. In this embodiment, Figure 1 As shown, the system 100 includes:

[0049] The application approval module 101 is used to approve the device application request based on the user and obtain the approval result.

[0050] Specifically, after receiving the user's equipment application request, the application approval module 101 can approve the application according to the information such as the application equipment type, application usage time and user identity information in the request, and then obtain the approval result, which is used to characterize whether the equipment application request meets the equipment usage conditions. For example, if a user applies to use a high-precision spectrometer for 5 hours, the system will consider factors such as the current use arrangement of the spectrometer and the identity of the user (such as whether he has the qualifications to operate the equipment) to determine whether to approve his application. This process can be automatically approved by the preset approval rules. Once the module completes the approval, the system can automatically feedback the approval result to the user, including approval, rejection or suggestions for adjusting the application conditions. If the approval result is approval, the system will generate an appointment confirmation and equipment scheduling information through the priority evaluation module 102 and the equipment scheduling module 103; if the approval result is rejection, the system will give the reason for rejection and may provide the option of re-application. Through this module, the reasonable allocation of equipment resources is ensured, the excessive use or abuse of equipment is avoided, and the normal operation and maintenance of equipment are guaranteed.

[0051] The priority evaluation module 102 is used to evaluate the priority of the user according to the user's level and the urgency of the application project when the approval result is approved.

[0052] When the approval result of the application approval module 101 is passed, the priority evaluation module 102 can evaluate the user's priority according to the user's level and the urgency of the application project. The user level can be determined based on the user's authority and identity level, and can be a numerical value or a level identifier. The urgency of the application project can be quantified by level classification or specific numerical values. Furthermore, the user's priority can be obtained by setting weights based on the user's level and the urgency of the application project. For example, a senior researcher with a high user level, the scientific research project he is responsible for is approaching the deadline, and the application project has a high urgency, then he will get a higher priority when using approved equipment; while a graduate student with a relatively low user level will have a lower priority for non-urgent projects.

[0053] The device scheduling module 103 is used to make device scheduling decisions based on priorities and real-time data of devices to obtain scheduling results.

[0054] Schematically, the real-time data of the equipment may include the use information, use rate, failure frequency, equipment maintenance history and user rating of the equipment. Equipment use information generally refers to the current use status of the equipment, including whether the equipment is working, the nature of the current task and the workload of the remaining tasks. The use rate refers to the ratio of the actual working time of the equipment to the total available time within a period of time, which can reflect the load of the equipment and help determine whether the equipment is overloaded or idle. The failure frequency refers to the frequency of equipment failures, which can reflect the reliability of the equipment. The equipment maintenance history can reveal the health of the equipment and whether there is a potential need for maintenance. The user rating refers to the feedback from the user after sharing or renting the equipment, which can be used as an important indicator of equipment availability or satisfaction. Through this information, the most suitable equipment can be selected for scheduling according to the user's priority and user needs to obtain the scheduling result. Schematically, this process can generate multiple scheduling plans through genetic algorithms or particle swarm optimization algorithms, and solve to obtain the optimal scheduling plan, that is, the scheduling result. The equipment scheduling module 103 can make intelligent and dynamic equipment scheduling decisions by comprehensively considering the real-time data and priority of the equipment. This decision can not only improve the use efficiency of the equipment and reduce the risk of failure, but also maximize user satisfaction, thereby achieving the optimal configuration of resources.

[0055] The real-time monitoring module 104 is used to obtain the equipment usage status in real time through the edge terminal, and generate monitoring reminder information when there is a difference between the equipment usage status and the scheduling result.

[0056] Specifically, the equipment usage status may include information such as whether the equipment is powered on and the identity information of the equipment user. The edge terminal refers to the distributed equipment in the system, which is close to the data source, that is, the equipment itself, for data collection and preliminary processing. The control terminal is usually a central management system used to monitor the operation of the entire equipment group or production line. The edge terminal can monitor the current, temperature, speed and other parameters of the equipment to confirm whether the equipment is in the power-on state. If the equipment is not powered on as planned or not started within the planned time, the system should be able to capture and mark it as abnormal in real time. In addition, the identity information of the current user of the equipment can be obtained at the edge terminal through identity authentication systems such as RFID cards, QR code scanning, fingerprint recognition, etc., to ensure the correct use and legal authorization of the equipment. When it is found that the actual equipment usage status is inconsistent with the scheduled scheduling results, a regulatory reminder message is generated to assist relevant personnel in intervening or processing according to the automation mechanism. This module can not only ensure that the equipment is used efficiently and reasonably according to the scheduled plan, but also timely discover potential problems and take corresponding countermeasures, which helps to improve the transparency and efficiency of equipment management.

[0057] The system is divided into four main modules. First, the application approval module 101 approves the equipment application request submitted by the user, comprehensively considers the type of equipment applied for, the length of use and the identity information of the user, and obtains the approval result. This process helps to promote the orderly progress of scientific research and ensure the safety and normal use of equipment. In the priority evaluation module 102, when the approval result is passed, the system can evaluate the user's priority according to the user level and the urgency of the project, so as to ensure that high-priority users can use the equipment first when necessary. Secondly, the equipment scheduling module 103 makes equipment scheduling decisions based on the evaluated priority and real-time data of the equipment, such as real-time dynamic information such as equipment usage information, usage rate and failure frequency, to obtain the final result of equipment scheduling. This module optimizes the resource allocation of equipment through real-time data monitoring and intelligent scheduling, ensuring that the equipment meets scientific research needs to the greatest extent.

[0058] Finally, the real-time monitoring module 104 obtains the usage status of the equipment in real time through the edge terminal, and generates a monitoring reminder message when the actual usage status of the equipment differs from the scheduling result. The usage status of the equipment includes whether the equipment is turned on and the identity information of the equipment user, ensuring the reasonable use of the equipment and timely feedback, further improving the accuracy and response speed of equipment management.

[0059] Through the collaborative work of the above four modules, the system can efficiently manage the shared use of scientific research instruments, optimize resource allocation, ensure the rational scheduling and efficient use of equipment, and at the same time enhance the transparency and supervision of equipment use through real-time supervision, thereby improving the level of intelligent management of shared scientific research instruments, reducing resource waste, and effectively promoting the smooth progress of scientific research activities.

[0060] In one embodiment, the device scheduling module includes:

[0061] A data normalization subunit is used to normalize the priority and the real-time data of the device to obtain normalized data;

[0062] A feature construction subunit is used to construct cross features according to normalized data, wherein the cross features include priority use demand and equipment health stability index;

[0063] The model building subunit is used to build an intelligent scheduling model based on cross-features, scheduling objectives and constraints. The scheduling objectives include maximizing equipment utilization, minimizing user waiting time, maximizing satisfaction of high-priority user needs and ensuring healthy operation of equipment.

[0064] The model solving subunit is used to solve the intelligent scheduling model based on reinforcement learning to obtain the scheduling result.

[0065] Since the user's priority and the real-time data of equipment in different dimensions may have different numerical ranges and dimensions, the data normalization subunit is first used to uniformly process these data with different characteristics and convert them into a specific, standard range to obtain normalized data, so as to eliminate the impact of differences in dimensions and other factors between the data. Secondly, based on the normalized data, the feature construction subunit is used to further mine and construct more representative cross-features. Cross-features refer to the combination of two or more variables to produce new and more identifiable features. Among them, the feature of priority use demand comprehensively considers multiple factors such as the user's priority and the current use status of the equipment, and can intuitively reflect the urgency of a user to use the equipment. The equipment health and stability index integrates information such as the equipment's failure frequency and maintenance history, and can measure the current health status and operational stability of the equipment. Compared with the original data, these cross-features help the model to more accurately understand the working status of the equipment and the needs of the user, so as to make more reasonable scheduling decisions.

[0066] Through the model building subunit, an intelligent scheduling model can be constructed according to the cross-features, scheduling objectives and constraints. The scheduling objectives include maximizing equipment utilization, minimizing user waiting time, maximizing the satisfaction of high-priority user needs and ensuring the healthy operation of equipment. At the same time, these objectives must be optimized under certain constraints, such as equipment availability, equipment health, and maintenance time. After the model is built, the intelligent scheduling model can be solved based on reinforcement learning through the model solving subunit. Reinforcement learning is a machine learning method that mainly improves the decision-making process by interacting with the environment, finds the optimal strategy, and then obtains the scheduling results. Through this process, the model's adaptability, decision-making accuracy and efficiency can be effectively improved, equipment overuse can be avoided, multi-objective scheduling can be optimized, and manual intervention can be reduced, making the system more flexible and intelligent in complex scheduling tasks.

[0067] In one embodiment, the scheduling target is calculated by the following formula:

[0068]

[0069]

[0070] Among them, U max Indicates the maximum value of equipment utilization, n indicates the total number of equipment, R i represents the utilization rate of the i-th device, T i represents the available time of the i-th device within the scheduling time period, W min represents the minimum waiting time of users, m represents the number of waiting users, W j represents the waiting time of the jth user, S max represents the maximum value of the satisfaction of high-priority users’ needs, l represents the number of high-priority users, P k represents the priority of the kth high-priority user, A k Indicates the satisfaction degree of the kth high-priority user’s needs, such as whether the user obtains the right to use the device within the expected time. min Indicates the minimum value for ensuring healthy operation of the equipment, H i Represents the health stability index of the i-th device.

[0071] In the above formula, the utilization rate of each device R i Multiply it by its available time T i Then, the total utilization of all devices is summed up to obtain the maximum utilization of all devices in the scheduling time period, U max .W jrepresents the waiting time of the jth user, which means the time it takes for the user to actually obtain the right to use the device from submitting the device application. It can be obtained by summing the waiting time W of all waiting users. j Sum the sum and minimize the sum by optimizing the scheduling strategy to minimize the user waiting time W min . This can be done by setting the priority level P of each high-priority user k A k Multiply them, and then sum all high-priority users to get the maximum value S of the high-priority user demand satisfaction. max .H i represents the health stability index of the i-th device, which takes into account factors such as the failure frequency and maintenance history of the device. The health stability index H of each device can be calculated by i Its available time T i Multiply them, and then sum all the devices to get the comprehensive situation of healthy operation guarantee of all devices in the scheduling time period. The goal is to minimize this value, that is, to ensure the healthy operation of the equipment H min These formulas define the goals of equipment scheduling from different aspects, and aim to build a scientific and reasonable equipment scheduling strategy by comprehensively considering equipment utilization, user waiting time, satisfaction of high-priority user needs, and equipment healthy operation guarantee.

[0072] In one of the embodiments, the edge terminal is further configured with a sensor, and the sensor is used to obtain device working data;

[0073] The system also includes a fault warning module for:

[0074] Receive device working data acquired by the edge terminal;

[0075] Build a fault detection model based on the random forest algorithm at the edge terminal;

[0076] Input the equipment working data into the fault detection model to perform fault detection and obtain fault warning information, which includes equipment number, fault type, and fault location;

[0077] The fault warning information is sent to the control terminal, and the fault warning information is used to instruct the control terminal to optimize the scheduling result according to the fault warning information to obtain the optimized scheduling result.

[0078] Specifically, the sensors equipped on the edge terminal can monitor various state parameters of the equipment, such as temperature, vibration frequency, pressure, speed, etc., to reflect the equipment's operating status, environmental conditions, workload and other information. And by using the random forest algorithm in the edge terminal to build a fault detection model, analyze the acquired equipment working data, and determine whether the equipment is in a fault state. Random forest is an integrated learning method that improves the accuracy of model prediction by combining multiple decision trees. Based on the equipment working data training model, it can learn the relationship between different working states and potential faults. Finally, the model outputs fault warning information, which may include equipment number, fault type, and fault location, so that relevant personnel can perform maintenance. And the fault warning information is sent to the control terminal of the system to optimize and adjust the equipment scheduling results, such as re-making equipment scheduling decisions. This module not only greatly improves the efficiency and reliability of equipment maintenance through edge computing, fault prediction maintenance and equipment scheduling optimization, but also reduces the risk of failure and maintenance costs, further improves the prediction accuracy and scheduling optimization capabilities, and promotes the development of equipment sharing management in a more efficient and intelligent direction.

[0079] In one embodiment, the system further includes a sharing evaluation module for:

[0080] Obtain the scientific research results of users after using the equipment, including the completion status of scientific research projects;

[0081] Calculate maintenance status indicators based on the historical usage of the equipment; historical usage includes failure frequency, equipment maintenance time, and equipment maintenance cost;

[0082] The comprehensive score of equipment sharing is calculated based on scientific research results, maintenance status indicators and user feedback, and is used to manage equipment.

[0083] Indicatively, scientific research results refer to the scientific research progress or research results achieved by users in the process of using equipment, including the completion of scientific research projects, such as the completion of scientific research projects, the publication of research papers, the collection and analysis of experimental data, etc. These results can not only reflect the use effect of the equipment, but also provide important reference value for future equipment sharing. And by calculating the maintenance status index based on the historical use of the equipment, such as failure frequency, equipment maintenance time and equipment maintenance cost, it is used to measure the maintenance level and reliability of the equipment. User feedback refers to the user's evaluation of the equipment's use experience, performance, ease of use, and maintenance convenience. This feedback helps the system understand the performance of the equipment in actual operation and make further optimization decisions on the management of the equipment. Combining these data from different dimensions, a comprehensive score, namely the equipment sharing comprehensive score, can be calculated through a certain weighted algorithm or scoring model. This score can fully reflect the comprehensive performance of the equipment and help equipment managers make more appropriate decisions, such as deciding whether the equipment needs to be repaired, upgraded or eliminated. Through this evaluation system, managers can efficiently evaluate the performance of the equipment, reasonably allocate resources, improve the efficiency of equipment use and maintenance, and at the same time improve user satisfaction and the overall operational efficiency of the equipment.

[0084] In one of the embodiments, the system further includes an equipment layout optimization module for obtaining a laboratory space model and an equipment model;

[0085] It is used to simulate different layouts of the equipment model in the laboratory space model and evaluate the different layouts to obtain evaluation indicators, including space adaptability evaluation results, operation process consistency evaluation results and equipment utilization efficiency evaluation results;

[0086] Used to select the optimal equipment layout solution based on evaluation indicators.

[0087] The laboratory space model can reflect the physical space layout of the laboratory, including information such as the size, structure and channels of the room. The equipment model refers to the attribute information of various equipment used in the laboratory, including the size, function, weight, usage, etc. of the equipment, including the physical characteristics and working requirements of each equipment. After obtaining the laboratory space and equipment information, the system can simulate the relative position and arrangement of different equipment and schedule multiple layout plans. The evaluation indicators are obtained by evaluating the spatial adaptability, operation process consistency and equipment utilization efficiency of the layout plan.

[0088] Specifically, the spatial adaptability assessment is an assessment of whether the equipment is reasonably placed in the laboratory space, such as whether there is any waste of space and whether the equipment can adapt to the space limitations of the laboratory. The operational process consistency assessment is an assessment of the impact of the equipment layout on the laboratory operation process, such as whether the equipment is easy to coordinate operations, whether the staff can move efficiently between the various equipment when performing experimental operations, and whether unnecessary walking or equipment adjustments can be reduced. The equipment utilization efficiency assessment is an assessment of the efficiency of equipment utilization, such as the accessibility of the equipment, whether bottlenecks or conflicts in equipment use are avoided, etc. The optimal equipment layout plan can be selected by considering the weights of different results in the evaluation indicators. This module can select the most appropriate equipment layout plan based on the actual needs of the laboratory through layout simulation and multi-dimensional evaluation, which helps to optimize laboratory design, improve work efficiency and the safety of experimental operations.

[0089] In one embodiment, the calculation formula of the operation process consistency evaluation result is:

[0090]

[0091] Among them, C op (t) represents the consistency score of the operation process under layout t, w ij represents the operation coherence weight between device i and device j, n represents the total number of devices, d ij (t) represents the distance between device i and device j under layout t, and t represents the number of the device layout, which is used to distinguish different device layout schemes.

[0092] The above formula is a double summation formula. It traverses all devices through the outer summation and considers each device as the starting device in turn. When a device number is determined, it enters the inner summation, starting from the selected device number and ending at n, considering the operation process continuity relationship between the device and all devices with numbers greater than the device. ij (t) represents the distance between equipment i and equipment j under layout t. This distance can be a physical distance, such as the actual spatial distance between equipment in a laboratory or factory, or a logical distance in the operation process, such as the number of steps required to complete the equipment operation and start the equipment operation. This formula can quantitatively evaluate the operation process consistency under a specific equipment layout by comprehensively considering the operation consistency weight and distance between equipment. And by changing the equipment layout, the consistency scores under different layout schemes can be compared, so as to select the equipment layout that is most conducive to the smooth operation process.

[0093] Based on the same inventive concept, Figure 2As shown, the embodiment of the present application also provides a real-time monitoring method for shared scientific research instruments based on a wireless network, which is applied to a scientific research instrument management device, in which a control terminal and multiple edge terminals are provided, and the edge terminals correspond to the device terminals; the control terminal and the edge terminals communicate through a wireless network;

[0094] The method includes:

[0095] S101: Approving the device application request of the user to obtain an approval result, which is used to indicate whether the device application request meets the device use conditions; the device application request includes the type of device applied for, the application duration, and the user identity information;

[0096] S102: When the approval result is approved, the user's priority is evaluated according to the user's level and the urgency of the application project;

[0097] S103: Make equipment scheduling decisions based on the priority and real-time equipment data to obtain scheduling results; the real-time equipment data includes equipment usage information, usage rate, failure frequency, equipment maintenance history and user ratings;

[0098] S104: Obtain device usage status in real time through the edge terminal, where the device usage status includes whether the device is powered on and the identity information of the device user.

[0099] In the above-mentioned real-time supervision method of shared scientific research instruments based on wireless networks, first, the application request for user equipment is approved, and the approval result reflects whether the application meets the conditions for equipment use. This process provides a strong guarantee for the reasonable sharing and use of equipment and the smooth progress of scientific research. If the equipment application request is approved, the user's priority will be further evaluated according to the user level and the urgency of the application project. This priority evaluation can give priority to meeting high-priority scientific research needs, thereby improving the efficiency of equipment use and optimizing resource allocation, and providing a decision-making basis for subsequent equipment scheduling. And make equipment scheduling decisions by integrating user priorities and real-time data of equipment. Real-time data of equipment includes equipment usage information, usage rate, failure frequency, equipment maintenance history and user rating. This information helps the scientific research instrument management system make more accurate scheduling decisions, thereby effectively improving equipment utilization, reducing equipment idle rate, and ensuring that equipment maintenance and use are reasonably monitored.

[0100] In addition, the edge terminal can obtain the device usage status in real time, including whether the device is turned on and the identity information of the device user. This information is fed back to the control terminal in real time, which helps to continuously grasp the actual operating status of the device and ensure that the use of the device is more transparent and controllable. Through this wireless network communication and real-time monitoring, the shared use of scientific research instruments becomes more efficient and standardized, and it can also effectively prevent the abuse or misuse of the equipment.

[0101] Compared with traditional scientific research instrument management methods, this method provides a more intelligent and precise scientific research instrument management method through wireless network communication, real-time data analysis of equipment and real-time monitoring of edge terminals. The combination of these technologies not only improves the efficiency of equipment use and management transparency, but also provides researchers with a more convenient and fair equipment use experience, and promotes the efficient sharing and utilization of scientific research resources.

[0102] Furthermore, the equipment scheduling decision is made based on the priority and real-time data of the equipment, and the scheduling results include:

[0103] Normalize the priority and the real-time data of the device to obtain normalized data;

[0104] Construct cross-features based on normalized data, including priority use demand and equipment health stability index;

[0105] The model building subunit is used to build an intelligent scheduling model based on cross-features, scheduling objectives and constraints. The scheduling objectives include maximizing equipment utilization, minimizing user waiting time, maximizing satisfaction of high-priority user needs and ensuring healthy operation of equipment.

[0106] The model solving subunit is used to solve the intelligent scheduling model based on reinforcement learning to obtain the scheduling result.

[0107] Furthermore, the scheduling target is calculated by the following formula:

[0108]

[0109]

[0110] Among them, U max Indicates the maximum value of equipment utilization, n indicates the total number of equipment, R i represents the utilization rate of the i-th device, T i represents the available time of the i-th device within the scheduling time period, W min represents the minimum waiting time of users, m represents the number of waiting users, W j represents the waiting time of the jth user, S maxrepresents the maximum value of the satisfaction of high-priority users’ needs, l represents the number of high-priority users, P k represents the priority of the kth high-priority user, A k Indicates the satisfaction degree of the kth high-priority user’s needs, such as whether the user obtains the right to use the device within the expected time. min Indicates the minimum value for ensuring healthy operation of the equipment, H i Represents the health stability index of the i-th device.

[0111] Furthermore, in the method, the edge terminal is also configured with a sensor, and the sensor is used to obtain device working data, and further includes:

[0112] Receive device working data acquired by the edge terminal;

[0113] Build a fault detection model based on the random forest algorithm at the edge terminal;

[0114] Input the equipment working data into the fault detection model to perform fault detection and obtain fault warning information, which includes equipment number, fault type, and fault location;

[0115] The fault warning information is sent to the control terminal, and the fault warning information is used to instruct the control terminal to optimize the scheduling result according to the fault warning information to obtain the optimized scheduling result.

[0116] Furthermore, the method also includes:

[0117] Obtain the scientific research results of users after using the equipment, including the completion status of scientific research projects;

[0118] Calculate maintenance status indicators based on the historical usage of the equipment; historical usage includes failure frequency, equipment maintenance time, and equipment maintenance cost;

[0119] The comprehensive score of equipment sharing is calculated based on scientific research results, maintenance status indicators and user feedback, and is used to manage equipment.

[0120] Further, the method includes:

[0121] Obtain laboratory space models and equipment models;

[0122] The equipment model is simulated in different layouts in the laboratory space model, and different layouts are evaluated to obtain evaluation indicators, including space adaptability evaluation results, operation process consistency evaluation results, and equipment utilization efficiency evaluation results;

[0123] According to the evaluation indicators, the optimal equipment layout solution is selected.

[0124] Furthermore, the calculation formula for the operation process consistency evaluation result is:

[0125]

[0126] Among them, C op (t) represents the consistency score of the operation process under layout t, w ij represents the operation coherence weight between device i and device j, n represents the total number of devices, d ij (t) represents the distance between device i and device j under layout t, and t represents the number of the device layout, which is used to distinguish different device layout schemes.

[0127] In an exemplary embodiment, the present invention further provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps of a real-time monitoring system for shared scientific research instruments based on a wireless network in the present application are implemented. A multi-core processor is preferred to improve the parallel processing capability of the system. Memory: Provides sufficient temporary storage space to support the operation of the program and the processing of data. The memory capacity should be large enough to accommodate a large amount of supply information and computing tasks.

[0128] In an exemplary embodiment, the present invention further provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps of a real-time monitoring system for shared scientific research instruments based on a wireless network in the present application are implemented. The computer-readable storage medium may include: a read-only memory (ROM), a random access memory (RAM), a solid-state drive (SSD), or an optical disk, etc. Among them, the random access memory may include a resistance random access memory (ReRAM) and a dynamic random access memory (DRAM).

[0129] The above-mentioned embodiments only express several implementation methods of the embodiments of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the patent of the embodiments of the present application. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the embodiments of the present application, and these all belong to the protection scope of the embodiments of the present application.

Claims

1. A real-time monitoring system for shared scientific research instruments based on wireless networks, characterized in that: Applied to a scientific research instrument management device, the scientific research instrument management device is provided with a control terminal and multiple edge terminals, the edge terminal corresponds to the device end; the control terminal and the edge terminal communicate through a wireless network; The system comprises: An application approval module is used to approve the device application request based on the user and obtain an approval result, wherein the approval result is used to indicate whether the device application request meets the device use conditions; the device application request includes the type of device applied for, the application use time and the user identity information; A priority evaluation module, used to evaluate the priority of the user according to the user's level and the urgency of the application project when the approval result is approved; An equipment scheduling module, used to make equipment scheduling decisions based on the priority and real-time equipment data to obtain scheduling results; the real-time equipment data includes equipment usage information, usage rate, failure frequency, equipment maintenance history and user ratings; The real-time monitoring module is used to obtain the device usage status in real time through the edge terminal and generate monitoring reminder information when there is a difference between the device usage status and the scheduling result. The device usage status includes whether the device is turned on and the identity information of the device user.

2. The real-time monitoring system for shared scientific research instruments according to claim 1 is characterized in that: The device scheduling module includes: A data normalization subunit, used for normalizing the priority and the real-time data of the device to obtain normalized data; A feature construction subunit, used to construct cross features according to the normalized data, wherein the cross features include a priority use demand degree and a device health stability index; A model building subunit, for building an intelligent scheduling model based on the cross-features, scheduling objectives and constraints, wherein the scheduling objectives include maximizing equipment utilization, minimizing user waiting time, maximizing satisfaction of high-priority user needs and ensuring healthy operation of equipment; The model solving subunit is used to solve the intelligent scheduling model based on reinforcement learning to obtain the scheduling result.

3. The real-time monitoring system for shared scientific research instruments according to claim 2 is characterized in that: The scheduling target is calculated by the following formula: Among them, U max Indicates the maximum value of equipment utilization, n indicates the total number of equipment, R i represents the utilization rate of the i-th device, T i represents the available time of the i-th device within the scheduling time period, W min represents the minimum waiting time of users, m represents the number of waiting users, W j represents the waiting time of the jth user, S max represents the maximum value of the satisfaction of high-priority users’ needs, l represents the number of high-priority users, P k represents the priority of the kth high-priority user, A k Indicates the satisfaction degree of the kth high-priority user’s needs, such as whether the user obtains the right to use the device within the expected time. min Indicates the minimum value for ensuring healthy operation of the equipment, H i Represents the health stability index of the i-th device.

4. The real-time monitoring system for shared scientific research instruments according to claim 1 is characterized in that: The edge terminal is also configured with a sensor, and the sensor is used to obtain device working data; The system also includes a fault warning module, which is used to: Receiving device working data acquired by the edge terminal; Building a fault detection model based on a random forest algorithm at the edge terminal; Inputting the equipment working data into the fault detection model to perform fault detection and obtain fault warning information, wherein the fault warning information includes equipment number, fault type, and fault location; The fault warning information is sent to the control terminal, and the fault warning information is used to instruct the control terminal to optimize the scheduling result according to the fault warning information to obtain an optimized scheduling result.

5. The real-time monitoring system for shared scientific research instruments according to claim 1 is characterized in that: The system also includes a sharing evaluation module for obtaining the scientific research results of the user after using the device, and the scientific research results include the completion status of the scientific research project; Used to calculate the maintenance status index based on the historical usage of the equipment; the historical usage includes the failure frequency, equipment maintenance duration and equipment maintenance cost; It is used to calculate according to the scientific research results, the maintenance status indicators and user feedback to obtain a comprehensive equipment sharing score, and the comprehensive equipment sharing score is used to manage the equipment.

6. The real-time monitoring system for shared scientific research instruments according to claim 1 is characterized in that: The system also includes an equipment layout optimization module for obtaining a laboratory space model and an equipment model; Used to simulate different layouts of the equipment model in the laboratory space model, and evaluate the different layouts to obtain evaluation indicators, wherein the evaluation indicators include space adaptability evaluation results, operation process consistency evaluation results, and equipment use efficiency evaluation results; Used to select the optimal equipment layout solution according to the evaluation index.

7. The real-time monitoring system for shared scientific research instruments according to claim 6 is characterized in that: The calculation formula for the operation process consistency evaluation result is: Among them, C op (t) represents the consistency score of the operation process under layout t, w ij represents the operation coherence weight between device i and device j, n represents the total number of devices, d ij (t) represents the distance between device i and device j under layout t, and t represents the number of the device layout, which is used to distinguish different device layout schemes.

8. A real-time monitoring method for shared scientific research instruments based on a wireless network, characterized in that: Applied to a scientific research instrument management device, the scientific research instrument management device is provided with a control terminal and multiple edge terminals, the edge terminal corresponds to the device end; the control terminal and the edge terminal communicate through a wireless network; The method comprises: Approving the device application request based on the user, and obtaining an approval result, wherein the approval result is used to indicate whether the device application request meets the device use conditions; the device application request includes the type of device applied for, the application use duration, and the user identity information; When the approval result is approved, the user's priority is evaluated according to the user's level and the urgency of the application project; Make equipment scheduling decisions based on the priority and real-time equipment data to obtain scheduling results; the real-time equipment data includes equipment usage information, usage rate, failure frequency, equipment maintenance history and user ratings; The device usage status is obtained in real time through the edge terminal, and the device usage status includes whether the device is turned on and the identity information of the device user.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the real-time monitoring system for shared scientific research instruments described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the real-time monitoring system for shared scientific research instruments described in any one of claims 1 to 7 are implemented.

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