Information system and method for closed loop management of device service orders

Abstract

The application relates to the technical field of information systems, and particularly discloses an information system and a device service work order closed-loop management system and method, wherein after receiving a work order order by the double closed-loop linkage module of the system, the work order order is checked and processed based on preset audit rules; if the work order order passes the check, the work order order is confirmed to be received and is synchronized to an operation and maintenance interaction module; if the work order order fails the check, the work order order is rejected, and a rejection reason log is generated and fed back to an information system module; the information system module re-generates the work order order; the double closed-loop linkage module judges whether new abnormal data is monitored according to operation data and order process information; if new abnormal data is monitored, a processing suggestion is obtained by analyzing the new abnormal data; the work order order is updated according to the processing suggestion, and the updated work order order is synchronized to the operation and maintenance interaction module and the information system module. In this way, the operation and maintenance efficiency can be improved.

Description

Technical Field

[0001] This invention relates to the field of information system technology, and in particular to a closed-loop management system and method for information system and equipment service work orders. Background Technology

[0002] In the field of information system and equipment operation and maintenance management, closed-loop work order management is a core component to ensure stable system operation. It primarily achieves full-process control over equipment anomalies through a process of generating fault work orders, dispatching maintenance tasks, and providing feedback on processing results. With the popularization of information technology, the scale of information systems is constantly expanding, and the number of distributed device nodes is surging, placing higher demands on the efficiency, accuracy, and closed-loop integrity of work order management.

[0003] Currently, most work order management systems adopt a single closed-loop model, relying solely on information systems to trigger work orders or on feedback from maintenance personnel, which has significant shortcomings. For example, Chinese patent application CN111126777A discloses an intelligent work order processing method, focusing on work order type confirmation, priority matching, engineer selection, and progress updates. This achieves a basic closed loop of work order generation, dispatch, and completion feedback, using work order processing status to characterize engineer capabilities. However, all equipment anomalies require triggering work orders and dispatching engineers for processing, making it impossible to resolve small-scale, low-level anomalies through node self-adjustment. In actual operation and maintenance, many minor anomalies can be quickly recovered through system self-adjustment. However, incorporating all anomalies into the work order dispatch and manual processing flow requires a significant investment of time to handle low-value basic anomalies, encroaching on the processing time for serious faults, causing resource misallocation, and increasing redundant processes in work order generation and dispatch, thus reducing overall operation and maintenance efficiency.

[0004] Meanwhile, monitoring only starts after the work order is processed. Its core purpose is to profile the engineer's capabilities rather than to detect anomalies in a timely manner. This results in potential problems during operation and maintenance not being captured in real time. On the one hand, if an engineer's improper operation causes a new anomaly, it can only be detected after the overall operation is completed. At this time, a new work order needs to be generated and an engineer needs to be dispatched for secondary operation and maintenance, resulting in repeated consumption of time and manpower and a significant extension of the total fault handling cycle. On the other hand, the dynamic fluctuations of equipment parameters during operation cannot be monitored in real time, which may cause minor anomalies to continue to deteriorate during operation and evolve into serious faults, increasing the difficulty and time required for subsequent repairs and reducing operation and maintenance efficiency.

[0005] Therefore, there is an urgent need for a work order management system and method that enables nodes to adjust autonomously and improves operational efficiency. Summary of the Invention

[0006] This invention provides a closed-loop management system and method for information system and equipment service work orders, which can improve operation and maintenance efficiency.

[0007] To solve the above-mentioned technical problems, this application provides the following technical solution: A closed-loop management system for service work orders of information systems and equipment includes an information system module, an operation and maintenance interaction module, and a dual closed-loop linkage module; The information system module includes several distributed monitoring nodes, each of which has a built-in monitoring unit, adjustment unit, and work order unit. The monitoring unit collects the operating data and location data of the monitoring node in real time. The adjustment unit identifies abnormal states and obtains abnormal data based on the operating data, performs automatic adjustment based on the abnormal data, and obtains adjustment data. If the normal state is not reached after a preset number of adjustments, the work order unit generates a work order based on the abnormal data, adjustment data, and location data and sends it to the operation and maintenance interaction module and the dual closed-loop linkage module. The operation and maintenance interaction module is used to receive work orders, collect the start instructions and process information of the work orders from operation and maintenance personnel, and send them to the dual closed-loop linkage module in real time; the dual closed-loop linkage module is used to realize bidirectional linkage between the information system feedback loop and the operation and maintenance personnel feedback loop. After receiving a work order, the dual closed-loop linkage module verifies the work order based on preset review rules. If the verification passes, the work order is confirmed to be received and synchronized to the operation and maintenance interaction module. If the verification fails, the work order is rejected and a rejection reason log is generated and fed back to the information system module. The information system module then regenerates the work order. After receiving the start command, the dual closed-loop linkage module monitors the operation process and starts the monitoring unit of the corresponding monitoring node to collect operation data according to the preset trigger conditions and preset trigger time nodes, and feeds it back to the dual closed-loop linkage module. The dual closed-loop linkage module determines whether new abnormal data is detected based on the operation data and order process information. If new abnormal data is detected, it analyzes the new abnormal data to obtain processing suggestions, updates the work order according to the processing suggestions, and synchronizes the updated work order to the operation and maintenance interaction module and the information system module.

[0008] The basic principle and beneficial effects of this solution are as follows: In this solution, the adjustment unit autonomously identifies abnormal states based on operational data, then automatically adjusts and generates adjustment data. Only after a preset number of consecutive adjustment failures does the work order unit generate a work order. This eliminates the need to dispatch work orders for small-scale, repairable abnormal states; instead, repairs are completed autonomously through monitoring nodes, reducing the number of low-value work orders. Simultaneously, the work order includes abnormal data, adjustment data, and location data, directly providing maintenance personnel with clues to the root cause of the fault and a reference for the adjustment process, saving additional troubleshooting time, shortening the fault handling cycle, and reducing the unnecessary occupation of maintenance resources. After receiving the start command from maintenance personnel, the dual-closed-loop linkage module does not wait for the entire operation to complete. Instead, based on preset trigger conditions and preset trigger time nodes, it starts the monitoring unit of the corresponding monitoring node to collect operational data. This allows for timely detection of new anomalies caused by improper operation during maintenance, eliminating the need to wait until the operation is completed to investigate. This prevents new anomalies from continuously worsening or generating other faults, and eliminates the need for secondary work order generation and secondary maintenance, fundamentally reducing time waste and repetitive work, significantly improving the one-time fault repair rate, and reducing the risk of business interruption due to excessively long monitoring intervals. Work orders generated by the information system module are synchronously sent to the operation and maintenance interaction module and the dual-closed-loop linkage module. The start instructions and order process information collected by the operation and maintenance interaction module are transmitted back to the dual-closed-loop linkage module in real time, realizing dynamic synchronization of operation and maintenance progress. If a new anomaly is detected, the dual-closed-loop linkage module can quickly analyze and generate handling suggestions, and synchronously update the work order to both modules, ensuring that operation and maintenance personnel can obtain new anomaly information and handling directions in a timely manner. The information system can also keep abreast of the operation and maintenance dynamics and optimize subsequent handling strategies. This two-way linkage can eliminate the lag in the transmission of anomaly information, avoid operation and maintenance delays caused by information gaps, and ensure efficient connection of operation and maintenance processes.

[0009] In addition, the dual-loop linkage module verifies work orders through preset review rules, rejecting invalid or mismatched work orders and providing feedback on the reasons. This allows the information system module to regenerate compliant work orders, avoiding the waste of maintenance resources caused by the dispatch of invalid work orders and improving maintenance accuracy from the source. Simultaneously, verified work orders are synchronized to the maintenance interaction module, ensuring the accuracy and timeliness of work order transmission. Compared to the passive monitoring mode after operation, the dual-loop linkage module proactively triggers real-time monitoring during the operation process, integrating and analyzing monitoring data with order process information to quickly identify new anomalies and generate handling suggestions. This achieves seamless integration of monitoring, analysis, and work order updates, shortens anomaly response time, avoids secondary maintenance costs, and improves maintenance efficiency. Meanwhile, the dual closed-loop linkage module enables real-time data exchange between the information system module and the operation and maintenance interaction module, allowing the information system to dynamically monitor the operation and maintenance progress, and enabling operation and maintenance personnel to obtain real-time monitoring data and work order update information from the information system. This prevents the closed-loop link from breaking or information from lagging behind, forming a complete and efficient closed loop of anomaly preprocessing, work order dispatch, process monitoring, dynamic updates, and result feedback. This transforms the operation and maintenance process from passive response to proactive management, improving operation and maintenance efficiency and system stability.

[0010] Furthermore, the adjustment unit identifies abnormal states and acquires abnormal data based on the operating data, including: extracting key parameters from the operating data, calculating the deviation between the key parameters and preset standard parameter thresholds to obtain parameter deviation values, identifying an abnormal state if the parameter deviation value exceeds a preset fluctuation range, and counting the duration of the abnormality and confirming the type of abnormality; and obtaining abnormal data by weighted calculation based on the parameter deviation value and the duration of the abnormality after normalization processing.

[0011] The beneficial effects are as follows: by refining the anomaly identification and automatic adjustment logic, the detection node function is optimized, the ability to accurately preprocess small-scale anomalies is enhanced, and the adjustment data retains complete information of the entire adjustment process, providing accurate basis for operation and maintenance personnel to troubleshoot faults, avoiding ineffective troubleshooting, and shortening the fault handling cycle.

[0012] Furthermore, the adjustment unit automatically adjusts based on abnormal data and obtains adjustment data, including: matching the adjustment algorithm in the preset adjustment strategy library based on the abnormality type, performing parameter correction, module restart or load transfer operations step by step according to the adjustment algorithm based on the abnormal data, and recording the execution time, parameter change amount and adjustment result of each step in real time, forming adjustment data containing adjustment strategy, operation steps, parameter change trajectory and adjustment result.

[0013] The beneficial effects are as follows: compared with the simple adjustment mode, it can achieve accurate quantification of abnormal data, and combined with the abnormal type matching adjustment algorithm, it can improve the success rate of automatic adjustment. More minor abnormalities can be resolved through node self-repair, reducing the dispatch of low-value work orders and reducing the occupation of operation and maintenance resources.

[0014] Furthermore, the work order unit generates work orders from abnormal data, adjustment data, and location data, including: structurally integrating the abnormal data, adjustment data, and location data and extracting core information; filling the core information according to a preset work order template to generate a structured work order containing a basic information area, an abnormal details area, an adjustment process area, and a location navigation area; and assigning a unique identification code associated with the corresponding detection node identifier to the work order.

[0015] The benefits are: maintenance personnel can quickly locate core information without having to sift through redundant data, thus shortening troubleshooting time; at the same time, it ensures the security of work order transmission and full-process traceability, avoiding information loss or corruption.

[0016] Furthermore, the operation and maintenance interaction module is used to receive work orders and collect the start instructions and process information of the work orders from operation and maintenance personnel. This includes: receiving and parsing the work order partition display, generating a work order receipt confirmation signal and feeding it back to the dual closed-loop linkage module; collecting the work order start instructions from operation and maintenance personnel through touch or voice, recording the start timestamp and synchronizing it to the dual closed-loop linkage module; collecting order process information in real time, storing it in a structured manner according to the timeline, and triggering a data upload every preset time interval or key operation node to synchronize the order process information to the dual closed-loop linkage module in real time.

[0017] The beneficial effects are as follows: partitioned display can help maintenance personnel quickly grasp key information and improve the efficiency of operation preparation; timestamp recording provides accurate basis for monitoring and timing; structured collection and real-time uploading of process information can dynamically grasp the progress of maintenance. Compared with the mode of only reporting the final result, it can achieve full-dimensional traceability. With the help of the dual closed-loop linkage mechanism, the information link is opened up, the continuity and efficiency of the maintenance process are improved, and the integrity of closed-loop management is guaranteed.

[0018] Furthermore, the information system module regenerates the work order, including: extracting the reasons for rejection that failed the verification of the work order based on the rejection reason log, supplementing or correcting the abnormal data, adjustment data and location data corresponding to the original work order by associating the rejection reasons with them, generating a new work order, and sending it to the dual closed-loop linkage module for re-verification.

[0019] The beneficial effects are as follows: Based on the reasons for rejection, targeted data completion and correction can ensure the integrity and accuracy of information in newly generated work orders, improve the pass rate of secondary verification of the dual closed-loop linkage module, and reduce invalid links in the work order process; In conjunction with the dual closed-loop audit mechanism, it can improve the efficiency of the process from the source of work order generation, improve the integrity of dual closed-loop management, and reduce the invalid occupation of operation and maintenance resources.

[0020] Furthermore, the dual closed-loop linkage module activates the monitoring unit of the corresponding monitoring node according to the preset trigger conditions and preset trigger time nodes, including: after receiving the order process information, matching the trigger conditions and trigger time nodes in real time, generating a monitoring start command immediately when any condition is met, matching the corresponding detection node based on the location data in the work order, sending the monitoring start command to the monitoring unit of the detection node, and triggering real-time collection of running data.

[0021] The beneficial effects are: accurate matching of detection nodes based on location data to ensure no deviation in the monitored objects; transforming process monitoring from passive waiting to active triggering, improving the efficiency of anomaly detection during operation, avoiding secondary maintenance, and working in synergy with the dual closed-loop linkage mechanism to improve overall maintenance efficiency.

[0022] Furthermore, the dual closed-loop linkage module determines whether new abnormal data has been detected based on the operating data and order process information, including: comparing the operating data with a preset normal parameter threshold to obtain parameter deviation data, and extracting the operation and maintenance sequence from the order process information; performing correlation analysis between the parameter deviation data and the operation and maintenance sequence to eliminate parameter fluctuations caused by normal operation and maintenance; if the remaining parameter deviation data exceeds the preset abnormal judgment threshold, it is determined that new abnormal data has been detected.

[0023] The beneficial effects are as follows: by associating operational data with the timing of maintenance operations, parameter fluctuations caused by normal operations can be accurately eliminated, the false positive rate of anomalies can be reduced, maintenance interference caused by invalid work order updates can be avoided, the accuracy and reliability of new abnormal data identification can be improved, and the risk of missed detection can be effectively avoided.

[0024] Furthermore, the dual-closed-loop linkage module analyzes new abnormal data to obtain processing suggestions, and updates the work order based on the processing suggestions. This includes: extracting the parameter type, deviation range, occurrence time, and associated maintenance operation nodes of the new abnormal data; performing feature matching with a preset fault solution library; and generating tiered processing suggestions that include operation steps, parameter correction ranges, and precautions, sorted by matching degree; retrieving the original work order; adding new abnormal data to the abnormal details area; filling the tiered processing suggestions in the processing suggestion area; marking the new abnormality discovery time and associated operation nodes; generating an updated work order; and associating it with the original work order's unique identification code.

[0025] The beneficial effects are: by generating graded handling suggestions through fault database feature matching, it provides operation and maintenance personnel with targeted operation solutions, which can shorten the decision-making time for handling new anomalies and improve the overall operation and maintenance efficiency and accuracy. Attached Figure Description

[0026] Figure 1 A system block diagram of an embodiment 1 of an information system and equipment service work order closed-loop management system; Figure 2 This is a flowchart of an embodiment 2 of a closed-loop management method for service work orders of an information system and equipment. Detailed Implementation

[0027] The following detailed description illustrates the specific implementation method: Example 1 This invention relates to an information system and a closed-loop management system for equipment service work orders, as shown in the attached document. Figure 1 As shown, the example of an enterprise distributed server cluster operation and maintenance scenario illustrates this. The server cluster contains 50 distributed monitoring nodes, which are physical servers deployed in different areas of the enterprise's data center. Each node corresponds to the operation support of the enterprise's core business. The overall system architecture includes an information system module, an operation and maintenance interaction module, and a dual closed-loop linkage module.

[0028] The information system module comprises 50 distributed monitoring nodes. Each node integrates a monitoring unit, an adjustment unit, and a work order unit. The monitoring unit uses an embedded data acquisition chip to collect real-time operational and location data of the corresponding server node. Operational data includes four key parameters: CPU utilization, memory usage, hard disk read / write speed, and network bandwidth usage, collected once per second. Location data is obtained through a pre-installed location coding module in the data center, formatted as "Data Center Area-Rack Number-Node Number," such as "Area A-Rack 08-Node 12," and bound to a unique hardware identifier for each node to ensure accurate positioning. The adjustment unit first extracts the four key parameters as core parameters and calculates the deviation between each core parameter and preset standard parameter thresholds. The preset standard parameter thresholds are: CPU utilization ≤ 70%, memory usage ≤ 80%, hard disk read / write speed ≥ 500MB / s, and network bandwidth usage ≤ 60Mbps. The parameter deviation is calculated using the following formula: in, Let be the deviation value of the i-th parameter. The actual collected value of the parameter. This is the standard threshold for the parameters. If any parameter deviation exceeds the preset fluctuation range, such as ±5%, it is identified as an abnormal state. At the same time, the duration of the abnormality is recorded (starting from the first time the threshold is exceeded) and the type of abnormality is confirmed (such as CPU overload abnormality, memory leak abnormality, etc.).

[0029] The adjustment unit performs weighted calculations based on the parameter deviation values ​​and the duration of the anomaly, after normalization. The normalization process maps the parameter deviation values ​​and anomaly durations of different physical quantities to the dimensionless interval [0,1], eliminating the influence of physical quantity differences on the weighted calculation and ensuring the rationality of the calculation logic. The weighted calculation is performed according to the following formula: in, Quantification value for abnormal data; (i=1-4) represents the weights of each operating parameter: CPU weight 0.25, memory weight 0.25, hard disk weight 0.15, bandwidth weight 0.15, and the total weight of the four types of parameters is 0.8. It is a dimensionless normalized function; The duration of the anomaly; The duration weight is 0.2; the sum of all weights is 1.0, which conforms to the conventional logic of weighted calculation.

[0030] The adjustment unit matches the anomaly type with the adjustment algorithms in the preset adjustment strategy library. This library includes three types of algorithms: parameter correction algorithms (for CPU, memory, and bandwidth anomalies); module restart algorithms (for hard disk read / write anomalies); and load transfer algorithms (for multi-parameter coordination anomalies). If the anomaly is CPU overload, the anomaly type matches the parameter correction algorithm, and the adjustment operation is executed step-by-step according to the algorithm: first, the priority of non-core business processes on the node is reduced; second, the CPU usage quota of non-core business processes is limited; and third, if the deviation is still not alleviated, temporary redundant processes are shut down. The execution time of each step (e.g., process priority adjustment at 14:32), parameter changes (e.g., CPU utilization decreasing from 80% to 75%), and adjustment results (e.g., after the first adjustment, the deviation value decreased to 7.14%, still exceeding the fluctuation range) are recorded in real time, forming adjustment data containing the adjustment strategy, operation steps, parameter change trajectory, and adjustment results. The preset number of adjustments is 3. If the CPU utilization remains above 75% after 3 consecutive adjustments and has not reached a normal state, a work order unit is triggered.

[0031] The adjustment unit matches the adjustment algorithms in the preset adjustment strategy library based on the anomaly type. The preset adjustment strategy library includes three categories: parameter correction algorithms, module restart algorithms, and load transfer algorithms. The specific execution operations of each type of algorithm are as follows: The parameter correction algorithm is for anomalies that can be repaired by parameter adjustment, such as CPU overload, excessive memory usage, abnormal network bandwidth, and disk read / write parameter deviation. It performs operations such as process priority adjustment, resource quota limit, redundant process shutdown, and bandwidth allocation ratio adjustment. The module restart algorithm is for anomalies such as hardware module freezing, process unresponsiveness, and service crash. It first saves the current node running status data, shuts down the abnormal hardware module or unresponsive process, and then reloads the module and restarts the service according to the preset startup order. After restarting, it verifies the node running status to confirm whether it has returned to normal. The load transfer algorithm is for overload anomalies where a single node's resources are exhausted and cannot be recovered through local adjustment. It migrates some of the node's business processes and data processing tasks to idle monitoring nodes in the same cluster to maintain continuous business operation. After the load of the source node drops to the normal range, the business load is migrated back as needed. The adjustment unit performs adjustment operations step by step based on the above adjustment algorithm, and records the execution time, parameter changes and adjustment results of each step in real time, forming adjustment data that includes adjustment strategy, operation steps, parameter change trajectory and adjustment results.

[0032] The work order unit structurally integrates abnormal data (quantitative value, abnormal type, duration), adjustment data (complete records of 3 adjustments), and location data ("Area A - Rack 08 - Node 12"), extracting core information including: abnormal data quantitative value 0.82, abnormal type CPU overload, number of adjustments 3, adjustment result not meeting standard, node location, and hardware identifier. The core information is then categorized and filled into a pre-set work order template to generate a structured work order. The template is divided into four main areas: basic information area (work order number, generation time, node identifier), abnormal details area (abnormal type, quantitative value, duration), adjustment process area (operation steps, parameter changes, and results of 3 adjustments), and location navigation area (associated with a data center location diagram and rack number label). Simultaneously, a unique identification code is assigned to the work order, associated with the hardware identifier of the detection node. After generating a complete work order, it is simultaneously sent to the operation and maintenance interaction module and the dual closed-loop linkage module.

[0033] The operation and maintenance interaction module is deployed on the handheld terminals of operation and maintenance personnel and the terminals in the data center monitoring center, adopting a dual interaction mode of touch and voice. After receiving a work order, the terminal decodes the structured data through the decoding module and displays it in sections such as basic information area and abnormal details area. At the same time, it generates a work order reception confirmation signal (including terminal identifier and reception time) and feeds it back to the dual closed-loop linkage module to confirm that the work order has been successfully received. Operation and maintenance personnel start the work order by clicking the start processing button on the tablet touch or by voice command. The module collects the start command, records the start timestamp, and synchronizes it to the dual closed-loop linkage module. During the operation and maintenance process, order process information is collected in real time, including: operation steps of operation and maintenance personnel, operation duration, parameter adjustment records, stage fault feedback, and operation pause / resumption signals. The data is stored in a structured manner according to the time axis with a preset time interval of 30 seconds. At the same time, real-time data upload is triggered at key operation nodes to ensure that the order process information is synchronized to the dual closed-loop linkage module in real time for subsequent analysis.

[0034] The dual-loop linkage module is built on an industrial-grade server and incorporates a closed-loop linkage algorithm and data processing module. It enables bidirectional linkage between the information system feedback loop and the maintenance personnel feedback loop. The specific workflow is as follows: After receiving a work order, the dual-loop linkage module performs verification based on preset review rules (including three rules: information integrity, node permission matching, and priority adaptation). Information integrity verification checks for missing core information. Node permission matching verifies whether the node corresponding to the work order falls within the current maintenance team's jurisdiction. Priority adaptation is based on the abnormal data quantification value: an abnormal data quantification value ≥ 0.8 indicates high priority, between 0.5 and 0.8 indicates medium priority, and < 0.5 indicates low priority. If the work order information is complete, node permissions match, and priority is clearly marked, the verification passes, and the work order is confirmed and synchronized to the maintenance interaction module. If the work order lacks a node hardware identifier and fails the information integrity verification, it is rejected, and a rejection reason log "Work order lacks node hardware identifier, information incomplete" is generated and fed back to the information system module. After receiving the rejection reason log, the information system module extracts the rejection reason, associates it with the abnormal data, adjustment data and location data corresponding to the original work order, supplements the hardware identifier of the node, regenerates a new work order according to the original work order template, and sends it to the dual closed-loop linkage module for re-verification. After this verification is passed, it is synchronized to the operation and maintenance interaction module.

[0035] After receiving the start command and timestamp from the operation and maintenance interaction module, the dual-closed-loop linkage module starts the timing unit to count the operation and maintenance time. Simultaneously, based on preset trigger conditions and trigger time nodes, it starts the monitoring unit of the corresponding detection node. Preset trigger conditions include: completion signals of key operation and maintenance steps (such as process shutdown or restart), fluctuations in the operating parameters of the detection node exceeding a preset threshold (±3%), and operation and maintenance pause signals. The preset trigger time node is within 10 seconds of the completion of the key step and when the timing duration reaches 1 minute. When the operation and maintenance personnel complete the key step of "closing redundant background processes" at 14:36:10, the operation and maintenance interaction module uploads a completion signal. The dual-closed-loop linkage module matches the trigger conditions and time node, generates a monitoring start command within 10 seconds, matches the corresponding detection node based on the location data in the work order, sends the command to the monitoring unit of that node, triggers its real-time collection of operating data, and feeds it back to the dual-closed-loop linkage module.

[0036] The dual-loop linkage module receives operational data from the monitoring unit and combines it with order process information uploaded by the operation and maintenance interaction module to determine if new abnormal data exists. First, the operational data is compared with preset normal parameter thresholds to obtain parameter deviation data. The operation and maintenance operation sequence (time nodes and operation content of each step) is extracted from the order process information. The parameter deviation data is correlated with the operation sequence for analysis. If the parameter fluctuation occurs within the operation and maintenance operation execution period, and the fluctuation trend matches the operation action (e.g., CPU utilization decreases after closing the process), it is determined to be a fluctuation caused by normal operation and is removed. If the fluctuation does not match the operation action, and the remaining parameter deviation data exceeds the preset abnormal judgment threshold (±3%), then new abnormal data is detected. For example, if monitoring finds that after restarting the core business process at 14:37:20, the node memory usage rate rapidly increased from 65% to 82%, exceeding the standard threshold of 80%, with a deviation of 2.5%, this fluctuation occurred after the restart operation, but the upward trend does not match the memory usage change after a normal restart and exceeds the abnormal judgment threshold, it is determined to be new abnormal data, i.e., a sudden increase in memory usage. The dual-loop linkage module extracts the parameter type, deviation range, occurrence time, and associated operation nodes of new abnormal data, performs feature matching with a preset fault solution library, and generates tiered handling suggestions based on the matching degree: Level 1 suggestion "Stop core business processes and investigate memory leaks," Level 2 suggestion "Temporarily expand memory to ensure temporary business operation," and Level 3 suggestion "Restart nodes and clear redundant memory data." Subsequently, the dual-loop linkage module retrieves the original work order, adds the aforementioned new abnormal data to the abnormality details area, fills the tiered handling suggestions in the handling suggestion area, and marks the new abnormality discovery time and associated operation nodes, generating an updated work order. The unique identifier still uses the original identifier, and an update identifier "V1" (indicating the first update) is added. This is simultaneously sent to the operation and maintenance interaction module and the information system module, while retaining the work order update log (recording the update time, new abnormality content, and handling suggestions), achieving complete linkage of the dual-loop system.

[0037] Example 2 Based on Embodiment 1, this embodiment discloses a closed-loop management method for information system and equipment service work orders, as shown in the attached figure. Figure 2 As shown, the specific execution process is as follows: S1: The monitoring unit of the detection node collects its own operation data and location data in real time; the adjustment unit identifies abnormal states and obtains abnormal data based on the operation data, and performs automatic adjustment based on the abnormal data, such as parameter correction, module restart or load transfer, and obtains adjustment data. If the normal state is not reached after a preset number of adjustments, the work order unit generates a work order based on the abnormal data, adjustment data and location data, and sends it to the operation and maintenance interaction module and the dual closed-loop linkage module. Each monitoring unit at each detection node collects its own operational and location data in real time via a remote data acquisition protocol, at a frequency of once per second. The adjustment unit extracts the operational data as key parameters and compares them with preset standard thresholds (such as CPU load ≤75%, memory utilization ≤85%, disk IO ≥600MB / s, and network latency ≤50ms) to calculate parameter deviation values. If the actual network latency of a node is 80ms, and the deviation value is 60%, exceeding the fluctuation range (±5%), it is identified as an abnormal state. The duration of the abnormality is recorded as 3 minutes, confirming the abnormality type as "excessive network latency". Based on the parameter deviation value and the normalized weighted calculation of the abnormal duration, an abnormal data quantification value of 0.85 is obtained. This is matched with the parameter correction algorithm in the preset adjustment strategy library, and adjustment operations are executed step by step: restarting the network adapter, adjusting the network bandwidth allocation ratio, and clearing the network cache. The execution time, parameter changes, and adjustment results of each step are recorded in real time to form adjustment data. The preset number of adjustments is 3. After continuous adjustments, the network latency is still 72ms. The work order unit integrates the abnormal data, adjustment data and location data to generate a structured work order, assigns a unique identification code, and sends it to the operation and maintenance interaction module and the dual closed-loop linkage module.

[0038] S2: The operation and maintenance interaction module receives work orders, collects the start instructions and order process information of the operation and maintenance personnel for the work orders, and sends them to the dual closed-loop linkage module in real time. After receiving a work order, the operations and maintenance interaction module parses and displays it in sections, generating a confirmation signal that is fed back to the dual-loop linkage module. Operations and maintenance personnel can initiate processing via touch on the management platform. The module collects the start command, records the timestamp, and simultaneously collects real-time order process information, such as operation steps, duration, parameter adjustment records, and phased feedback. This information is stored along a timeline and uploaded every 30 seconds or at key operation nodes to ensure real-time synchronization to the dual-loop linkage module.

[0039] S3: The dual closed-loop linkage module verifies the work order based on preset review rules. If the verification passes, the work order is confirmed and synchronized to the operation and maintenance interaction module. If the verification fails, the work order is rejected and a rejection reason log is generated and fed back to the information system module, which then regenerates the work order. The dual-loop linkage module verifies work orders based on preset review rules. If the verification reveals that the work order lacks the "tenant's business type" information, it fails the verification and generates a rejection reason log, which is then sent to the information system module. The information system module then correlates the original work order data, adds the tenant's business type "core financial business," regenerates the work order, and sends it back to the dual-loop linkage module for re-verification. Once the verification passes, it is synchronized to the operations and maintenance interaction module.

[0040] S4: After receiving the start command, the dual closed-loop linkage module monitors the operation and maintenance process. Based on the preset trigger conditions and preset trigger time nodes, it starts the monitoring unit of the corresponding detection node to collect operation data and provide feedback. After receiving the start command, the dual-loop linkage module activates the timing unit. Based on preset trigger conditions (completion of key steps, parameter fluctuation exceeding ±3%, operation pause) and trigger time nodes (within 15 seconds after the key step, 1 minute of timing), it activates the monitoring unit of the corresponding detection node. When the maintenance personnel complete the key step of "changing the network switch port" at 15:11:30, the module generates a monitoring start command within 15 seconds. Based on the location data matching node, it triggers the monitoring unit to increase the collection frequency to 2 times / second, collecting and feeding back operational data in real time.

[0041] S5: The dual closed-loop linkage module combines the feedback operation data and order process information to determine whether new abnormal data has been detected. If detected, it analyzes the new abnormal data to obtain processing suggestions, updates the work order according to the processing suggestions, and synchronizes it to the operation and maintenance interaction module and information system module. The dual-loop linkage module correlates and analyzes the feedback operational data with order process information, eliminating parameter fluctuations caused by normal operations. If a node's memory usage suddenly spikes to 88% (exceeding the threshold) after a port change, it is identified as new abnormal data. New abnormal characteristics are extracted and matched against the fault solution library to generate tiered handling suggestions. The original work order is updated (adding new abnormal information and handling suggestions), and synchronized to the operations and maintenance interaction module and information system module. Operations personnel then perform subsequent operations based on the first-level suggestion, "Check for memory leaks," completing closed-loop management. This embodiment, through specific scenario implementation, achieves accurate anomaly identification, process monitoring, and dual-loop linkage, effectively solving the problems of low operational efficiency and delayed feedback in existing technologies, ensuring the stable operation of data center servers.

[0042] The above are merely embodiments of the present invention. The invention is not limited to the fields covered by these embodiments. Commonly known structures and characteristics in the solutions are not described in detail here. Those skilled in the art are aware of all common technical knowledge in the field prior to the application date or priority date, are able to access all existing technologies in that field, and have the ability to apply conventional experimental methods prior to that date. Those skilled in the art can, under the guidance of this application, improve and implement this solution in combination with their own capabilities. Some typical known structures or methods should not be obstacles for those skilled in the art to implement this application. It should be noted that those skilled in the art can make several modifications and improvements without departing from the structure of the present invention. These should also be considered within the scope of protection of the present invention, and will not affect the effectiveness of the implementation of the present invention or the practicality of the patent. The scope of protection claimed in this application should be determined by the content of its claims, and the specific embodiments described in the specification can be used to interpret the content of the claims.

Claims

1. A closed-loop management system for service work orders of information systems and equipment, characterized in that, It includes an information system module, an operation and maintenance interaction module, and a dual closed-loop linkage module; The information system module includes several distributed monitoring nodes, each of which has a built-in monitoring unit, adjustment unit, and work order unit. The monitoring unit collects the operating data and location data of the monitoring node in real time. The adjustment unit identifies abnormal states and obtains abnormal data based on the operating data. Based on the abnormal data, it performs automatic adjustments such as parameter correction, module restart, or load transfer and obtains adjustment data. If the normal state is not reached after a preset number of adjustments, the work order unit generates a work order based on the abnormal data, adjustment data, and location data and sends it to the operation and maintenance interaction module and the dual closed-loop linkage module. The operation and maintenance interaction module is used to receive work orders, collect the start instructions and process information of the work orders from operation and maintenance personnel, and send them to the dual closed-loop linkage module in real time; the dual closed-loop linkage module is used to realize bidirectional linkage between the information system feedback loop and the operation and maintenance personnel feedback loop. After receiving a work order, the dual closed-loop linkage module verifies the work order based on preset review rules. If the verification passes, the work order is confirmed to be received and synchronized to the operation and maintenance interaction module. If the verification fails, the work order is rejected and a rejection reason log is generated and fed back to the information system module. The information system module then regenerates the work order. After receiving the start command, the dual closed-loop linkage module monitors the operation process and starts the monitoring unit of the corresponding monitoring node to collect operation data and feed it back to the dual closed-loop linkage module according to the preset trigger conditions and preset trigger time nodes. The dual closed-loop linkage module determines whether new abnormal data is detected based on the operation data and order process information. If new abnormal data is detected, it analyzes the new abnormal data to obtain processing suggestions, updates the work order according to the processing suggestions, and synchronizes the updated work order to the operation and maintenance interaction module and the information system module.

2. The information system and equipment service work order closed-loop management system according to claim 1, characterized in that, The adjustment unit identifies abnormal states and acquires abnormal data based on the operating data, including: extracting key parameters from the operating data, calculating the deviation between the key parameters and preset standard parameter thresholds to obtain parameter deviation values, identifying an abnormal state if the parameter deviation value exceeds a preset fluctuation range, and counting the duration of the abnormality and confirming the type of abnormality; and calculating the abnormal data by weighting the parameter deviation value and the duration of the abnormality after normalization.

3. The information system and equipment service work order closed-loop management system according to claim 2, characterized in that, The adjustment unit automatically adjusts parameters, restarts modules, or transfers load based on abnormal data and obtains adjustment data, including: matching adjustment algorithms in a preset adjustment strategy library based on the abnormality type; performing parameter correction, module restart, or load transfer operations step by step according to the adjustment algorithm based on the abnormal data; recording the execution time, parameter change amount, and adjustment result of each step in real time; and forming adjustment data that includes adjustment strategies, operation steps, parameter change trajectory, and adjustment results.

4. The information system and equipment service work order closed-loop management system according to claim 3, characterized in that, The work order unit generates work orders from abnormal data, adjustment data, and location data, including: structurally integrating the abnormal data, adjustment data, and location data and extracting core information; filling the core information according to a preset work order template to generate a structured work order containing a basic information area, an abnormal details area, an adjustment process area, and a location navigation area; and assigning a unique identification code associated with the corresponding detection node identifier to the work order.

5. The information system and equipment service work order closed-loop management system according to claim 4, characterized in that, The operation and maintenance interaction module is used to receive work orders and collect the start instructions and process information of the work orders from operation and maintenance personnel. This includes: receiving and parsing the work order partition display, generating a work order receipt confirmation signal and feeding it back to the dual closed-loop linkage module; collecting the work order start instructions from operation and maintenance personnel through touch or voice, recording the start timestamp and synchronizing it to the dual closed-loop linkage module; collecting order process information in real time, storing it in a structured manner according to the timeline, and triggering a data upload once every preset time interval or key operation node to synchronize the order process information to the dual closed-loop linkage module in real time.

6. The information system and equipment service work order closed-loop management system according to claim 5, characterized in that, The information system module regenerates the work order, including: extracting the reasons for rejection that failed the verification of the work order from the rejection reason log, supplementing or correcting the abnormal data, adjustment data and location data corresponding to the original work order by associating the rejection reasons with them, generating a new work order, and sending it to the dual closed-loop linkage module for re-verification.

7. The information system and equipment service work order closed-loop management system according to claim 6, characterized in that, The dual closed-loop linkage module activates the monitoring unit of the corresponding monitoring node according to the preset trigger conditions and preset trigger time nodes, including: receiving order process information and matching the trigger conditions and trigger time nodes in real time; generating a monitoring start command immediately when any condition is met; matching the corresponding detection node based on the location data in the work order; sending the monitoring start command to the monitoring unit of the detection node; and triggering real-time collection of running data.

8. The information system and equipment service work order closed-loop management system according to claim 7, characterized in that, The dual-closed-loop linkage module determines whether new abnormal data has been detected based on the operating data and order process information, including: comparing the operating data with a preset normal parameter threshold to obtain parameter deviation data, and extracting the operation and maintenance sequence from the order process information; performing correlation analysis between the parameter deviation data and the operation and maintenance sequence to eliminate parameter fluctuations caused by normal operation and maintenance; if the remaining parameter deviation data exceeds the preset abnormal judgment threshold, it is determined that new abnormal data has been detected.

9. The information system and equipment service work order closed-loop management system according to claim 8, characterized in that, The dual-closed-loop linkage module analyzes new abnormal data to obtain processing suggestions, and updates the work order based on the processing suggestions. This includes: extracting the parameter type, deviation range, occurrence time, and associated maintenance operation nodes of the new abnormal data; performing feature matching with a preset fault solution library; and generating tiered processing suggestions that include operation steps, parameter correction ranges, and precautions, sorted by matching degree; retrieving the original work order; adding new abnormal data to the abnormal details area; filling the tiered processing suggestions in the processing suggestion area; marking the new abnormality discovery time and associated operation nodes; generating an updated work order; and associating it with the original work order's unique identification code.

10. A closed-loop management method for service work orders of information systems and equipment, characterized in that, Including the following steps: S1. The monitoring unit of the detection node collects its own operation data and location data in real time; the adjustment unit identifies abnormal states and obtains abnormal data based on the operation data, and performs automatic adjustment of parameters, module restart or load transfer based on the abnormal data and obtains adjustment data. If the normal state is not reached after a preset number of adjustments, the work order unit generates a work order based on the abnormal data, adjustment data and location data and sends it to the operation and maintenance interaction module and the dual closed-loop linkage module. S2, the operation and maintenance interaction module receives work orders, collects the start instructions and order process information of operation and maintenance personnel for work orders, and sends them to the dual closed-loop linkage module in real time; S3, the dual closed-loop linkage module verifies the work order based on preset review rules. If the verification passes, the work order is confirmed and synchronized to the operation and maintenance interaction module. If the verification fails, the work order is rejected and a rejection reason log is generated and fed back to the information system module, which then regenerates the work order. S4. After receiving the start command, the dual closed-loop linkage module monitors the operation and maintenance process. Based on the preset trigger conditions and preset trigger time nodes, it starts the monitoring unit of the corresponding detection node to collect operation data and provide feedback. The S5 dual-closed-loop linkage module combines the feedback operation data and order process information to determine whether new abnormal data has been detected. If detected, it analyzes the new abnormal data to obtain processing suggestions, updates the work order based on the processing suggestions, and synchronizes it to the operation and maintenance interaction module and information system module.

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