Informatization data management system and method for intelligent operation and maintenance equipment box

Abstract

The invention discloses an informatization data management system and method for an intelligent operation and maintenance equipment box, and relates to the technical field of informatization data management. Comprising a temperature monitoring and acquisition frequency regulation and control module, a gas concentration vector correction module, a leakage point analysis module, a strain gauge data analysis module, a loosening fault judgment module and a maintenance point screening and maintenance recording module, initial acquisition frequency is set, the temperature of an equipment box is monitored in real time, and the acquisition frequency is adjusted according to the real-time temperature condition; a monitored gas concentration prediction model is established; a predicted gas concentration is calculated; a concentration prediction error value is obtained; a leakage point position coordinate and an initial concentration are analyzed; according to the method, the concentration prediction model is established, the gas diffusion path and the real-time concentration are mastered, and the improvement of the overall operation and maintenance level is promoted.

Description

Technical Field

[0001] The present invention relates to the technical field of information data management, and in particular to an information data management system and method for an intelligent operation and maintenance equipment box. Background Art

[0002] With the development of science and technology, intelligent operation and maintenance equipment boxes are deployed in large numbers in key areas such as industry, energy, and communications. However, traditional operation and maintenance has obvious shortcomings in the temperature monitoring link. In the past, fixed-frequency collection of equipment box temperature data was mostly adopted at fixed times and points, which lacked flexibility. Once the temperature inside the equipment box rises abnormally due to sudden load changes, heat dissipation obstruction, etc., conventional timed collection is very likely to miss the key nodes of rapid temperature changes and fail to detect high temperature hazards in time.

[0003] The gas condition of the environment in which the equipment box is located is also critical to its safe operation. Previous monitoring methods only stayed at the level of simple measurement of gas concentration, without considering the two key dynamic factors of wind direction and wind speed. For example, if a gas leak occurs near the equipment box in a chemical park, it is difficult for the staff to accurately determine the scope of the leakage area and evacuate the surrounding personnel in time due to the unclear diffusion direction of the gas driven by the wind direction and the real-time change of the concentration under the action of wind speed. It is difficult to quickly locate the leakage point, which increases the difficulty of subsequent environmental repair. On the way to the fault point, maintenance personnel cannot avoid the safety risks brought by being too close to the leakage point. Even if the location of the leakage point is located, due to the extremely low efficiency of the physical structure stability of the manual inspection equipment, it is impossible to continuously obtain strain gauge data in real time to determine the looseness, and it is difficult to find the long-term accumulated small looseness. The maintenance link lacks a scientific system for comprehensive evaluation of maintenance points, and cannot make quick decisions based on factors such as the number of maintenance personnel and the distance between the maintenance point and the fault point. In addition, the lack of maintenance process records is not conducive to reviewing experience and troubleshooting the root causes of similar faults, which hinders the improvement of operation and maintenance level. Summary of the invention

[0004] The object of the present invention is to provide an information data management system and method for an intelligent operation and maintenance equipment box to solve the problems raised in the above background technology.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions: an information data management method for an intelligent operation and maintenance equipment box, comprising the following steps: S1. Set the initial acquisition frequency, monitor the equipment box temperature in real time, and adjust the acquisition frequency according to the real-time temperature conditions; S2. Performing vector correction on the gas concentration according to the wind direction and wind speed to obtain a corrected gas concentration vector; S3. Establish a monitoring gas concentration prediction model, calculate the predicted gas concentration, obtain the concentration prediction error value, and analyze the leakage point location coordinates and initial concentration; S4. Real-time collection of strain values ​​of strain gauges in the equipment box to analyze the overall looseness of the equipment box; S5. judging whether the equipment box has a loose fault according to the comparison result between the continuously collected overall loose fault coefficient of the equipment box and the threshold value; S6. Analyze the positional relationship between the leakage point, the equipment box and the maintenance point, consider the number of people doing maintenance at the maintenance point in real time, choose to go to the maintenance point where the equipment box with loose faults is to be repaired, record the maintenance operations in real time during maintenance and upload the maintenance operations to the database after the maintenance is completed.

[0006] Furthermore, in step S1, the initial acquisition frequency f0 and the equipment high temperature alarm threshold T0 are set. The acquisition frequency represents the number of times data is collected in one acquisition cycle. The acquisition cycle is set by the equipment box. The real-time monitoring of the equipment box temperature is T. When T<T0, it is judged that the equipment is in a normal working state, and the acquisition frequency remains unchanged at f0; when T≥T0, the temperature abnormality alarm is triggered, and the acquisition frequency is dynamically adjusted to the real-time acquisition frequency f: ; Where k is the adjustment coefficient of the acquisition frequency, and the maximum acquisition frequency of the equipment box is f max , when f≥f is calculated max When the acquisition frequency is adjusted to f max .

[0007] Further, in step S2, the gas concentration, wind direction and wind speed of the monitored gas are collected at A locations, wherein the gas concentration of the monitored gas collected at the ath location is B a , wind direction is vector U a , the wind speed is u a , establish a plane rectangular coordinate system, perform vector correction on the gas concentration according to the wind direction and wind speed, and obtain the corrected gas concentration vector C at the ath location a : ; The corrected gas concentration vector C a The direction of indicates the diffusion direction of the monitored gas, and the corrected gas concentration vector C a The size of the mode indicates the gas concentration of the monitored gas; The monitored gas is a dangerous gas generated by the equipment itself during operation. For example, in an electric equipment box, harmful gases such as ozone may be generated due to heating and discharge of electrical components. If the equipment box is used in a chemical scene, toxic and harmful gases may be generated by the volatilization and reaction of chemical raw materials. The specific monitored gas is set by the system.

[0008] From the data collection point of view, the gas concentration B is collected at location A. a , wind direction vector Ua With wind speed u a , which builds a comprehensive information foundation for subsequent precise analysis. The summary of data from different locations can reflect the overall situation of the gas environment.

[0009] A plane rectangular coordinate system is established to closely associate wind direction, wind speed and gas concentration data. Taking the power equipment box as an example, harmful gases such as ozone may damage the insulation of the line due to chemical activity and cause short circuits. Accurately monitoring its concentration and diffusion direction can intervene in advance to prevent problems before they occur.

[0010] In the chemical industry, although the types of toxic and harmful gases depend on the system, the vector-corrected C a Accurately presenting its dynamic distribution allows staff to quickly determine the scope of the leak, ensuring the normal operation of the equipment and avoiding shutdowns due to gas problems, greatly improving the safety, reliability and efficiency of intelligent operation and maintenance.

[0011] Further, in step S3, the analysis coordinates are in (x a ,y a ) and establish a monitoring gas concentration prediction model based on the monitoring gas diffusion situation at the ath location: ; in Indicates that at point (x a ,y a ), C0 is the initial concentration of the monitoring gas leakage point to be calculated, D represents the known diffusion coefficient, and r represents the coordinate (x a ,y a ) and the distance between the gas leakage point with coordinates (x0, y0), and obtain the concentration prediction error value e at the a-th location a , , establish the objective function: ; Where S is the sum of squares of the predicted concentration errors of A locations. The partial derivative of S with respect to x0 is ∂S / ∂x0, the partial derivative of S with respect to y0 is ∂S / ∂y0, and the partial derivative of S with respect to C0 is ∂S / ∂C0. In addition, considering , combined to get the system of equations: ; Substitute into the elimination method to obtain the coordinates of the leakage point (x0, y0) and the initial concentration C0 of the leakage point; By establishing a professional gas concentration prediction model, the gas diffusion trend can be accurately simulated, so that staff can predict in advance the range that the gas may spread and quickly know the leakage area when the leakage just occurs.

[0012] Relying on mathematical derivation and calculation, from constructing the objective function to solving the equations simultaneously, the location of the leak point and the initial concentration are finally determined. This provides a clear direction for quickly repairing the leak problem, shortens the time spent on troubleshooting, allows the equipment box to resume normal operating environment faster, reduces the loss of shutdown caused by gas leakage, improves the overall operation and maintenance efficiency, and ensures the continuous stability of the environment in which the equipment box is located.

[0013] Furthermore, in step S4, the strain values ​​of N strain gauges in the equipment box are collected according to the real-time collection frequency f, and the mean value E of the strain value of the nth strain gauge is calculated: ; Where V represents the number of cycles for collecting strain values ​​of the strain gauge, E n_t represents the strain value of the ith strain gauge collected at the tth time, calculates the standard deviation e of the strain value of the nth strain gauge, and sets the upper threshold of the strain value of the nth strain gauge to E max_n =E+3e, the lower limit threshold of the strain value of the nth strain gauge is E min_n =E-3e, for the strain value collected for the tth time, calculate the loosening failure coefficient F of the nth strain gauge e_t : ; Calculate the overall looseness failure coefficient F of the equipment box t : ; Real-time collection of strain gauge data can keenly capture even the slightest structural changes compared to the traditional manual inspection. Relevant values ​​are obtained through scientific calculations, and then a reasonable warning range is set to accurately identify potential loosening hazards.

[0014] The looseness of the equipment box is quantified as a specific failure coefficient, which is different from the ambiguous judgment method. Once these coefficients are abnormal, they can respond quickly, deploy maintenance resources in advance, and reinforce maintenance in time, effectively preventing small problems from deteriorating into major failures, ensuring the continuous and stable operation of the equipment, and eliminating production interruptions caused by sudden damage.

[0015] Maintaining its structure stably over the long term will keep it in good operating condition at all times, comprehensively improve the level of intelligent operation and maintenance and reliability, and provide solid support for the efficient operation of all industries.

[0016] Further, in step S5, the loose fault threshold F is set min , when continuous g max When the overall looseness fault coefficient of the equipment box is higher than the looseness fault threshold, it is judged that the equipment box has a loose fault; otherwise, it is judged that the equipment box is operating normally, where g maxThe maximum tolerable number of times the loose failure coefficient set for the system is higher than the loose failure threshold.

[0017] Further, in step S6, the real-time number of maintenance personnel at I maintenance points is collected, the route distance between I maintenance points and the equipment box with loose faults is collected, and the maintenance priority coefficient J of the i-th maintenance point is calculated. i : ; Where P i represents the real-time maintenance staff of the i-th maintenance point, Q i R represents the route distance from the i-th maintenance point to the equipment box with loose fault, i It represents the minimum distance between the route from the i-th maintenance point to the equipment box and the gas leakage point. The maintenance personnel are dispatched from the maintenance point with the highest maintenance priority coefficient to check and repair the equipment box. After the maintenance point is determined, the real-time distance between the maintenance personnel and the equipment box is monitored, and the time for the maintenance personnel to reach the equipment box is estimated. During the maintenance of the equipment box, the maintenance process is recorded in real time through the equipment box and uploaded to the database, and the leakage point is avoided as much as possible. On the one hand, it is for safety reasons. On the other hand, if the leakage point is under construction and repair, it is not conducive for the maintenance personnel to go to the equipment box. The analysis method of the minimum distance between the route from the maintenance point to the equipment box and the gas leakage point is as follows: first, the route is discretized, that is, the route is approximated as a broken line formed by connecting many small segments in sequence. The more small segments there are, the higher the approximation degree is. First, the distance from the point to these approximate segments is calculated, and then the minimum distance among them is found, which is used as the approximate minimum distance between the point and the original curve. As the discretization degree continues to increase, the approximation degree is close to the actual minimum distance.

[0018] An information data management system for an intelligent operation and maintenance equipment box, the system comprising: a temperature monitoring and acquisition frequency control module, a gas concentration vector correction module, a leakage point analysis module, a strain gauge data analysis module, a loose fault identification module, and a maintenance point screening and maintenance record module; The temperature monitoring and acquisition frequency control module sets the initial acquisition frequency, monitors the equipment box temperature in real time, and adjusts the acquisition frequency according to the real-time temperature conditions; The gas concentration vector correction module performs vector correction on the gas concentration according to the wind direction and wind speed to obtain a corrected gas concentration vector; The leakage point analysis module establishes a monitoring gas concentration prediction model, calculates the predicted gas concentration, obtains the concentration prediction error value, and analyzes the leakage point location coordinates and the initial concentration; The strain gauge data analysis module collects the strain value of the strain gauge in the frequency collection equipment box in real time to analyze the overall looseness of the equipment box; The loose fault identification module determines whether the equipment box has a loose fault according to the comparison result of the overall loose fault coefficient of the equipment box collected continuously and the threshold value; The maintenance point screening and maintenance record module analyzes the maintenance point that is most suitable for repairing the equipment box with loose faults, and records and uploads the maintenance process to the database in real time during maintenance.

[0019] Compared with the prior art, the beneficial effects achieved by the present invention are: on the one hand, by setting the initial acquisition frequency and dynamically adjusting it according to the real-time temperature of the equipment box, the temperature change can be accurately captured. When the equipment box heats up due to an unexpected situation, the system can respond quickly and increase the acquisition frequency in time, so as to detect the high temperature hidden danger at the first time and trigger the alarm, which greatly reduces the risk of equipment failure caused by overheating and ensures production continuity; On the one hand, by comprehensively considering the vector correction of wind direction and wind speed on gas concentration and establishing a concentration prediction model, the gas diffusion path and real-time concentration can be accurately grasped. Once there is a gas leak around the equipment box in the chemical park, the leak point can be quickly located and the leak area can be accurately delineated.

[0020] On the other hand, real-time collection of strain gauge data continuously monitors the looseness of equipment, detects potential structural problems in advance, and prevents them from happening. A maintenance point screening system is established to calculate priority coefficients based on factors such as maintenance personnel and distance, avoid safety risks posed by leakage points to maintenance personnel, and quickly determine the best maintenance point. This not only improves maintenance efficiency, but also provides strong support for subsequent operation and maintenance optimization, thereby promoting the improvement of the overall operation and maintenance level. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings: Figure 1 It is a structural diagram of an information data management system for an intelligent operation and maintenance equipment box of the present invention; Figure 2 It is a flow chart of an information data management method for an intelligent operation and maintenance equipment box of the present invention. DETAILED DESCRIPTION

[0022] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0023] See also Figure 1 and Figure 2The present invention provides a technical solution: an information data management method for an intelligent operation and maintenance equipment box, comprising the following steps: S1. Set the initial acquisition frequency, monitor the equipment box temperature in real time, and adjust the acquisition frequency according to the real-time temperature conditions; S2. Performing vector correction on the gas concentration according to the wind direction and wind speed to obtain a corrected gas concentration vector; S3. Establish a monitoring gas concentration prediction model, calculate the predicted gas concentration, obtain the concentration prediction error value, and analyze the leakage point location coordinates and initial concentration; S4. Real-time collection of strain values ​​of strain gauges in the equipment box to analyze the overall looseness of the equipment box; S5. judging whether the equipment box has a loose fault according to the comparison result between the continuously collected overall loose fault coefficient of the equipment box and the threshold value; S6. Analyze the positional relationship between the leakage point, the equipment box and the maintenance point, consider the number of people in real-time maintenance at the maintenance point, choose to go to the maintenance point where the equipment box with loose faults is repaired, record the maintenance operations in real time during maintenance, and upload the maintenance operations to the database after the maintenance is completed. In step S1, set the initial acquisition frequency f0 and the equipment high temperature alarm threshold T0. The acquisition frequency represents the number of times data is collected in a collection cycle. The collection cycle is set by the equipment box. The real-time monitoring of the equipment box temperature is T. When T<T0, it is judged that the equipment is in normal working condition, and the acquisition frequency remains unchanged at f0; when T≥T0, the abnormal temperature alarm is triggered, and the acquisition frequency is dynamically adjusted to the real-time acquisition frequency f: ; Where k is the adjustment coefficient of the acquisition frequency, and the maximum acquisition frequency of the equipment box is f max , when f≥f is calculated max When the acquisition frequency is adjusted to f max ; In step S2, the gas concentration, wind direction and wind speed of the monitored gas are collected at A locations, wherein the gas concentration of the monitored gas collected at the ath location is B a , wind direction is vector U a , the wind speed is u a , establish a plane rectangular coordinate system, perform vector correction on the gas concentration according to the wind direction and wind speed, and obtain the corrected gas concentration vector C at the ath location a : ; The corrected gas concentration vector C a The direction of indicates the diffusion direction of the monitored gas, and the corrected gas concentration vector C a The size of the mode indicates the gas concentration of the monitored gas; The monitored gas is a dangerous gas generated by the equipment itself during operation. For example, in an electric equipment box, harmful gases such as ozone may be generated due to heating and discharge of electrical components. If the equipment box is used in a chemical scene, toxic and harmful gases may be generated by the volatilization and reaction of chemical raw materials. The specific monitored gas is set by the system.

[0024] From the data collection point of view, the gas concentration B is collected at location A. a , wind direction vector U a With wind speed u a , which builds a comprehensive information foundation for subsequent precise analysis. The summary of data from different locations can reflect the overall situation of the gas environment.

[0025] A plane rectangular coordinate system is established to closely associate wind direction, wind speed and gas concentration data. Taking the power equipment box as an example, harmful gases such as ozone may damage the insulation of the line due to chemical activity and cause short circuits. Accurately monitoring its concentration and diffusion direction can intervene in advance to prevent problems before they occur.

[0026] In the chemical industry, although the types of toxic and harmful gases depend on the system, the vector-corrected C a Accurately presenting its dynamic distribution allows staff to quickly determine the scope of the leak, ensuring the normal operation of the equipment and avoiding shutdowns due to gas problems, greatly improving the safety, reliability and efficiency of intelligent operation and maintenance.

[0027] In step S3, the analysis coordinates are in (x a ,y a ) and establish a monitoring gas concentration prediction model based on the monitoring gas diffusion situation at the ath location: ; in Indicates that at point (x a ,y a ), C0 is the initial concentration of the monitoring gas leakage point to be calculated, D represents the known diffusion coefficient, and the diffusion coefficient of common gases can be obtained through the network. r represents the coordinate (x a ,y a ) and the distance between the gas leakage point with coordinates (x0, y0), and obtain the concentration prediction error value of the a-th location , establish the objective function: ; Where S is the sum of squares of the predicted concentration errors of A locations. The partial derivative of S with respect to x0 is ∂S / ∂x0, the partial derivative of S with respect to y0 is ∂S / ∂y0, and the partial derivative of S with respect to C0 is ∂S / ∂C0. In addition, considering , combined to get the system of equations: ; Substitute into the elimination method to obtain the coordinates of the leakage point (x0, y0) and the initial concentration C0 of the leakage point; By establishing a professional gas concentration prediction model, the gas diffusion trend can be accurately simulated, so that staff can predict in advance the range that the gas may spread and quickly know the leakage area when the leakage just occurs.

[0028] Relying on mathematical derivation and calculation, from constructing the objective function to solving the equations simultaneously, the location of the leak point and the initial concentration are finally determined. This provides a clear direction for quickly repairing the leak problem, shortens the time spent on troubleshooting, allows the equipment box to resume normal operating environment faster, reduces the loss of shutdown caused by gas leakage, improves the overall operation and maintenance efficiency, and ensures the continuous stability of the environment in which the equipment box is located.

[0029] In step S4, the strain values ​​of N strain gauges in the equipment box are collected according to the real-time collection frequency f, and the mean value E of the strain value of the nth strain gauge is calculated: ; Where V represents the number of cycles for collecting strain values ​​of the strain gauge, E n_t represents the strain value of the ith strain gauge collected at the tth time, calculates the standard deviation e of the strain value of the nth strain gauge, and sets the upper threshold of the strain value of the nth strain gauge to E max_n =E+3e, the lower limit threshold of the strain value of the nth strain gauge is E min_n =E-3e, for the strain value collected for the tth time, calculate the loosening failure coefficient F of the nth strain gauge e_t : ; Calculate the overall looseness failure coefficient F of the equipment box t : ; Real-time collection of strain gauge data can keenly capture even the slightest structural changes compared to the traditional manual inspection. Relevant values ​​are obtained through scientific calculations, and then a reasonable warning range is set to accurately identify potential loosening hazards.

[0030] The looseness of the equipment box is quantified as a specific failure coefficient, which is different from the ambiguous judgment method. Once these coefficients are abnormal, they can respond quickly, deploy maintenance resources in advance, and reinforce maintenance in time, effectively preventing small problems from deteriorating into major failures, ensuring the continuous and stable operation of the equipment, and eliminating production interruptions caused by sudden damage.

[0031] Maintaining its structure stably over the long term will keep it in good operating condition at all times, comprehensively improve the level of intelligent operation and maintenance and reliability, and provide solid support for the efficient operation of all industries.

[0032] In step S5, the loose fault threshold F is set min , when continuous g max When the overall looseness fault coefficient of the equipment box is higher than the looseness fault threshold, it is judged that the equipment box has a loose fault; otherwise, it is judged that the equipment box is operating normally, where g max The maximum tolerable number of times the loose failure coefficient set for the system is higher than the loose failure threshold.

[0033] In step S6, the real-time number of maintenance personnel at I maintenance point is collected, the route distance between I maintenance point and the equipment box with loose fault is collected, and the maintenance priority coefficient J of the i-th maintenance point is calculated. i : ; Where P i represents the real-time maintenance staff of the i-th maintenance point, Q i R represents the route distance from the i-th maintenance point to the equipment box with loose fault, i It represents the minimum distance between the route from the i-th maintenance point to the equipment box and the gas leakage point. The maintenance personnel are dispatched from the maintenance point with the highest maintenance priority coefficient to check and repair the equipment box. After the maintenance point is determined, the real-time distance between the maintenance personnel and the equipment box is monitored, and the time for the maintenance personnel to reach the equipment box is estimated. During the maintenance of the equipment box, the maintenance process is recorded in real time through the equipment box and uploaded to the database, and the leakage point is avoided as much as possible. On the one hand, it is for safety reasons. On the other hand, if the leakage point is under construction and repair, it is not conducive for the maintenance personnel to go to the equipment box. The analysis method of the minimum distance between the route from the maintenance point to the equipment box and the gas leakage point is as follows: first, the route is discretized, that is, the route is approximated as a broken line formed by connecting many small segments in sequence. The more small segments there are, the higher the approximation degree is. First, the distance from the point to these approximate segments is calculated, and then the minimum distance among them is found, which is used as the approximate minimum distance between the point and the original curve. As the discretization degree continues to increase, the approximation degree is close to the actual minimum distance.

[0034] An information data management system for an intelligent operation and maintenance equipment box, the system comprising: a temperature monitoring and acquisition frequency control module, a gas concentration vector correction module, a leakage point analysis module, a strain gauge data analysis module, a loose fault identification module, and a maintenance point screening and maintenance record module; The temperature monitoring and acquisition frequency control module sets the initial acquisition frequency, monitors the equipment box temperature in real time, and adjusts the acquisition frequency according to the real-time temperature conditions; The gas concentration vector correction module performs vector correction on the gas concentration according to the wind direction and wind speed to obtain a corrected gas concentration vector; The leakage point analysis module establishes a monitoring gas concentration prediction model, calculates the predicted gas concentration, obtains the concentration prediction error value, and analyzes the leakage point location coordinates and the initial concentration; The strain gauge data analysis module collects the strain value of the strain gauge in the frequency collection equipment box in real time to analyze the overall looseness of the equipment box; The loose fault identification module determines whether the equipment box has a loose fault according to the comparison result of the overall loose fault coefficient of the equipment box collected continuously and the threshold value; The maintenance point screening and maintenance record module analyzes the maintenance point that is most suitable for repairing the equipment box with loose faults, and records and uploads the maintenance process to the database in real time during maintenance.

[0035] Example 1: Taking the intelligent operation and maintenance equipment box used to store hazardous chemical raw materials in a chemical park as an example, the practical application value of the information data management method is fully demonstrated.

[0036] In terms of temperature monitoring, the initial collection cycle is set to 1 hour, 6 collections per hour, and the high temperature alarm threshold T0 is set to 50°C. Under normal circumstances, the temperature T of the equipment box is maintained at around 40°C, and the collection frequency is operated at f0. One day, due to poor heat dissipation of peripheral equipment, the temperature of the equipment box rose rapidly. When T reached 52°C, a high temperature alarm was triggered. According to the set adjustment coefficient k (combined with the maximum collection frequency of the equipment box, k here is 3, and a maximum of 60 collections per hour), the collection frequency is dynamically adjusted to real-time collection to quickly capture temperature changes. The operation and maintenance personnel received the alarm in time to check and avoid the danger of raw materials deteriorating due to high temperature.

[0037] In the gas monitoring phase, data is collected at five key locations around the equipment box. At a certain moment, the chemical gas concentration B is detected at point A. a Rise, wind direction vector U a Pointing to the park living area, wind speed u a is 3m / s, and after vector correction, C a , accurately determine the gas diffusion direction and real-time concentration, and the staff quickly block the dangerous area and evacuate the crowd.

[0038] Once a gas leak is suspected, the concentration prediction model is used to collect data at each point and calculate to successfully locate the coordinates of the leak point (x0, y0) and the initial concentration C0, thus providing a direction for emergency repairs.

[0039] Strain gauge monitoring, real-time collected strain gauge data shows that the overall looseness failure factor F of the equipment box continues to rise over a period of time, exceeding the looseness failure threshold F min , the number of continuous acquisitions reaches the system setting gmax =5 times, it is determined that the equipment box is loose and needs to be reinforced in advance to prevent leakage risks.

[0040] In the maintenance phase, there are 3 maintenance points in the park. According to the real-time number of maintenance personnel at each maintenance point, P i , the distance from the faulty equipment box to the route Q i And the minimum distance R from the gas leakage point i , calculate the maintenance priority coefficient J i , select the best maintenance point, maintenance personnel arrive quickly, and upload the maintenance process in real time to ensure subsequent operation and maintenance review and optimization.

[0041] It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above and that the invention can be implemented in other specific forms without departing from the spirit or essential features of the invention. Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description, and it is intended that all variations falling within the meaning and scope of the equivalent elements of the claims be included in the invention. Any reference numeral in a claim should not be considered as limiting the claim to which it relates.

Claims

1. An information data management method for an intelligent operation and maintenance equipment box, characterized in that: The method comprises the following steps: S1. Set the initial acquisition frequency, monitor the equipment box temperature in real time, and adjust the acquisition frequency according to the real-time temperature conditions; S2. Performing vector correction on the gas concentration according to the wind direction and wind speed to obtain a corrected gas concentration vector; S3. Establish a monitoring gas concentration prediction model, calculate the predicted gas concentration, obtain the concentration prediction error value, and analyze the leakage point location coordinates and initial concentration; S4. Real-time collection of strain values ​​of strain gauges in the equipment box to analyze the overall looseness of the equipment box; S5. judging whether the equipment box has a loose fault according to the comparison result between the continuously collected overall loose fault coefficient of the equipment box and the threshold value; S6. Analyze the positional relationship between the leakage point, the equipment box and the maintenance point, consider the number of people doing maintenance at the maintenance point in real time, choose to go to the maintenance point where the equipment box with loose faults is to be repaired, record the maintenance operations in real time during maintenance and upload the maintenance operations to the database after the maintenance is completed.

2. The information data management method for an intelligent operation and maintenance equipment box according to claim 1 is characterized in that: In step S1, the initial acquisition frequency f0 and the equipment high temperature alarm threshold T0 are set. The acquisition frequency represents the number of times data is collected in one acquisition cycle. The acquisition cycle is set by the equipment box. The real-time monitoring temperature of the equipment box is T. When T<T0, the equipment is judged to be in normal working state, and the acquisition frequency remains unchanged at f0; when T≥T0, the abnormal temperature alarm is triggered, and the acquisition frequency is dynamically adjusted to the real-time acquisition frequency f: ； Where k is the adjustment coefficient of the acquisition frequency.

3. The information data management method for an intelligent operation and maintenance equipment box according to claim 2 is characterized in that: In step S2, the gas concentration, wind direction and wind speed of the monitored gas are collected at A locations, wherein the gas concentration of the monitored gas collected at the ath location is B a , wind direction is vector U a , the wind speed is u a , establish a plane rectangular coordinate system, perform vector correction on the gas concentration according to the wind direction and wind speed, and obtain the corrected gas concentration vector C at the ath location a : ； The corrected gas concentration vector C a The direction of indicates the diffusion direction of the monitored gas, and the corrected gas concentration vector C a The size of the modulus indicates the gas concentration of the monitored gas.

4. The information data management method for an intelligent operation and maintenance equipment box according to claim 3 is characterized in that: In step S3, the analysis coordinates are in (x a ,y a ) and establish a monitoring gas concentration prediction model based on the monitoring gas diffusion situation at the a-th location: ； in Indicates that at point (x a ,y a ), C0 is the initial concentration of the monitoring gas leakage point to be calculated, D represents the known diffusion coefficient, and r represents the coordinate (x a ,y a The distance between the position of the ath location and the gas leakage point with coordinates (x0, y0) is used to obtain the concentration prediction error value e at the ath location. a , , establish the objective function: ； Where S is the sum of squares of the predicted concentration errors of A locations. The partial derivative of S with respect to x0 is ∂S / ∂x0, the partial derivative of S with respect to y0 is ∂S / ∂y0, and the partial derivative of S with respect to C0 is ∂S / ∂C0. In addition, considering , combined to get the system of equations: ； Substituting into the elimination method, we can obtain the coordinates of the leakage point (x0, y0) and the initial concentration C0 of the leakage point.

5. The information data management method for intelligent operation and maintenance equipment box according to claim 4 is characterized in that: In step S4, the strain values ​​of N strain gauges in the equipment box are collected according to the real-time collection frequency f, and the mean value E of the strain value of the nth strain gauge is calculated: ； Where V represents the number of cycles for collecting strain values ​​of the strain gauge, E n_t Indicates the strain value of the i-th strain gauge collected for the t-th time, calculates the standard deviation e of the strain value of the n-th strain gauge, and sets the upper threshold of the strain value of the n-th strain gauge to E max_n =E+3e, the lower limit threshold of the strain value of the nth strain gauge is E min_n =E-3e, for the strain value collected for the tth time, calculate the loosening failure coefficient F of the nth strain gauge e_t : ； Calculate the overall looseness failure coefficient F of the equipment box t : 。 6. The information data management method for intelligent operation and maintenance equipment box according to claim 5 is characterized in that: In step S5, the loose fault threshold F is set min , when continuous g max When the overall looseness fault coefficient of the equipment box is higher than the looseness fault threshold, it is judged that the equipment box has a loose fault; otherwise, it is judged that the equipment box is operating normally, where g max The maximum tolerable number of times the loose failure coefficient set for the system is higher than the loose failure threshold.

7. The information data management method for intelligent operation and maintenance equipment box according to claim 6 is characterized in that: In step S6, the real-time number of maintenance personnel at I maintenance point is collected, the route distance between I maintenance point and the equipment box with loose fault is collected, and the maintenance priority coefficient J of the i-th maintenance point is calculated. i : ； Where P i represents the real-time maintenance staff of the i-th maintenance point, Q i represents the route distance from the ith maintenance point to the equipment box with loose fault, R i It represents the minimum distance between the route from the i-th maintenance point to the equipment box and the gas leakage point, and dispatches maintenance personnel from the maintenance point with the highest maintenance priority coefficient to inspect and repair the equipment box.

8. The information data management method for intelligent operation and maintenance equipment box according to claim 7 is characterized in that: After the maintenance point is determined, the real-time distance between the maintenance personnel and the equipment box is monitored, and the time it takes for the maintenance personnel to reach the equipment box is estimated. When the maintenance personnel is repairing the equipment box, the maintenance process is recorded in real time through the equipment box and uploaded to the database.

9. An information data management system for an intelligent operation and maintenance equipment box, the system being applied to an information data management method for an intelligent operation and maintenance equipment box according to any one of claims 1 to 8, characterized in that: The system includes: a temperature monitoring and acquisition frequency control module, a gas concentration vector correction module, a leakage point analysis module, a strain gauge data analysis module, a loose fault identification module and a maintenance point screening and maintenance record module; The temperature monitoring and acquisition frequency control module sets the initial acquisition frequency, monitors the equipment box temperature in real time, and adjusts the acquisition frequency according to the real-time temperature conditions; The gas concentration vector correction module performs vector correction on the gas concentration according to the wind direction and wind speed to obtain a corrected gas concentration vector; The leakage point analysis module establishes a monitoring gas concentration prediction model, calculates the predicted gas concentration, obtains the concentration prediction error value, and analyzes the leakage point location coordinates and the initial concentration; The strain gauge data analysis module collects the strain value of the strain gauge in the frequency collection equipment box in real time to analyze the overall looseness of the equipment box; The loose fault identification module determines whether the equipment box has a loose fault according to the comparison result of the overall loose fault coefficient of the equipment box collected continuously and the threshold value; The maintenance point screening and maintenance record module analyzes the most suitable maintenance point for repairing the equipment box with loose faults, records the maintenance operation in real time during maintenance, and uploads the maintenance operation video to the database.

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