A fire protection pipeline monitoring method, system, terminal equipment and storage medium

Abstract

The present application relates to the field of fire protection technology, and in particular to a fire protection pipeline monitoring method, system, terminal device and storage medium. The method includes: if the pipeline surface image data meets the preset pipeline shallow hidden danger standard, then obtain the pipeline quality monitoring item corresponding to the fire protection pipeline; if the pipeline quality monitoring item does not meet the preset pipeline quality monitoring index, then obtain the corresponding abnormal pipeline quality monitoring item; if there are multiple abnormal pipeline quality monitoring items, then obtain the first-level pipeline damage coefficient corresponding to each abnormal pipeline quality monitoring item; if there is a correlation effect between the abnormal pipeline quality monitoring items, then obtain the second-level pipeline damage coefficient corresponding to the abnormal pipeline quality monitoring item; combine the first-level pipeline damage coefficient, the second-level pipeline damage coefficient and the pipeline surface image data to generate a damage determination report corresponding to the fire protection pipeline. The fire protection pipeline monitoring method, system, terminal device and storage medium provided in the present application have the effect of improving the safety of fire protection pipeline monitoring.

Description

Technical Field

[0001] The present application relates to the field of fire protection technology, and in particular to a fire protection pipeline monitoring method, system, terminal equipment and storage medium. Background Art

[0002] Fire pipes are special pipes used to discharge water to prevent fires and protect lives and property. They can be connected to fire water pools or other water sources and inject water into the fire scene to suppress the flames when necessary.

[0003] At present, the safety monitoring of fire protection pipelines includes: regular inspection and maintenance, installation of data acquisition systems to monitor the internal pressure, flow and temperature of the pipelines in real time, installation of sensors to monitor the water quality of the pipelines, installation of alarms and regular pipeline inspections to ensure the safe use of the pipelines.

[0004] In actual applications, current technology cannot effectively monitor subtle changes inside the pipeline, such as deformation and deterioration of the pipeline material, thinning of the inner wall of the pipeline, etc., which will cause instability in the fire protection pipeline system, resulting in rupture of the fire protection pipeline, causing loss of life and property. Summary of the invention

[0005] In order to improve the safety of fire protection pipeline monitoring, the present application provides a fire protection pipeline monitoring method, system, terminal device and storage medium.

[0006] In a first aspect, the present application provides a fire protection pipeline monitoring method, comprising the following steps:

[0007] Obtain monitoring data of fire protection pipelines;

[0008] Identify the monitoring data and obtain corresponding pipeline surface image data;

[0009] If the pipeline surface image data meets the preset pipeline shallow hidden danger standard, then obtain the pipeline quality monitoring item corresponding to the fire protection pipeline;

[0010] If the pipeline quality monitoring item does not meet the preset pipeline quality monitoring index, the corresponding abnormal pipeline quality monitoring item is obtained;

[0011] If there are multiple abnormal pipeline quality monitoring items, then obtain the primary pipeline damage coefficient corresponding to each abnormal pipeline quality monitoring item;

[0012] If there is a correlation effect between the abnormal pipeline quality monitoring items, then obtaining the secondary pipeline damage coefficient corresponding to the abnormal pipeline quality monitoring item;

[0013] A damage determination report corresponding to the fire protection pipeline is generated by combining the primary pipeline damage coefficient, the secondary pipeline damage coefficient and the pipeline surface image data.

[0014] By adopting the above technical scheme, it is judged whether the pipeline surface image data corresponding to the current fire protection pipeline is abnormal according to the preset pipeline shallow hidden danger standard, that is, whether the pipeline has shallow defects. If so, it means that the current pipeline has been damaged. In order to further analyze its damage, the pipeline quality monitoring items corresponding to the fire protection pipeline are analyzed and judged one by one according to the preset pipeline quality monitoring indicators. If an abnormality occurs, the corresponding abnormal pipeline quality monitoring item is obtained. If there are multiple abnormal pipeline quality monitoring items, the first-level pipeline damage coefficient of each abnormal pipeline quality monitoring item causing direct damage to the pipeline is obtained. If there is a correlation effect between the abnormal pipeline quality monitoring items at the same time, the second-level pipeline damage coefficient of the abnormal pipeline quality monitoring item causing indirect damage to the pipeline is further obtained. Then, the first-level pipeline damage coefficient, the second-level pipeline damage coefficient and the pipeline surface image data obtained above are combined to generate a damage determination report for comprehensive damage assessment of the fire protection pipeline. Due to the comprehensive analysis and evaluation of the shallow hidden dangers of the fire protection pipeline and the corresponding deep damage hidden dangers of the specific shallow hidden dangers, the safety of fire protection pipeline monitoring is improved.

[0015] Optionally, after identifying the monitoring data and acquiring the corresponding pipeline surface image data, the following steps are also included:

[0016] If the pipeline surface image data meets the preset pipeline shallow hidden danger standard, then obtain the corresponding shallow hidden danger characteristics;

[0017] If there is a corresponding historical hidden danger feature record for the shallow hidden danger feature, then the historical induction frequency and historical damage identification score corresponding to the shallow hidden danger feature in the historical hidden danger feature record are obtained;

[0018] The shallow hidden danger characteristics are analyzed in combination with the historical induction frequency and the historical damage identification score to generate a target damage level corresponding to the current fire protection pipeline.

[0019] By adopting the above technical solution, the damage level of the current pipeline is graded in combination with the historical induction frequency of shallow hidden danger characteristics and the historical damage identification score, thereby improving the accuracy of pipeline safety monitoring.

[0020] Optionally, if there is a corresponding historical hidden danger feature record for the shallow hidden danger feature, after obtaining the historical induction frequency and historical damage identification score corresponding to the shallow hidden danger feature in the historical hidden danger feature record, the following steps are also included:

[0021] If the historical induction frequency exceeds the preset frequency standard, the damage distribution level corresponding to the fire protection pipeline is obtained according to the historical damage identification score;

[0022] In combination with the damage distribution level and the historical induction frequency, a service life prediction result corresponding to the fire protection pipeline is output.

[0023] By adopting the above technical solution, if the historical induction frequency exceeds the corresponding preset frequency standard, it means that the current fire protection pipeline has experienced a large number of similar or abnormal damages in history. Further combined with the damage distribution level and historical induction frequency corresponding to each historical damage identification score, a comprehensive assessment is performed to obtain the prediction result of the remaining service life of the fire protection pipeline, thereby improving the monitoring effect of the safety of fire protection pipeline use.

[0024] Optionally, if there are multiple abnormal pipeline quality monitoring items, obtaining the primary pipeline damage coefficient corresponding to each abnormal pipeline quality monitoring item includes the following steps:

[0025] If there are multiple abnormal pipeline quality monitoring items, then obtaining the target monitoring value corresponding to each abnormal pipeline quality monitoring item;

[0026] If the target monitoring value exceeds the preset pipeline damage threshold, the corresponding damage category level is obtained according to the target monitoring value;

[0027] A comprehensive damage determination is performed on the fire protection pipeline in combination with the damage category level, and a primary pipeline damage coefficient corresponding to the fire protection pipeline is output.

[0028] By adopting the above technical solution, if the target monitoring value exceeds the preset pipeline damage threshold, it means that the abnormal pipeline quality monitoring item corresponding to the target monitoring value is already in the stage of seriously affecting the fire protection pipeline. The fire protection pipeline is further comprehensively judged for damage based on the damage category level corresponding to the target monitoring value, thereby improving the damage monitoring effect of the fire protection pipeline.

[0029] Optionally, if there are multiple abnormal pipeline quality monitoring items, after obtaining the target monitoring value corresponding to each abnormal pipeline quality monitoring item, the method further includes the following steps:

[0030] If the target monitoring value exceeds the preset pipeline damage threshold, obtaining the inducing source of the abnormal pipeline quality monitoring item corresponding to the target monitoring value;

[0031] If there are multiple inducing sources, then obtain the abnormal contribution ratio corresponding to each of the inducing sources;

[0032] In combination with the abnormal contribution ratio, an abnormal item distribution table corresponding to the abnormal pipeline quality monitoring item is generated.

[0033] By adopting the above technical solution and combining the abnormal contribution ratio of each inducing source, the distribution of abnormal factors that indirectly affect the safety of fire protection pipelines can be obtained more intuitively.

[0034] Optionally, if there is a correlation influence between the abnormal pipeline quality monitoring items, obtaining the secondary pipeline damage coefficient corresponding to the abnormal pipeline quality monitoring item includes the following steps:

[0035] If there is a correlation influence between the abnormal pipeline quality monitoring items, then obtaining the correlation influence degree between the abnormal pipeline quality monitoring items corresponding to the mutual correlation influence;

[0036] According to the correlation influence degree, the secondary pipeline damage coefficient corresponding to the abnormal pipeline quality monitoring item is output.

[0037] By adopting the above technical solution, the specific correlation impact degree between abnormal pipeline quality monitoring items is used as the secondary pipeline damage coefficient corresponding to the fire protection pipeline. On the basis of monitoring the direct damage to the fire protection pipeline, the corresponding potential indirect damage can also be evaluated, thereby improving the safety monitoring effect of the fire protection pipeline.

[0038] Optionally, if there is a correlation influence between the abnormal pipeline quality monitoring items, after obtaining the correlation influence degree between the abnormal pipeline quality monitoring items corresponding to the mutual correlation influence, the following steps are also included:

[0039] According to the association impact, obtaining a corresponding association category;

[0040] If the association category is a one-way association, the corresponding association root point and association inducing point in the abnormal pipeline quality monitoring item are determined and acquired, and a corresponding association indication table is generated according to the association root point and the association inducing point;

[0041] If the association category is a bidirectional association, the corresponding association indication table is generated according to the association influence coefficient corresponding to the abnormal pipeline quality monitoring item.

[0042] By adopting the above technical solution, corresponding influencing factor analysis strategies between abnormal pipeline quality monitoring items are set according to the association categories corresponding to the association influence degrees, thereby improving the safety analysis effect of potential hidden dangers of fire protection pipelines.

[0043] In a second aspect, the present application provides a fire protection pipeline monitoring system, comprising:

[0044] A first acquisition module is used to acquire monitoring data of fire protection pipelines;

[0045] An identification module, used to identify the monitoring data and obtain corresponding pipeline surface image data;

[0046] A second acquisition module, if the pipeline surface image data meets the preset pipeline shallow hidden danger standard, the second acquisition module is used to obtain the pipeline quality monitoring item corresponding to the fire protection pipeline;

[0047] A third acquisition module, if the pipeline quality monitoring item does not meet the preset pipeline quality monitoring index, the third acquisition module is used to obtain the corresponding abnormal pipeline quality monitoring item;

[0048] A first evaluation module, if there are multiple abnormal pipeline quality monitoring items, the first evaluation module is used to obtain the primary pipeline damage coefficient corresponding to each abnormal pipeline quality monitoring item;

[0049] A second evaluation module, if there is a correlation influence between the abnormal pipeline quality monitoring items, the second evaluation module is used to obtain the secondary pipeline damage coefficient corresponding to the abnormal pipeline quality monitoring item;

[0050] The combining module is used to combine the primary pipeline damage coefficient, the secondary pipeline damage coefficient and the pipeline surface image data to generate a damage determination report corresponding to the fire protection pipeline.

[0051] By adopting the above technical scheme, it is judged whether the pipeline surface image data corresponding to the fire protection pipeline currently obtained by the identification module is abnormal according to the preset pipeline shallow hidden danger standard, that is, whether the pipeline has shallow defects. If it is, it means that the current pipeline has been damaged. In order to further analyze its damage, the pipeline quality monitoring items corresponding to the fire protection pipeline are analyzed and judged one by one according to the preset pipeline quality monitoring indicators. If an abnormality occurs, the corresponding abnormal pipeline quality monitoring items are obtained through the third acquisition module. If there are multiple abnormal pipeline quality monitoring items, the first-level pipeline damage coefficient of each abnormal pipeline quality monitoring item causing direct damage to the pipeline is obtained through the first evaluation module. If there is a correlation effect between the abnormal pipeline quality monitoring items at the same time, the second-level pipeline damage coefficient of the abnormal pipeline quality monitoring item causing indirect damage to the pipeline is further obtained through the second evaluation module. Then, the combination module combines the first-level pipeline damage coefficient, the second-level pipeline damage coefficient and the pipeline surface image data obtained above to generate a damage determination report for comprehensive damage assessment of the fire protection pipeline. Due to the comprehensive analysis and evaluation of the shallow hidden dangers of the fire protection pipeline and the corresponding deep damage hidden dangers of the specific shallow hidden dangers, the safety of fire protection pipeline monitoring is improved.

[0052] In a third aspect, the present application provides a terminal device, which adopts the following technical solution:

[0053] A terminal device includes a memory and a processor, wherein the memory stores computer instructions that can be run on the processor, and when the processor loads and executes the computer instructions, the above-mentioned fire protection pipeline monitoring method is adopted.

[0054] By adopting the above technical solution, the above-mentioned fire pipeline monitoring method is generated into computer instructions and stored in the memory so as to be loaded and executed by the processor, thereby making a terminal device based on the memory and the processor for easy use.

[0055] In a fourth aspect, the present application provides a computer-readable storage medium, which adopts the following technical solution:

[0056] A computer-readable storage medium stores computer instructions. When the computer instructions are loaded and executed by a processor, the above-mentioned fire protection pipeline monitoring method is adopted.

[0057] By adopting the above technical solution, the above-mentioned fire pipeline monitoring method is generated into computer instructions, and stored in a computer-readable storage medium so as to be loaded and executed by a processor. The computer-readable storage medium facilitates the reading and storage of computer instructions.

[0058] In summary, the present application includes at least one of the following beneficial technical effects: judging whether the pipeline surface image data corresponding to the current fire protection pipeline is abnormal according to the preset pipeline shallow hidden danger standard, that is, whether the pipeline has shallow defects; if so, it means that the current pipeline has been damaged; in order to further analyze its damage, the pipeline quality monitoring items corresponding to the fire protection pipeline are analyzed and judged one by one according to the preset pipeline quality monitoring indicators; if an abnormality occurs, the corresponding abnormal pipeline quality monitoring item is obtained; if there are multiple abnormal pipeline quality monitoring items, the first-level pipeline damage coefficient of direct damage caused by each abnormal pipeline quality monitoring item to the pipeline is obtained; if there is a correlation effect between the abnormal pipeline quality monitoring items at the same time, the second-level pipeline damage coefficient of indirect damage caused by the abnormal pipeline quality monitoring item to the pipeline is further obtained; then, the first-level pipeline damage coefficient, the second-level pipeline damage coefficient and the pipeline surface image data obtained above are combined to generate a damage determination report for comprehensive damage assessment of the fire protection pipeline; due to the comprehensive analysis and evaluation of the shallow hidden dangers of the fire protection pipeline and the corresponding deep damage hidden dangers of the specific shallow hidden dangers, the safety of fire protection pipeline monitoring is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 It is a flow chart of steps S101 to S107 in a fire protection pipeline monitoring method of the present invention.

[0060] Figure 2 It is a flow chart of steps S201 to S203 in a fire protection pipeline monitoring method of the present invention.

[0061] Figure 3 It is a flow chart of step S301 to step S302 in a fire protection pipeline monitoring method of the present invention.

[0062] Figure 4 It is a flow chart of steps S401 to S403 in a fire protection pipeline monitoring method of the present invention.

[0063] Figure 5 It is a flow chart of steps S501 to S503 in a fire protection pipeline monitoring method of the present invention.

[0064] Figure 6 It is a flow chart of step S601 to step S602 in a fire protection pipeline monitoring method of the present invention.

[0065] Figure 7 It is a flow chart of step S701 to step S702 in a fire protection pipeline monitoring method of the present invention.

[0066] Figure 8 It is a module schematic diagram of a fire protection pipeline monitoring system of the present invention.

[0067] Description of reference numerals:

[0068] 1. First acquisition module; 2. Identification module; 3. Second acquisition module; 4. Third acquisition module; 5. First evaluation module; 6. Second evaluation module; 7. Combination module. DETAILED DESCRIPTION

[0069] The following is combined with Figure 1-8 This application is described in further detail.

[0070] The present application embodiment discloses a fire protection pipeline monitoring method, such as Figure 1 As shown, the following steps are included:

[0071] S101. Obtain monitoring data of fire protection pipeline;

[0072] S102. Identify monitoring data and obtain corresponding pipeline surface image data;

[0073] S103. If the pipeline surface image data meets the preset pipeline shallow hidden danger standard, then obtain the pipeline quality monitoring item corresponding to the fire protection pipeline;

[0074] S104. If the pipeline quality monitoring item does not meet the preset pipeline quality monitoring index, obtain the corresponding abnormal pipeline quality monitoring item;

[0075] S105. If there are multiple abnormal pipeline quality monitoring items, obtain the primary pipeline damage coefficient corresponding to each abnormal pipeline quality monitoring item;

[0076] S106. If there is a correlation effect between the abnormal pipeline quality monitoring items, obtain the secondary pipeline damage coefficient corresponding to the abnormal pipeline quality monitoring item;

[0077] S107. Generate a damage assessment report corresponding to the fire protection pipeline by combining the primary pipeline damage coefficient, the secondary pipeline damage coefficient and the pipeline surface image data.

[0078] In step S101, the monitoring data of the fire protection pipeline refers to the data required to be monitored when conducting a safety inspection on the fire protection pipeline, for example, the water pressure, flow, pressure, temperature, water level, water quality, humidity, pipeline surface image and other data corresponding to the fire protection pipeline showing the safety status of the fire protection pipeline.

[0079] Among them, the above-mentioned monitoring data can be obtained through monitoring instruments or devices with corresponding supporting functions. For example, water quality can be measured by installing a water quality analyzer or water quality tester in the fire protection pipe, or the surface image of the pipe can be obtained by installing a camera.

[0080] In step S102, by identifying the monitoring data, the pipeline surface image data corresponding to the fire protection pipeline can be further obtained. The pipeline surface image data refers to the pipeline structure, pipeline material, pipeline diameter / thickness and pipeline characteristic information obtained by identifying the pipeline surface image.

[0081] In step S103, the preset pipeline shallow hidden danger standard refers to a preset characteristic standard for identifying damage to the fire protection pipeline or related shallow hidden dangers. For example, the preset pipeline shallow hidden danger standard can be a characteristic identification standard for identifying wear, cracking or corrosion on the pipeline surface.

[0082] Among them, if the pipeline surface image data meets the preset pipeline shallow hidden danger standard, it means that the current fire protection pipeline has been damaged. In order to further analyze the deep safety hazards of the fire protection pipeline, the pipeline quality monitoring items corresponding to the fire protection pipeline are obtained. The pipeline quality monitoring items refer to items for the quality and safety monitoring of fire protection pipelines. Specifically, the pipeline quality monitoring items may include inspecting the pipeline outer shell, inspecting the water pressure inside the pipeline, monitoring the accumulated water, adding fire spray in the pipeline and inspecting it regularly, testing the strength of the pipeline material, and regularly testing the performance of the fire protection pipeline.

[0083] Furthermore, if the pipeline surface image data does not meet the preset pipeline shallow hidden danger standard, it means that the current fire protection pipeline has not yet encountered relevant safety hazards, and then continue to obtain the pipeline surface image data corresponding to the current fire protection pipeline through relevant monitoring equipment.

[0084] In step S104, the preset pipeline quality monitoring index refers to the preset safety identification standard corresponding to the fire protection pipeline monitoring items. The pipeline quality monitoring items mentioned in this solution include but are not limited to the ambient temperature, humidity, wind speed of the fire protection pipeline, and internal factors of the pipeline, such as water quality, flow size, flow rate and water pressure.

[0085] Among them, if the pipeline quality monitoring items do not meet the preset pipeline quality monitoring indicators, it means that there are corresponding potential hidden dangers in the current fire protection pipeline. In order to further distinguish and deeply analyze the potential hidden dangers, the pipeline quality monitoring items that do not meet the preset pipeline quality monitoring indicators will be marked as abnormal pipeline quality monitoring items.

[0086] Furthermore, if the pipeline quality monitoring items meet the preset pipeline quality monitoring indicators, it means that the surface damage of the current fire protection pipeline may be caused by some external forces. For example, vehicle collision, building vibration or earthquake, etc., which may cause the fire protection pipeline to deform, or even cause the pipeline to rupture and leak.

[0087] In step S105, if there are multiple abnormal pipeline quality monitoring items, the first-level pipeline damage coefficient corresponding to each abnormal pipeline quality monitoring item is obtained. The first-level pipeline damage coefficient refers to an indicator of the deformation, thinning, corrosion and deterioration of the pipeline. It indicates the operating status of the pipeline. Generally, the larger the pipeline damage coefficient, the more serious the deformation, thinning and deterioration of the pipeline, and timely maintenance or replacement is required to ensure the normal operation of the fire protection system.

[0088] For example, the abnormal pipeline quality monitoring item is pipeline vibration. Since the vibration of the fire-fighting pipeline may cause the bending, deformation and fracture of the pipeline, and may also cause brittle fracture of the welded structure, the corresponding first-level pipeline damage coefficient is the amplitude or degree of vibration. If the vibration of the fire-fighting pipeline reaches more than 10 times the allowable standard, the above-mentioned damage may be caused. The allowable standard is a linear buffer of vibration time of 150-500 microseconds / meter.

[0089] Furthermore, if there is only one abnormal pipeline quality monitoring item, the monitoring data corresponding to the abnormal pipeline quality monitoring item is directly output, and relevant safety protection processing is further performed on the fire protection pipeline based on the monitoring data.

[0090] In step S106, the existence of associated influences between abnormal pipeline quality monitoring items refers to the existence of an influence and being influenced relationship between abnormal pipeline quality monitoring items. For example, there is a correlation between the temperature and water pressure in the fire-fighting pipe. When the temperature in the fire-fighting pipe is too high, the water pressure will increase. Among them, the increase in water pressure in the fire-fighting pipe will have a great impact on the pipe. It may cause uneven force on the pipe, thereby causing failures such as breakage and bursting, and may also cause the pipe structure to deform, and may even cause the pipe to leak. On the contrary, when the temperature in the fire-fighting pipe is too low, the water pressure in the pipe will decrease. The decrease in water pressure in the fire-fighting pipe will have a significant impact on the pipe. For example, it may reduce the durability of the pipe, thereby causing abnormal conditions such as breakage and deformation of the pipe, and may also cause the pipe to leak.

[0091] If there is a correlation influence between the abnormal pipeline quality monitoring items, the secondary pipeline damage coefficient corresponding to the abnormal pipeline quality monitoring item is obtained, and the secondary pipeline damage coefficient refers to the correlation influence degree of one type of abnormal pipeline quality monitoring item on another type of abnormal pipeline quality monitoring item. For example, the influence degree of the temperature in the fire protection pipeline on the water pressure in the fire protection pipeline.

[0092] In step S107, based on the first-level pipeline damage coefficient and the second-level pipeline damage coefficient obtained above and combined with the pipeline surface image data, a damage determination report indicating the specific damage degree of the current fire protection pipeline is generated. Through the damage determination report, the direct damage suffered by the currently monitored fire protection pipeline and the corresponding potential damage-related hidden dangers can be obtained.

[0093] The fire protection pipeline monitoring method provided in the present embodiment determines whether the pipeline surface image data corresponding to the current fire protection pipeline is abnormal, that is, whether the pipeline has shallow defects according to the preset pipeline shallow hidden danger standard. If it is, it means that the current pipeline has been damaged. In order to further analyze its damage, the pipeline quality monitoring items corresponding to the fire protection pipeline are analyzed and judged one by one according to the preset pipeline quality monitoring indicators. If an abnormality occurs, the corresponding abnormal pipeline quality monitoring item is obtained. If there are multiple abnormal pipeline quality monitoring items, the first-level pipeline damage coefficient of each abnormal pipeline quality monitoring item causing direct damage to the pipeline is obtained. If there is a correlation effect between the abnormal pipeline quality monitoring items at the same time, the second-level pipeline damage coefficient of the abnormal pipeline quality monitoring item causing indirect damage to the pipeline is further obtained. Then, the first-level pipeline damage coefficient, the second-level pipeline damage coefficient and the pipeline surface image data obtained above are combined to generate a damage determination report for comprehensive damage assessment of the fire protection pipeline. Due to the comprehensive analysis and evaluation of the shallow hidden dangers of the fire protection pipeline and the corresponding deep damage hidden dangers of the specific shallow hidden dangers, the safety of fire protection pipeline monitoring is improved.

[0094] In one implementation of this embodiment, Figure 2 As shown, after step S102, that is, identifying the monitoring data and obtaining the corresponding pipeline surface image data, the following steps are also included:

[0095] S201. If the pipeline surface image data meets the preset pipeline shallow hidden danger standard, then obtain the corresponding shallow hidden danger characteristics;

[0096] S202. If there is a corresponding historical hidden danger feature record for the shallow hidden danger feature, then the historical induced frequency and historical damage identification score corresponding to the shallow hidden danger feature in the historical hidden danger feature record are obtained;

[0097] S203. Analyze the characteristics of shallow hidden dangers by combining the historical induction frequency and historical damage identification score, and generate the target damage level corresponding to the current fire protection pipeline.

[0098] In step S201, the shallow hidden danger features refer to the hidden danger features of the fire protection pipeline surface discoloration, abnormal temperature change, scaling, cracks, wear and condensation. If the pipeline surface image data meets the preset pipeline shallow hidden danger standard, it means that the current fire protection pipeline surface has actually been damaged, and the shallow hidden danger features of its surface are further obtained to facilitate the identification of the damage.

[0099] In step S202, the historical hidden danger feature record refers to the relevant historical record of damage features that have appeared in the fire protection pipeline, the historical induction frequency refers to the number of times the same type of damage features appear in the historical hidden danger feature record, and the historical damage identification score refers to the damage situation identification score for each occurrence of the same type of damage features.

[0100] For example, the shallow hidden danger feature corresponding to the current fire protection pipeline is surface cracks. The feature is further identified to obtain the corresponding historical surface crack feature record, that is, the historical hidden danger feature record. The corresponding historical induction frequency is further obtained through the historical surface crack feature record, which is 3 times. The 3 specific historical damage identification scores are based on the size, type, location and other conditions of the cracks on the pipeline surface. The specific identification and scoring standards can refer to the relevant provisions on "pipeline surface defects" in the "Technical Specifications for Fire Protection Pipeline Quality Assessment".

[0101] In step S203, the historical induction frequency will affect the determination of the target damage level corresponding to the fire protection pipeline. Generally speaking, multiple cracks will increase the damage level. On the other hand, the damage identification score induced by each surface row is also a condition for the determination of the target damage level of the fire protection pipeline. Therefore, a comprehensive evaluation can be performed based on the actual historical induction frequency of the current fire protection pipeline and the corresponding historical damage identification score of each induction to generate the target damage level corresponding to the fire protection pipeline. The target damage level can be divided into three levels: mild, moderate and severe, and the corresponding damage identification scores are 0-60 points, 61-80 points and 81 points-100 points respectively.

[0102] The fire protection pipeline monitoring method provided in this embodiment combines the historical induction frequency of shallow hidden danger characteristics and the historical damage identification score to grade the damage of the current pipeline, thereby improving the accuracy of safety monitoring of the pipeline.

[0103] In one implementation of this embodiment, Figure 3 As shown, in step S202, i.e., if there is a corresponding historical hidden danger feature record for the shallow hidden danger feature, then after obtaining the historical induced frequency and historical damage identification score corresponding to the shallow hidden danger feature in the historical hidden danger feature record, the following steps are also included:

[0104] S301. If the historical induction frequency exceeds the preset frequency standard, the damage distribution level corresponding to the fire protection pipeline is obtained according to the historical damage identification score;

[0105] S302. Combine the damage distribution level and the historical induction frequency to output the corresponding service life prediction result of the fire protection pipeline.

[0106] In step S301, the preset frequency standard refers to the preset safety frequency standard for the number of times the same type of damage is induced. For example, according to the preset frequency standard of the Technical Specifications for Fire Pipeline Quality Assessment, if the number of fire pipeline cracks that occur exceeds 10 times within 3-6 months, it is a dangerous state, and its dangers include deterioration or strength reduction of pipeline materials, peeling of coatings, abnormal odors, and significant temperature changes, etc. The corresponding damage assessment score is 85 points, which belongs to the severe target damage level.

[0107] For example, the characteristic of shallow hidden dangers is surface wear, and its corresponding preset frequency standard is that the number of cracks in fire pipes appears more than 8 times within 3-6 months, which is a dangerous state. The specific damage identification scoring standards are: the wear length is greater than or equal to 2mm, and the corresponding damage identification score is 3 points, which belongs to the light target damage level; the wear depth is greater than 2mm, and the corresponding damage identification score is 6 points, which belongs to the moderate target damage level; the wear shape is grooves, and the corresponding damage identification score is 9 points, which belongs to the severe target damage level; the influencing factors are mechanical and physical effects, and the corresponding damage identification score is 12 points, which belongs to the serious target damage level.

[0108] Among them, the above-mentioned shallow hidden danger characteristics may appear alone or in combination. According to the actual situation, a comprehensive analysis is conducted based on the historical damage identification scores corresponding to the above-mentioned shallow hidden danger characteristics to obtain the damage distribution level corresponding to the fire protection pipeline. For example, when the shallow hidden danger characteristics appear as surface wear and surface cracks, the corresponding damage distribution level includes the target damage level corresponding to surface wear and surface cracks.

[0109] In step S302, the damage distribution level and historical induction frequency can provide important information for the service life prediction of fire protection pipelines. First, by evaluating the structure, material and damage status of the fire protection pipeline, the damage distribution level can be obtained. Then, according to the historical damage induction frequency, the damage impact range and potential safety hazards can be evaluated accordingly, and finally the service life prediction results corresponding to the consumer pipeline can be obtained.

[0110] In the fire protection pipeline monitoring method provided in this embodiment, if the historical induction frequency exceeds the corresponding preset frequency standard, it means that the current fire protection pipeline has experienced a relatively large number of similar or abnormal damages in history. Further, a comprehensive assessment is performed based on the damage distribution level and the historical induction frequency corresponding to each historical damage identification score to obtain a prediction result of the remaining service life of the fire protection pipeline, thereby improving the monitoring effect of the safety of fire protection pipeline use.

[0111] In one implementation of this embodiment, Figure 4 As shown, step S105, that is, if there are multiple abnormal pipeline quality monitoring items, obtaining the primary pipeline damage coefficient corresponding to each abnormal pipeline quality monitoring item includes the following steps:

[0112] S401. If there are multiple abnormal pipeline quality monitoring items, obtain the target monitoring value corresponding to each abnormal pipeline quality monitoring item;

[0113] S402. If the target monitoring value exceeds the preset pipeline damage threshold, the corresponding damage category level is obtained according to the target monitoring value;

[0114] S403. Perform a comprehensive damage assessment on the fire protection pipeline in combination with the damage category level, and output the first-level pipeline damage coefficient corresponding to the fire protection pipeline.

[0115] In step S401, the abnormal pipeline quality monitoring items mentioned in this solution are mainly abnormal monitoring items that affect the subtle changes inside the monitoring pipeline, such as deformation and deterioration of pipeline materials, thinning of the inner wall of the pipeline, etc.

[0116] Among them, the quality monitoring indicators that affect the deformation, thinning of the pipe wall and deterioration of fire protection pipes mainly include temperature monitoring, water pressure monitoring, material appearance monitoring, water stain performance monitoring, surface wear monitoring, wall thickness change monitoring, etc. By monitoring the above indicators, the deformation, thinning of the pipe wall and deterioration of fire protection pipes can be effectively identified, thereby ensuring the safe use of fire protection pipes.

[0117] Secondly, the target monitoring values ​​corresponding to the abnormal pipeline quality monitoring items can be set according to different types (group types). For example, in terms of water pressure monitoring, it can be set according to three levels: low pressure, medium pressure and high pressure, while in terms of material appearance monitoring, it should be set according to the use environment and fire protection system requirements.

[0118] In step S402, the preset pipeline damage threshold refers to a standard for determining that the pipeline is currently in a damaged state when a preset target monitoring value is within a certain numerical range.

[0119] For example, the abnormal pipeline quality monitoring item is the water pressure of aluminum alloy fire protection pipeline, and its corresponding target monitoring value is 11MPa. According to its corresponding preset pipeline damage threshold, the maximum working pressure of aluminum alloy pipeline can be as high as 10MPa. When the water pressure exceeds this pressure value, it will cause different degrees of mechanical damage to the pipeline, depending on the size of the water pressure, the thickness of the pipeline and the degree of surface treatment of the pipeline. When the water pressure is relatively high, it will cause deformation, cracking and fracture of the pipeline, corresponding to different damage categories, among which deformation corresponds to the first level of water pressure damage, cracking corresponds to the second level of water pressure damage, and fracture corresponds to the third level of water pressure damage.

[0120] For example, while fire-fighting pipes are damaged by water pressure, they are also affected by water corrosion. Water with different pH levels will cause different damages to fire-fighting pipes. When the pH value is relatively low, acidic water can easily corrode the surface of the fire-fighting pipe, making it thinner and easy to damage. When the pH value is relatively high, alkaline water will react chemically with the metal pipe wall, causing damage such as hydrogen corrosion, oxidation peeling and leakage. The actual pH value of the water quality in the fire-fighting pipe, that is, the target monitoring value, is compared and analyzed with the corresponding preset pipe damage threshold, that is, the water quality pH safety standard range. The water quality pH safety standard range should generally be between 6.5-8.5. If it exceeds this range, the corresponding water quality damage category level is obtained according to the actual pH value of the water quality in the current fire-fighting pipe.

[0121] In step S403, a comprehensive damage judgment is performed on the actual damage of the current fire protection pipeline in combination with the damage category levels corresponding to the different damages obtained above, and a primary pipeline damage coefficient corresponding to the fire protection pipeline is output. The primary pipeline damage coefficient can be used to evaluate the status of the current fire protection pipeline to determine whether it needs to be repaired or replaced with a new pipeline.

[0122] In the fire protection pipeline monitoring method provided in this embodiment, if the target monitoring value exceeds the preset pipeline damage threshold, it means that the abnormal pipeline quality monitoring item corresponding to the target monitoring value is already in the stage of seriously affecting the fire protection pipeline. The fire protection pipeline is further comprehensively judged for damage based on the damage category level corresponding to the target monitoring value, thereby improving the damage monitoring effect of the fire protection pipeline.

[0123] In one implementation of this embodiment, Figure 5 As shown, in step S401, if there are multiple abnormal pipeline quality monitoring items, after obtaining the target monitoring value corresponding to each abnormal pipeline quality monitoring item, the following steps are also included:

[0124] S501. If the target monitoring value exceeds the preset pipeline damage threshold, the inducing source of the abnormal pipeline quality monitoring item corresponding to the target monitoring value is obtained;

[0125] S502. If there are multiple inducing sources, obtain the abnormal contribution ratio corresponding to each inducing source;

[0126] S503. Based on the abnormal contribution ratio, generate an abnormal item distribution table corresponding to the abnormal pipeline quality monitoring items.

[0127] In step S501, the inducing source refers to the source that induces abnormal pipeline quality monitoring items. For example, the water pressure in the fire protection pipeline rises abnormally, and the corresponding inducing sources may include pipeline equipment failure, internal leakage, unqualified pipeline specifications, incorrect construction methods or materials, problems with the pressurizing device, and pump system failure. Among them, partial detection of the above-mentioned inducing sources can be achieved by using laser or nuclear magnetic resonance technology to locally check for internal leakage, measure pipeline system parameters to verify whether the specifications are appropriate, etc.

[0128] In step S502 to step S503, the abnormal contribution ratio refers to the abnormal influence ratio of each inducing source on the same abnormal pipeline quality monitoring item. For example, the abnormal pipeline quality monitoring item is the abnormal water pressure of the fire pipeline, and its corresponding inducing sources include internal water accumulation in the pipeline, insufficient water pump pressure and pipeline blockage. Among them, after the water pressure abnormality detection, the abnormal contribution ratio corresponding to the internal water accumulation is 50%, the abnormal contribution ratio corresponding to the insufficient water pump pressure is 30%, and the abnormal contribution ratio corresponding to the pipeline blockage is 20%. Then, combined with the above-mentioned abnormal contribution ratios, the abnormal project distribution table corresponding to the abnormal fire pipeline water pressure abnormality, that is, the abnormal pipeline quality monitoring item, is generated. Through this abnormal project distribution table, the staff can conduct in-depth analysis of the specific data corresponding to the inducing source that causes the abnormal water pressure of the fire pipeline.

[0129] The fire protection pipeline monitoring method provided in this embodiment, combined with the abnormal contribution ratio of each inducing source, can more intuitively obtain the distribution of abnormal factors that indirectly affect the safety of fire protection pipelines.

[0130] In one implementation of this embodiment, Figure 6 As shown, step S106, that is, if there is a correlation influence between the abnormal pipeline quality monitoring items, obtaining the secondary pipeline damage coefficient corresponding to the abnormal pipeline quality monitoring item includes the following steps:

[0131] S601. If there is a correlation influence between the abnormal pipeline quality monitoring items, then obtain the correlation influence degree between the abnormal pipeline quality monitoring items corresponding to the mutual correlation influence;

[0132] S602. Output the secondary pipeline damage coefficient corresponding to the abnormal pipeline quality monitoring item according to the degree of associated influence.

[0133] In step S601, the associated impact refers to the relationship of influence and being affected between abnormal pipeline quality monitoring items. For example, the abnormal pipeline quality monitoring items are the fire pipeline water pressure and fire pipeline temperature. The abnormal fire pipeline temperature will cause the fire pipeline water pressure to be abnormal. Since the volume of water changes with the temperature, when the temperature rises, the water volume will also increase, which will cause the internal water pressure to increase. Therefore, when the water pressure and temperature in the fire pipeline are abnormal, the two will have a cross-influence, increasing the degree of damage to the fire pipeline.

[0134] Secondly, the correlation impact degree refers to the specific quantitative impact degree between abnormal pipeline quality monitoring items that have correlation impacts on each other. For example, when the water pressure of the fire pipeline is between 20MPa and 25MPa, the temperature range is -1℃~+3.5℃, and when the water pressure exceeds 25MPa, the temperature will be greatly affected and may reach 95℃, thus bringing the risk of pipeline rupture and leakage.

[0135] In step S602, the corresponding correlation influence degree between the abnormal pipeline quality monitoring items is obtained according to the actual situation, and then the secondary pipeline damage coefficient corresponding to the abnormal pipeline quality monitoring item is output. Among them, the secondary pipeline damage coefficient can be set according to the rate of change of the numerical value caused by the mutual influence between the abnormal pipeline quality monitoring items. For example, when the temperature of the fire-fighting pipeline rises by 1°C, the water pressure may increase by 0.14MPa accordingly. Although the impact is not as significant as those, when the temperature and water pressure of the fire-fighting pipeline are abnormal at the same time, this part of the correlation impact exceeds the critical value of the fire-fighting pipeline, and it is still very likely to cause the pipeline to rupture or leak.

[0136] The fire protection pipeline monitoring method provided in this embodiment uses the specific correlation influence degree between abnormal pipeline quality monitoring items as the secondary pipeline damage coefficient corresponding to the fire protection pipeline. On the basis of monitoring the direct damage to the fire protection pipeline, the corresponding potential indirect damage can also be evaluated, thereby improving the safety monitoring effect of the fire protection pipeline.

[0137] In one implementation of this embodiment, Figure 7 As shown, in step S601, i.e., if there is a correlation influence between the abnormal pipeline quality monitoring items, then after obtaining the correlation influence degree between the abnormal pipeline quality monitoring items corresponding to the mutual correlation influence, the following steps are also included:

[0138] S701. According to the association impact, obtain the corresponding association category;

[0139] S702. If the association type is a one-way association, determine and obtain the corresponding association root point and association inducing point in the abnormal pipeline quality monitoring item, and generate a corresponding association indication table according to the association root point and the association inducing point;

[0140] S703. If the association category is a bidirectional association, a corresponding association indication table is generated according to the association influence coefficient corresponding to the abnormal pipeline quality monitoring item.

[0141] In step S701, the association category refers to the category divided according to the specific association influence between the abnormal pipeline quality monitoring items. For example, the vibration of the fire pipeline will affect the change of the air pressure of the fire pipeline, and produce a mixture of gas and water by affecting the flow of water in the pipeline. Therefore, the vibration of the fire pipeline may cause the air pressure in the fire pipeline to increase. At the same time, the air pressure of the fire pipeline is also one of the factors causing damage to the fire pipeline. Therefore, the corresponding association category is fire pipeline (vibration-air pressure).

[0142] In step S702 to step S703, in order to deeply analyze the correlation effects between abnormal pipeline quality monitoring items, the correlation types are further divided into unidirectional correlation and bidirectional correlation. Among them, unidirectional correlation means that the change of one type of abnormal pipeline quality monitoring item will affect the other type of abnormal pipeline quality monitoring item, but will not be affected, and bidirectional correlation means the mutual influence between two or more types of abnormal pipeline quality monitoring items, which will act on each other, be affected by each other and coordinate with each other.

[0143] Among them, if the association category is a unidirectional association, the corresponding association root point and association induction point in the abnormal pipeline quality monitoring item are judged and obtained. Among them, the association root point refers to the root point where the change of one type of abnormal pipeline quality monitoring item affects other types of abnormal pipeline quality monitoring items. For example, the vibration of the fire pipeline may cause the water pressure of the fire pipeline to rise. The vibration of the fire pipeline is the association root point, and the increase in the water pressure of the fire pipeline is the association induction point. Then, according to the above-set association root point and association induction point, the corresponding association indication table is generated. The association indication table records the directional relationship of the unidirectional vibration of the fire pipeline causing the water pressure of the fire pipeline to rise.

[0144] Secondly, if the association category is a bidirectional association, then the association influence coefficient corresponding to the abnormal pipeline quality monitoring item is used. Among them, the association influence coefficient depends on the specific degree of influence between multiple abnormal pipeline quality monitoring items, such as the abnormal pipeline quality monitoring items are the fire pipeline temperature and water pressure. For example, when the fire pipeline temperature rises by 1°C, the water pressure may increase by 0.14MPa accordingly. Conversely, when the water pressure rises by 1 bar, the temperature will increase by about 2°C. When the water pressure rises from 3.5 Bar to 4.5 Bar, the temperature will increase by about 4°C. Then, the corresponding association indication table is generated according to the association influence coefficient obtained above. Through this association indication table, the type of abnormal pipeline quality monitoring items and the degree of mutual correlation influence between abnormal pipeline quality monitoring items can be obtained.

[0145] The fire protection pipeline monitoring method provided in this embodiment sets corresponding influencing factor analysis strategies between abnormal pipeline quality monitoring items according to the association categories corresponding to the association influence degrees, thereby improving the safety analysis effect of potential hidden dangers of fire protection pipelines.

[0146] The present application embodiment discloses a fire protection pipeline monitoring system, such as Figure 8 As shown, including:

[0147] The first acquisition module 1 is used to acquire monitoring data of the fire protection pipeline;

[0148] Identification module 2, used to identify monitoring data and obtain corresponding pipeline surface image data;

[0149] The second acquisition module 3 is used to acquire the pipeline quality monitoring items corresponding to the fire protection pipeline if the pipeline surface image data meets the preset pipeline shallow hidden danger standard;

[0150] The third acquisition module 4 is used to acquire the corresponding abnormal pipeline quality monitoring item if the pipeline quality monitoring item does not meet the preset pipeline quality monitoring index;

[0151] The first evaluation module 5 is used to obtain the primary pipeline damage coefficient corresponding to each abnormal pipeline quality monitoring item if there are multiple abnormal pipeline quality monitoring items;

[0152] The second evaluation module 6 is used to obtain the secondary pipeline damage coefficient corresponding to the abnormal pipeline quality monitoring item if there is a correlation influence between the abnormal pipeline quality monitoring items;

[0153] Combination module 7 is used to combine the primary pipeline damage coefficient, the secondary pipeline damage coefficient and the pipeline surface image data to generate a damage determination report corresponding to the fire protection pipeline.

[0154] The fire protection pipeline monitoring system provided in this embodiment determines whether the pipeline surface image data corresponding to the fire protection pipeline currently obtained by the identification module 2 is abnormal, that is, whether the pipeline has shallow defects, according to the preset pipeline shallow hidden danger standard. If it is, it means that the current pipeline has been damaged. In order to further analyze its damage, the pipeline quality monitoring items corresponding to the fire protection pipeline are analyzed and judged one by one according to the preset pipeline quality monitoring indicators. If an abnormality occurs, the corresponding abnormal pipeline quality monitoring items are obtained through the third acquisition module 4. If there are multiple abnormal pipeline quality monitoring items, the first-level pipeline damage coefficient of each abnormal pipeline quality monitoring item causing direct damage to the pipeline is obtained through the first evaluation module 5. If there is a correlation between the abnormal pipeline quality monitoring items at the same time, the second-level pipeline damage coefficient of the abnormal pipeline quality monitoring item causing indirect damage to the pipeline is further obtained through the second evaluation module 6. Then, the combination module 7 combines the above-mentioned first-level pipeline damage coefficient, the second-level pipeline damage coefficient and the pipeline surface image data to generate a damage determination report for comprehensive damage assessment of the fire protection pipeline. Due to the comprehensive analysis and evaluation of the shallow hidden dangers of the fire protection pipeline and the corresponding deep damage hidden dangers of the specific shallow hidden dangers, the safety of fire protection pipeline monitoring is improved.

[0155] It should be noted that the fire protection pipe monitoring system provided in the embodiment of the present application also includes modules and / or corresponding sub-modules corresponding to the logical functions or logical steps of any of the above-mentioned fire protection pipe monitoring systems, to achieve the same effects as the various logical functions or logical steps, and the details will not be repeated here.

[0156] An embodiment of the present application also discloses a terminal device, including a memory, a processor, and computer instructions stored in the memory and capable of running on the processor, wherein when the processor executes the computer instructions, any one of the fire protection pipeline monitoring methods in the above embodiments is adopted.

[0157] The terminal device may be a computer device such as a desktop computer, a laptop computer or a cloud server, and the terminal device includes but is not limited to a processor and a memory. For example, the terminal device may also include input and output devices, a network access device and a bus.

[0158] Among them, the processor can adopt a central processing unit (CPU). Of course, according to actual usage, other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. can also be adopted. The general-purpose processor can adopt a microprocessor or any conventional processor, etc., and this application does not impose any restrictions on this.

[0159] Among them, the memory can be an internal storage unit of the terminal device, such as a hard disk or memory of the terminal device, or it can be an external storage device of the terminal device, such as a plug-in hard disk, a smart memory card (SMC), a secure digital card (SD) or a flash memory card (FC) equipped on the terminal device, etc., and the memory can also be a combination of an internal storage unit and an external storage device of the terminal device. The memory is used to store computer instructions and other instructions and data required by the terminal device. The memory can also be used to temporarily store data that has been output or is to be output, and this application does not impose any restrictions on this.

[0160] Among them, through this terminal device, any one of the fire protection pipeline monitoring methods in the above embodiments is stored in the memory of the terminal device, and is loaded and executed on the processor of the terminal device for easy use.

[0161] The embodiment of the present application further discloses a computer-readable storage medium, and the computer-readable storage medium stores computer instructions, wherein when the computer instructions are executed by a processor, any one of the fire protection pipeline monitoring methods in the above embodiments is adopted.

[0162] Among them, computer instructions can be stored in computer-readable media, computer instructions include computer instruction codes, computer instruction codes can be in source code form, object code form, executable files or certain middleware forms, etc. Computer-readable media include any entity or device that can carry computer instruction codes, recording media, USB flash drives, mobile hard drives, magnetic disks, optical disks, computer memories, read-only memories (ROMs), random access memories (RAMs), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that computer-readable media include but are not limited to the above-mentioned components.

[0163] Among them, through this computer-readable storage medium, any one of the fire protection pipeline monitoring methods in the above embodiments is stored in a computer-readable storage medium, and is loaded and executed on a processor to facilitate the storage and application of the above method.

[0164] The above are all preferred embodiments of the present application, and the protection scope of the present application is not limited thereto. Therefore, any equivalent changes made according to the structure, shape, and principle of the present application should be included in the protection scope of the present application.

Claims

1. A fire protection pipeline monitoring method, characterized in that: The following steps are involved: Obtain monitoring data of fire protection pipelines; Identify the monitoring data and obtain corresponding pipeline surface image data; If the pipeline surface image data meets the preset pipeline shallow hidden danger standard, then obtain the pipeline quality monitoring item corresponding to the fire protection pipeline; If the pipeline quality monitoring item does not meet the preset pipeline quality monitoring index, the corresponding abnormal pipeline quality monitoring item is obtained; If there are multiple abnormal pipeline quality monitoring items, then obtain the primary pipeline damage coefficient corresponding to each abnormal pipeline quality monitoring item; If there is a correlation effect between the abnormal pipeline quality monitoring items, then obtaining the secondary pipeline damage coefficient corresponding to the abnormal pipeline quality monitoring item; Combining the primary pipeline damage coefficient, the secondary pipeline damage coefficient and the pipeline surface image data, generating a damage determination report corresponding to the fire protection pipeline; If there are multiple abnormal pipeline quality monitoring items, obtaining the primary pipeline damage coefficient corresponding to each abnormal pipeline quality monitoring item includes the following steps: If there are multiple abnormal pipeline quality monitoring items, then obtaining the target monitoring value corresponding to each abnormal pipeline quality monitoring item; If the target monitoring value exceeds the preset pipeline damage threshold, the corresponding damage category level is obtained according to the target monitoring value; Performing a comprehensive damage determination on the fire protection pipeline in combination with the damage category level, and outputting a primary pipeline damage coefficient corresponding to the fire protection pipeline; Among them, the primary pipeline damage factor is an indicator of the deformation, thinning, corrosion and deterioration of the pipeline, indicating the operating status of the pipeline; If there is a correlation effect between the abnormal pipeline quality monitoring items, obtaining the secondary pipeline damage coefficient corresponding to the abnormal pipeline quality monitoring item includes the following steps: If there is a correlation influence between the abnormal pipeline quality monitoring items, then obtaining the correlation influence degree between the abnormal pipeline quality monitoring items corresponding to the mutual correlation influence; Outputting the secondary pipeline damage coefficient corresponding to the abnormal pipeline quality monitoring item according to the correlation influence degree; Among them, the secondary pipeline damage coefficient refers to the degree of correlation and influence of one type of abnormal pipeline quality monitoring items on another type of abnormal pipeline quality monitoring items.

2. A fire protection pipeline monitoring method according to claim 1, characterized in that: After identifying the monitoring data and acquiring the corresponding pipeline surface image data, the following steps are also included: If the pipeline surface image data meets the preset pipeline shallow hidden danger standard, then obtain the corresponding shallow hidden danger characteristics; If there is a corresponding historical hidden danger feature record for the shallow hidden danger feature, then the historical induction frequency and historical damage identification score corresponding to the shallow hidden danger feature in the historical hidden danger feature record are obtained; The shallow hidden danger characteristics are analyzed in combination with the historical induction frequency and the historical damage identification score to generate a target damage level corresponding to the current fire protection pipeline.

3. A fire protection pipeline monitoring method according to claim 2, characterized in that: If there is a corresponding historical hidden danger feature record for the shallow hidden danger feature, after obtaining the historical induction frequency and historical damage identification score corresponding to the shallow hidden danger feature in the historical hidden danger feature record, the following steps are also included: If the historical induction frequency exceeds the preset frequency standard, the damage distribution level corresponding to the fire protection pipeline is obtained according to the historical damage identification score; In combination with the damage distribution level and the historical induction frequency, a service life prediction result corresponding to the fire protection pipeline is output.

4. A fire protection pipeline monitoring method according to claim 1, characterized in that: If there are multiple abnormal pipeline quality monitoring items, after obtaining the target monitoring value corresponding to each abnormal pipeline quality monitoring item, the method further includes the following steps: If the target monitoring value exceeds the preset pipeline damage threshold, obtaining the inducing source of the abnormal pipeline quality monitoring item corresponding to the target monitoring value; If there are multiple inducing sources, then obtain the abnormal contribution ratio corresponding to each of the inducing sources; In combination with the abnormal contribution ratio, an abnormal item distribution table corresponding to the abnormal pipeline quality monitoring item is generated.

5. A fire protection pipeline monitoring method according to claim 1, characterized in that: If there is a correlation influence between the abnormal pipeline quality monitoring items, after obtaining the correlation influence degree between the abnormal pipeline quality monitoring items corresponding to the mutual correlation influence, the following steps are also included: According to the association impact, obtaining a corresponding association category; If the association category is a one-way association, the corresponding association root point and association inducing point in the abnormal pipeline quality monitoring item are determined and acquired, and a corresponding association indication table is generated according to the association root point and the association inducing point; If the association category is a bidirectional association, the corresponding association indication table is generated according to the association influence coefficient corresponding to the abnormal pipeline quality monitoring item.

6. A fire protection pipeline monitoring system, characterized in that: The fire protection pipeline monitoring method according to any one of claims 1 to 5 is adopted, and the system comprises: A first acquisition module (1) is used to acquire monitoring data of fire protection pipelines; An identification module (2) is used to identify the monitoring data and obtain corresponding pipeline surface image data; A second acquisition module (3), if the pipeline surface image data meets the preset pipeline shallow hidden danger standard, the second acquisition module (3) is used to obtain the pipeline quality monitoring item corresponding to the fire protection pipeline; A third acquisition module (4), if the pipeline quality monitoring item does not meet the preset pipeline quality monitoring index, the third acquisition module (4) is used to acquire the corresponding abnormal pipeline quality monitoring item; A first evaluation module (5), if there are multiple abnormal pipeline quality monitoring items, the first evaluation module (5) is used to obtain the primary pipeline damage coefficient corresponding to each abnormal pipeline quality monitoring item; A second evaluation module (6), if there is a correlation influence between the abnormal pipeline quality monitoring items, the second evaluation module (6) is used to obtain a secondary pipeline damage coefficient corresponding to the abnormal pipeline quality monitoring item; A combining module (7) is used to combine the primary pipeline damage coefficient, the secondary pipeline damage coefficient and the pipeline surface image data to generate a damage determination report corresponding to the fire protection pipeline.

7. A terminal device, comprising a memory and a processor, characterized in that: The memory stores computer instructions that can be run on the processor. When the processor loads and executes the computer instructions, a fire protection pipeline monitoring method according to any one of claims 1 to 5 is adopted.

8. A computer-readable storage medium, wherein computer instructions are stored in the computer-readable storage medium, characterized in that: When the computer instructions are loaded and executed by the processor, a fire protection pipeline monitoring method as claimed in any one of claims 1 to 5 is adopted.

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