CN116617616A

CN116617616A - Fire-fighting pipeline monitoring method, fire-fighting pipeline monitoring system, terminal equipment and storage medium

Info

Publication number: CN116617616A
Application number: CN202310472355.XA
Authority: CN
Inventors: 赵立波; 王跃军; 赵晓波; 南晓敏
Original assignee: Shen Zhen Zhule Sci Teck Co ltd
Current assignee: Shen Zhen Zhule Sci Teck Co ltd
Priority date: 2023-04-24
Filing date: 2023-04-24
Publication date: 2023-08-22

Abstract

The application relates to the technical field of fire protection, in particular to a fire protection pipeline monitoring method, a fire protection pipeline monitoring system, terminal equipment and a storage medium. The method comprises the following steps: if the pipeline surface image data accords with the preset pipeline shallow hidden trouble standard, acquiring a pipeline quality monitoring item corresponding to the fire-fighting pipeline; if the pipeline quality monitoring item does not accord with the preset pipeline quality monitoring index, acquiring a corresponding abnormal pipeline quality monitoring item; if the number of the abnormal pipeline quality monitoring items is multiple, obtaining a primary pipeline damage coefficient corresponding to each abnormal pipeline quality monitoring item; if the abnormal pipeline quality monitoring items have correlation influence, acquiring a secondary pipeline damage coefficient corresponding to the abnormal pipeline quality monitoring items; and combining the primary pipeline damage coefficient, the secondary pipeline damage coefficient and the pipeline surface image data to generate a damage judgment report corresponding to the fire-fighting pipeline. The fire-fighting pipeline monitoring method, the fire-fighting pipeline monitoring system, the terminal equipment and the storage medium have the effect of improving the monitoring safety of the fire-fighting pipeline.

Description

Fire-fighting pipeline monitoring method, fire-fighting pipeline monitoring system, terminal equipment and storage medium

Technical Field

The application relates to the technical field of fire protection, in particular to a fire protection pipeline monitoring method, a fire protection pipeline monitoring system, terminal equipment and a storage medium.

Background

Fire pipes are a special pipe for discharging water for fire protection, life protection and property protection, which can be connected to a fire water pond or other water source and, if necessary, inject water into the fire to suppress flames.

Currently, the safety monitoring of fire pipes includes: and (3) periodically checking and maintaining, installing a data acquisition system to monitor the pressure, flow and temperature in the pipeline in real time, installing a sensor to monitor the water quality of the pipeline, installing an alarm and periodically checking the pipeline to ensure the safe use of the pipeline.

In practical application, the current technology cannot effectively monitor the fine changes in the pipeline, such as deformation and deterioration of pipeline materials, thinning of the inner wall of the pipeline and the like, which can cause instability of a fire-fighting pipeline system, so that the fire-fighting pipeline is broken, and life and property losses are caused.

Disclosure of Invention

In order to improve the safety of fire-fighting pipeline monitoring, the application provides a fire-fighting pipeline monitoring method, a fire-fighting pipeline monitoring system, terminal equipment and a storage medium.

In a first aspect, the present application provides a fire protection pipe monitoring method, comprising the steps of:

Acquiring monitoring data of a fire control pipeline;

identifying the monitoring data and acquiring corresponding pipeline surface image data;

if the pipeline surface image data accords with a preset pipeline shallow hidden danger standard, acquiring a pipeline quality monitoring item corresponding to the fire-fighting pipeline;

if the pipeline quality monitoring item does not accord with the preset pipeline quality monitoring index, acquiring a corresponding abnormal pipeline quality monitoring item;

if the number of the abnormal pipeline quality monitoring items is multiple, obtaining a primary pipeline damage coefficient corresponding to each abnormal pipeline quality monitoring item;

if the abnormal pipeline quality monitoring items have correlation influence, acquiring a secondary pipeline damage coefficient corresponding to the abnormal pipeline quality monitoring items;

and combining the primary pipeline damage coefficient, the secondary pipeline damage coefficient and the pipeline surface image data to generate a damage judgment report corresponding to the fire-fighting pipeline.

By adopting the technical scheme, whether the pipeline surface image data corresponding to the current fire-fighting pipeline is abnormal or not, namely whether the pipeline has a shallow defect or not is judged according to the preset pipeline shallow hidden danger standard, if the current pipeline has the damage condition, the pipeline quality monitoring items corresponding to the fire-fighting pipeline are analyzed and judged one by one according to the preset pipeline quality monitoring index in order to further analyze the damage condition, if the abnormal pipeline quality monitoring items are abnormal, the corresponding abnormal pipeline quality monitoring items are obtained, if the abnormal pipeline quality monitoring items are a plurality of, the first-stage pipeline damage coefficient of direct damage to the pipeline by each abnormal pipeline quality monitoring item is obtained, if the abnormal pipeline quality monitoring items have the associated influence, the second-stage pipeline damage coefficient of indirect damage to the pipeline by the abnormal pipeline quality monitoring items is further obtained, and then the obtained first-stage pipeline damage coefficient, the second-stage pipeline damage coefficient and the pipeline surface image data are combined, and a damage judgment report for evaluating the fire-fighting pipeline is generated, and the safety of fire-fighting pipeline monitoring is improved due to the comprehensive analysis of the shallow hidden danger and the deep hidden danger corresponding to the deep damage.

Optionally, after identifying the monitoring data and acquiring corresponding pipeline surface image data, the method further comprises the following steps:

if the pipeline surface image data accords with a preset pipeline shallow hidden danger standard, acquiring corresponding shallow hidden danger characteristics;

if the shallow hidden danger feature has a corresponding history hidden danger feature record, acquiring a history induction frequency and a history damage identification score corresponding to the shallow hidden danger feature in the history hidden danger feature record;

and analyzing the characteristics of the shallow hidden trouble by combining the historical induction frequency and the historical damage identification score to generate a target damage grade corresponding to the fire-fighting pipeline at present.

By adopting the technical scheme, the current pipeline is subjected to damage grading by combining the historical induction frequency and the historical damage identification score of the shallow hidden danger characteristics, so that the accuracy of safety monitoring of the pipeline is improved.

Optionally, after the step of obtaining the historical induction frequency and the historical damage identification score corresponding to the shallow hidden danger feature in the history hidden danger feature record if the shallow hidden danger feature has the corresponding history hidden danger feature record, the step of:

if the historical induction frequency exceeds a preset frequency standard, acquiring a damage distribution grade corresponding to the fire-fighting pipeline according to the historical damage identification score;

And outputting a service life prediction result corresponding to the fire-fighting pipeline by combining the damage distribution level and the historical induction frequency.

By adopting the technical scheme, if the historical induction frequency exceeds the corresponding preset frequency standard, the fact that the current fire-fighting pipeline has similar or abnormal damage in a history is indicated, comprehensive evaluation is further carried out by combining the damage distribution grade corresponding to each historical damage identification score and the historical induction frequency, and the residual service life prediction result of the fire-fighting pipeline is obtained, so that the monitoring effect of the use safety of the fire-fighting pipeline is improved.

Optionally, if the number of the abnormal pipeline quality monitoring items is multiple, obtaining the first-stage pipeline damage coefficient corresponding to each abnormal pipeline quality monitoring item includes the following steps:

if the number of the abnormal pipeline quality monitoring items is multiple, obtaining target monitoring values corresponding to the abnormal pipeline quality monitoring items;

if the target monitoring value exceeds a preset pipeline damage threshold, acquiring a corresponding damage class level according to the target monitoring value;

and carrying out comprehensive damage judgment on the fire-fighting pipeline by combining the damage class grade, and outputting a primary pipeline damage coefficient corresponding to the fire-fighting pipeline.

By adopting the technical scheme, if the target monitoring value exceeds the preset pipeline damage threshold, the abnormal pipeline quality monitoring item corresponding to the target monitoring value is explained to be in a stage of seriously affecting the fire-fighting pipeline, and comprehensive damage judgment is further carried out on the fire-fighting pipeline by combining the damage class grade corresponding to the target monitoring value, so that the damage monitoring effect of the fire-fighting pipeline is improved.

Optionally, after the obtaining the target monitoring values corresponding to the abnormal pipeline quality monitoring items if the abnormal pipeline quality monitoring items are multiple, the method further includes the following steps:

if the target monitoring value exceeds the preset pipeline damage threshold, acquiring an induction source of the abnormal pipeline quality monitoring item corresponding to the target monitoring value;

if the number of the induction sources is multiple, obtaining the abnormal contribution duty ratio corresponding to each induction source;

and generating an abnormal item distribution table corresponding to the abnormal pipeline quality monitoring item by combining the abnormal contribution proportion.

By adopting the technical scheme, the abnormal factor distribution situation indirectly influencing the safety of the fire-fighting pipeline can be intuitively obtained by combining the abnormal contribution proportion corresponding to each induction source.

Optionally, if there is an influence of the correlation between the abnormal pipeline quality monitoring items, acquiring the diode damage coefficient corresponding to the abnormal pipeline quality monitoring item includes the following steps:

if the abnormal pipeline quality monitoring items have correlation influence, acquiring correlation influence degrees among the abnormal pipeline quality monitoring items corresponding to the correlation influence;

and outputting the damage coefficient of the secondary pipeline corresponding to the abnormal pipeline quality monitoring item according to the association influence degree.

By adopting the technical scheme, the specific association influence degree among abnormal pipeline quality monitoring items is used as the secondary pipeline damage coefficient corresponding to the fire-fighting pipeline, and the corresponding potential indirect damage can be evaluated on the basis of monitoring the direct damage of the fire-fighting pipeline, so that the fire-fighting pipeline safety monitoring effect is improved.

Optionally, after the correlation influence exists among the abnormal pipeline quality monitoring items, the method further includes the following steps:

acquiring a corresponding association category according to the association influence;

If the association category is one-way association, judging and acquiring corresponding association root source points and association induction points in the abnormal pipeline quality monitoring item, and generating a corresponding association indication table according to the association root source points and the association induction points;

and if the association category is bidirectional association, generating the corresponding association indication table according to the association influence coefficient corresponding to the abnormal pipeline quality monitoring item.

By adopting the technical scheme, corresponding influence factor analysis strategies among abnormal pipeline quality monitoring items are respectively set according to the association categories corresponding to the association influence degrees, so that the safety analysis effect of potential hidden danger of the fire-fighting pipeline is improved.

In a second aspect, the present application provides a fire conduit monitoring system comprising:

the first acquisition module is used for acquiring monitoring data of the fire control pipeline;

the identification module is used for identifying the monitoring data and acquiring corresponding pipeline surface image data;

the second acquisition module is used for acquiring a pipeline quality monitoring item corresponding to the fire-fighting pipeline if the pipeline surface image data accords with a preset pipeline shallow hidden danger standard;

the third acquisition module is used for acquiring the corresponding abnormal pipeline quality monitoring item if the pipeline quality monitoring item does not accord with a preset pipeline quality monitoring index;

The first evaluation module is used for acquiring primary pipeline damage coefficients corresponding to the abnormal pipeline quality monitoring items if the abnormal pipeline quality monitoring items are multiple;

the second evaluation module is used for acquiring a secondary pipeline damage coefficient corresponding to the abnormal pipeline quality monitoring item if the abnormal pipeline quality monitoring item has a correlation influence;

and the combining module is used for combining the primary pipeline damage coefficient, the secondary pipeline damage coefficient and the pipeline surface image data to generate a damage judgment report corresponding to the fire-fighting pipeline.

By adopting the technical scheme, whether the pipeline surface image data corresponding to the fire-fighting pipeline is abnormal or not, namely whether the pipeline has a shallow defect or not is judged according to the preset pipeline shallow hidden danger standard, if the current pipeline has a damage condition, the pipeline quality monitoring items corresponding to the fire-fighting pipeline are analyzed and judged one by one according to the preset pipeline quality monitoring index, if the abnormal pipeline quality monitoring items are abnormal, the corresponding abnormal pipeline quality monitoring items are obtained through the third obtaining module, if the abnormal pipeline quality monitoring items are a plurality of, the first-stage pipeline damage coefficient of direct damage to the pipeline caused by each abnormal pipeline quality monitoring item is obtained through the first evaluating module, if the abnormal pipeline quality monitoring items have an associated influence, the second-stage pipeline damage coefficient of indirect damage to the pipeline caused by the abnormal pipeline quality monitoring items is further obtained through the second evaluating module, and then the damage judging report of comprehensive damage evaluation to the fire-fighting pipeline is generated by combining the obtained first-stage pipeline damage coefficient, the second-stage pipeline damage coefficient and the pipeline surface image data, and the comprehensive hidden danger potential danger analyzing and the deep hidden danger corresponding to the deep damage of the fire-fighting pipeline are combined, so that the fire-fighting hidden danger is monitored and the safety is evaluated.

In a third aspect, the present application provides a terminal device, which adopts the following technical scheme:

the terminal equipment comprises a memory and a processor, wherein the memory stores computer instructions capable of running on the processor, and the processor adopts the fire control pipeline monitoring method when loading and executing the computer instructions.

By adopting the technical scheme, the computer instruction is generated by the fire control pipeline monitoring method and is stored in the memory to be loaded and executed by the processor, so that the terminal equipment is manufactured according to the memory and the processor, and the fire control pipeline monitoring method is convenient to use.

In a fourth aspect, the present application provides a computer readable storage medium, which adopts the following technical scheme:

a computer readable storage medium having stored therein computer instructions which, when loaded and executed by a processor, employ a fire pipe monitoring method as described above.

By adopting the technical scheme, the computer instruction is generated by the fire control pipeline monitoring method and is stored in the computer readable storage medium to be loaded and executed by the processor, and the computer instruction is convenient to read and store by the computer readable storage medium.

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-fighting pipeline is abnormal or not, namely whether the pipeline has shallow defects or not according to preset pipeline shallow hidden danger standards, if so, analyzing the damage condition of the current pipeline further, analyzing and judging pipeline quality monitoring items corresponding to the fire-fighting pipeline one by one according to preset pipeline quality monitoring indexes, if so, acquiring corresponding abnormal pipeline quality monitoring items, if so, acquiring primary pipeline damage coefficients of direct damage to the pipeline by each abnormal pipeline quality monitoring item, and if the abnormal pipeline quality monitoring items have associated influence, further acquiring secondary pipeline damage coefficients of indirect damage to the pipeline by the abnormal pipeline quality monitoring items, and then combining the acquired primary pipeline damage coefficients, secondary pipeline damage coefficients and pipeline surface image data to generate a damage judgment report for comprehensive damage evaluation on the fire-fighting pipeline.

Drawings

Fig. 1 is a schematic flow chart of steps S101 to S107 in the fire fighting pipeline monitoring method according to the present application.

Fig. 2 is a schematic flow chart of steps S201 to S203 in the fire fighting pipeline monitoring method according to the present application.

Fig. 3 is a schematic flow chart of steps S301 to S302 in the fire fighting pipeline monitoring method according to the present application.

Fig. 4 is a schematic flow chart of steps S401 to S403 in the fire fighting pipeline monitoring method according to the present application.

Fig. 5 is a schematic flow chart of steps S501 to S503 in the fire fighting pipeline monitoring method according to the present application.

Fig. 6 is a schematic flow chart of steps S601 to S602 in the fire fighting pipeline monitoring method according to the present application.

Fig. 7 is a schematic flow chart of steps S701 to S702 in the fire fighting pipeline monitoring method according to the present application.

Fig. 8 is a schematic block diagram of a fire fighting pipeline monitoring system according to the present application.

Reference numerals illustrate:

1. a first acquisition module; 2. an identification module; 3. a second acquisition module; 4. a third acquisition module; 5. a first evaluation module; 6. a second evaluation module; 7. and (5) combining the modules.

Detailed Description

The application is described in further detail below with reference to fig. 1-8.

The embodiment of the application discloses a fire control pipeline monitoring method, which is shown in fig. 1 and comprises the following steps:

S101, acquiring monitoring data of a fire control pipeline;

s102, identifying monitoring data and acquiring corresponding pipeline surface image data;

s103, if the image data of the surface of the pipeline meets the preset pipeline shallow hidden trouble standard, acquiring a pipeline quality monitoring item corresponding to the fire-fighting pipeline;

s104, if the pipeline quality monitoring item does not accord with a preset pipeline quality monitoring index, acquiring a corresponding abnormal pipeline quality monitoring item;

s105, if a plurality of abnormal pipeline quality monitoring items are provided, obtaining first-stage pipeline damage coefficients corresponding to the abnormal pipeline quality monitoring items;

s106, if the abnormal pipeline quality monitoring items have correlation influence, acquiring a secondary pipeline damage coefficient corresponding to the abnormal pipeline quality monitoring items;

s107, combining the primary pipeline damage coefficient, the secondary pipeline damage coefficient and the pipeline surface image data to generate a damage judgment report corresponding to the fire-fighting pipeline.

In step S101, the monitoring data of the fire fighting pipeline refers to data that needs to be monitored when the fire fighting pipeline is subjected to security inspection. For example, the data of the fire-fighting pipeline safety condition is displayed by the water pressure, flow, pressure, temperature, water level, water quality, humidity, pipeline surface layer image and the like corresponding to the fire-fighting pipeline.

The monitoring data can be obtained through a monitoring instrument or device with corresponding matched functions, for example, the water quality can be measured by installing a water quality analyzer or a water quality tester in a fire-fighting pipeline, or the surface layer image of the pipeline can be obtained by installing a camera.

In step S102, the monitoring data is identified, so that the pipeline surface image data corresponding to the fire-fighting pipeline can be further obtained, and the pipeline surface image data refers to the characteristic information about the pipeline structure, the pipeline material, the pipeline diameter/thickness and the pipeline is obtained by identifying the pipeline surface image.

In step S103, the preset pipeline shallow hidden danger standard refers to a preset characteristic standard for identifying damage or related shallow hidden danger of the fire-fighting pipeline, for example, the preset pipeline shallow hidden danger standard may be a characteristic identification standard for identifying abrasion, cracking or corrosion of the surface of the pipeline.

If the image data of the surface of the pipeline accords with the preset pipeline shallow hidden danger standard, the current firefighting pipeline is indicated to be damaged, in order to further analyze the hidden danger of the deep layer of the firefighting pipeline, a pipeline quality monitoring item corresponding to the firefighting pipeline is obtained, the pipeline quality monitoring item is an item for monitoring the quality safety of the firefighting pipeline by a pointer, specifically, the pipeline quality monitoring item can comprise an inspection pipeline shell, an inspection pipeline internal water pressure condition, water accumulation is monitored, firefighting spray is added in the pipeline and is inspected regularly, the pipeline material strength is detected, and the fire fighting pipeline performance and other items are detected regularly.

And if the pipeline surface image data does not meet the preset pipeline shallow hidden danger standard, the fact that the current fire-fighting pipeline has no related hidden danger is indicated, and the pipeline surface image data corresponding to the current fire-fighting pipeline is continuously acquired through the related monitoring equipment.

In step S104, the preset pipeline quality monitoring index refers to a preset safety certification standard corresponding to the fire-fighting pipeline monitoring item. The pipeline quality monitoring items mentioned in the scheme include, but are not limited to, the environment temperature, the humidity and the wind speed of the fire-fighting pipeline, and pipeline internal factors such as water quality, flow size, flow rate, water pressure and the like.

If the pipeline quality monitoring item does not accord with the preset pipeline quality monitoring index, the corresponding potential hidden danger exists in the current fire-fighting pipeline, and in order to further distinguish and deeply analyze the potential hidden danger, the pipeline quality monitoring item label which does not accord with the preset pipeline quality monitoring index is marked as an abnormal pipeline quality monitoring item.

Furthermore, if the pipeline quality monitoring item meets the preset pipeline quality monitoring index, the condition that the surface of the current fire-fighting pipeline is damaged possibly due to certain external force is indicated. For example, collisions of vehicles, vibrations of buildings, or earthquakes, etc., which may cause the fire pipe to deform, even causing the pipe to break and leak.

In step S105, if the number of the abnormal pipeline quality monitoring items is plural, the first-stage pipeline damage coefficient corresponding to each abnormal pipeline quality monitoring item is obtained, where the first-stage pipeline damage coefficient refers to an index of deformation, thinning, corrosion and deterioration degree of the pipeline, and indicates a state of operation of the pipeline, and in general, the larger the pipeline damage coefficient, the more serious the deformation, thinning and deterioration degree of the pipeline is, the timely maintenance or replacement is required to ensure normal operation of the fire protection system.

For example, the abnormal pipeline quality monitoring item is pipeline vibration, and the vibration of the fire-fighting pipeline can cause bending, deformation and fracture of the pipeline and also can cause brittle fracture of a welded structure, wherein the corresponding primary pipeline damage coefficient is the amplitude or degree of vibration, and the damage can be caused when the vibration of the fire-fighting pipeline reaches more than 10 times of an allowable standard, and the allowable standard is that the linear buffer of the vibration time is 150-500 microseconds/meter.

And if the abnormal pipeline quality monitoring items are single, directly outputting monitoring data corresponding to the abnormal pipeline quality monitoring items, and further carrying out relevant safety protection treatment on the fire-fighting pipeline according to the monitoring data.

In step S106, the existence of the correlation influence between the abnormal pipe quality monitoring items means that there is an influence and an influenced relationship between the abnormal pipe quality monitoring items. For example, there is a correlation between the temperature and water pressure within the fire line, which can result in an increase in water pressure when the temperature within the fire line is too high. The pressure rise in the fire-fighting pipeline can greatly influence the pipeline, and the pressure rise can cause uneven stress of the pipeline, so that faults such as fracture and burst are caused, the pipeline structure can be deformed, and even the pipeline can be leaked. Conversely, when the temperature in the fire-fighting pipeline is too low, the water pressure in the pipeline is reduced, the water pressure in the fire-fighting pipeline is reduced to cause great influence on the pipeline, for example, the durability of the pipeline can be reduced, so that the pipeline is broken, deformed and other abnormal conditions are caused, and the pipeline can be leaked.

If the abnormal pipeline quality monitoring items have the associated influence, a secondary pipeline damage coefficient corresponding to the abnormal pipeline quality monitoring items is obtained, wherein the secondary pipeline damage coefficient refers to the associated influence degree of one type of abnormal pipeline quality monitoring item on the other type of abnormal pipeline quality monitoring item. Such as the extent to which the temperature in the fire line affects the water pressure in the fire line.

In step S107, based on the obtained primary pipeline damage coefficient and secondary pipeline damage coefficient and the pipeline surface image data, a damage judgment report corresponding to the specific damage degree of the current fire-fighting pipeline is generated, and the direct damage to the current monitored fire-fighting pipeline and the corresponding potential damage related hidden danger conditions can be obtained through the damage judgment report.

According to the fire-fighting pipeline monitoring method provided by the embodiment, whether the pipeline surface image data corresponding to the current fire-fighting pipeline is abnormal or not, namely whether the pipeline has a shallow defect is judged according to the preset pipeline shallow hidden danger standard, if the current pipeline has the damage condition, the pipeline quality monitoring items corresponding to the fire-fighting pipeline are analyzed and judged one by one according to the preset pipeline quality monitoring index, if the abnormal pipeline quality monitoring items are abnormal, the corresponding abnormal pipeline quality monitoring items are obtained, the primary pipeline damage coefficient of each abnormal pipeline quality monitoring item, which directly damages the pipeline, is obtained, and if the abnormal pipeline quality monitoring items have the associated influence, the secondary pipeline damage coefficient, which indirectly damages the pipeline, is further obtained, is then combined with the obtained primary pipeline damage coefficient, the secondary pipeline damage coefficient and the pipeline surface image data, so that a damage judgment report for comprehensive damage evaluation of the fire-fighting pipeline is generated, and the safety of fire-fighting pipeline monitoring is improved due to the comprehensive analysis and evaluation of the shallow hidden danger of the fire-fighting pipeline and the specific shallow hidden danger.

In one implementation manner of this embodiment, as shown in fig. 2, in step S102, the monitoring data is identified, and the following steps are further included after the corresponding pipe surface image data is acquired:

s201, if the image data of the surface of the pipeline meets the preset pipeline shallow hidden danger standard, acquiring corresponding shallow hidden danger characteristics;

s202, if corresponding historical hidden danger feature records exist in the shallow hidden danger features, acquiring historical induction frequency and historical damage identification scores corresponding to the shallow hidden danger features in the historical hidden danger feature records;

s203, analyzing shallow hidden danger characteristics by combining the historical induction frequency and the historical damage identification score, and generating a target damage grade corresponding to the current fire-fighting pipeline.

In step S201, the shallow hidden danger features refer to hidden danger features such as discoloration, abnormal temperature change, scaling, cracking, abrasion, condensation and the like of the surface layer of the fire fighting pipeline. If the pipeline surface image data accords with the preset pipeline shallow hidden danger standard, the fact that the surface layer of the current fire-fighting pipeline has actually appeared is indicated, and the shallow hidden danger characteristics of the surface of the current fire-fighting pipeline are further obtained so as to be convenient for identifying the damaged condition.

In step S202, the history hidden danger feature record refers to a related history record of damage features occurring in the fire fighting pipeline, the history induction frequency refers to the occurrence times of similar damage features in the history hidden danger feature record, and the history damage identification score refers to a damage condition identification score indicating that similar damage features occur each time.

For example, the shallow hidden trouble feature corresponding to the current fire-fighting pipeline is a surface crack, the feature is further identified to obtain a corresponding historical surface crack feature record, namely a historical hidden trouble feature record, and the corresponding historical induction frequency is further obtained through the historical surface crack feature record for 3 times, wherein the 3 times of specific historical damage identification scores are determined and scored according to the size, type, position and other conditions of the pipeline surface crack, and specific determination score criteria can refer to relevant clauses about 'pipeline surface defects' in the fire-fighting pipeline quality assessment technical specification.

In step S203, the number of historical induction frequencies affects the identification of the target damage level corresponding to the fire-fighting pipeline, and generally, the damage level is improved due to the occurrence of cracks for multiple times, and on the other hand, the damage identification score of each time the surface train is induced is also a condition for identifying the target damage level of the fire-fighting pipeline, so that the actual historical induction frequency of the fire-fighting pipeline and the corresponding historical damage identification score of each time the fire-fighting pipeline is evaluated comprehensively to generate the target damage level corresponding to the fire-fighting pipeline, wherein the target damage level can be divided into three levels of slight, moderate and severe, and the corresponding damage identification scores are respectively 0-60 score, 61-80 score and 81-100 score.

According to the fire-fighting pipeline monitoring method, the current pipeline is subjected to damage grading by combining the historical induction frequency and the historical damage identification score of the shallow hidden danger characteristics, so that the accuracy of safety monitoring of the pipeline is improved.

In one implementation manner of this embodiment, as shown in fig. 3, in step S202, if the shallow hidden danger feature has a corresponding history hidden danger feature record, the step of obtaining the history induction frequency and the history damage identification score corresponding to the shallow hidden danger feature in the history hidden danger feature record further includes the following steps:

s301, if the historical induction frequency exceeds a preset frequency standard, acquiring a damage distribution grade corresponding to the fire-fighting pipeline according to the historical damage identification score;

s302, combining the damage distribution level and the historical induction frequency, and outputting a service life prediction result corresponding to the fire-fighting pipeline.

In step S301, the preset frequency standard refers to a preset safety frequency standard of the same kind of damage induction frequency. For example, the preset frequency standard is specified according to fire-fighting pipeline quality assessment technical specification, and the number of occurrence of cracks of the fire-fighting pipeline exceeds 10 in 3-6 months, and the fire-fighting pipeline belongs to dangerous states, wherein the dangers comprise deterioration or strength reduction of pipeline materials, peeling of a coating, abnormal smell, obvious temperature change and the like, and the corresponding damage identification score is 85 points, namely the serious target damage grade.

For another example, the shallow hidden trouble is characterized by surface abrasion, the corresponding preset frequency standard is that the number of times of occurrence of cracks of the fire-fighting pipeline exceeds 8 in 3-6 months, the fire-fighting pipeline belongs to a dangerous state, and the specific damage identification scoring standard is as follows: the abrasion length is more than or equal to 2mm, and the corresponding damage identification score is 3, which belongs to the mild target damage grade; the abrasion depth is more than 2mm, and the corresponding damage identification score is 6, which belongs to the medium target damage grade; the abrasion form is a groove, and the corresponding damage identification score is 9, which belongs to the severe target damage grade; the influencing factors are mechanical and physical effects, and the corresponding injury identification score is 12, which belongs to the serious target injury grade.

The listed shallow hidden danger feature histories can be singly or simultaneously appeared in a plurality of modes, and comprehensive analysis is carried out according to the actual conditions and the historical damage identification scores corresponding to the shallow hidden danger features, so as to obtain the damage distribution grade corresponding to the fire-fighting pipeline. For example, when the emerging shallow hidden trouble is characterized by surface wear and surface cracks, its corresponding damage profile level includes a target damage level for the surface wear and surface cracks.

In step S302, the damage distribution level and the historical induction frequency may provide important information for life prediction of the fire pipe. First, by evaluating the structure, material, damage state, etc. of the fire-fighting pipeline, the damage distribution level can be obtained. Then, according to the historical damage induction frequency, the damage influence range and the potential safety hazard can be correspondingly evaluated, and finally, the service life prediction related result corresponding to the consumption pipeline is obtained.

According to the fire-fighting pipeline monitoring method, if the historical induction frequency exceeds the corresponding preset frequency standard, the fact that similar or abnormal damage occurs to the current fire-fighting pipeline is indicated, comprehensive evaluation is further carried out by combining the damage distribution grade corresponding to each historical damage identification score and the historical induction frequency, the residual service life prediction result of the fire-fighting pipeline is obtained, and therefore the monitoring effect of the use safety of the fire-fighting pipeline is improved.

In one implementation manner of this embodiment, as shown in fig. 4, in step S105, if the number of abnormal pipeline quality monitoring items is plural, obtaining the primary pipeline damage coefficient corresponding to each abnormal pipeline quality monitoring item includes the following steps:

s401, if a plurality of abnormal pipeline quality monitoring items are provided, acquiring target monitoring values corresponding to the abnormal pipeline quality monitoring items;

s402, if the target monitoring value exceeds a preset pipeline damage threshold, acquiring a corresponding damage class grade according to the target monitoring value;

s403, comprehensively judging damage to the fire-fighting pipeline by combining the damage class grade, and outputting a first-stage pipeline damage coefficient corresponding to the fire-fighting pipeline.

In step S401, the abnormal pipe quality monitoring items mentioned in this scheme are mainly the abnormal monitoring items for the fine changes affecting the inside of the monitoring pipe, such as corresponding monitoring items that cause deformation and deterioration of the pipe material, thinning of the inner wall of the pipe, and the like.

The quality monitoring indexes influencing the deformation, the thinning and the deterioration of the fire-fighting pipeline mainly comprise temperature monitoring, water pressure monitoring, material appearance monitoring, water stain performance monitoring, surface abrasion monitoring, wall thickness change monitoring and the like, and the deformation, the thinning and the deterioration of the pipe wall of the fire-fighting pipeline can be effectively identified through the monitoring of the indexes, so that the safe use of the fire-fighting pipeline is ensured.

Secondly, the target monitoring value corresponding to the abnormal pipeline quality monitoring item can be set according to different types (popular types). For example, in the aspect of water pressure monitoring, the setting can be performed according to three levels of low pressure, medium pressure and high pressure, and in the aspect of material appearance monitoring, the setting should be performed according to the use environment and fire protection system requirements.

In step S402, the preset pipeline damage threshold refers to a criterion that the preset target monitoring value is within a certain range of values and is considered as the current damage state of the pipeline.

For example, the abnormal pipeline quality monitoring item is an aluminum alloy fire-fighting pipeline water pressure, the corresponding target monitoring value is 11MPa, the maximum working pressure of the aluminum alloy pipeline can be up to 10MPa according to the corresponding preset pipeline damage threshold value, and when the water pressure exceeds the pressure value, mechanical damage with different degrees can be brought to the pipeline, and the mechanical damage is particularly dependent on the water pressure, the thickness of the pipeline and the treatment degree of the pipeline surface. When the water pressure is relatively large, deformation, cracking and fracture of the pipeline are caused, the deformation corresponds to the first-level water pressure damage level, the fracture corresponds to the second-level water pressure damage level, and the fracture corresponds to the third-level water pressure damage level.

For example, when the fire-fighting pipeline is damaged by water pressure and is also affected by water quality corrosion, different damage can be brought to the fire-fighting pipeline by water quality with different pH degrees, when the pH value is relatively low, acidic water easily erodes the surface of the fire-fighting pipeline, so that the surface of the fire-fighting pipeline is thinned and easily damaged, when the pH value is relatively high, alkaline water can chemically react with the metal pipe wall, so that damage such as hydrogen corrosion, oxidation stripping and leakage is caused, the damage is caused, the actual pH value in the fire-fighting pipeline, namely the target monitoring value, is compared with the corresponding preset pipeline damage threshold, namely the water quality PH safety standard range, and the corresponding water quality damage class grade is obtained according to the actual pH value of water quality in the current fire-fighting pipeline when the pH value exceeds the range.

In step S403, the actual damage of the current fire-fighting pipeline is comprehensively determined by combining the obtained damage class grades corresponding to the different damage, and a first-stage pipeline damage coefficient corresponding to the fire-fighting pipeline is output, through which the state of the current fire-fighting pipeline can be evaluated to determine whether repair or replacement of a new pipeline is required.

According to the fire-fighting pipeline monitoring method, if the target monitoring value exceeds the preset pipeline damage threshold, the abnormal pipeline quality monitoring item corresponding to the target monitoring value is indicated to be in a stage of seriously affecting the fire-fighting pipeline, and comprehensive damage judgment is further carried out on the fire-fighting pipeline by combining the damage class grade corresponding to the target monitoring value, so that the damage monitoring effect of the fire-fighting pipeline is improved.

In one implementation manner of this embodiment, as shown in fig. 5, in step S401, if the number of abnormal pipeline quality monitoring items is plural, the method further includes the following steps after obtaining the target monitoring values corresponding to the abnormal pipeline quality monitoring items:

s501, if the target monitoring value exceeds a preset pipeline damage threshold, acquiring an induction source of an abnormal pipeline quality monitoring item corresponding to the target monitoring value;

s502, if a plurality of induction sources are provided, acquiring the abnormal contribution duty ratio corresponding to each induction source;

s503, combining the abnormal contribution proportion, and generating an abnormal item distribution table corresponding to the abnormal pipeline quality monitoring item.

In step S501, the induction source refers to a source that induces an abnormal pipeline quality monitoring item. For example, abnormal increases in water pressure within a fire pipe may be induced by pipe equipment failure, internal leaks, pipe specifications disqualification, incorrect construction methods or materials, problems with the pressurization device, and pump system failure. Wherein, the partial detection of the induction source can be realized by locally checking internal leakage by laser or nuclear magnetic resonance technology, measuring parameters of a pipeline system, verifying whether the specifications are proper, and the like.

In steps S502 to S503, the abnormal contribution ratio refers to the abnormal influence specific gravity of each induction source on the same abnormal pipe quality monitoring item. For example, the abnormal pipeline quality monitoring item is a fire-fighting pipeline water pressure abnormality, the corresponding induction sources comprise internal accumulated water in the pipeline, insufficient water pump pressure and pipeline blockage, wherein the abnormal contribution ratio corresponding to the internal accumulated water is 50%, the abnormal contribution ratio corresponding to the water pump pressure is 30% and the abnormal contribution ratio corresponding to the pipeline blockage is 20% after the water pressure abnormality detection, and then the obtained abnormal contribution ratio is combined to generate an abnormal item distribution table corresponding to the fire-fighting pipeline water pressure abnormality, namely the abnormal pipeline quality monitoring item, and the staff can carry out depth analysis on specific data corresponding to the induction sources causing the fire-fighting pipeline water pressure abnormality through the abnormal item distribution table.

According to the firefighting pipeline monitoring method, the abnormal factor distribution situation indirectly influencing the safety of the firefighting pipeline can be intuitively obtained by combining the abnormal contribution proportion corresponding to each induction source.

In one implementation manner of this embodiment, as shown in fig. 6, in step S106, if there is an influence of correlation between the abnormal pipeline quality monitoring items, obtaining the diode damage coefficient corresponding to the abnormal pipeline quality monitoring item includes the following steps:

S601, if correlation influence exists among abnormal pipeline quality monitoring items, acquiring correlation influence degree among the abnormal pipeline quality monitoring items corresponding to the correlation influence exists;

s602, outputting a secondary pipeline damage coefficient corresponding to the abnormal pipeline quality monitoring item according to the association influence degree.

In step S601, the associated influence refers to a relationship in which there is an influence and an influence between abnormal pipe quality monitoring items. For example, the abnormal pipeline quality monitoring items are fire-fighting pipeline water pressure and fire-fighting pipeline temperature, the fire-fighting pipeline temperature is abnormal, the fire-fighting pipeline water pressure is abnormal, the volume of water changes along with the change of temperature, when the temperature rises, the water volume is increased, the internal water pressure is increased, and therefore when the water pressure and the temperature in the fire-fighting pipeline are abnormal, the fire-fighting pipeline water pressure and the fire-fighting pipeline water pressure are crossed, and the damage degree of the fire-fighting pipeline is increased.

Secondly, the association influence degree refers to a specific quantitative influence degree among abnormal pipeline quality monitoring items with association influence. For example, when the water pressure of the fire-fighting pipeline is 20-25 MPa, the temperature change range is-1 ℃ to +3.5 ℃, and when the water pressure exceeds 25MPa, the temperature is greatly affected and can reach 95 ℃, so that the pipeline is broken and leaked.

In step S602, the corresponding association 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 items is output. The damage coefficient of the secondary pipeline can be set according to the numerical change rate generated by the mutual influence among abnormal pipeline quality monitoring items. For example, when the fire pipe temperature rises by 1 ℃, the water pressure may correspondingly rise by 0.14MPa, although the effects are not significant, when the fire pipe temperature and the water pressure are simultaneously abnormal, the partial association effects exceed the fire pipe bearing critical value, or the pipe is likely to be broken or leaked.

According to the fire-fighting pipeline monitoring method provided by the embodiment, the specific association influence degree among abnormal pipeline quality monitoring items is used as the secondary pipeline damage coefficient corresponding to the fire-fighting pipeline, and corresponding potential indirect damage can be evaluated on the basis of monitoring the direct damage of the fire-fighting pipeline, so that the fire-fighting pipeline safety monitoring effect is improved.

In one implementation manner of this embodiment, as shown in fig. 7, in step S601, that is, if there is an association influence between abnormal pipeline quality monitoring items, the method further includes the following steps after obtaining the association influence degree between abnormal pipeline quality monitoring items corresponding to the association influence.

S701, acquiring a corresponding association category according to the association influence;

s702, if the association category is one-way association, judging and acquiring corresponding association root source points and association induction points in the abnormal pipeline quality monitoring items, and generating a corresponding association indication table according to the association root source points and the association induction points;

s703, if the association category is bidirectional association, generating a corresponding association indication table according to the association influence coefficient corresponding to the abnormal pipeline quality monitoring item.

In step S701, the association class refers to a class divided according to specific association influences between abnormal pipe quality monitoring items. For example, vibration of the fire-fighting pipe affects the change of the air pressure of the fire-fighting pipe, and generates a mixture of air and water by affecting the flow of water in the pipe, so that the vibration of the fire-fighting pipe may cause the air pressure in the fire-fighting pipe to rise, and the air pressure of the fire-fighting pipe is one of factors causing damage to the fire-fighting pipe, so that the corresponding associated category is the fire-fighting pipe (vibration-air pressure).

In steps S702 to S703, in order to analyze the influence of the association between the abnormal pipeline quality monitoring items in depth, the association types are further classified into a unidirectional association and a bidirectional association. Wherein, the unidirectional association refers to that the change of one type of abnormal pipeline quality monitoring item can affect the other type of abnormal pipeline quality monitoring item, but the change of the other type of abnormal pipeline quality monitoring item cannot be affected, and the bidirectional association refers to the mutual influence between two or more types of abnormal pipeline quality monitoring items, and the two or more types of abnormal pipeline quality monitoring items can interact, are mutually affected and coordinate with each other.

If the association category is one-way association, judging and acquiring an association root source point and an association induction point corresponding to the abnormal pipeline quality monitoring item. The association root source points refer to root points of influence of changes of the abnormal pipeline quality monitoring items on the abnormal pipeline quality monitoring items, for example, fire-fighting pipeline vibration can cause the rise of fire-fighting pipeline water pressure, the fire-fighting pipeline vibration is the association root source point, the fire-fighting pipeline water pressure rises to be the association induction point, and then a corresponding association indication table is generated according to the set association root source point and the association induction point, and the association indication table records the pointing relation of the fire-fighting pipeline water pressure rise caused by the fire-fighting pipeline vibration in one direction.

And secondly, if the association type is bidirectional association, according to the association influence coefficient corresponding to the abnormal pipeline quality monitoring item. Wherein the associated influence coefficient depends on a specific influence degree among a plurality of abnormal pipeline quality monitoring items, such as fire pipeline temperature and water pressure. For example, when the fire line temperature rises by 1 ℃, the water pressure may correspondingly rise by 0.14MPa, whereas when the water pressure rises by 1 Bar (Bar), the temperature increases by about 2 ℃, and when the water pressure rises from 3.5 Bar to 4.5 Bar, the temperature increases by about 4 ℃. And then generating a corresponding association indicator according to the obtained association influence coefficient, and obtaining the type of the abnormal pipeline quality monitoring item and the mutual association influence degree among the abnormal pipeline quality monitoring items through the association indicator.

According to the fire-fighting pipeline monitoring method, corresponding influence factor analysis strategies among abnormal pipeline quality monitoring items are respectively set according to the association categories corresponding to the association influence degrees, so that the safety analysis effect of potential hidden danger of the fire-fighting pipeline is improved.

The embodiment of the application discloses a fire-fighting pipeline monitoring system, as shown in fig. 8, comprising:

the first acquisition module 1 is used for acquiring monitoring data of the fire control pipeline;

the identification module 2 is used for identifying the monitoring data and acquiring corresponding pipeline surface image data;

the second acquisition module 3 is used for acquiring a pipeline quality monitoring item corresponding to the fire-fighting pipeline if the pipeline surface image data accords with a preset pipeline shallow hidden danger standard;

the third obtaining module 4 is configured to obtain a corresponding abnormal pipeline quality monitoring item if the pipeline quality monitoring item does not conform to the preset pipeline quality monitoring index;

the first evaluation module 5 is used for acquiring a primary pipeline damage coefficient corresponding to each abnormal pipeline quality monitoring item if the abnormal pipeline quality monitoring items are multiple;

the second evaluation module 6 is used for acquiring a secondary pipeline damage coefficient corresponding to the abnormal pipeline quality monitoring item if the abnormal pipeline quality monitoring item has a correlation influence;

And the combining module 7 is used for combining the primary pipeline damage coefficient, the secondary pipeline damage coefficient and the pipeline surface image data to generate a damage judgment report corresponding to the fire-fighting pipeline.

According to the fire fighting pipeline monitoring system provided by the embodiment, whether the pipeline surface image data corresponding to the fire fighting pipeline is abnormal or not, namely whether the pipeline is in a shallow defect or not is judged according to the preset pipeline shallow hidden danger standard, if the current pipeline is in a damaged condition, the pipeline quality monitoring items corresponding to the fire fighting pipeline are analyzed and judged one by one according to the preset pipeline quality monitoring index, if the corresponding abnormal pipeline quality monitoring items are obtained through the third obtaining module 4, the first pipeline damage coefficient of direct damage to the pipeline caused by each abnormal pipeline quality monitoring item is obtained through the first evaluating module 5, if the abnormal pipeline quality monitoring items have a correlation influence, the second pipeline damage coefficient of indirect damage to the pipeline caused by the abnormal pipeline quality monitoring items is obtained through the second evaluating module 6, and then the damage judgment report of comprehensive damage evaluation of the fire fighting pipeline is generated by combining the obtained first pipeline damage coefficient, the second pipeline damage coefficient and the pipeline surface image data, and the fire fighting pipeline hidden danger monitoring safety is evaluated due to the fact that the fire fighting pipeline is combined and the hidden danger corresponding to the deep hidden danger is comprehensively improved.

It should be noted that, the fire protection pipeline monitoring system provided by the embodiment of the present application further includes each module and/or the corresponding sub-module corresponding to the logic function or the logic step of any one of the above fire protection pipeline monitoring systems, so that the same effects as each logic function or logic step are achieved, and detailed descriptions thereof are omitted herein.

The embodiment of the application also discloses a terminal device which comprises a memory, a processor and computer instructions which are stored in the memory and can run on the processor, wherein when the processor executes the computer instructions, any fire fighting pipeline monitoring method in the embodiment is adopted.

The terminal device may be a computer device such as a desktop computer, a notebook 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 further include an input/output device, a network access device, a bus, and the like.

The processor may be a Central Processing Unit (CPU), or of course, according to actual use, other general purpose processors, digital Signal Processors (DSP), application Specific Integrated Circuits (ASIC), ready-made programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc., and the general purpose processor may be a microprocessor or any conventional processor, etc., which is not limited in this respect.

The memory may be an internal storage unit of the terminal device, for example, a hard disk or a memory of the terminal device, or an external storage device of the terminal device, for example, a plug-in hard disk, a Smart Memory Card (SMC), a secure digital card (SD), or a flash memory card (FC) provided on the terminal device, or the like, and may be a combination of the internal storage unit of the terminal device and the external storage device, where the memory is used to store computer instructions and other instructions and data required by the terminal device, and the memory may be used to temporarily store data that has been output or is to be output, which is not limited by the present application.

Any one of the fire-fighting pipeline monitoring methods in the embodiment is stored in the memory of the terminal equipment through the terminal equipment, and is loaded and executed on the processor of the terminal equipment, so that the fire-fighting pipeline monitoring method is convenient to use.

The embodiment of the application also 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 fire fighting pipeline monitoring method in the embodiment is adopted.

The computer instructions may be stored in a computer readable medium, where the computer instructions include computer instruction codes, where the computer instruction codes may be in a source code form, an object code form, an executable file form, or some middleware form, etc., and the computer readable medium includes any entity or device capable of carrying the computer instruction codes, a recording medium, a usb disk, a mobile hard disk, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a Random Access Memory (RAM), an electrical carrier signal, a telecommunication signal, a software distribution medium, etc., where the computer readable medium includes but is not limited to the above components.

Any of the fire fighting pipeline monitoring methods in the above embodiments is stored in the computer readable storage medium through the computer readable storage medium, and is loaded and executed on a processor, so as to facilitate the storage and application of the method.

The above embodiments are not intended to limit the scope of the present application, so: all equivalent changes in structure, shape and principle of the application should be covered in the scope of protection of the application.

Claims

1. A method for monitoring a fire fighting pipeline, comprising the steps of:

acquiring monitoring data of a fire control pipeline;

2. A fire pipe monitoring method according to claim 1, further comprising the steps of, after said identifying said monitoring data, acquiring corresponding pipe surface image data:

3. The method for monitoring a fire protection pipeline according to claim 2, wherein after the step of obtaining the historical induction frequency and the historical damage identification score corresponding to the shallow hidden danger feature in the historical hidden danger feature record if the corresponding historical hidden danger feature record exists, the method further comprises the steps of:

4. The method for monitoring fire pipes according to claim 1, wherein if the number of the abnormal pipe quality monitoring items is plural, obtaining the first-stage pipe damage coefficient corresponding to each abnormal pipe quality monitoring item comprises the steps of:

5. The method for monitoring fire pipes according to claim 4, further comprising the steps of, after the obtaining target monitoring values corresponding to the abnormal pipe quality monitoring items if the abnormal pipe quality monitoring items are plural:

6. The method for monitoring fire pipes according to claim 1, wherein if there is an influence of the correlation between the abnormal pipe quality monitoring items, obtaining the secondary pipe damage coefficient corresponding to the abnormal pipe quality monitoring item comprises the following steps:

7. The fire protection pipe monitoring method according to claim 1, wherein after the correlation influence exists among the abnormal pipe quality monitoring items, the correlation influence degree among the abnormal pipe quality monitoring items corresponding to the correlation influence exists is obtained, the method further comprises the following steps:

8. A fire pipe monitoring system, comprising:

the first acquisition module (1) is used for acquiring monitoring data of the fire-fighting pipeline;

the identification module (2) is used for identifying the monitoring data and acquiring corresponding pipeline surface image data;

the second acquisition module (3) is used for acquiring a pipeline quality monitoring item corresponding to the fire-fighting pipeline if the pipeline surface image data accords with a preset pipeline shallow hidden danger standard;

the third acquisition module (4) is used for acquiring a corresponding abnormal pipeline quality monitoring item if the pipeline quality monitoring item does not accord with a preset pipeline quality monitoring index;

the first evaluation module (5) is used for acquiring a primary pipeline damage coefficient corresponding to each abnormal pipeline quality monitoring item if the abnormal pipeline quality monitoring items are multiple;

the second evaluation module (6) is used for acquiring a diode damage coefficient corresponding to the abnormal pipeline quality monitoring item if the abnormal pipeline quality monitoring item has a correlation influence;

And the combining module (7) is used for combining the primary pipeline damage coefficient, the secondary pipeline damage coefficient and the pipeline surface image data to generate a damage judgment report corresponding to the fire-fighting pipeline.

9. A terminal device comprising a memory and a processor, wherein the memory has stored therein computer instructions executable on the processor, which processor, when loaded and executed, employs a fire pipe monitoring method according to any one of claims 1 to 7.

10. A computer readable storage medium having stored therein computer instructions which, when loaded and executed by a processor, employ a fire pipe monitoring method according to any one of claims 1 to 7.