Environmental protection equipment self-adaptive adjusting system and method based on environmental perception

Abstract

The invention discloses an environmental protection equipment self-adaptive adjustment system and method based on environmental perception, and relates to the technical field of equipment self-adaptive adjustment, and the method comprises the steps: obtaining historical adjustment records of environmental protection equipment, analyzing the change condition presented by the sensing data of a sensor in each adjustment record, and extracting a first mark record from the adjustment records; the change degree corresponding to each sensor is obtained, and a second mark record is extracted from the adjustment record; a feature adjustment record is obtained, a three-dimensional model of the building space is established, and a reference sensing set is obtained; and establishing a three-dimensional model of the to-be-detected building space, obtaining a to-be-detected sensing set, and judging whether to carry out early warning prompt on the sensors in the to-be-detected building space or not. According to the method, the sensing set is established by analyzing the historical adjustment records, and early warning prompt is performed on unreasonably deployed sensors in the current to-be-detected building space, so that powerful data support is provided for follow-up related technicians to analyze the environment quality.

Description

Technical Field

[0001] The present invention relates to the technical field of equipment adaptive adjustment, and in particular to an environmental protection equipment adaptive adjustment system and method based on environment perception. Background Art

[0002] Environmental protection equipment refers to mechanical products, structures and systems used to control environmental pollution and improve environmental quality. Environmental protection equipment has a wide range of applications, including solid waste treatment, environmental monitoring, air purification and sewage treatment. The adaptive adjustment process of environmental protection equipment includes: using high-precision sensors deployed at key locations of environmental protection equipment and target environmental areas to form a three-dimensional perception network. These sensors can collect relevant parameter information in the environment in real time and continuously, and transmit it to the central control system through wired or wireless transmission, and then realize adaptive adjustment through intelligent data analysis.

[0003] However, when deploying sensors, if the complexity of the environment and the environmental area are not fully considered, the sensor layout will be unreasonable. For example, when the sensor deployment location is too hidden or interfered with by other equipment, the data changes on the sensor will be abnormal compared with normal changes when the environment is adjusted. As a result, the data detected by the sensor is not representative, and it is impossible to fully and accurately characterize the actual data changes in the environmental area and the true state of the overall environment, and it is impossible to provide strong data support for relevant technical personnel to analyze environmental quality. Summary of the invention

[0004] The purpose of the present invention is to provide an environmental protection equipment adaptive adjustment system and method based on environmental perception to solve the problems raised in the prior art.

[0005] To achieve the above object, the present invention provides the following technical solutions:

[0006] The method for adaptively adjusting environmental protection equipment based on environmental perception includes the following steps:

[0007] Step S100: obtaining historical adjustment records of environmental protection equipment, where the adjustment records are records of adjusting the environment through the environmental protection equipment when the sensor data of the sensor is not within a normal value range; analyzing the changes in the sensor data of the sensor in each adjustment record, and extracting a first marking record from the adjustment record;

[0008] Step S200: obtaining the degree of change corresponding to each sensor according to the sensing data of each sensor corresponding to each adjustment record, and extracting a second marking record from the adjustment record according to the degree of change;

[0009] Step S300: obtaining a feature adjustment record according to the first marking record and the second marking record; establishing a three-dimensional model of the building space where the environmental protection equipment is located, marking the location of each sensor, and obtaining a reference perception set according to the sensor location corresponding to each feature adjustment record;

[0010] The purpose of obtaining the characteristic adjustment record according to the first marking record and the second marking record is as follows: the first marking record is obtained according to the sensor data corresponding to the adjustment record. When the change of the sensor data is normal, it means that the adjustment record is normal; the second marking record is a record when the change degree corresponding to the target sensor is distributed more evenly. In general, when the change degree of each sensor is quite different, that is, when the distribution is more even, the change value of the sensor at this time has greater reference significance for analyzing the change of the entire environmental space, and this is exactly the characteristic that this scheme hopes to have. Therefore, this type of adjustment record is used as the second marking record. The adjustment record corresponding to the characteristic adjustment record not only has normal changes in the sensor data, but also has greater reference significance for its degree of change. Therefore, this scheme uses the characteristic adjustment record as the reference standard, and obtains the benchmark perception set by summarizing the laws of the characteristic adjustment record, which provides important reference significance for the following exploration of whether the changes of the sensors in the space to be detected are reasonable.

[0011] Step S400: Establish a three-dimensional model of the building space to be detected, obtain the perception set to be detected according to the location of each sensor in the building space to be detected and the sensor data of each sensor, and combine it with the benchmark perception set to determine whether to issue an early warning prompt for the sensors in the building space to be detected.

[0012] Furthermore, step S100 includes:

[0013] Step S110: Obtain the normal value range (V1, V2) corresponding to the sensor data, where V1 and V2 are the minimum normal value and the maximum normal value respectively; obtain the sensor data of all sensors in the building space where the environmental protection equipment is located, and capture the start adjustment time, end adjustment time and target sensor corresponding to each adjustment record. The target sensor is the sensor whose sensor data is outside the normal value range in the time period T1 before the start adjustment time;

[0014] Step S120: for all target sensors corresponding to a certain adjustment record, the function of the change of the sensor data over time during the adjustment process is set as a first change function, and the function of the change of the sensor data over time in a time period T2 after the adjustment is finished is set as a second change function;

[0015] The middle value of the normal value range is taken as V0, a ​​certain moment in the adjustment process is taken as a, and the next moment of moment a is taken as b; if the sensor data at moment b in the first change function F1 corresponding to a certain target sensor is closer to V0 than the sensor data at moment a, then the moment a in the function F1 is marked, and then all the marked moments in the function F1 are obtained. If the number of marked moments in the function F1 is greater than the number threshold, a certain target sensor in a certain adjustment record is first marked;

[0016] If all target sensors in a certain adjustment record are first marked, and in the second variation functions corresponding to all target sensors, the sensing data at each moment are within the normal value range, then the certain adjustment record is taken as the first marked record, and all first marked records are obtained.

[0017] Further, step S200 includes:

[0018] Step S210: Obtain a first change function of a target sensor E corresponding to a certain adjustment record, extract all marked moments in the first change function, and summarize them to obtain a total marking duration D, and use the difference between the maximum sensor data and the minimum sensor data in the marked moment as the data difference V, and then obtain the change degree B=V / D of the target sensor E;

[0019] Step S220: If the degree of change B is greater than a preset degree of change threshold, the target sensor E is second-marked, and then all the second-marked target sensors in a certain adjustment record are obtained; according to the degree of change of each second-marked target sensor, the variance is calculated as the adjustment value of a certain adjustment record. If the adjustment value is greater than the adjustment threshold, the certain adjustment record is recorded as a second mark, and all the second mark records are obtained.

[0020] Furthermore, step S300 includes:

[0021] Step S310: if a certain adjustment record is both a first mark record and a second mark record, the certain adjustment record is used as a characteristic adjustment record; according to the change degree of each target sensor corresponding to each characteristic adjustment record, all the change degrees corresponding to a certain target sensor are added together to obtain an average value, which is used as the characteristic degree of the certain target sensor;

[0022] Step S320: Establish a three-dimensional model of the building space where the environmental protection equipment is located, and mark the equipment adjustment part in the three-dimensional model. The equipment adjustment part is the output port on the environmental protection equipment for realizing the environmental adjustment function, and sort the target sensors in order from near to far from the equipment adjustment part;

[0023] Then establish the benchmark perception set X, X = {(L1, C1), (L2, C2), ..., (L m ,Cm )}, where L1,L2,…,L m are the distances between the target sensors with serial numbers 1, 2, ..., m and the adjustment parts of the equipment, C1, C2, ..., C m are the characteristic levels of the target sensors numbered 1, 2, …, m respectively.

[0024] It should be noted that in this solution, the judgment of whether the location of each sensor is reasonable is mainly based on the change of the sensor data of the sensors at each distance device adjustment location. Under normal circumstances, the data changes of the same type of sensors deployed at different locations should have a certain logical consistency. Taking the sensor as a temperature sensor, for example, to monitor the air temperature, the temperature sensors are deployed at locations from near to far from the device adjustment location. Under normal circumstances, the degree of change of the temperature sensor should gradually decrease as the distance increases, so the degree of change of the sensor with a closer distance should generally be higher than that of the sensor with a farther distance. If the distance is reasonable but the sensor data is unreasonable, that is, the data has illogical jumps or fluctuations, it may mean that the location of some sensors is affected by local interference factors, or the location setting is unreasonable, resulting in the data not accurately reflecting the natural changes of the air temperature. Then it is enough to show that the current sensor position is unreasonable relative to the historical change law, and it is necessary to warn its position and inform the relevant personnel that further adjustments are needed.

[0025] Furthermore, step S400 includes:

[0026] Step S410: deploy at least M sensors in the building space to be detected; obtain a first change function of each target sensor corresponding to a certain adjustment record in the building space to be detected, and obtain a change degree of each target sensor according to each first change function, and use each change degree as a characteristic degree of each target sensor;

[0027] According to the distance between each target sensor and the equipment adjustment part in the building space to be detected, the target sensors are sorted in order from near to far, and the perception set to be detected Y is obtained, Y = {(L1, C1), (L2, C2), …, (L n ,C n )}, where L1,L2,…,L n are the distances between the target sensors with serial numbers 1, 2, ..., n and the adjustment parts of the equipment, C1, C2, ..., C n are the characteristic degrees of the target sensors numbered 1, 2, …, n respectively;

[0028] Step S420: Establish a two-dimensional coordinate system in which the characteristic degree varies with the distance, extract each element in the set X and Y, and mark the coordinates of each element in the two-dimensional coordinate system, and perform fitting C=k*L+b according to the least squares method, where C is the characteristic degree, L is the distance, k is the slope, and b is the intercept, and obtain the goodness of fit R obtained in the fitting process 2 , when the goodness of fit R 2 ≤k R When k R As the early warning factor, early warning prompts are given to the sensors in the building space to be detected.

[0029] An environmental protection equipment adaptive adjustment system based on environmental perception includes a first mark record extraction module, a second mark record extraction module, a benchmark perception set establishment module and an early warning prompt module;

[0030] The first marked record extraction module is used to obtain the adjustment record of the environmental protection equipment history, where the adjustment record is a record of the environment being adjusted by the environmental protection equipment when the sensor data of the sensor is not within the normal value range; analyze the changes in the sensor data of the sensor in each adjustment record, and extract the first marked record from the adjustment record;

[0031] A second marked record extraction module: used to obtain the change degree corresponding to each sensor according to the sensor data of each sensor corresponding to each adjustment record, and extract the second marked record from the adjustment record according to the change degree;

[0032] The reference perception set establishment module is used to obtain the feature adjustment record according to the first marking record and the second marking record; establish a three-dimensional model of the building space where the environmental protection equipment is located, and mark the location of each sensor, and obtain the reference perception set according to the sensor location corresponding to each feature adjustment record;

[0033] Early warning module: used to establish a three-dimensional model of the building space to be detected, obtain the perception set to be detected according to the location of each sensor in the building space to be detected and the sensor data of each sensor, and combine it with the benchmark perception set to determine whether to issue an early warning to the sensors in the building space to be detected.

[0034] Further, the first marked record extraction module includes a target sensor determination unit and a first marked record extraction unit;

[0035] Target sensor determination unit: used to obtain the sensor data of all sensors in the building space where the environmental protection equipment is located, and capture the start adjustment time, end adjustment time and target sensor corresponding to each adjustment record;

[0036] The first marking record extraction unit is used to obtain all the first change functions and the second change functions corresponding to a certain adjustment record, and extract the first marking record from the adjustment record according to the first change function and the second change function.

[0037] Furthermore, the early warning prompt module has a detection perception set establishment unit and an early warning prompt unit;

[0038] The sensing set to be detected is established by a unit for establishing a three-dimensional model of the building space to be detected, and the sensing set to be detected is obtained according to the location of each sensor in the building space to be detected and the sensing data of each sensor;

[0039] Early warning prompt unit: It is used to determine whether to issue an early warning prompt to the sensors in the building space to be detected based on the obtained perception set to be detected and combined with the benchmark perception set.

[0040] Compared with the prior art, the beneficial effects of the present invention are as follows: the present invention provides an adaptive adjustment system and method for environmental protection equipment based on environmental perception, including: obtaining the historical adjustment records of environmental protection equipment, analyzing the changes presented by the sensor data of the sensor in each adjustment record, and extracting the first mark record from the adjustment record; obtaining the degree of change corresponding to each sensor, and extracting the second mark record from the adjustment record; obtaining the characteristic adjustment record, establishing a three-dimensional model of the building space, and obtaining a baseline perception set; establishing a three-dimensional model of the building space to be detected, obtaining the perception set to be detected, and determining whether to issue an early warning prompt for the sensors in the building space to be detected. The present invention analyzes the historical adjustment records, establishes a perception set, and issues early warning prompts for unreasonable sensors deployed in the current building space to be detected, thereby providing strong data support for subsequent related technical personnel to analyze environmental quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 It is a flow chart of the method for adaptively adjusting environmental protection equipment based on environmental perception of the present invention;

[0042] Figure 2 This is a structural diagram of the environmental protection equipment adaptive adjustment system based on environmental perception of the present invention. DETAILED DESCRIPTION

[0043] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0044] Example: Figure 1As shown, the present invention provides a system and method for adaptively adjusting environmental protection equipment based on environmental perception, comprising the following steps:

[0045] Step S100: obtaining historical adjustment records of environmental protection equipment, where the adjustment records are records of adjusting the environment through the environmental protection equipment when the sensor data of the sensor is not within a normal value range; analyzing the changes in the sensor data of the sensor in each adjustment record, and extracting a first marking record from the adjustment record;

[0046] Step S110: Obtain the normal value range (V1, V2) corresponding to the sensor data, where V1 and V2 are the minimum normal value and the maximum normal value respectively; obtain the sensor data of all sensors in the building space where the environmental protection equipment is located, and capture the start adjustment time, end adjustment time and target sensor corresponding to each adjustment record. The target sensor is the sensor whose sensor data is outside the normal value range in the time period T1 before the start adjustment time;

[0047] In this embodiment, the adjustment scenario is: taking the temperature and humidity in the factory as an example, when the temperature or humidity in the factory is too high, it is necessary to cool down through air conditioning or dehumidifiers, and the air conditioners and dehumidifiers are used to improve the environment through corresponding exhaust vents; when the temperature or humidity in the factory reaches a certain value, that is, outside the normal value range, adjustment is performed, and the sensor outside the normal value range is used as the target sensor at this time, and when the temperature or humidity in the factory reaches a certain value within the normal value range, the adjustment is stopped.

[0048] Step S120: for all target sensors corresponding to a certain adjustment record, the function of the change of the sensor data over time during the adjustment process is set as a first change function, and the function of the change of the sensor data over time in a time period T2 after the adjustment is finished is set as a second change function;

[0049] The middle value of the normal value range is taken as V0, a ​​certain moment in the adjustment process is taken as a, and the next moment of moment a is taken as b; if the sensor data at moment b in the first change function F1 corresponding to a certain target sensor is closer to V0 than the sensor data at moment a, then the moment a in the function F1 is marked, and then all the marked moments in the function F1 are obtained. If the number of marked moments in the function F1 is greater than the number threshold, a certain target sensor in a certain adjustment record is first marked;

[0050] If all target sensors in a certain adjustment record are first marked, and in the second variation functions corresponding to all target sensors, the sensing data at each moment are within the normal value range, then the certain adjustment record is taken as the first marked record, and all first marked records are obtained.

[0051] Step S200: obtaining the degree of change corresponding to each sensor in each adjustment record according to the sensing data of each sensor, and extracting a second marking record from the adjustment record according to the degree of change.

[0052] Step S210: Obtain a first change function of a target sensor E corresponding to a certain adjustment record, extract all marked moments in the first change function, and summarize them to obtain a total marking duration D, and use the difference between the maximum sensor data and the minimum sensor data in the marked moment as the data difference V, and then obtain the change degree B=V / D of the target sensor E;

[0053] Step S220: If the degree of change B is greater than a preset degree of change threshold, the target sensor E is second-marked, and then all the second-marked target sensors in a certain adjustment record are obtained; according to the degree of change of each second-marked target sensor, the variance is calculated as the adjustment value of a certain adjustment record. If the adjustment value is greater than the adjustment threshold, the certain adjustment record is recorded as a second mark, and all the second mark records are obtained.

[0054] Step S300: obtaining a feature adjustment record according to the first marking record and the second marking record; establishing a three-dimensional model of the building space where the environmental protection equipment is located, marking the location of each sensor, and obtaining a reference perception set according to the sensor location corresponding to each feature adjustment record;

[0055] Step S310: If an adjustment record is both a first mark record and a second mark record, the adjustment record is used as a characteristic adjustment record; according to the degree of change of each target sensor corresponding to each characteristic adjustment record, all the degree of change corresponding to a certain target sensor are added together to obtain an average value as the characteristic degree of the certain target sensor.

[0056] Here, the purpose of obtaining the characteristic adjustment record according to the first mark record and the second mark record is: the first mark record is obtained according to the sensor data corresponding to the adjustment record, and when the change of the sensor data is normal, it means that the adjustment record is normal; the second mark record is a record when the change degree corresponding to the target sensor is distributed more evenly. Because in general, when the change degree of each sensor is greatly different, that is, when the distribution is more even, the change value of the sensor at this time has greater reference significance for the analysis of the change of the entire environmental space, and this is exactly the characteristic that this scheme hopes to have, so this type of adjustment record is used as the second mark record. The adjustment record corresponding to the characteristic adjustment record not only has normal changes in sensor data, but also has greater reference significance in terms of its degree of change. Therefore, this scheme uses the characteristic adjustment record as the reference standard, and obtains the benchmark perception set by summarizing the laws of the characteristic adjustment record, which provides important reference significance for the following exploration of whether the changes of sensors in the space to be detected are reasonable.

[0057] Step S320: Establish a three-dimensional model of the building space where the environmental protection equipment is located, and mark the equipment adjustment part in the three-dimensional model. The equipment adjustment part is the output port on the environmental protection equipment for realizing the environmental adjustment function, and sort the target sensors in order from near to far from the equipment adjustment part;

[0058] Then establish the benchmark perception set X, X = {(L1, C1), (L2, C2), ..., (L m ,C m )}, where L1,L2,…,L m are the distances between the target sensors with serial numbers 1, 2, ..., m and the adjustment parts of the equipment, C1, C2, ..., C m are the characteristic levels of the target sensors numbered 1, 2,…, m respectively.

[0059] It should be noted that in this solution, the judgment of whether the location of each sensor is reasonable is mainly based on the change of the sensor data of the sensors at each distance device adjustment location. Under normal circumstances, the data changes of the same type of sensors deployed at different locations should have a certain logical consistency. Taking the sensor as a temperature sensor, for example, to monitor the air temperature, the temperature sensors are deployed at locations from near to far from the device adjustment location. Under normal circumstances, the degree of change of the temperature sensor should gradually decrease as the distance increases, so the degree of change of the sensor with a closer distance should generally be higher than that of the sensor with a farther distance. If the distance is reasonable but the sensor data is unreasonable, that is, the data has illogical jumps or fluctuations, it may mean that the location of some sensors is affected by local interference factors, or the location setting is unreasonable, resulting in the data not accurately reflecting the natural changes of the air temperature. Then it is sufficient to show that the current sensor position is unreasonable relative to the historical change law, and it is necessary to warn its position and inform the relevant personnel that further adjustments are needed.

[0060] Step S400: Establish a three-dimensional model of the building space to be detected, obtain the perception set to be detected according to the location of each sensor in the building space to be detected and the sensor data of each sensor, and combine it with the benchmark perception set to determine whether to issue an early warning prompt for the sensors in the building space to be detected.

[0061] Step S410: deploy at least M sensors in the building space to be detected; obtain a first change function of each target sensor corresponding to a certain adjustment record in the building space to be detected, and obtain a change degree of each target sensor according to each first change function, and use each change degree as a characteristic degree of each target sensor;

[0062] In this plan, M should be determined according to the actual size of the factory. When the factory is large, the value of M should be larger for the reliability and rationality of data analysis. When the factory is small, it can be relatively small, but the value of M should not be less than 2.

[0063] According to the distance between each target sensor and the equipment adjustment part in the building space to be detected, the target sensors are sorted in order from near to far, and the perception set to be detected Y is obtained, Y = {(L1, C1), (L2, C2), …, (L n ,C n )}, where L1,L2,…,L n are the distances between the target sensors with serial numbers 1, 2, ..., n and the adjustment parts of the equipment, C1, C2, ..., C n are the characteristic degrees of the target sensors numbered 1, 2, …, n respectively;

[0064] Step S420: Establish a two-dimensional coordinate system in which the characteristic degree varies with the distance, extract each element in the set X and Y, and mark the coordinates of each element in the two-dimensional coordinate system, and perform fitting C=k*L+b according to the least squares method, where C is the characteristic degree, L is the distance, k is the slope, and b is the intercept, and obtain the goodness of fit R obtained in the fitting process 2 , when the goodness of fit R 2 ≤k R When k R As the early warning factor, early warning prompts are given to the sensors in the building space to be detected.

[0065] It should be noted that the goodness of fit R 2 It is used to evaluate the degree of fit of the model to the observed data, that is, to analyze the elements in the baseline perception set and the perception set to be detected. For the deviation of the fitting C=k*L+b, when the deviation is large, it means that the data change of the sensor in the building space to be detected is unreasonable, and it is necessary to give timely warning prompts to the sensors in the building space to be detected. Goodness of fit R 2 The calculation process of is the prior art, which is obtained by calculating the residual sum of squares and the total sum of squares, and will not be described in detail here.

[0066] It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above and that the invention can be implemented in other specific forms without departing from the spirit or essential features of the invention. Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description, and it is intended that all variations falling within the meaning and scope of the equivalent elements of the claims be included in the invention. Any reference numeral in a claim should not be considered as limiting the claim to which it relates.

Claims

1. An adaptive adjustment method for environmental protection equipment based on environmental perception, characterized in that: The following steps are involved: Step S100: Acquire historical adjustment records of environmental protection equipment, wherein the adjustment records are records of adjusting the environment through the environmental protection equipment when the sensor data of the monitored sensor is not within the normal value range; Analyze the changes in the sensor data of the sensor in each adjustment record, and extract a first marking record from the adjustment record; Step S200: obtaining the degree of change corresponding to each sensor according to the sensing data of each sensor corresponding to each adjustment record, and extracting a second marking record from the adjustment record according to the degree of change; Step S300: Obtain a feature adjustment record according to the first marking record and the second marking record; Establish a three-dimensional model of the building space where the environmental protection equipment is located, mark the location of each sensor, adjust and record the corresponding sensor location according to each feature, and obtain the benchmark perception set; Step S400: Establish a three-dimensional model of the building space to be detected, obtain a perception set to be detected based on the location of each sensor in the building space to be detected and the sensor data of each sensor, and combine the benchmark perception set to determine whether to issue an early warning prompt for the sensors in the building space to be detected.

2. The method for adaptively adjusting environmental protection equipment based on environmental perception according to claim 1, characterized in that: Step S100 includes: Step S110: obtaining a normal value range (V1, V2) corresponding to the sensor data, where V1 and V2 are the minimum normal value and the maximum normal value respectively; obtaining sensor data of all sensors in the building space where the environmental protection equipment is located, capturing the start adjustment time, end adjustment time and target sensor corresponding to each adjustment record, wherein the target sensor is a sensor whose sensor data is outside the normal value range within the time period T1 before the start adjustment time; Step S120: for all target sensors corresponding to a certain adjustment record, the function of the change of the sensor data over time during the adjustment process is set as a first change function, and the function of the change of the sensor data over time in a time period T2 after the adjustment is finished is set as a second change function; The middle value of the normal value range is taken as V0, a ​​certain moment in the adjustment process is taken as a, and the next moment of moment a is taken as b; if the sensor data at moment b in the first change function F1 corresponding to a certain target sensor is closer to V0 than the sensor data at moment a, then the moment a in the function F1 is marked, and then all the marked moments in the function F1 are obtained. If the number of marked moments in the function F1 is greater than the number threshold, a certain target sensor in a certain adjustment record is first marked; If all target sensors in a certain adjustment record are first marked, and in the second variation functions corresponding to all target sensors, the sensing data at each moment are within the normal value range, then the certain adjustment record is taken as the first marked record, and all first marked records are obtained.

3. The method for adaptively adjusting environmental protection equipment based on environmental perception according to claim 2 is characterized in that: Step S200 includes: Step S210: Obtain a first change function of a target sensor E corresponding to a certain adjustment record, extract all marked moments in the first change function, and summarize them to obtain a total marking duration D, and use the difference between the maximum sensor data and the minimum sensor data in the marked moment as the data difference V, and then obtain the change degree B=V / D of the target sensor E; Step S220: If the degree of change B is greater than a preset degree of change threshold, the target sensor E is second-marked, and then all the second-marked target sensors in a certain adjustment record are obtained; according to the degree of change of each second-marked target sensor, the variance is calculated as the adjustment value of the certain adjustment record, and if the adjustment value is greater than the adjustment threshold, the certain adjustment record is used as the second-marked record, and all the second-marked records are obtained.

4. The method for adaptively adjusting environmental protection equipment based on environmental perception according to claim 3 is characterized in that: Step S300 includes: Step S310: if a certain adjustment record is both a first mark record and a second mark record, the certain adjustment record is used as a characteristic adjustment record; according to the change degree of each target sensor corresponding to each characteristic adjustment record, all the change degrees corresponding to a certain target sensor are added together to obtain an average value, which is used as the characteristic degree of the certain target sensor; Step S320: Establish a three-dimensional model of the building space where the environmental protection equipment is located, and mark the equipment adjustment part in the three-dimensional model, where the equipment adjustment part is the output port on the environmental protection equipment for realizing the environmental adjustment function, and sort the target sensors in order from near to far from the equipment adjustment part; Then establish the benchmark perception set X, X = {(L1, C1), (L2, C2), ..., (L m ,C m )}, where L1,L2,…,L m are the distances between the target sensors with serial numbers 1, 2, ..., m and the adjustment parts of the equipment, C1, C2, ..., C m are the characteristic levels of the target sensors numbered 1, 2, …, m respectively.

5. The method for adaptively adjusting environmental protection equipment based on environmental perception according to claim 4 is characterized in that: Step S400 includes: Step S410: deploy at least M sensors in the building space to be detected; obtain a first change function of each target sensor corresponding to a certain adjustment record in the building space to be detected, and obtain a change degree of each target sensor according to each first change function, and use each change degree as a characteristic degree of each target sensor; According to the distance between each target sensor and the equipment adjustment part in the building space to be detected, the target sensors are sorted in order from near to far, and the perception set to be detected Y is obtained, Y = {(L1, C1), (L2, C2), …, (L n ,C n )}, where L1,L2,…,L n are the distances between the target sensors with serial numbers 1, 2, ..., n and the adjustment parts of the equipment, C1, C2, ..., C n are the characteristic degrees of the target sensors numbered 1, 2, …, n respectively; Step S420: Establish a two-dimensional coordinate system in which the characteristic degree varies with the distance, extract each element in the set X and Y, and mark the coordinates of each element in the two-dimensional coordinate system, and perform fitting C=k*L+b according to the least squares method, where C is the characteristic degree, L is the distance, k is the slope, and b is the intercept, and obtain the goodness of fit R obtained in the fitting process 2 , when the goodness of fit R 2 ≤k R When k R As the early warning factor, early warning prompts are given to the sensors in the building space to be detected.

6. An environmental protection equipment adaptive adjustment system, used to execute the environmental protection equipment adaptive adjustment method based on environment perception according to any one of claims 1 to 5, characterized in that: The system includes a first marked record extraction module, a second marked record extraction module, a benchmark perception set establishment module and an early warning prompt module; The first mark record extraction module is used to obtain the historical adjustment record of the environmental protection equipment, wherein the adjustment record is a record of adjusting the environment through the environmental protection equipment when the sensor data of the monitored sensor is not within the normal value range; Analyze the changes in the sensor data of the sensor in each adjustment record, and extract a first marking record from the adjustment record; A second marked record extraction module: used to obtain the change degree corresponding to each sensor according to the sensor data of each sensor corresponding to each adjustment record, and extract the second marked record from the adjustment record according to the change degree; A reference perception set establishment module: used for obtaining a feature adjustment record according to the first marking record and the second marking record; Establish a three-dimensional model of the building space where the environmental protection equipment is located, mark the location of each sensor, adjust and record the corresponding sensor location according to each feature, and obtain the benchmark perception set; Early warning module: used to establish a three-dimensional model of the building space to be detected, obtain the perception set to be detected according to the location of each sensor in the building space to be detected and the sensor data of each sensor, and combine the benchmark perception set to determine whether to issue an early warning to the sensors in the building space to be detected.

7. The environmental protection equipment adaptive adjustment system according to claim 6, characterized in that: The first marked record extraction module includes a target sensor determination unit and a first marked record extraction unit; Target sensor determination unit: used to obtain the sensor data of all sensors in the building space where the environmental protection equipment is located, and capture the start adjustment time, end adjustment time and target sensor corresponding to each adjustment record; The first marking record extraction unit is used to obtain all the first change functions and the second change functions corresponding to a certain adjustment record, and extract the first marking record from the adjustment record according to the first change function and the second change function.

8. The environmental protection equipment adaptive adjustment system according to claim 7, characterized in that: The early warning prompt module has a detection perception set establishment unit and an early warning prompt unit; The sensing set to be detected is established by a unit for establishing a three-dimensional model of the building space to be detected, and the sensing set to be detected is obtained according to the location of each sensor in the building space to be detected and the sensing data of each sensor; Early warning prompt unit: used to determine whether to issue an early warning prompt to the sensor in the building space to be detected based on the obtained perception set to be detected and in combination with the reference perception set.

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