Online intelligent early warning method and system for gas detection

Abstract

The invention relates to the technical field of environmental gas detection, and particularly discloses an online intelligent early warning method and system for gas detection, and the method comprises the steps: obtaining pollution source information in a space, determining a gas detection point according to the pollution source information, and synchronously determining the level of the gas detection point; selecting and installing a gas detector based on the level of the gas detection point, and acquiring gas data in the space on line according to the installed gas detector; performing spatial domain identification and time domain identification on the acquired gas data, and generating an early warning signal according to an identification result of the spatial domain identification and an identification result of the time domain identification; and reading a recognition result of time domain recognition to adjust an online acquisition process. The gas detection point is determined according to the pollution source information, the gas detector is installed at the gas detection point, the gas data is acquired in real time, spatial domain identification and time domain identification are carried out on the gas data, and then the early warning signal is generated, the process does not need manual participation or the manual participation amount is extremely small, and the intelligent level is extremely high.

Description

Technical Field

[0001] The present invention relates to the technical field of environmental gas detection, and in particular to an online intelligent early warning method and system for gas detection. Background Art

[0002] The online intelligent early warning system of gas detection is mainly used to monitor the concentration of harmful gases in the air in real time and issue an alarm when an abnormality is detected to prevent the occurrence of safety accidents; it is widely used in industrial production, environmental monitoring, mine safety, laboratories, home safety and other fields.

[0003] Most existing gas detection scenarios rely on intelligent devices to collect gas data, which is then manually analyzed. This process is very cumbersome, and the gas data itself is a number of numerical values, so it is easy to ignore certain special cases. Therefore, how to provide an intelligent automatic identification solution is the technical problem that the technical solution of the present invention wants to solve. Summary of the invention

[0004] The purpose of the present invention is to provide an online intelligent early warning method and system for gas detection to solve the problems raised in the above background technology.

[0005] To achieve the above object, the present invention provides the following technical solutions: An online intelligent early warning method for gas detection, the method comprising: Acquire pollution source information in the space, determine the gas detection point according to the pollution source information, and simultaneously determine the level at the gas detection point; the pollution source information includes the location of the pollution source and the pollution level of the pollution source; Select and install gas detectors based on the level of gas detection points, and obtain gas data in the space online based on the installed gas detectors; when the gas detectors obtain gas data, they record time tags; Perform spatial domain recognition and time domain recognition on the acquired gas data, and generate a warning signal according to the recognition results of the spatial domain recognition and the time domain recognition; The recognition results of the read time domain recognition are used to adjust the online acquisition process.

[0006] As a further solution of the present invention: the steps of obtaining pollution source information and environmental control equipment information in the space, determining the gas detection point according to the pollution source information and the environmental control equipment information, and simultaneously determining the level at the gas detection point include: Query the types of all pollution sources in the space; For each type, the location of the pollution source and the pollution level of the pollution source are obtained; the pollution level is used to characterize the concentration of the polluted gas of the pollution source, and the concentration is proportional to the pollution level; Determine the characteristic value of each location in the space according to the location of the pollution source and the pollution level of the pollution source; Determine a gas detection point according to the characteristic value, and simultaneously determine the level at the gas detection point; The process of determining the eigenvalue is: ; In the formula, express The eigenvalue at For the The pollution sources are The pollution level at Indicates Pollution sources and The distance between is the total number of pollution sources, is the preset correction factor; The rules for determining the gas detection points are: The characteristic value is compared with the preset characteristic value threshold. When the characteristic value of a certain position reaches the preset characteristic value threshold and there is no other gas detection point within the preset distance radius with the position as the center of the circle, the corresponding position is marked as a gas detection point; The levels at the gas detection points are: The level of the gas detection point is determined based on the direct ratio of the characteristic values.

[0007] As a further solution of the present invention: the step of selecting and installing a gas detector based on the level of the gas detection point, and obtaining the gas data in the space online according to the installed gas detector comprises: Querying the gas detector corresponding to the level of the gas detection point in a preset instrument table; the instrument table includes at least a semiconductor sensor and an electrochemical sensor; Install gas detectors at gas detection points and establish connection channels with gas detectors; Acquire the gas concentration detected by the gas detector based on the connection channel, determine the position tag according to the position of the gas detector, and determine the time tag according to the acquisition time; The gas concentration is counted according to the location tag and time tag to obtain the gas data at each moment in the space.

[0008] As a further solution of the present invention: the step of performing spatial domain recognition and time domain recognition on the acquired gas data and generating a warning signal according to the recognition results of the spatial domain recognition and the time domain recognition comprises: Receiving an abnormal data array input by an administrator; the abnormal data array represents the gas concentration distribution under a certain abnormal situation; Determine the abnormal position according to the gas data at each moment traversed by the abnormal data array; Perform time domain identification on each abnormal location and calculate the degree of abnormality; The abnormality degree is compared with a preset abnormality threshold to generate a warning signal; wherein the abnormality threshold includes at least one, each abnormality threshold corresponds to a warning signal, and the corresponding relationship is a preset value.

[0009] As a further solution of the present invention: the step of performing time domain identification on each abnormal position and calculating the abnormality degree comprises: Read the data at each moment of the abnormal position, sort them in chronological order, and obtain a data sequence; Performing discrete Fourier transform on the data sequence to obtain frequency spectrum features; The frequency spectrum feature is compared with a preset standard frequency spectrum feature to obtain an abnormality degree.

[0010] As a further solution of the present invention: the step of adjusting the online acquisition process of the recognition result of the reading time domain recognition includes: For any gas detector, query the time when it is most recently marked as an abnormal position; Read the abnormality degree at that moment; The gas data acquisition cycle of the gas detector is adjusted according to the time and the abnormality degree.

[0011] The technical solution of the present invention also provides an online intelligent early warning system for gas detection, the system comprising: A detection point calibration module is used to obtain pollution source information in the space, determine the gas detection point according to the pollution source information, and simultaneously determine the level at the gas detection point; the pollution source information includes the pollution source location and the pollution level of the pollution source; A gas data acquisition module is used to select and install gas detectors based on the level of gas detection points, and to obtain gas data in the space online according to the installed gas detectors; wherein, when the gas detector obtains gas data, a time tag is recorded; A gas data recognition module is used to perform spatial domain recognition and temporal domain recognition on the acquired gas data, and generate an early warning signal according to the recognition results of the spatial domain recognition and the recognition results of the temporal domain recognition; The acquisition process adjustment module is used to read the recognition result of time domain recognition and adjust the online acquisition process.

[0012] As a further solution of the present invention: the detection point calibration module includes: Type query unit, used to query the types of all pollution sources in the space; A level acquisition unit is used to acquire the location of the pollution source and the pollution level of the pollution source for each type; the pollution level is used to characterize the concentration of the polluted gas of the pollution source, and the concentration is proportional to the pollution level; An eigenvalue calculation unit, used to determine the eigenvalue of each position in the space according to the location of the pollution source and the pollution level of the pollution source; a calibration execution unit, for determining a gas detection point according to the characteristic value, and simultaneously determining a level at the gas detection point; The process of determining the eigenvalue is: ; In the formula, express The eigenvalue at For the The pollution sources are The pollution level at Indicates Pollution sources and The distance between is the total number of pollution sources, is the preset correction factor; The rules for determining the gas detection points are: The characteristic value is compared with the preset characteristic value threshold. When the characteristic value of a certain position reaches the preset characteristic value threshold and there is no other gas detection point within the preset distance radius with the position as the center of the circle, the corresponding position is marked as a gas detection point; The levels at the gas detection points are: The level of the gas detection point is determined based on the direct ratio of the characteristic values.

[0013] As a further solution of the present invention: the gas data acquisition module includes: An instrument query unit, used to query a gas detector corresponding to the level of a gas detection point in a preset instrument table; the instrument table includes at least a semiconductor sensor and an electrochemical sensor; A channel establishing unit, used to install a gas detector at a gas detection point and establish a connection channel with the gas detector; A tag determination unit, used for acquiring the gas concentration detected by the gas detector based on the connection channel, determining the position tag according to the position of the gas detector, and determining the time tag according to the acquisition time; The data statistics unit is used to count the gas concentration according to the location tag and the time tag to obtain the gas data at each moment in the space.

[0014] As a further solution of the present invention: the gas data identification module includes: The abnormal characteristic determination unit is used to receive an abnormal data array input by an administrator; the abnormal data array represents the gas concentration distribution under a certain abnormal situation; An abnormal position determination unit, used to determine the abnormal position according to the gas data at each moment of the abnormal data array; An abnormality calculation unit, used to identify each abnormal position in the time domain and calculate the abnormality degree; The abnormality comparison unit is used to compare the abnormality degree with a preset abnormality threshold to generate a warning signal; wherein the abnormality threshold includes at least one, each abnormality threshold corresponds to a warning signal, and the corresponding relationship is a preset value.

[0015] Compared with the prior art, the beneficial effects of the present invention are: the present invention determines the gas detection point according to the pollution source information, installs the gas detector at the gas detection point, obtains the gas data in real time, performs spatial domain identification and time domain identification on the gas data, and then generates an early warning signal. This process does not require human participation or the amount of human participation is very small, and the level of intelligence is extremely high. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention.

[0017] Figure 1 The flowchart of the online intelligent early warning method for gas detection is shown in FIG.

[0018] Figure 2 The first sub-process flowchart of the online intelligent early warning method for gas detection.

[0019] Figure 3 The second sub-process flowchart of the online intelligent early warning method for gas detection.

[0020] Figure 4 The third sub-process flowchart of the online intelligent early warning method for gas detection.

[0021] Figure 5 The fourth sub-process flowchart of the online intelligent early warning method for gas detection.

[0022] Figure 6 This is a structural block diagram of the online intelligent early warning system for gas detection. DETAILED DESCRIPTION

[0023] In order to make the technical problems, technical solutions and beneficial effects to be solved by the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0024] Figure 1 The flowchart of the online intelligent early warning method for gas detection is shown in the following figure. In an embodiment of the present invention, an online intelligent early warning method for gas detection includes: Step S100: obtaining pollution source information in the space, determining a gas detection point according to the pollution source information, and simultaneously determining the level at the gas detection point; the pollution source information includes the pollution source location and the pollution level of the pollution source; The scenario where gas detection is needed is the space mentioned above, and the pollution source information in the space is obtained. The pollution source is some production equipment that can emit exhaust gas, etc. The location of the production equipment is called the pollution source location, and the pollution degree of the exhaust gas emitted is represented by the pollution level. By analyzing the pollution source information, some gas detection points can be determined based on the pollution source, and the level at the gas detection point can be determined simultaneously.

[0025] Step S200: Select and install a gas detector based on the level of the gas detection point, and obtain gas data in the space online according to the installed gas detector; wherein the gas detector records a time tag when obtaining the gas data; After the location and level of the gas detection point are determined, gas detectors are selected and installed according to the level of the gas detection point. The gas data in the space is acquired online based on the installed gas detectors. The acquisition process is a real-time transmission process. Each gas detector operates independently to acquire the corresponding gas data. When acquiring the gas data, a time tag is recorded to indicate when the gas data was collected.

[0026] For this application, the same type of polluted gases are analyzed by default. Correspondingly, the gas data is actually the gas concentration. The more polluted gases a gas-generating device generates per unit time, the higher the pollution level.

[0027] Furthermore, there are many types of gas detectors, including electrochemical sensors, catalytic combustion sensors, infrared (NDIR) sensors, PID sensors and semiconductor sensors; they can all be used to obtain gas data, that is, gas concentration. Different sensors have different acquisition accuracy and costs. The higher the level of the gas detection point, the higher the acquisition accuracy of the sensor used.

[0028] Step S300: performing spatial domain recognition and time domain recognition on the acquired gas data, and generating a warning signal according to the recognition results of the spatial domain recognition and the time domain recognition; Read the gas data obtained by each gas detector and identify the obtained gas data. The identification process has two parts: one is spatial domain identification, and the other is time domain identification. Spatial domain identification is to compare and analyze the gas data at different locations at the same time, and time domain identification is to analyze the gas data at different times at the same location. After analysis in two dimensions, the current spatial state can be judged, and then it can be determined whether an early warning signal needs to be generated.

[0029] Step S400: reading the recognition result of the time domain recognition to adjust the online acquisition process; Read the recognition result of time domain recognition. The time domain recognition result reflects the data situation at different times. By comparing the data situation at different times, the stability of the data at each position can be determined at the same time. If the stability is high, the acquisition process can be carried out at a lower frequency. The purpose of this process is to increase the service life of the gas detector. Many gas detectors are based on the gas detection process of chemical principles. The detection components are consumables. The lower the frequency of use, the longer the use time. For example, a gas detector can detect 100 times. If it detects 10 times a day, it can be used for 10 days. If it detects 20 times a day, it can only be used for 5 days. Of course, this is just an example. The actual detection frequency will be higher.

[0030] Figure 2 The first sub-flow chart of the online intelligent early warning method for gas detection, wherein the steps of obtaining pollution source information and environmental control equipment information in the space, determining the gas detection point according to the pollution source information and the environmental control equipment information, and synchronously determining the level at the gas detection point include: Step S101: Query the types of all pollution sources in the space; Step S102: for each type, obtaining the location of the pollution source and the pollution level of the pollution source; the pollution level is used to characterize the concentration of the polluted gas of the pollution source, and the concentration is proportional to the pollution level; Step S103: determining the characteristic value of each position in the space according to the location of the pollution source and the pollution level of the pollution source; Step S104: determining a gas detection point according to the characteristic value, and simultaneously determining the level at the gas detection point; In an example of the technical solution of the present invention, the selection process of gas detection points and the level determination process are explained, and the types of all pollution sources in the query space are queried. In the same space, there must be more than one type of polluted gas. For the convenience of analysis, this application analyzes each type of polluted gas separately in turn. Even if there are multiple types of polluted gases, this application analyzes the same gas in turn. In other words, the analysis process of this application defaults to the same type of polluted gas.

[0031] For each type, the location of the pollution source and the pollution level of the pollution source are obtained. The pollution level is related to the concentration of the polluted gas from the pollution source. The higher the concentration, the higher the pollution level and the higher the danger. According to the location of the pollution source and the pollution level of the pollution source, the characteristic value of each position in the space is determined. The characteristic value is used to characterize the degree of danger of the position. The characteristic value is compared with the preset threshold to determine some positions to be selected as gas detection points, and the level is determined according to the characteristic value.

[0032] The process of determining the eigenvalue is: ; In the formula, express The eigenvalue at For the The pollution sources are The pollution level at Indicates Pollution sources and The distance between is the total number of pollution sources, is the preset correction factor.

[0033] The calculation process of the characteristic value is as follows: for any location, the impact of each pollution source at that location is calculated, and then the results are superimposed and multiplied by a preset coefficient. The final value obtained is called the characteristic value.

[0034] The rules for determining the gas detection points are: The characteristic value is compared with the preset characteristic value threshold. When the characteristic value of a certain position reaches the preset characteristic value threshold and there is no other gas detection point within the preset distance radius with the position as the center of the circle, the corresponding position is marked as a gas detection point.

[0035] The rule for determining the gas detection point is very simple. When the characteristic value of a certain position reaches the preset characteristic value threshold, it can be used as a gas detection point. At the same time, the present application also introduces a condition, that is, only one gas detection point is arranged within a range. When there are other gas detection points within the preset distance radius, even if the characteristic value of a certain position reaches the preset characteristic value threshold, the position will not be marked as a gas detection point.

[0036] The levels at the gas detection points are: The level of the gas detection point is determined based on the direct ratio of the characteristic values.

[0037] The simplest way to calculate the proportionality of eigenvalues ​​is to use a linear function with a positive coefficient. In this case, the larger the eigenvalue, the higher the level.

[0038] Figure 3 The second sub-flow chart of the online intelligent early warning method for gas detection, wherein the steps of selecting and installing gas detectors based on the level of gas detection points, and obtaining gas data in the space online according to the installed gas detectors include: Step S201: querying a preset instrument table for a gas detector corresponding to the level of a gas detection point; the instrument table includes at least a semiconductor sensor and an electrochemical sensor; Step S202: installing a gas detector at a gas detection point and establishing a connection channel with the gas detector; Step S203: acquiring the gas concentration detected by the gas detector based on the connection channel, determining the position tag according to the position of the gas detector, and determining the time tag according to the acquisition time; Step S204: Count the gas concentration according to the location tag and the time tag to obtain the gas data at each moment in the space.

[0039] In one example of the technical solution of the present invention, the gas detector corresponding to the level of the gas detection point is queried in a preset instrument table. The instrument table is a pre-set instrument table determined in advance by the staff. For this application, it is known data. The gas detectors corresponding to each level can be read in the instrument table, which also means that the instrument table contains at least level items and equipment items, and may also include identification items, etc.; the equipment items include at least semiconductor sensors and electrochemical sensors.

[0040] A gas detector is installed at the gas detection point, and a connection channel with the gas detector is established. The gas concentration detected by the gas detector is obtained based on the connection channel. The location tag is determined according to the location of the gas detector, and the time tag is determined according to the acquisition time. Thus, the gas data obtained is the data at a certain position at a certain moment. The gas data adopts gas concentration, and the gas concentration obtained is statistically obtained according to the location tag and the time tag to obtain the gas data at each moment in the space.

[0041] The process of obtaining the gas concentration based on the location tag and time tag statistics is as follows: first select some time nodes, obtain the gas concentration of the time closest to the time node (determined by the time tag) on ​​each location tag at the time node, and arrange the gas concentration at the same time according to the location tag to obtain a three-dimensional array. The row and column position (x, y, z) in the three-dimensional array represents a location tag, and its value represents the gas concentration. For example, A[1][1][1]=B, A[1][1][1] represents the data at the (1,1,1) position at the same time, and B represents the specific value.

[0042] It is worth mentioning that the gas concentration counted in this application is essentially a four-dimensional data, with a time dimension, that is, (t, x, y, z). At this time, A[1][1][1][1]=B means the data at the position (1,1,1) at time 1, and B represents the specific value.

[0043] Figure 4 The third sub-process flowchart of the online intelligent early warning method for gas detection is shown in FIG. 1 , wherein the steps of performing spatial domain recognition and time domain recognition on the acquired gas data and generating an early warning signal according to the recognition results of the spatial domain recognition and the time domain recognition include: Step S301: receiving an abnormal data array input by an administrator; the abnormal data array represents the gas concentration distribution under a certain abnormal situation; Step S302: Determine the abnormal position according to the gas data at each moment of the abnormal data array; Step S303: performing time domain identification on each abnormal position and calculating the abnormality degree; Step S304: Compare the abnormality with a preset abnormality threshold to generate a warning signal; wherein the abnormality threshold includes at least one, each abnormality threshold corresponds to a warning signal, and the corresponding relationship is a preset value.

[0044] In an example of the technical solution of the present invention, the identification process of the acquired gas data is limited. It can be known from the above content that the acquired gas data is a four-dimensional matrix. The administrator first predetermines an abnormal data array. The abnormal data array is the gas concentration of a small area within a period of time under abnormal conditions. It is also a four-dimensional matrix, but its range in each dimension is very small; the gas data at each moment is traversed according to the abnormal data array, and the matching degree is calculated in real time. When the matching degree reaches a preset matching degree threshold, the matched position is used as the abnormal position, and then, each abnormal position is identified in the time domain, and the abnormal degree is calculated. When the abnormal degree reaches the preset abnormal threshold, an early warning signal is generated; wherein, there are multiple abnormal thresholds, each abnormal threshold corresponds to an early warning signal, and the corresponding relationship is pre-set by the staff. For this application, it is a known relationship.

[0045] Specifically, regarding the process of traversing the gas data at each moment according to the abnormal data array and calculating the matching degree in real time, it is actually an extended application of the image traversal and comparison technology, which is also a unique migration application of the present application. The image traversal process is a two-dimensional feature. For example, a 3*3 image feature is traversed in a large image, and the similarity between the image feature and the traversed corresponding area is calculated as the matching degree; similarly, the abnormal data array is equivalent to a four-dimensional "image feature", and the gas data at each moment is equivalent to a four-dimensional "image". The similarity calculation scheme can be expanded to a four-dimensional calculation process based on the two-dimensional calculation process.

[0046] As a preferred embodiment of the technical solution of the present invention, the step of performing time domain identification on each abnormal position and calculating the abnormality degree includes: Read the data at each moment of the abnormal position, sort them in chronological order, and obtain a data sequence; Performing discrete Fourier transform on the data sequence to obtain frequency spectrum features; The frequency spectrum feature is compared with a preset standard frequency spectrum feature to obtain an abnormality degree.

[0047] In an example of the technical solution of the present invention, a specific time domain identification solution is provided, wherein the abnormal position is a matched area that is sufficiently similar to the abnormal data array; the size of the abnormal position is the same as the size of the abnormal data array, and for any position therein, data at each moment is obtained, and the data are sorted in chronological order to obtain a data sequence; a discrete Fourier transform is performed on the data sequence to obtain a spectrum feature, and the spectrum feature is compared with a preset standard spectrum feature to obtain an abnormality degree, and finally, the abnormality degrees corresponding to all positions are counted to obtain a final comprehensive abnormality degree, and the statistical process can be performed by calculating the mean.

[0048] Figure 5 The fourth sub-flow chart of the online intelligent early warning method for gas detection, wherein the step of adjusting the online acquisition process of the recognition result of the reading time domain recognition comprises: Step S401: for any gas detector, query the time when it is most recently marked as an abnormal position; Step S402: reading the abnormality degree at that moment; Step S403: adjusting the gas data acquisition cycle of the gas detector according to the time and the abnormality degree.

[0049] In one example of the technical solution of the present invention, for any gas detector, the most recent time when it is marked as an abnormal position is queried, the degree of abnormality at that time is read, and the gas data acquisition cycle of the gas detector is adjusted according to the time and the degree of abnormality. The principle of the adjustment process is that the farther the time when the position is marked as an abnormal position is from the current time, the safer the position is, and the longer it has not been marked as an abnormal position, the longer the data acquisition cycle is; the smaller the degree of abnormality is, the smaller the degree of abnormality is, even if it is marked as an abnormal position, the degree of abnormality is very small, and the safer the position is, the longer the data acquisition cycle is.

[0050] Figure 6 The structure block diagram of the online intelligent early warning system for gas detection is shown in FIG. 1 . In an embodiment of the present invention, an online intelligent early warning system for gas detection is provided. The system 10 includes: The detection point calibration module 11 is used to obtain the pollution source information in the space, determine the gas detection point according to the pollution source information, and simultaneously determine the level at the gas detection point; the pollution source information includes the pollution source location and the pollution level of the pollution source; The gas data acquisition module 12 is used to select and install gas detectors based on the level of the gas detection point, and to obtain the gas data in the space online according to the installed gas detectors; wherein the gas detector records the time tag when obtaining the gas data; The gas data recognition module 13 is used to perform spatial domain recognition and time domain recognition on the acquired gas data, and generate a warning signal according to the recognition results of the spatial domain recognition and the time domain recognition; The acquisition process adjustment module 14 is used to read the recognition result of the time domain recognition and adjust the online acquisition process.

[0051] Furthermore, the detection point calibration module 11 includes: Type query unit, used to query the types of all pollution sources in the space; A level acquisition unit is used to acquire the location of the pollution source and the pollution level of the pollution source for each type; the pollution level is used to characterize the concentration of the polluted gas of the pollution source, and the concentration is proportional to the pollution level; An eigenvalue calculation unit, used to determine the eigenvalue of each position in the space according to the location of the pollution source and the pollution level of the pollution source; a calibration execution unit, for determining a gas detection point according to the characteristic value, and simultaneously determining a level at the gas detection point; Among them, the process of determining the eigenvalue is: The rules for determining the gas detection points are: The levels at the gas detection points are:.

[0052] Specifically, the gas data acquisition module 12 includes: An instrument query unit, used to query a gas detector corresponding to the level of a gas detection point in a preset instrument table; the instrument table includes at least a semiconductor sensor and an electrochemical sensor; A channel establishing unit, used to install a gas detector at a gas detection point and establish a connection channel with the gas detector; A tag determination unit, used for acquiring the gas concentration detected by the gas detector based on the connection channel, determining the position tag according to the position of the gas detector, and determining the time tag according to the acquisition time; The data statistics unit is used to count the gas concentration according to the location tag and the time tag to obtain the gas data at each moment in the space.

[0053] Furthermore, the gas data identification module 13 includes: The abnormal characteristic determination unit is used to receive an abnormal data array input by an administrator; the abnormal data array represents the gas concentration distribution under a certain abnormal situation; An abnormal position determination unit, used to determine the abnormal position according to the gas data at each moment of the abnormal data array; An abnormality calculation unit, used to identify each abnormal position in the time domain and calculate the abnormality degree; The abnormality comparison unit is used to compare the abnormality degree with a preset abnormality threshold to generate a warning signal; wherein the abnormality threshold includes at least one, each abnormality threshold corresponds to a warning signal, and the corresponding relationship is a preset value.

[0054] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. An online intelligent early warning method for gas detection, characterized in that: The method comprises: Acquire pollution source information in the space, determine the gas detection point according to the pollution source information, and simultaneously determine the level at the gas detection point; the pollution source information includes the location of the pollution source and the pollution level of the pollution source; Select and install gas detectors based on the level of gas detection points, and obtain gas data in the space online based on the installed gas detectors; when the gas detectors obtain gas data, they record time tags; Perform spatial domain recognition and time domain recognition on the acquired gas data, and generate a warning signal according to the recognition results of the spatial domain recognition and the time domain recognition; The recognition results of the read time domain recognition are used to adjust the online acquisition process.

2. The online intelligent early warning method for gas detection according to claim 1 is characterized in that: The steps of obtaining pollution source information and environmental control equipment information in the space, determining the gas detection point according to the pollution source information and the environmental control equipment information, and simultaneously determining the level at the gas detection point include: Query the types of all pollution sources in the space; For each type, the location of the pollution source and the pollution level of the pollution source are obtained; the pollution level is used to characterize the concentration of the polluted gas of the pollution source, and the concentration is proportional to the pollution level; Determine the characteristic value of each location in the space according to the location of the pollution source and the pollution level of the pollution source; Determine a gas detection point according to the characteristic value, and simultaneously determine the level at the gas detection point; The process of determining the eigenvalue is: ; In the formula, express The eigenvalue at For the The pollution sources are The pollution level at Indicates Pollution sources and The distance between is the total number of pollution sources, is the preset correction factor; The rules for determining the gas detection points are: The characteristic value is compared with the preset characteristic value threshold. When the characteristic value of a certain position reaches the preset characteristic value threshold and there is no other gas detection point within the preset distance radius with the position as the center of the circle, the corresponding position is marked as a gas detection point; The levels at the gas detection points are: The level of the gas detection point is determined based on the direct ratio of the characteristic values.

3. The online intelligent early warning method for gas detection according to claim 1 is characterized in that: The step of selecting and installing a gas detector based on the level of the gas detection point and obtaining gas data in the space online according to the installed gas detector comprises: Querying the gas detector corresponding to the level of the gas detection point in a preset instrument table; the instrument table includes at least a semiconductor sensor and an electrochemical sensor; Install gas detectors at gas detection points and establish connection channels with gas detectors; Acquire the gas concentration detected by the gas detector based on the connection channel, determine the position tag according to the position of the gas detector, and determine the time tag according to the acquisition time; The gas concentration is counted according to the location tag and time tag to obtain the gas data at each moment in the space.

4. The online intelligent early warning method for gas detection according to claim 1 is characterized in that: The steps of performing spatial domain recognition and time domain recognition on the acquired gas data and generating an early warning signal according to the recognition results of the spatial domain recognition and the time domain recognition include: Receiving an abnormal data array input by an administrator; the abnormal data array represents the gas concentration distribution under a certain abnormal situation; Determine the abnormal position according to the gas data at each moment traversed by the abnormal data array; Perform time domain identification on each abnormal location and calculate the degree of abnormality; The abnormality is compared with a preset abnormality threshold to generate a warning signal; wherein the abnormality threshold includes at least one, each abnormality threshold corresponds to a warning signal, and the corresponding relationship is a preset value.

5. The online intelligent early warning method for gas detection according to claim 4 is characterized in that: The step of performing time domain identification on each abnormal position and calculating the abnormality degree comprises: Read the data at each moment of the abnormal position, sort them in chronological order, and obtain a data sequence; Performing discrete Fourier transform on the data sequence to obtain frequency spectrum features; The frequency spectrum feature is compared with a preset standard frequency spectrum feature to obtain an abnormality degree.

6. The online intelligent early warning method for gas detection according to claim 1 is characterized in that: The steps of adjusting the online acquisition process of the recognition result of the reading time domain recognition include: For any gas detector, query the time when it is most recently marked as an abnormal position; Read the abnormality degree at that moment; The gas data acquisition cycle of the gas detector is adjusted according to the time and the abnormality degree.

7. An online intelligent early warning system for gas detection, characterized in that: The system comprises: A detection point calibration module is used to obtain pollution source information in the space, determine the gas detection point according to the pollution source information, and simultaneously determine the level at the gas detection point; the pollution source information includes the pollution source location and the pollution level of the pollution source; A gas data acquisition module is used to select and install gas detectors based on the level of gas detection points, and to obtain gas data in the space online according to the installed gas detectors; wherein, when the gas detector obtains gas data, a time tag is recorded; A gas data recognition module is used to perform spatial domain recognition and temporal domain recognition on the acquired gas data, and generate an early warning signal according to the recognition results of the spatial domain recognition and the recognition results of the temporal domain recognition; The acquisition process adjustment module is used to read the recognition result of time domain recognition and adjust the online acquisition process.

8. The online intelligent early warning system for gas detection according to claim 7 is characterized in that: The detection point calibration module includes: Type query unit, used to query the types of all pollution sources in the space; A level acquisition unit is used to acquire the location of the pollution source and the pollution level of the pollution source for each type; the pollution level is used to characterize the concentration of the polluted gas of the pollution source, and the concentration is proportional to the pollution level; An eigenvalue calculation unit, used to determine the eigenvalue of each position in the space according to the location of the pollution source and the pollution level of the pollution source; a calibration execution unit, for determining a gas detection point according to the characteristic value, and simultaneously determining a level at the gas detection point; The process of determining the eigenvalue is: ; In the formula, express The eigenvalue at For the The pollution sources are The pollution level at Indicates Pollution sources and The distance between is the total number of pollution sources, is the preset correction factor; The rules for determining the gas detection points are: The characteristic value is compared with the preset characteristic value threshold. When the characteristic value of a certain position reaches the preset characteristic value threshold and there is no other gas detection point within the preset distance radius with the position as the center of the circle, the corresponding position is marked as a gas detection point; The levels at the gas detection points are: The level of the gas detection point is determined based on the direct ratio of the characteristic values.

9. The online intelligent early warning system for gas detection according to claim 7 is characterized in that: The gas data acquisition module comprises: An instrument query unit, used to query a gas detector corresponding to the level of a gas detection point in a preset instrument table; the instrument table includes at least a semiconductor sensor and an electrochemical sensor; A channel establishing unit, used to install a gas detector at a gas detection point and establish a connection channel with the gas detector; A tag determination unit, used for acquiring the gas concentration detected by the gas detector based on the connection channel, determining the position tag according to the position of the gas detector, and determining the time tag according to the acquisition time; The data statistics unit is used to count the gas concentration according to the location tag and the time tag to obtain the gas data at each moment in the space.

10. The online intelligent early warning system for gas detection according to claim 7, characterized in that: The gas data identification module comprises: The abnormal characteristic determination unit is used to receive an abnormal data array input by an administrator; the abnormal data array represents the gas concentration distribution under a certain abnormal situation; An abnormal position determination unit, used to determine the abnormal position according to the gas data at each moment of the abnormal data array; An abnormality calculation unit, used to identify each abnormal position in the time domain and calculate the abnormality degree; The abnormality comparison unit is used to compare the abnormality degree with a preset abnormality threshold to generate a warning signal; wherein the abnormality threshold includes at least one, each abnormality threshold corresponds to a warning signal, and the corresponding relationship is a preset value.

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