An online intelligent early warning method and system for gas detection

Abstract

The present invention relates to the technical field of environmental gas detection, and specifically discloses an online intelligent early warning method and system for gas detection. The method includes obtaining pollution source information in a space, determining gas detection points according to the pollution source information, and synchronously determining the levels at the gas detection points; selecting and installing gas detectors based on the levels of the gas detection points, and online obtaining gas data in the space according to the installed gas detectors; performing spatial domain identification and time domain identification on the obtained gas data, and generating an early warning signal according to the identification results of the spatial domain identification and the time domain identification; reading the identification results of the time domain identification to adjust the online obtaining process. According to the present invention, gas detection points are determined according to the pollution source information, gas detectors are installed at the gas detection points, gas data is obtained in real time, spatial domain identification and time domain identification are performed on the gas data, and then an early warning signal is generated. This process requires little or no manual participation, and the level of intelligence 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 Technique

[0002] The online intelligent early warning system for 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] In existing gas detection scenarios, gas data is mostly collected by means of intelligent devices, and then the collected gas data is analyzed manually. This process is very cumbersome, and the gas data itself is some numerical values, and it is easy to ignore some special situations. Therefore, how to provide an intelligent automatic recognition 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 technique.

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

[0006] An online intelligent early warning method for gas detection, the method includes:

[0007] Obtain the pollution source information in the space, determine the gas detection points according to the pollution source information, and synchronously determine the level at the gas detection points; the pollution source information includes the pollution source location and the pollution level of the pollution source;

[0008] Select and install gas detectors based on the level of the gas detection points, and obtain the gas data in the space online according to the installed gas detectors; wherein, when the gas detectors obtain gas data, time tags are recorded.

[0009] Perform spatial domain recognition and time domain recognition on the obtained gas data, and generate an early warning signal according to the recognition results of the spatial domain recognition and the recognition results of the time domain recognition.

[0010] Read the recognition results of the time domain recognition to adjust the online acquisition process.

[0011] As a further solution of the present invention: the step of obtaining the pollution source information and environmental control equipment information in the space, determining the gas detection points according to the pollution source information and environmental control equipment information, and synchronously determining the level at the gas detection points includes:

[0012] Query the types of all pollution sources in the space;

[0013] For each type, obtain 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 directly proportional to the pollution level.

[0014] Determine the characteristic values of each position in the space according to the location of the pollution source and the pollution level of the pollution source.

[0015] Determine the gas detection points according to the characteristic values, and synchronously determine the levels at the gas detection points.

[0016] Among them, the process of determining the characteristic value is as follows:

[0017] ; in the formula, represents the characteristic value at is the th pollution source at the pollution level at represents the th pollution source and the distance at is the total number of pollution sources, is a preset correction coefficient;

[0018] The rule for determining the gas detection points is:

[0019] Compare the characteristic value with a preset characteristic value threshold. When the characteristic value at a certain position reaches the preset characteristic value threshold and there are no other gas detection points within a preset distance radius centered on this position, mark the corresponding position as a gas detection point.

[0020] The level at the gas detection point is:

[0021] Determine the level of the gas detection point according to the direct proportion of the characteristic value.

[0022] As a further solution of the present invention: the steps of selecting and installing a gas detector based on the level of the gas detection point and online obtaining gas data in the space according to the installed gas detector include:

[0023] Query the gas detector corresponding to the level of the gas detection point in a preset instrument table; the instrument table at least includes a semiconductor sensor and an electrochemical sensor;

[0024] Install a gas detector at the gas detection point and establish a connection channel with the gas detector.

[0025] Obtain the gas concentration detected by the gas detector based on the connection channel, determine the position label according to the position of the gas detector, and determine the time label according to the acquisition time.

[0026] Statistically analyze the gas concentration according to the position tag and time tag to obtain the gas data at each moment in the space.

[0027] As a further solution of the present invention: The step of performing spatial domain recognition and time domain recognition on the obtained gas data and generating a warning signal according to the recognition results of the spatial domain recognition and the time domain recognition includes:

[0028] Receive the abnormal data matrix input by the administrator; the abnormal data matrix represents the gas concentration distribution in a certain abnormal situation;

[0029] Traverse the gas data at each moment according to the abnormal data matrix to determine the abnormal position;

[0030] Perform time domain recognition on each abnormal position and calculate the abnormality degree;

[0031] Compare the abnormality degree with a preset abnormality threshold to generate a warning signal; wherein, there is at least one abnormality threshold, and each abnormality threshold corresponds to a warning signal, and the corresponding relationship is a preset value.

[0032] As a further solution of the present invention: The step of performing time domain recognition on each abnormal position and calculating the abnormality degree includes:

[0033] Read the data at each moment at the abnormal position, sort them in chronological order to obtain a data sequence;

[0034] Perform discrete Fourier transform on the data sequence to obtain spectral characteristics;

[0035] Compare the spectral characteristics with the preset standard spectral characteristics to obtain the abnormality degree.

[0036] As a further solution of the present invention: The step of reading the recognition result of time domain recognition to adjust the online acquisition process includes:

[0037] For any gas detector, query the moment closest to it that is marked as an abnormal position;

[0038] Read the abnormality degree at this moment;

[0039] According to the moment and the abnormality degree, jointly adjust the gas data acquisition period of the gas detector.

[0040] The technical solution of the present invention also provides an online intelligent warning system for gas detection, and the system includes:

[0041] A detection point calibration module, which is used to obtain the pollution source information in the space, determine the gas detection points according to the pollution source information, and synchronously determine the levels at the gas detection points; the pollution source information includes the pollution source position and the pollution level of the pollution source;

[0042] A gas data acquisition module, which is used to select and install gas detectors based on the levels of gas detection points, and online acquire gas data in the space according to the installed gas detectors; wherein, when the gas detectors acquire gas data, time tags are recorded.

[0043] A gas data identification module, which is used to perform spatial domain identification and time domain identification on the acquired gas data, and generate a warning signal according to the identification results of the spatial domain identification and the time domain identification.

[0044] An acquisition process adjustment module, which is used to read the identification result of the time domain identification to adjust the online acquisition process.

[0045] As a further solution of the present invention: the detection point calibration module includes:

[0046] A type query unit, which is used to query the types of all pollution sources in the space.

[0047] A level acquisition unit, which is used to, for each type, acquire the pollution source location 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 directly proportional to the pollution level.

[0048] An eigenvalue calculation unit, which is used to determine the eigenvalues of each position in the space according to the pollution source location and the pollution level of the pollution source.

[0049] A calibration execution unit, which is used to determine the gas detection points according to the eigenvalues, and synchronously determine the levels at the gas detection points.

[0050] Wherein, the process of determining the eigenvalues is as follows:

[0051] ; in the formula, represents the eigenvalue at , is the pollution level of the th pollution source at , represents the distance between the th pollution source and , is the total number of pollution sources, is a preset correction coefficient.

[0052] The rule for determining the gas detection points is as follows:

[0053] Compare the eigenvalues with a preset eigenvalue threshold. When the eigenvalue of a certain position reaches the preset eigenvalue threshold and there are no other gas detection points within a preset distance radius centered on this position, mark the corresponding position as a gas detection point.

[0054] The level at the gas detection point is:

[0055] Determine the level of the gas detection point according to the direct ratio of the eigenvalue.

[0056] As a further solution of the present invention: the gas data acquisition module includes:

[0057] An instrument query unit for querying the gas detector corresponding to the level of the gas detection point in a preset instrument list; the instrument list at least includes a semiconductor sensor and an electrochemical sensor;

[0058] A channel establishment unit for installing a gas detector at the gas detection point and establishing a connection channel with the gas detector;

[0059] A tag determination unit for obtaining the gas concentration detected by the gas detector based on the connection channel, determining a position tag according to the position of the gas detector, and determining a time tag according to the acquisition time;

[0060] A data statistics unit for statistically analyzing the gas concentration according to the position tag and the time tag to obtain the gas data at each moment in the space.

[0061] As a further solution of the present invention: the gas data recognition module includes:

[0062] An abnormal feature determination unit for receiving the abnormal data matrix input by the administrator; the abnormal data matrix represents the gas concentration distribution in a certain abnormal situation;

[0063] An abnormal position determination unit for traversing the gas data at each moment according to the abnormal data matrix to determine the abnormal position;

[0064] An abnormality degree calculation unit for performing time-domain identification on each abnormal position and calculating the abnormality degree;

[0065] An abnormal comparison unit for comparing the abnormality degree with a preset abnormal threshold to generate a warning signal; wherein, there is at least one abnormal threshold, and each abnormal threshold corresponds to a warning signal, and the corresponding relationship is a preset value.

[0066] Compared with the prior art, the beneficial effect of the present invention is that: the present invention determines the gas detection point according to the pollution source information, installs a gas detector at the gas detection point, obtains gas data in real time, performs spatial domain identification and time domain identification on the gas data, and then generates a warning signal. This process requires little or no manual participation, and the intelligent level is extremely high. Description of the Drawings

[0067] To more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention.

[0068] Figure 1 It is a flowchart of an online intelligent early warning method for gas detection.

[0069] Figure 2 It is the first sub-flowchart of an online intelligent early warning method for gas detection.

[0070] Figure 3 It is the second sub-flowchart of an online intelligent early warning method for gas detection.

[0071] Figure 4 It is the third sub-flowchart of an online intelligent early warning method for gas detection.

[0072] Figure 5 It is the fourth sub-flowchart of an online intelligent early warning method for gas detection.

[0073] Figure 6 It is a block diagram of the composition structure of an online intelligent early warning system for gas detection. Detailed implementation manners

[0074] 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 will be further described in detail below with reference to 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.

[0075] Figure 1 It is a flowchart of an online intelligent early warning method for gas detection. In an embodiment of the present invention, an online intelligent early warning method for gas detection, the method includes:

[0076] Step S100: Obtain pollution source information in the space, determine gas detection points according to the pollution source information, and synchronously determine the level at the gas detection points; the pollution source information includes the pollution source location and the pollution level of the pollution source;

[0077] For the scenario where gas detection is required, it is the space in the above content. Obtain the pollution source information in the space. The pollution sources are some production equipment that can emit tail gas, etc. The location of the production equipment is called the pollution source location, and the pollution degree of the emitted tail gas 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 points can be determined synchronously.

[0078] Step S200: Select and install gas detectors based on the levels of gas detection points, and obtain the gas data in the space online according to the installed gas detectors; wherein, when the gas detectors obtain the gas data, time tags are recorded.

[0079] After the positions and levels of the gas detection points are determined, select and install gas detectors according to the levels of the gas detection points, and obtain the gas data in the space online according to the installed gas detectors. The acquisition process is a real-time transmission process. Each gas detector operates independently to obtain the corresponding gas data. When obtaining the gas data, time tags are recorded to indicate when the gas data is collected.

[0080] For this application, it is default to analyze the same type of polluting gas. Correspondingly, the gas data is actually the gas concentration. The more polluting gas generated by a certain gas-generating device per unit time, the higher the pollution level.

[0081] 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. The acquisition accuracies of different sensors are different, and the costs are also different. The higher the level of the gas detection point, the higher the acquisition accuracy of the sensor used.

[0082] Step S300: Perform spatial domain identification and time domain identification on the obtained gas data, and generate a warning signal according to the identification results of the spatial domain identification and the time domain identification.

[0083] 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 positions at the same moment, and time domain identification is to analyze the gas data at the same position at different moments. After the analysis in two dimensions, the current spatial state can be judged, and then it can be determined whether a warning signal needs to be generated.

[0084] Step S400: Read the identification result of the time domain identification to adjust the online acquisition process.

[0085] Read the recognition results of time-domain recognition. The time-domain recognition results reflect the data conditions at different times. By comparing the data conditions at different times, the stability of the data at each position can be determined simultaneously. If the stability is relatively high, the acquisition process can be carried out at a lower frequency. The purpose of this process is to extend the service life of the gas detector. Many gas detectors are based on chemical principle gas detection processes, and the detection components are consumables. The lower the usage frequency, the longer the usage duration. 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, and the actual detection frequency will be higher.

[0086] Figure 2 It is the first sub-process block diagram of the online intelligent early warning method for gas detection. The steps of obtaining the pollution source information and environmental control equipment information in the space and determining the gas detection points according to the pollution source information and environmental control equipment information and synchronously determining the levels at the gas detection points include:

[0087] Step S101: Query the types of all pollution sources in the space;

[0088] Step S102: For each type, obtain the pollution source location and the pollution level of the pollution source; the pollution level is used to represent the concentration of the polluted gas of the pollution source, and the concentration is directly proportional to the pollution level;

[0089] Step S103: Determine the characteristic values of each position in the space according to the pollution source location and the pollution level of the pollution source;

[0090] Step S104: Determine the gas detection points according to the characteristic values, and synchronously determine the levels at the gas detection points;

[0091] In an example of the technical solution of the present invention, the process of selecting the gas detection points and the process of determining the levels are described. Query the types of all pollution sources in the space. 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 sequence. Even if there are multiple polluted gases, this application also analyzes the same type of gas in sequence. In other words, the analysis process of this application defaults to facing the same type of polluted gas.

[0092] For each type, obtain the pollution source location and the pollution level of the pollution source. The pollution level is related to the concentration of the polluted gas of the pollution source. The greater the concentration, the higher the pollution level and the greater the danger. Determine the characteristic values of each position in the space according to the pollution source location and the pollution level of the pollution source. The characteristic values are used to represent the degree of danger at this position. Compare the characteristic values with the preset threshold to determine some positions as gas detection points, and at the same time determine the levels according to the characteristic values.

[0093] Among them, the process of determining the eigenvalue is as follows:

[0094] ; in the formula, represents the eigenvalue at is the th pollution source's pollution level at , represents the th pollution source's distance from , is the total number of pollution sources, is a preset correction coefficient.

[0095] The calculation process of the eigenvalue is that for any position, calculate the influence degree of each pollution source at this position, then perform superposition, multiply by a preset coefficient, and the final value obtained is called the eigenvalue.

[0096] The determination rule of the gas detection point is as follows:

[0097] Compare the eigenvalue with a preset eigenvalue threshold. When the eigenvalue at a certain position reaches the preset eigenvalue threshold and there is no other gas detection point within a preset distance radius centered on this position, mark the corresponding position as a gas detection point.

[0098] The determination rule of the gas detection point is very simple. When the eigenvalue at a certain position reaches the preset eigenvalue threshold, it can be used as a gas detection point. At the same time, this application also introduces a condition, that is, only one gas detection point is arranged within a range. When there is other gas detection point within the preset distance radius, even if the eigenvalue at a certain position reaches the preset eigenvalue threshold, this position is not marked as a gas detection point.

[0099] The level at the gas detection point is:

[0100] Determine the level of the gas detection point according to the proportional relationship of the eigenvalue.

[0101] The simplest way of the proportional relationship of the eigenvalue is to use a linear function with a positive coefficient. At this time, the larger the eigenvalue, the higher the level.

[0102] Figure 3 is the second sub-process block diagram of the online intelligent early warning method for gas detection. The steps 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 include:

[0103] Step S201: Query 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;

[0104] Step S202: Install a gas detector at the gas detection point and establish a connection channel with the gas detector;

[0105] Step S203: Obtain the gas concentration detected by the gas detector based on the connection channel, determine the position label according to the position of the gas detector, and determine the time label according to the acquisition time;

[0106] Step S204: Statistically analyze the gas concentration according to the position label and the time label to obtain the gas data at each moment in the space.

[0107] In an example of the technical solution of the present invention, query the gas detector corresponding to the level of the gas detection point in a preset instrument table. The instrument table is a preset instrument table, which is determined in advance by the staff and is known data for this application. In the instrument table, the gas detectors corresponding to each level can be read. This also means that the instrument table at least contains a level item and a device item, and may also include an identification item, etc.; at least a semiconductor sensor and an electrochemical sensor are included in the device item.

[0108] Install a gas detector at the gas detection point, establish a connection channel with the gas detector, obtain the gas concentration detected by the gas detector based on the connection channel, determine the position label according to the position of the gas detector, and determine the time label according to the acquisition time. Thus, the obtained gas data is the data at a certain position at a certain moment. The gas data uses the gas concentration. Statistically analyze the obtained gas concentration according to the position label and the time label to obtain the gas data at each moment in the space.

[0109] Among them, the process of statistically analyzing the obtained gas concentration according to the position label and the time label is as follows: First, select some time nodes, obtain the gas concentration at the time closest to the time node on each position label at the time node (judged by the time label), arrange the gas concentrations at the same moment according to the position label to obtain a three-dimensional array. The row and column positions (x, y, z) in the three-dimensional array represent a position label, and its value represents the gas concentration. For example, A[1][1][1]=B, where A[1][1][1] represents the data at the position (1, 1, 1) at the same moment, and B represents the specific value.

[0110] It is worth mentioning that the gas concentration statistically analyzed in this application is essentially a four-dimensional data, and there is also a time dimension, that is, (t, x, y, z). At this time, A[1][1][1][1]=B represents the data at the position (1, 1, 1) at the moment of 1, and B represents the specific value.

[0111] Figure 4It is the third sub-process block diagram of the online intelligent early warning method for gas detection. 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:

[0112] Step S301: Receive the abnormal data matrix input by the administrator; the abnormal data matrix represents the gas concentration distribution in a certain abnormal situation;

[0113] Step S302: Traverse the gas data at each moment according to the abnormal data matrix to determine the abnormal position;

[0114] Step S303: Perform time domain recognition on each abnormal position and calculate the abnormality degree;

[0115] Step S304: Compare the abnormality degree with a preset abnormality threshold to generate an early warning signal; wherein, there is at least one abnormality threshold, and each abnormality threshold corresponds to an early warning signal, and the corresponding relationship is a preset value.

[0116] In an example of the technical solution of the present invention, the recognition process of the acquired gas data is defined. From the above content, it can be known that the acquired gas data is a four-dimensional matrix. First, the administrator pre-determines an abnormal data matrix. The abnormal data matrix is the gas concentration in a small area within a period of time in an abnormal situation. It is also a four-dimensional matrix, but the range of each dimension is very small. Traverse the gas data at each moment according to the abnormal data matrix, calculate the matching degree in real time. When the matching degree reaches the preset matching degree threshold, the matching position is used as the abnormal position. Then, perform time domain recognition on each abnormal position and calculate the abnormality degree. When the abnormality degree reaches the preset abnormality threshold, generate an early warning signal; wherein, there are multiple abnormality thresholds, and each abnormality threshold corresponds to an early warning signal, and the corresponding relationship is pre-set by the staff. For this application, it belongs to a known relationship.

[0117] Specifically, regarding the process of traversing the gas data at each moment according to the abnormal data matrix and calculating the matching degree in real time, it is actually an extended application of the image traversal comparison technology, which is also a unique migration application of this application. The traversal process of the image is two-dimensional features. For example, the 3*3 image features are traversed in a large image, and the similarity between the image features and the traversed corresponding area is calculated as the matching degree. Similarly, the abnormal data matrix is equivalent to the four-dimensional "image features", and the gas data at each moment is equivalent to the four-dimensional "image", and the similarity calculation scheme is extended from the two-dimensional calculation process to the four-dimensional calculation process.

[0118] As a preferred embodiment of the technical solution of the present invention, the steps of performing time domain recognition on each abnormal position and calculating the abnormality degree include:

[0119] Read the data at each moment at the abnormal position, sort them in chronological order to obtain a data sequence;

[0120] Perform a discrete Fourier transform on the data sequence to obtain spectral features;

[0121] Compare the spectral features with preset standard spectral features to obtain the degree of abnormality.

[0122] In an example of the technical solution of the present invention, a specific time-domain recognition scheme is provided. The abnormal position is the area that is matched to be similar enough to the abnormal data array; the size of the abnormal position is the same as the size of the abnormal data array. For any position therein, obtain the data at each moment, sort them in chronological order to obtain a data sequence; perform a discrete Fourier transform on the data sequence to obtain spectral features, compare the spectral features with preset standard spectral features to obtain the degree of abnormality. Finally, count the degrees of abnormality corresponding to all positions to obtain the final comprehensive degree of abnormality. The counting process can adopt the method of calculating the mean value.

[0123] Figure 5 It is the fourth sub-process block diagram of the online intelligent early warning method for gas detection. The steps of reading the recognition result of time-domain recognition to adjust the online acquisition process include:

[0124] Step S401: For any gas detector, query the moment corresponding to its nearest marked abnormal position;

[0125] Step S402: Read the degree of abnormality at this moment;

[0126] Step S403: Co-adjust the gas data acquisition period of the gas detector according to the moment and the degree of abnormality.

[0127] In an example of the technical solution of the present invention, for any gas detector, query the moment corresponding to its nearest marked abnormal position, read the degree of abnormality at this moment, and co-adjust the gas data acquisition period of the gas detector according to the moment and the degree of abnormality. The principle of the adjustment process is that the farther the moment marked as the abnormal position is from the current moment, the safer the position is. If it has not been marked as an abnormal position for a long time, the data acquisition period is larger; the smaller the degree of abnormality is, the smaller the abnormal degree is even if it is marked as an abnormal position, the safer the position is, and the data acquisition period is larger.

[0128] Figure 6 It is the composition structure block diagram of the online intelligent early warning system for gas detection. In an embodiment of the present invention, an online intelligent early warning system for gas detection, the system 10 includes:

[0129] The detection point calibration module 11 is used to obtain the pollution source information in the space, determine the gas detection points according to the pollution source information, and synchronously determine the levels at the gas detection points; the pollution source information includes the pollution source location and the pollution level of the pollution source;

[0130] The gas data acquisition module 12 is used to select and install gas detectors based on the levels of the gas detection points, and online acquire the gas data in the space according to the installed gas detectors; wherein, when the gas detectors acquire gas data, time tags are recorded;

[0131] The gas data identification module 13 is used to perform spatial domain identification and time domain identification on the acquired gas data, and generate warning signals according to the identification results of the spatial domain identification and the time domain identification;

[0132] The acquisition process adjustment module 14 is used to read the identification results of the time domain identification to adjust the online acquisition process.

[0133] Further, the detection point calibration module 11 includes:

[0134] The type query unit is used to query the types of all pollution sources in the space;

[0135] The level acquisition unit is used to, for each type, acquire the pollution source location 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;

[0136] The eigenvalue calculation unit is used to determine the eigenvalues of each position in the space according to the pollution source location and the pollution level of the pollution source;

[0137] The calibration execution unit is used to determine the gas detection points according to the eigenvalues, and synchronously determine the levels at the gas detection points;

[0138] Among them, the process of determining the eigenvalues is:;

[0139] The rule for determining the gas detection points is:;

[0140] The level at the gas detection points is:.

[0141] Specifically, the gas data acquisition module 12 includes:

[0142] The instrument query unit is used to query the gas detectors corresponding to the levels of the gas detection points in a preset instrument list; at least a semiconductor sensor and an electrochemical sensor are included in the instrument list;

[0143] The channel establishment unit is used to install gas detectors at the gas detection points and establish connection channels with the gas detectors;

[0144] A label determination unit, configured to obtain the gas concentration detected by a gas detector based on a connection channel, determine a position label according to the position of the gas detector, and determine a time label according to the acquisition time;

[0145] A data statistics unit, configured to count the gas concentration according to the position label and the time label to obtain the gas data at each moment in space.

[0146] Furthermore, the gas data recognition module 13 includes:

[0147] An abnormal feature determination unit, configured to receive an abnormal data matrix input by an administrator; the abnormal data matrix represents the gas concentration distribution in a certain abnormal situation;

[0148] An abnormal position determination unit, configured to traverse the gas data at each moment according to the abnormal data matrix to determine the abnormal position;

[0149] An abnormality degree calculation unit, configured to perform time-domain identification on each abnormal position and calculate the abnormality degree;

[0150] An abnormal comparison unit, configured to compare the abnormality degree with a preset abnormal threshold to generate a warning signal; wherein, there is at least one abnormal threshold, and each abnormal threshold corresponds to a warning signal, and the corresponding relationship is a preset value.

[0151] The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements, and improvements made within the spirit and principle of the present invention shall 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 includes: Obtaining pollution source information in the space, determining gas detection points according to the pollution source information, and synchronously determining the levels at the gas detection points; the pollution source information includes the pollution source location and the pollution level of the pollution source; Selecting and installing gas detectors based on the levels of the gas detection points, and online obtaining gas data in the space according to the installed gas detectors; when the gas detectors obtain gas data, time tags are recorded; Performing spatial domain identification and time domain identification on the obtained gas data, and generating a warning signal according to the identification results of the spatial domain identification and the time domain identification; Reading the identification results of the time domain identification to adjust the online acquisition process; The steps of obtaining pollution source information in the space, determining gas detection points according to the pollution source information, and synchronously determining the levels at the gas detection points include: Querying the types of all pollution sources in the space; For each type, obtaining the pollution source location 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; Determining the characteristic values of each position in the space according to the pollution source location and the pollution level of the pollution source; Determining gas detection points according to the characteristic values, and synchronously determining the levels at the gas detection points; Among them, the determination process of the characteristic values is: ; wherein, represents the eigenvalue at is the th pollution source at the pollution level at represents the th pollution source and the distance at is the total number of pollution sources, is a preset correction coefficient; The determination rule of the gas detection points is: Comparing the characteristic values with a 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 a preset distance radius centered on this position, marking the corresponding position as a gas detection point; The level at the gas detection point is: Determining the level of the gas detection point according to the proportional relationship of the characteristic values.

2. The online intelligent early warning method for gas detection according to claim 1, wherein The steps of selecting and installing gas detectors based on the levels of the gas detection points, and online obtaining gas data in the space according to the installed gas detectors include: Querying the gas detectors corresponding to the levels of the gas detection points in a preset instrument table; the instrument table at least includes semiconductor sensors and electrochemical sensors; Installing gas detectors at the gas detection points and establishing a connection channel with the gas detectors; Obtaining the gas concentration detected by the gas detectors based on the connection channel, determining a position tag according to the position of the gas detectors, and determining a time tag according to the acquisition time; Statistical gas concentration according to the position tag and the time tag to obtain the gas data at each moment in the space.

3. The online intelligent early warning method for gas detection according to claim 1, wherein, The steps of performing spatial domain identification and time domain identification on the obtained gas data, and generating a warning signal according to the identification results of the spatial domain identification and the time domain identification include: Receiving the abnormal data matrix input by the administrator; the abnormal data matrix represents the gas concentration distribution in a certain abnormal situation; Traversing the gas data at each moment according to the abnormal data matrix to determine the abnormal positions; Performing time domain identification on each abnormal position and calculating the abnormality degree; Comparing the abnormality degree with a preset abnormality threshold to generate a warning signal; among them, there is at least one abnormal threshold, and each abnormal threshold corresponds to a warning signal, and the corresponding relationship is a preset value.

4. The online intelligent early warning method for gas detection according to claim 3, wherein The steps of performing time domain identification on each abnormal position and calculating the abnormality degree include: Read the data at each moment at the abnormal position, sort them in chronological order to obtain a data sequence; Perform a discrete Fourier transform on the data sequence to obtain spectral features; Compare the spectral features with preset standard spectral features to obtain the degree of abnormality.

5. The online intelligent early warning method for gas detection according to claim 1, wherein The steps of adjusting the online acquisition process according to the recognition result of the time-domain recognition include: For any gas detector, query the moment closest to it that is marked as an abnormal position; Read the degree of abnormality at this moment; Jointly adjust the gas data acquisition period of the gas detector according to the moment and the degree of abnormality.

6. An online intelligent early warning system for gas detection, characterized in that, The system includes: A detection point calibration module, which is used to obtain pollution source information in the space, determine gas detection points according to the pollution source information, and synchronously determine the levels at the gas detection points; the pollution source information includes the pollution source position and the pollution level of the pollution source; A gas data acquisition module, which is used to select and install gas detectors based on the levels of gas detection points, and online acquire gas data in the space according to the installed gas detectors; when the gas detectors acquire gas data, time tags are recorded; A gas data recognition module, which 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; An acquisition process adjustment module, which is used to read the recognition result of the time domain recognition to adjust the online acquisition process; The detection point calibration module includes: A type query unit, which is used to query the types of all pollution sources in the space; A level acquisition unit, which is used to obtain the pollution source position and the pollution level of the pollution source for each type; the pollution level is used to represent the concentration of the polluting gas of the pollution source, and the concentration is proportional to the pollution level; An eigenvalue calculation unit, which is used to determine the eigenvalues of each position in the space according to the pollution source position and the pollution level of the pollution source; A calibration execution unit, which is used to determine gas detection points according to the eigenvalues, and synchronously determine the levels at the gas detection points; Among them, the process of determining the eigenvalue is: ; In the formula, represents the eigenvalue at is the th pollution source's pollution level at represents the th pollution source's distance from is the total number of pollution sources, is the preset correction coefficient; The rule for determining gas detection points is: Compare the eigenvalue with a preset eigenvalue threshold. When the eigenvalue of a certain position reaches the preset eigenvalue threshold and there are no other gas detection points within a preset distance radius centered on this position, mark the corresponding position as a gas detection point; The level at the gas detection point is: Determine the level of the gas detection point according to the proportional relationship of the eigenvalue.

7. The online intelligent early warning system for gas detection according to claim 6, characterized in that The gas data acquisition module includes: An instrument query unit, which is used to query the gas detector corresponding to the level of the gas detection point in a preset instrument list; the instrument list includes at least a semiconductor sensor and an electrochemical sensor; A channel establishment unit, which is used to install a gas detector at the gas detection point and establish a connection channel with the gas detector; A tag determination unit, which is used to obtain 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; A data statistics unit, which is used to statistically analyze the gas concentration according to the position tag and the time tag to obtain the gas data at each moment in the space.

8. The on-line intelligent early warning system for gas detection according to claim 6, characterized in that, The gas data recognition module includes: An abnormal feature determination unit, configured to receive an abnormal data matrix input by an administrator; the abnormal data matrix represents the gas concentration distribution in a certain abnormal situation; An abnormal position determination unit, configured to traverse the gas data at each moment according to the abnormal data matrix to determine the abnormal position; An abnormality degree calculation unit, configured to perform time-domain identification on each abnormal position and calculate the abnormality degree; An abnormal comparison unit, configured to compare the abnormality degree with a preset abnormal threshold to generate a warning signal; wherein, there is at least one abnormal threshold, and each abnormal threshold corresponds to a warning signal, and the corresponding relationship is a preset value.

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