Signal monitoring method, electronic device and computer storage medium

Abstract

This application provides a signal monitoring method, electronic device, and computer storage medium. The method acquires signal monitoring data such as ultrasonic signal waveform and / or ultrasonic signal intensity reported by an ultrasonic gas meter. Based on this signal monitoring data, it performs anomaly monitoring on the ultrasonic signal waveform and / or ultrasonic signal intensity and issues anomaly alarms. It can monitor signal quality anomalies from the dimensions of signal waveform and / or signal intensity. Compared with signal monitoring based on gain data, whether it is anomaly monitoring of signal waveform, anomaly monitoring of signal intensity, or anomaly monitoring of both signal waveform and signal intensity simultaneously, it can reduce false alarms and missed alarms of signal anomalies to varying degrees, improve the accuracy of signal monitoring, and thus improve the accuracy of measurement.

Description

Technical Field

[0001] This application relates to the field of Internet of Things (IoT) technology, and more particularly to a signal monitoring method, electronic device, and computer storage medium. Background Technology

[0002] Ultrasonic gas meters rely on an ultrasonic metering module within the meter for measurement, and the accuracy of this module depends on the quality of the ultrasonic signal. Damage to the ultrasonic transducer / hardware circuitry, noise interference, and the gas usage environment can all affect the quality of the ultrasonic signal, thus impacting the accuracy of the measurement. Therefore, monitoring the quality of the ultrasonic signal is crucial.

[0003] Currently, the signal quality of ultrasonic metering modules is generally monitored indirectly by using the gain data (corresponding to the amplification factor of the ultrasonic signal) reported by the gas meter. However, judging the quality of ultrasonic signals based on gain data can lead to missed or false alarms due to abnormal ultrasonic signals, resulting in low accuracy in signal monitoring. Summary of the Invention

[0004] This application provides a signal monitoring method, electronic device, and computer storage medium to improve the accuracy of signal monitoring.

[0005] In a first aspect, this application provides a signal monitoring method, comprising:

[0006] Acquire signal monitoring data from the ultrasonic gas meter, the signal monitoring data including the ultrasonic signal waveform and / or ultrasonic signal intensity reported by the ultrasonic gas meter; based on the signal monitoring data from the ultrasonic gas meter, perform anomaly monitoring on the ultrasonic signal waveform and / or the ultrasonic signal intensity, and issue an anomaly alarm.

[0007] Secondly, this application provides an electronic device, including: a memory, a processor, and a transceiver;

[0008] The memory stores computer-executable instructions; the processor executes the computer-executable instructions stored in the memory to implement the method as described in the first aspect.

[0009] Thirdly, this application provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the method described in the first aspect.

[0010] This application provides a signal monitoring method, electronic device, and computer storage medium. The method acquires signal monitoring data such as ultrasonic signal waveform and / or ultrasonic signal intensity reported by an ultrasonic gas meter. Based on this signal monitoring data, it performs anomaly monitoring on the ultrasonic signal waveform and / or ultrasonic signal intensity and issues anomaly alarms. It can monitor signal quality anomalies from the dimensions of signal waveform and / or signal intensity. Compared with signal monitoring based on gain data, whether it is anomaly monitoring of signal waveform, anomaly monitoring of signal intensity, or anomaly monitoring of both signal waveform and signal intensity simultaneously, it can reduce false alarms and missed alarms of signal anomalies to varying degrees, improve the accuracy of signal monitoring, and thus improve the accuracy of measurement. Attached Figure Description

[0011] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0012] Figure 1 The normal waveform of the measurement signal provided in the embodiments of this application;

[0013] Figure 2 The waveform of the measurement signal provided in the embodiments of this application when subjected to strong external noise interference;

[0014] Figure 3 The waveform of the measurement signal after damage to the ultrasonic transducer provided in the embodiments of this application;

[0015] Figure 4 A schematic flowchart illustrating a signal monitoring method provided in an embodiment of this application;

[0016] Figure 5 Three exemplary waveforms are provided for embodiments of this application;

[0017] Figure 6 This is a schematic diagram of the architecture of a signal monitoring system provided in an embodiment of this application;

[0018] Figure 7 This is a schematic diagram of the structure of a signal monitoring device provided in an embodiment of this application;

[0019] Figure 8 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.

[0020] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0021] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0022] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in one or more embodiments of this specification are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, use and processing of related data must comply with relevant laws, regulations and standards, and corresponding operation entry points are provided for users to choose to authorize or refuse.

[0023] It should be noted that in the embodiments of this application, certain software, components, models and other existing solutions in the industry may be mentioned. These should be regarded as exemplary and are only intended to illustrate the feasibility of implementing the technical solution of this application. However, it does not mean that the applicant has used or necessarily used the solution.

[0024] Ultrasonic gas meters (hereinafter referred to as gas meters or meters) rely on an ultrasonic metering module (hereinafter referred to as the metering module) within the meter for measurement. The accuracy of the metering module, in turn, depends on the quality of the ultrasonic signal. If the waveform of the metering module's measurement signal becomes abnormal due to damage to the ultrasonic transducer / hardware circuitry, or strong noise from external electromagnetic / turbulent interference, then measurement anomalies will occur. Furthermore, if the ultrasonic transducer weakens due to harsh gas usage environments or prolonged use of the meter, or if hardware circuitry malfunctions, the measurement signal strength of the metering module may also decrease, potentially leading to measurement anomalies. Therefore, monitoring the quality of the ultrasonic signal is crucial.

[0025] Current technologies typically rely on indirect data—the gain data (i.e., the amplification factor of the measured signal)—reported by the gas meter to monitor the signal quality of the metering module. For example, a high gain indicates a weak ultrasonic signal that requires amplification to obtain a satisfactory signal; conversely, a low gain indicates a strong ultrasonic signal that doesn't require amplification. However, judging ultrasonic signal quality based solely on gain data is prone to false alarms and missed detections, resulting in low accuracy in signal monitoring.

[0026] For example, when damage to the ultrasonic transducer causes a change in the waveform of the measurement signal, or when strong external electromagnetic interference introduces intense noise, the signal-to-noise ratio of the measurement signal decreases significantly. However, in these situations, the amplitude of the measurement signal often does not change significantly, and correspondingly, the gain data dynamically adjusted based on the signal amplitude will not change noticeably. For example, Figure 1 To measure the normal waveform of the signal, Figure 2 To measure the waveform of a signal when it is subjected to strong external noise interference, Figure 3 The waveform of the measured signal after ultrasonic transducer damage, such as Figures 1-3 As shown, Figure 2 and Figure 3 The amplitudes of the measured signal waveforms shown are all related to Figure 1 The amplitudes of the normal waveforms shown are similar, but the waveforms of the measured signals are quite different, which can lead to problems with the accuracy of the measurements. Figures 1-3 In the diagram, the horizontal axis represents time (unit: seconds), and the vertical axis represents voltage (unit: mV).

[0027] Furthermore, due to differences in the composition and properties of natural gas used by different users, as well as variations in the current gas usage environment (temperature, pressure), these factors can significantly impact the strength of the measurement signal. Gain data alone cannot accurately assess the degree of signal attenuation in the current metering module, leading to false alarms and missed alarms.

[0028] For example, for an ultrasonic gas meter, the gain is 50 when the gas composition is pure methane and 80 when the gas composition is methane + 6% carbon dioxide. The signal strength is significantly weaker in the case of methane + 6% carbon dioxide than in pure methane. However, based solely on the gain data of 80 reported by the ultrasonic gas meter, it is difficult to accurately determine whether the signal has attenuated.

[0029] To address the aforementioned technical problems, this application proposes a signal monitoring method. This method acquires signal monitoring data such as ultrasonic signal waveform and / or ultrasonic signal intensity reported by an ultrasonic gas meter. Based on this signal monitoring data, it performs anomaly monitoring on the ultrasonic signal waveform and / or ultrasonic signal intensity and issues anomaly alarms. This method can monitor signal quality anomalies from the dimensions of signal waveform and / or signal intensity. Compared to signal monitoring based on gain data, whether it is anomaly monitoring of signal waveform, anomaly monitoring of signal intensity, or anomaly monitoring of both signal waveform and signal intensity simultaneously, it can reduce false alarms and missed alarms of signal anomalies to varying degrees, improve the accuracy of signal monitoring, and thus improve the accuracy of metering.

[0030] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0031] Figure 4 This is a flowchart illustrating a signal monitoring method provided in an embodiment of this application. The executing entity of this method can be an electronic device used for signal monitoring, implemented through software and hardware. Specifically, it can be a server deployed locally or in the cloud, such as a server of a remote business system used for signal quality monitoring. The specific steps of this method are as follows:

[0032] S401. Obtain signal monitoring data from the ultrasonic gas meter, including the ultrasonic signal waveform and / or ultrasonic signal intensity reported by the ultrasonic gas meter.

[0033] In this step, to achieve signal quality monitoring, the remote business system can acquire signal monitoring data related to the ultrasonic gas meter. This signal monitoring data includes the monitoring data required for signal monitoring of the ultrasonic gas meter. The signal monitoring data of the ultrasonic gas meter includes at least the ultrasonic signal waveform and / or ultrasonic signal intensity reported by the ultrasonic gas meter.

[0034] In ultrasonic gas meters, the ultrasonic signal includes a measurement signal and a metering signal. The measurement signal is the signal received by the ultrasonic transducer; it reflects the actual propagation of ultrasound waves in the gas, and its quality directly affects the final metering result. The metering signal is the signal obtained after amplifying the measurement signal (the amplification factor is the gain data). Subsequent processing and analysis of the metering signal enables accurate metering.

[0035] Among them, the ultrasonic signal waveform and ultrasonic signal intensity reported by the ultrasonic gas meter refer to the waveform and signal intensity of the metering signal.

[0036] In addition, signal monitoring data may also include other relevant information about the ultrasonic gas meter itself, including but not limited to: the gas temperature and pressure inside the meter reported at regular intervals, the standard signal strength and original signal waveform at the time of manufacture, the meter number, the meter mounting address and its corresponding gas gate station information.

[0037] Signal monitoring data can also include gas quality composition information inside the ultrasonic gas meter. This can be obtained by acquiring the gas quality composition information reported by the gas gate station corresponding to the gas meter, which can be used as the gas quality composition information inside the gas meter.

[0038] Specifically, before leaving the factory, relevant personnel will test and record the standard condition signal strength and original signal waveform of the gas meter. After the meter is installed and the account is opened, the remote business system stores the meter number, its factory standard condition signal strength and original signal waveform, the meter address and its corresponding gas station information in the database. The factory standard condition signal strength of the ultrasonic gas meter refers to the signal strength of the ultrasonic gas meter measured under air, at a normal temperature of 20°C and a pressure of 101.325 kPa. The original signal waveform is the waveform of the measured signal.

[0039] During subsequent use, the gas meter periodically uploads real-time ultrasonic signal waveforms, ultrasonic signal strength, and gas temperature and pressure inside the meter to the remote service system. The remote service system receives the ultrasonic signal waveforms, ultrasonic signal strength, gas temperature and pressure information reported by the gas meter and stores them in its database.

[0040] The gas station gas quality monitoring system periodically reports gas quality composition information from various gas stations at different time periods to the remote business system. The remote business system receives this information and stores it in its database. During signal monitoring of ultrasonic gas meters, the most recently reported gas quality composition information from the gas service provider to which the ultrasonic gas meter belongs is used as the current gas quality composition information for the meter.

[0041] It should be noted that the ultrasonic gas meter and the gas station gas quality monitoring system report data to the remote business system at regular intervals according to their respective reporting frequencies. The reporting frequencies of the ultrasonic gas meter and the gas station gas quality monitoring system can be different, and can be set according to the actual application needs; this embodiment does not impose any limitations on this.

[0042] In one example scenario, the ultrasonic gas meter reports once a day, while the gas gate station reports once a week. The remote business system can monitor signal quality daily based on the real-time data reported by the ultrasonic gas meter. If gas composition information is required during signal quality monitoring, the gas composition information from the corresponding gas gate station will be used.

[0043] S402. Based on the signal monitoring data of the ultrasonic gas meter, perform abnormal monitoring on the ultrasonic signal waveform and / or ultrasonic signal intensity, and issue an abnormal alarm.

[0044] In this step, when monitoring for anomalies in the ultrasonic signal, the waveform of the ultrasonic signal reported by the ultrasonic gas meter can be used to identify meters with abnormal ultrasonic signal waveforms and issue corresponding alarms. This notifies maintenance personnel to address the issue promptly, reducing settlement disputes caused by metering anomalies. By monitoring anomalies in the ultrasonic signal waveform from the perspective of signal waveform, compared to signal monitoring based on gain data, false alarms and missed alarms can be reduced, improving the accuracy of signal monitoring to a certain extent, thereby enhancing the accuracy of metering.

[0045] In this step, when monitoring for ultrasonic signal anomalies, the ultrasonic signal strength reported by the ultrasonic gas meter in the signal monitoring data can be used to identify ultrasonic gas meters with abnormal signal strength and issue corresponding alarms. This notifies maintenance personnel to handle the issue promptly, reducing settlement disputes caused by metering anomalies. By monitoring ultrasonic signal strength anomalies from the perspective of signal strength, compared to signal monitoring based on gain data, false alarms and missed alarms can be reduced, improving the accuracy of signal monitoring to a certain extent, thereby enhancing the accuracy of metering.

[0046] In this step, when monitoring for ultrasonic signal anomalies, the waveform and intensity of the ultrasonic signal from the ultrasonic gas meter can be monitored simultaneously based on the signal monitoring data. Ultrasonic gas meters with abnormal ultrasonic signal waveforms or intensities can be identified, and corresponding alarms can be triggered to notify maintenance personnel for timely on-site handling, reducing settlement disputes caused by metering anomalies. By monitoring abnormal ultrasonic signal intensity from both waveform and intensity dimensions, compared to signal monitoring based on gain data, false alarms and missed alarms due to signal intensity anomalies can be reduced or even avoided, significantly improving the accuracy of signal monitoring and thus greatly enhancing metering accuracy.

[0047] In this embodiment, by acquiring signal monitoring data such as ultrasonic signal waveform and / or ultrasonic signal intensity reported by the ultrasonic gas meter, and based on this signal monitoring data, anomaly monitoring of the ultrasonic signal waveform and / or ultrasonic signal intensity is performed, and anomaly alarms are issued. This allows for monitoring of signal quality anomalies from the perspective of signal waveform and / or signal intensity. Compared to signal monitoring based on gain data, whether anomaly monitoring is performed on the signal waveform, anomaly monitoring is performed on the signal intensity, or anomaly monitoring is performed on both the signal waveform and signal intensity simultaneously, it can reduce false alarms and missed alarms of signal anomalies to varying degrees, improve the accuracy of signal monitoring, and thus improve the accuracy of measurement.

[0048] In an optional embodiment, in the aforementioned S402, based on the signal monitoring data of the ultrasonic gas meter, abnormal monitoring of the ultrasonic signal waveform is performed, and an abnormal alarm is issued, specifically including:

[0049] Calculate the similarity between the ultrasonic signal waveform reported by each ultrasonic gas meter under the same gas pipeline network and the reference waveform; based on the similarity between the ultrasonic signal waveform reported by each ultrasonic gas meter and the reference waveform, select the first gas meter with abnormal similarity; and issue a first alarm message, which indicates that the ultrasonic signal waveform of the first gas meter is abnormal.

[0050] Specifically, the remote service system identifies ultrasonic gas meters located within the same gas pipeline network based on their installation addresses. For each ultrasonic gas meter within the same network, the system calculates the similarity between the ultrasonic signal waveform currently reported by the meter and a reference waveform.

[0051] The reference waveform refers to the waveform used for comparison with the ultrasonic signals periodically reported by each ultrasonic gas meter. The reference waveforms may differ across different gas pipeline networks. Optionally, the original signal waveform of each ultrasonic gas meter at the time of manufacture can be used as the reference waveform for each ultrasonic gas meter, and the similarity between the ultrasonic signal waveform currently reported by each ultrasonic gas meter and its corresponding reference waveform can be calculated. Optionally, one of the original signal waveforms from each ultrasonic gas meter at the time of manufacture within the same gas pipeline network can be selected as the reference waveform, or the reference waveform can be specified by relevant technical personnel. This embodiment does not specifically limit the setting of the reference waveform.

[0052] Optionally, the remote service system can also update the reference waveform based on ultrasonic signal waveforms whose similarity to the reference waveform is greater than a waveform similarity threshold. For example, for ultrasonic signal waveforms reported by ultrasonic gas meters located within the same gas pipeline network, ultrasonic signal waveforms with a similarity greater than the reference waveform are sorted, and the ultrasonic signal waveform in the middle position of the sorted result is used as the new reference waveform. If there are two ultrasonic signal waveforms in the middle position of the sorted result, either one can be selected as the new reference waveform. By continuously updating the reference waveform during signal monitoring based on ultrasonic signal waveforms with a similarity greater than the waveform similarity threshold, the accuracy of the reference waveform can be ensured, thereby improving the accuracy of signal monitoring. Any algorithm for calculating waveform similarity can be used to calculate the similarity between the reported ultrasonic signal waveform and the reference waveform; this embodiment does not limit this. For example, the similarity between two waveforms can be calculated using a cross-correlation function, or the average Euclidean distance between each waveform point in the two waveforms can be directly calculated to measure the similarity between the two waveforms. The smaller the similarity between waveforms, the greater the waveform difference. For example, for... Figure 5The waveforms 1, 2, and 3 shown are similar to each other. After calculating the similarity between the waveforms, the similarity between waveform 1 and waveform 2 is 138.211, and the similarity between waveform 1 and waveform 3 is 133.342. Therefore, waveform 1 and waveform 2 are more similar, while waveform 1 and waveform 3 are more different. Figure 5 In the diagram, the vertical axis represents voltage (unit: mV), and the horizontal axis represents time (unit: seconds).

[0053] Based on the similarity between the ultrasonic signal waveform reported by each ultrasonic gas meter and the reference waveform, the first gas meter with a significantly abnormal similarity between the ultrasonic signal waveform and the reference waveform can be screened out, and the first alarm message can be issued to notify the maintenance personnel to handle it in a timely manner.

[0054] Optionally, when screening gas meters with abnormal ultrasonic signal waveforms, gas meters with similarity less than the waveform similarity threshold can be selected as key monitoring targets. The key monitoring targets that show abnormal ultrasonic signal waveforms N times consecutively are identified as the first gas meters with abnormal ultrasonic signal waveforms. Here, N is a positive integer.

[0055] Specifically, based on a pre-set waveform similarity threshold, ultrasonic gas meters with a similarity lower than the threshold are selected from those within the same gas pipeline network and designated as key monitoring targets. The waveform similarity threshold can be set according to the needs of the actual application; this embodiment does not impose any limitations on it.

[0056] If the similarity to the reference waveform is less than the waveform similarity threshold, it indicates that the ultrasonic signal waveform differs significantly from the reference waveform and may be abnormal. Therefore, ultrasonic gas meters with a similarity to the reference waveform less than the waveform similarity threshold are designated as key monitoring targets.

[0057] For key monitoring targets, the frequency of signal monitoring for these targets can be increased or maintained to enable more frequent and closer monitoring. If any key monitoring target shows abnormal ultrasonic signal waveforms for N consecutive monitoring tests, a first alarm message is issued to prompt maintenance personnel to address the issue promptly. Here, N is a positive integer, and can be set according to the needs of the actual application; this embodiment does not impose any limitations on this.

[0058] If, in the subsequent N signal monitoring sessions for a key monitoring target, an abnormal ultrasound signal waveform of that key monitoring target is not detected in any of them, then the frequency of signal monitoring for that key monitoring target shall be restored.

[0059] Optionally, when screening the first gas meter with abnormal ultrasonic signal waveform, the waveform similarity of each ultrasonic gas meter can be sorted, the difference value between any two adjacent similarities can be calculated, and the first gas meter with abnormal similarity can be screened based on the difference value between any two adjacent similarities.

[0060] Specifically, for ultrasonic gas meters within the same gas pipeline network, the ultrasonic gas meters are sorted from highest to lowest similarity to a reference waveform. The average difference (called the average difference) between any two adjacent similarities is calculated based on the sorting results. The difference threshold is obtained by adding the difference increment to the average difference. Ultrasonic gas meters ranked after a preset position whose similarity difference with the preceding ultrasonic gas meter is greater than the difference threshold, along with all ultrasonic gas meters ranked after that, are designated as the first gas meter with abnormal similarity. For example, if the difference between the last similarity (i.e., the smallest similarity) and the preceding similarity is greater than the difference threshold, meaning the difference between the last similarity and its adjacent similarities is significantly greater than the average difference, an anomaly is considered to exist. Therefore, the ultrasonic gas meter corresponding to the last similarity is designated as the first gas meter with abnormal ultrasonic signal waveform.

[0061] The difference increment and preset position can be set according to the needs of actual application, and this embodiment does not limit them. For example, the preset position is the 80th percentile from the beginning to the end of the sorting.

[0062] Optionally, after determining that the ultrasonic signal waveform of the first gas meter is abnormal, an alarm message can be issued immediately to indicate that the ultrasonic signal waveform of the first gas meter is abnormal, and to remind maintenance personnel to go to the site in time to investigate the abnormality.

[0063] In this embodiment, by calculating the similarity between the ultrasonic signal waveform reported by the ultrasonic gas meter and the reference waveform, it is possible to more accurately determine whether there is an abnormality in the ultrasonic signal waveform, thereby improving the accuracy of signal monitoring.

[0064] In an optional embodiment, in the aforementioned S402, based on the signal monitoring data of the ultrasonic gas meter, abnormal monitoring of the ultrasonic signal waveform is performed, and an abnormal alarm is issued. Specifically, this includes: calculating the signal-to-noise ratio (SNR) of each ultrasonic gas meter based on the ultrasonic signal waveform reported by the ultrasonic gas meters located in the same gas pipeline network; filtering out the second gas meter with an abnormal SNR based on the SNR of each ultrasonic gas meter; and issuing a second alarm message indicating that the SNR of the ultrasonic signal of the second gas meter is abnormal.

[0065] Specifically, for ultrasonic gas meters within the same gas pipeline network, the signal-to-noise ratio (SNR) of the corresponding ultrasonic signal is calculated based on the waveform of the ultrasonic signal reported by each ultrasonic gas meter, and this SNR is used as the corresponding SNR for each ultrasonic gas meter. Any method for calculating the SNR based on the waveform of the ultrasonic signal can be used, such as frequency domain analysis or waveform sampling; this embodiment does not limit the specific method used.

[0066] Furthermore, by comparing and analyzing the signal-to-noise ratios of various ultrasonic gas meters under the same gas pipeline network, ultrasonic gas meters with significantly lower signal-to-noise ratios are selected from those meters. This indicates that these ultrasonic gas meters may be subject to strong external electromagnetic interference or disturbed airflow. These ultrasonic gas meters are then identified as second gas meters with abnormal signal-to-noise ratios, and a second alarm message is issued to notify maintenance personnel that the ultrasonic signal of the second gas meter has an abnormal signal-to-noise ratio, enabling maintenance personnel to conduct timely on-site maintenance.

[0067] Optionally, by comparing and analyzing the signal-to-noise ratios of various ultrasonic gas meters within the same gas pipeline network, ultrasonic gas meters with significantly lower signal-to-noise ratios can be selected from those meters. This can include:

[0068] Ultrasonic gas meters with a signal-to-noise ratio (SNR) lower than a first SNR threshold are selected as the second gas meters with abnormal SNR. The first SNR threshold can be set according to the needs of the actual application; this embodiment does not limit its setting.

[0069] Optionally, by comparing and analyzing the signal-to-noise ratios (SNRs) of various ultrasonic gas meters within the same gas pipeline network, and selecting ultrasonic gas meters with significantly lower SNRs from the network, the following steps can be taken: For each ultrasonic gas meter within the same network, calculate the average SNR of all meters, and subtract a first preset difference from this average to obtain a second SNR threshold. Ultrasonic gas meters with SNRs lower than the second threshold are then selected as second gas meters exhibiting abnormal SNRs. The first preset difference can be set according to the needs of the actual application; this embodiment does not limit its setting.

[0070] Optionally, the second alarm information may also include anomaly investigation information. For example, if the signal-to-noise ratio of the ultrasonic signal is abnormal, the anomaly investigation information may include: focusing on checking whether the pressure regulator before the gas meter is working properly, whether the gas pipeline has been modified, and whether there are strong electromagnetic interference sources near the meter installation location. Based on the second alarm information, when maintenance personnel go to the site to handle the problem, they can focus on checking whether the pressure regulator of the second gas meter is working properly, whether the gas pipeline has been modified, and whether there are strong electromagnetic interference sources near the meter installation location, thus improving the efficiency of anomaly investigation.

[0071] In this embodiment, a low signal-to-noise ratio (SNR) of the ultrasonic signal indicates high noise in the ultrasonic signal. High noise in the ultrasonic signal can lead to distortion or deformation of the ultrasonic signal. By calculating the SNR corresponding to the ultrasonic gas meter, it is determined that an SNR lower than the first or second SNR threshold is abnormal. This allows for accurate determination of whether there is an abnormality in the ultrasonic signal waveform, thereby improving the accuracy of signal monitoring.

[0072] In an optional embodiment, in the aforementioned S402, based on the signal monitoring data of the ultrasonic gas meter, abnormal monitoring of the ultrasonic signal waveform is performed, and an abnormal alarm is issued. Specifically, this includes: calculating the envelope curve of each ultrasonic signal waveform based on the ultrasonic signal waveform reported by the ultrasonic gas meters located in the same gas pipeline network; selecting a third gas meter with an abnormal envelope curve shape based on the envelope curve of each ultrasonic signal waveform; and issuing a third alarm message, which indicates that the envelope curve shape of the ultrasonic signal waveform of the third gas meter is abnormal.

[0073] Specifically, for each ultrasonic gas meter located within the same gas pipeline network, the envelope curve of each ultrasonic signal waveform is calculated based on the ultrasonic signal waveform reported by each ultrasonic gas meter. Any method for calculating the envelope curve of the ultrasonic signal waveform can be used, such as the instantaneous amplitude method or the smoothing filtering method; this embodiment does not limit the specific method used.

[0074] The envelope curve of the ultrasound signal waveform whose reporting time is closest to the account opening time is used as the reference envelope curve. The similarity between the envelope curve of each ultrasound signal waveform and the reference envelope curve is calculated to obtain the envelope curve similarity of each ultrasound signal waveform.

[0075] If the similarity of the envelope curve corresponding to any ultrasound signal waveform is less than the first envelope curve similarity threshold, then the shape of the envelope curve corresponding to that ultrasound signal waveform is determined to be abnormal. The first envelope curve similarity threshold can be set according to the needs of actual applications; this embodiment does not limit its setting.

[0076] Based on the similarity of the envelope curves of ultrasonic signal waveforms corresponding to ultrasonic gas meters located within the same gas pipeline network, the average value of each envelope curve similarity is calculated. Subtracting a second preset difference from the average envelope curve similarity yields a second envelope curve similarity threshold. Ultrasonic signal waveforms with envelope curve similarities less than the second envelope curve similarity threshold are then selected, indicating abnormal morphology of their envelope curves. The second preset difference can be set according to the needs of actual applications; this embodiment does not impose any limitations on it.

[0077] Furthermore, by comparing and analyzing the envelope curves of the ultrasonic signal waveforms reported by various ultrasonic gas meters within the same gas pipeline network, ultrasonic gas meters with envelope curve shapes significantly different from other gas meters are selected. This may indicate an abnormality in the ultrasonic metering module within the gas meter. Therefore, the ultrasonic gas meter with the abnormal envelope curve shape is designated as the third gas meter with an abnormal envelope curve shape, and a third alarm message is issued. This third alarm message indicates that the envelope curve shape of the ultrasonic signal waveform of the third gas meter is abnormal, thus notifying maintenance personnel to promptly address the issue.

[0078] Optionally, the third alarm information may also include anomaly investigation information. For example, for anomalies in the shape of the ultrasonic signal envelope curve, the anomaly investigation information may include: focusing on checking the ultrasonic metering module inside the gas meter. Based on the anomaly investigation information in the third alarm information, when maintenance personnel go to handle the problem, they can first check whether the ultrasonic metering module inside the third gas meter is abnormal. If the ultrasonic metering module inside the second gas meter is abnormal, the meter can be replaced directly, improving the efficiency of anomaly handling.

[0079] In this embodiment, by calculating the envelope curve of the ultrasonic signal, it is determined whether there is an abnormality in the envelope curve of the ultrasonic signal, which can accurately determine whether there is an abnormality in the ultrasonic signal waveform, thereby improving the accuracy of signal monitoring.

[0080] In an optional embodiment, in the aforementioned S402, based on the signal monitoring data of the ultrasonic gas meter, abnormal monitoring of the ultrasonic signal waveform is performed, and an abnormal alarm is issued, specifically including:

[0081] For any ultrasonic gas meter, acquire the historical waveforms reported by the ultrasonic gas meter within a historical time period; based on the ultrasonic signal waveforms reported by the ultrasonic gas meter and the historical waveforms, determine the quality change curve of the ultrasonic signal of the ultrasonic gas meter; based on the quality change curve, screen out ultrasonic gas meters with abnormal signal quality and issue corresponding alarm information.

[0082] In this step, for any ultrasonic gas meter, the ultrasonic signal waveform reported by the meter within a historical period is acquired and used as the historical waveform. The historical period may contain multiple reported historical waveforms, and the length of the historical period can be configured and adjusted according to actual application requirements; no specific limitation is made here.

[0083] Furthermore, the ultrasonic signal waveforms reported by the ultrasonic gas meters, as well as each historical waveform, are compared with a reference waveform to determine the quality of the ultrasonic signal waveforms and each historical waveform relative to the reference waveform, and a quality change curve is plotted. Further, based on the quality change curve, ultrasonic gas meters with abnormal signal quality are identified, and corresponding alarm messages are issued to notify maintenance personnel to promptly address the issue.

[0084] In one optional implementation, the waveform similarity between the ultrasonic signal waveform reported by the ultrasonic gas meter and the historical waveform and the reference waveform is calculated, and the waveform similarity variation curve is determined.

[0085] Specifically, the waveform similarity between the ultrasonic signal waveform reported by the ultrasonic gas meter and the historical waveform and the reference waveform is calculated to obtain the waveform similarity at the reporting time of the ultrasonic signal waveform and the historical waveform. A curve showing the change in waveform similarity with the reporting time is then plotted to obtain the waveform similarity variation curve. A higher waveform similarity to the reference waveform indicates a higher quality ultrasonic signal waveform / historical waveform. The slope of the waveform similarity variation curve represents the trend of change in waveform similarity to the reference waveform.

[0086] Furthermore, the average slope of the waveform similarity change curve at each reporting time in the recent period (referred to as the recent slope) and the average slope of the waveform similarity change curve at each reporting time before the recent period (referred to as the historical slope) are calculated. The recent slope is compared with the historical slope. If the absolute value of the difference between the recent slope and the historical slope is greater than a preset increment, it indicates that the waveform similarity curve is significantly abnormal in the recent period, the signal quality may be rapidly decaying, and the metering module within the meter may already be abnormal or about to be abnormal. This confirms that the ultrasonic signal waveform of the ultrasonic gas meter is abnormal, and a fourth alarm message is issued. The fourth alarm message indicates that the ultrasonic signal waveform of the ultrasonic gas meter is abnormal, thus notifying maintenance personnel to promptly handle the situation.

[0087] The duration of the recent period can be set according to the needs of the actual application. The shorter the duration of the recent period, the higher the monitoring sensitivity. This embodiment does not limit this. The preset increment can be set according to the needs of the actual application. This embodiment does not limit this.

[0088] Optionally, the fourth alarm information may also include anomaly investigation information. For example, in the case of an abnormal waveform similarity curve of the ultrasonic signal, the anomaly investigation information may include: the metering module inside the meter may already be abnormal or is about to be abnormal, and needs to be replaced in time. Based on the anomaly investigation information in the fourth alarm information, maintenance personnel can replace the ultrasonic gas meter during on-site handling, improving the efficiency of anomaly handling.

[0089] In another optional implementation, the signal-to-noise ratio (SNR) corresponding to the ultrasonic signal waveform reported by the ultrasonic gas meter and the historical waveform are calculated respectively, and the curve of SNR changing with the reporting time is plotted to determine the curve of SNR change.

[0090] Furthermore, based on the signal-to-noise ratio (SNR) change curve, if it is determined that the SNR of the ultrasonic signal waveform reported by the ultrasonic gas meter has suddenly decreased recently, it indicates that an interference source may have appeared nearby. Therefore, the ultrasonic signal waveform of the ultrasonic gas meter is determined to be abnormal, and a fifth alarm message is issued. The fifth alarm message indicates that the SNR of the ultrasonic gas meter is abnormal, so that maintenance personnel can be notified to handle the situation promptly.

[0091] For example, using the first moment as a dividing point, the signal-to-noise ratio (SNR) of the currently reported ultrasonic signal waveform is subtracted from the SNR of the ultrasonic signal waveform reported at the first moment to obtain the SNR change. Subtracting the first moment from the current reporting moment yields the time change. Dividing the SNR change by the time change gives the overall slope of the SNR change curve over the recent period (i.e., from the first moment to the current reporting moment). If the overall slope is negative and its absolute value is greater than a slope threshold, it indicates a sudden decrease in the SNR recently, thus confirming an abnormal ultrasonic signal waveform of the ultrasonic gas meter.

[0092] The first moment can be selected from the moment before the current report, depending on the actual application needs; this embodiment does not limit this selection. The slope threshold can be set according to the actual application needs; this embodiment does not limit this setting either.

[0093] Optionally, the fifth alarm message may also include anomaly investigation information. For example, in the case of an abnormal signal-to-noise ratio (SNR) curve of the ultrasonic signal, the anomaly investigation information may include: a sudden decrease in the SNR recently, which may indicate the presence of an interference source near the gas meter. Based on the anomaly investigation information in the fifth alarm message, maintenance personnel can prioritize investigating the ultrasonic gas meter for interference sources when handling the issue, thereby improving the efficiency of anomaly handling.

[0094] In this embodiment, the quality change curve of the ultrasonic signal of the ultrasonic gas meter is determined based on the ultrasonic signal waveform reported by the ultrasonic gas meter and historical waveforms. The quality change curve can reflect the trend of the ultrasonic signal quality of the ultrasonic gas meter changing over time. Based on the recent quality change values, it is possible to accurately determine whether there is any abnormality in the ultrasonic signal waveform reported by the ultrasonic gas meter, thereby improving the accuracy of signal monitoring.

[0095] It should be noted that the various specific implementation schemes for monitoring the abnormality of ultrasonic signal waveforms in the foregoing embodiments can be used in combination to minimize false alarms and missed alarms of signal waveform abnormalities, improve the accuracy of signal monitoring, and thus improve the accuracy of measurement.

[0096] In an optional embodiment, in the aforementioned S402, based on the signal monitoring data of the ultrasonic gas meter, abnormal monitoring of the ultrasonic signal intensity is performed, and an abnormal alarm is issued, specifically including:

[0097] Based on the ultrasonic signal intensity, gas temperature and pressure reported by the ultrasonic gas meter, and the gas quality composition information of the corresponding gas gate station, the standard condition signal intensity of the ultrasonic gas meter is calculated.

[0098] In this embodiment, the ultrasonic signal intensity of the ultrasonic gas meter under standard conditions is referred to as the standard condition signal intensity, and the ultrasonic signal intensity of the ultrasonic gas meter under actual working conditions is referred to as the operating condition signal intensity. The standard conditions include the gas composition, gas temperature, and gas pressure inside the ultrasonic gas meter. The standard conditions can be set according to the needs of actual applications, and this embodiment does not limit this. For example, the standard conditions are an environment where the gas composition is air, the gas temperature inside the meter is 20°C, and the gas pressure inside the meter is 101.325 kPa.

[0099] Specifically, the ultrasonic signal intensity reported by the ultrasonic gas meter is the ultrasonic signal intensity under the current actual operating conditions. The current actual operating conditions are: the most recent gas quality composition information reported by the gas gate station to which the ultrasonic gas meter belongs is used as the gas quality composition information in the ultrasonic gas meter at present, along with the reported gas temperature and gas pressure inside the meter.

[0100] Based on the conversion relationship between actual operating condition signal strength and standard condition signal strength, and based on the reported gas temperature and pressure inside the meter, as well as the operating condition information of the gas quality composition information most recently reported by the corresponding gas gate station, the ultrasonic signal strength reported by the ultrasonic gas meter is converted into the standard condition signal strength, and the current standard condition signal strength of the ultrasonic gas meter can be obtained.

[0101] For example, for any ultrasonic gas meter, the signal intensity ratio of the standard gas quality components and the working gas quality components under the same gas temperature and pressure (called the gas quality ratio factor); the signal intensity ratio of the standard gas temperature and the working gas temperature under the same gas quality components and gas pressure (called the temperature ratio factor); the signal intensity ratio of the standard gas pressure and the working gas pressure under the same gas quality components and gas temperature (called the pressure ratio factor); and the amplification factor corresponding to the gain data; by dividing the working signal intensity by the amplification factor, and then multiplying by the gas quality ratio factor, the temperature ratio factor, and the temperature ratio factor, the working signal intensity can be converted into the standard signal intensity.

[0102] For example, assuming the ultrasonic signal intensity of an ultrasonic gas meter in an environment with methane, an internal gas temperature of 40℃, and a pressure of 105kPa is 800mV, the gas quality proportionality factor is 1 / 3, the temperature proportionality factor is 1 / 1.5, the pressure proportionality factor is 1 / 1.1, the gain is 10, and the amplification factor corresponding to the gain is 20, then the standard condition signal intensity can be calculated as: 800mV / 20×1 / 3×1 / 1.5×1 / 1.1=8.08mV.

[0103] It should be noted that different ultrasonic gas meters have different amplification factors, gas quality proportionality coefficients, temperature proportionality coefficients, and current characteristics due to differences in the ultrasonic transducers, circuits, and current channels used. These can be obtained by relevant technical personnel through extensive testing and the establishment of corresponding databases to provide a data basis for converting operating condition signal strength into standard condition signal strength.

[0104] Furthermore, based on the ultrasonic signal strength reported by ultrasonic gas meters within the same gas station's gas supply range, a sixth gas meter with abnormal ultrasonic signal strength is identified; a sixth alarm message is issued, indicating that the ultrasonic signal strength of the sixth gas meter is abnormal, so as to notify maintenance personnel to handle the anomaly in a timely manner.

[0105] Optionally, based on the gas gate station corresponding to the ultrasonic gas meter, the ultrasonic gas meters corresponding to the same gas gate station can be identified, thus obtaining the ultrasonic gas meters within the gas supply range of the same gas gate station. For each ultrasonic gas meter within the gas supply range of any gas gate station, the ultrasonic signal intensity reported by each ultrasonic gas meter is converted into the corresponding standard condition signal intensity. The average value of the standard condition signal intensity of each ultrasonic meter is subtracted by a specified difference to obtain a first signal intensity threshold. If the standard condition signal intensity of any ultrasonic gas meter within the gas supply range of the same gas gate station is less than the first signal intensity threshold, it indicates that the standard condition signal intensity of this ultrasonic gas meter is significantly weaker than that of other gas meters, and this ultrasonic gas meter is identified as the sixth gas meter with abnormal ultrasonic signal intensity.

[0106] The differential signal and the first signal strength threshold can be set according to the needs of actual applications, and this embodiment does not limit them.

[0107] After identifying the sixth gas meter as having abnormal ultrasonic signal intensity, it can be designated as a key monitoring target. The frequency of signal monitoring for the sixth gas meter can be increased or maintained to allow for more frequent and close monitoring. If, during subsequent M monitoring sessions of the increased frequency, the abnormal ultrasonic signal intensity is not detected in any of the remaining monitoring sessions, the sixth gas meter will no longer be designated as a key monitoring target, and the original monitoring frequency will be restored.

[0108] For any sixth gas meter, if the standard signal strength of the sixth gas meter is detected to be less than the second signal strength threshold for M consecutive times, it can be determined that the ultrasonic signal strength of the ultrasonic gas meter is abnormal, and a sixth alarm message is issued. The sixth alarm message indicates that the ultrasonic signal strength of the sixth gas meter is abnormal. The second signal strength threshold can be set according to the needs of actual application and the meter manufacturer's experience data; this embodiment does not limit it. M is a positive integer and can be set according to the needs of actual application; this embodiment does not limit it.

[0109] Optionally, after determining that the sixth gas meter has an abnormal ultrasonic signal strength, an alarm message can be issued immediately to indicate that the ultrasonic signal strength of the sixth gas meter is abnormal, and to remind maintenance personnel to go to the site in time to investigate the abnormality.

[0110] In this embodiment, the operating condition signal strength reported by ultrasonic gas meters within the same gas station supply range is converted into standard condition signal strength. By performing a horizontal comparison of the standard condition signal strength of ultrasonic gas meters within the same gas station supply range, ultrasonic gas meters with abnormal standard condition signal strength (signal strength significantly insufficient) are screened out. This enables abnormal monitoring of the ultrasonic signal strength of ultrasonic gas meters, which can reduce false alarms and missed alarms due to abnormal signal strength, improve the accuracy of signal monitoring, and thus improve the accuracy of metering.

[0111] In an optional embodiment, in the aforementioned S402, based on the signal monitoring data of the ultrasonic gas meter, abnormal monitoring of the ultrasonic signal strength is performed, and an abnormal alarm is issued. Specifically, this includes: for any ultrasonic gas meter, obtaining the historical signal strength reported by the ultrasonic gas meter within a historical time period; determining the signal attenuation curve of the ultrasonic gas meter based on the ultrasonic signal strength reported by the ultrasonic gas meter and the historical signal strength; and filtering out ultrasonic gas meters with abnormal signal attenuation based on the signal attenuation curve and issuing corresponding alarm information.

[0112] Specifically, based on the relationship between the ultrasonic signal strength reported by the ultrasonic gas meter and the historical signal strength and reporting time, the signal attenuation curve of the ultrasonic gas meter is plotted.

[0113] For any ultrasonic gas meter, calculate the average slope of its signal attenuation curve at each reporting time within a recent period. If the average slope is negative and its absolute value is greater than the attenuation threshold, it indicates that the ultrasonic signal strength attenuation of the gas meter is abnormal within a recent period. In this case, the gas meter will be designated as an ultrasonic gas meter with abnormal signal attenuation, and an alarm message can be immediately issued to indicate the abnormal ultrasonic signal waveform and remind maintenance personnel to promptly conduct on-site troubleshooting.

[0114] Optionally, if the average slope is negative and its absolute value is greater than the attenuation threshold, it indicates that the ultrasonic gas meter has experienced abnormal attenuation of its ultrasonic signal intensity in the recent period. In this case, the ultrasonic gas meter will be designated as a key monitoring target and subject to focused monitoring. The "recent period" and the attenuation threshold can be set according to the actual application requirements; this embodiment does not impose any limitations on them.

[0115] For ultrasonic gas meters that require close monitoring, increase or maintain the frequency of signal monitoring for that gas meter to enable more frequent and intensive monitoring. If, after increasing the frequency of signal monitoring, no abnormal ultrasonic signal waveform is detected in any of the subsequent T signal monitoring sessions, that gas meter will no longer be considered a key monitoring target, and the frequency of signal monitoring for that gas meter will be restored.

[0116] If the ultrasonic signal waveform of the gas meter is detected as abnormal for T consecutive times, the signal attenuation of the gas meter is abnormal, and a corresponding alarm message is issued. This alarm message indicates that the ultrasonic signal waveform of the gas meter has been detected as abnormal for T consecutive times, so as to prompt maintenance personnel to handle the situation promptly. Here, T is a positive integer, and T can be set according to the actual application needs. This embodiment does not limit it.

[0117] In this embodiment, based on the relationship between the ultrasonic signal strength reported by the ultrasonic gas meter and the historical signal strength and reporting time, a signal attenuation curve of the ultrasonic gas meter is plotted. The signal attenuation curve can accurately reflect the relationship between the ultrasonic signal strength and time. Based on the signal attenuation curve, ultrasonic gas meters with abnormal signal attenuation are screened out and corresponding alarm information is issued. This can reduce false alarms and missed alarms of abnormal signal strength, improve the accuracy of signal monitoring, and thus improve the accuracy of measurement.

[0118] It should be noted that the various specific implementation schemes for monitoring the abnormal intensity of ultrasonic signals in the foregoing embodiments can be used in combination to minimize false alarms and missed alarms of signal intensity abnormalities, improve the accuracy of signal monitoring, and thus improve the accuracy of measurement.

[0119] Based on any of the aforementioned embodiments, the remote service system can also record the moment when the ultrasonic gas meter first exhibits any of the aforementioned abnormalities, as the moment the abnormality occurs. When the abnormality is resolved (e.g., after maintenance personnel handle and resolve the issue), the moment the abnormality is resolved is recorded. Based on the moments of occurrence and resolution of the abnormalities, the abnormal period for each ultrasonic gas meter is determined and stored. Furthermore, based on the abnormal periods of each ultrasonic gas meter, the cumulative gas consumption during the abnormal period can be promptly corrected, improving the accuracy of the cumulative gas consumption and thus avoiding billing disputes with users.

[0120] For example, the remote business system can provide the gas company with the abnormal periods of each ultrasonic gas meter, so that the gas company can adjust and correct the cumulative gas consumption used for settlement in a timely manner based on the abnormal periods of each ultrasonic gas meter (generally, the average gas consumption during the normal period is taken to correct the cumulative gas consumption during the abnormal period).

[0121] Figure 6 This is a schematic diagram of the architecture of a signal monitoring system provided in an embodiment of this application. Figure 6 As shown, the signal monitoring system includes an ultrasonic gas meter, a gas station gas quality monitoring system, and a remote service system. The ultrasonic gas meter, the gas station gas quality monitoring system, and the remote service system are connected by a communication link. Additionally, the remote service system may include a database to store data reported by the ultrasonic gas meter and the gas station, as well as other data required or generated during the information monitoring process.

[0122] The remote business system stores the standard signal strength, original signal waveform, meter number, meter mounting address, and corresponding gas gate station information of each ultrasonic gas meter in the database.

[0123] During signal monitoring, the ultrasonic gas meter periodically uploads real-time ultrasonic signal waveforms, ultrasonic signal strength, gas temperature, and pressure inside the meter to the remote service system according to a primary reporting frequency (e.g., daily). The remote service system stores the ultrasonic gas meter's factory-set signal strength, original signal waveform, meter number, meter mounting address, and corresponding gas station information in its database.

[0124] The gas station gas quality monitoring system is responsible for monitoring the gas quality components at each gas station and, according to a second reporting frequency (e.g., weekly), periodically reporting the gas quality component information of each gas station for different time periods to the remote business system. The remote business system stores the gas quality component information of each gas station in a database. The remote business system can also retrieve necessary data from the database. It should be noted that the first and second reporting frequencies can be set according to the needs of actual applications, and this embodiment does not limit this.

[0125] The remote service system can monitor the signals of each ultrasonic gas meter at regular intervals. For example, based on the signal monitoring data reported by each ultrasonic gas meter that day, as well as other monitoring data, the remote service system can monitor the ultrasonic signals of each ultrasonic gas meter for anomalies from two dimensions: waveform and signal strength, and issue an anomaly alarm.

[0126] The remote business system can effectively screen gas meters with significantly different similarities from normal values ​​by uniformly performing correlation calculations on the waveforms of metering signals reported by ultrasonic gas meters within the same pipeline network (such as waveform similarity, signal-to-noise ratio, envelope curve, etc. in the aforementioned embodiment), thus avoiding interference to the signal waveform caused by external factors such as gas quality, temperature, and pressure.

[0127] After screening out the abnormal table, by judging whether the signal-to-noise ratio is abnormal, it can identify whether there may be abnormal situations such as external electromagnetic / gas disturbance interference, and issue an alarm to facilitate maintenance personnel to conduct on-site investigation.

[0128] After screening out the anomaly table, by judging whether the waveform envelope curve is abnormal, it is possible to identify whether there is damage to the metering module components, and an alarm is issued to facilitate on-site inspection by maintenance personnel.

[0129] The remote business system can also record historical waveform data of a single meter and perform relevant calculations on the current and historical data (such as waveform similarity, signal-to-noise ratio, and envelope curve in the aforementioned embodiment). By using historical waveform similarity, signal-to-noise ratio, and waveform envelope curve, it can promptly and effectively identify possible sudden metering module signal attenuation / failure, sudden external electromagnetic / gas disturbance interference, and other situations that may exist in the meter, and promptly issue alarms to facilitate on-site troubleshooting by maintenance personnel.

[0130] The remote business system can also obtain the gas composition information at the time of meter reporting by combining the gas gas composition information of each gas gate station at different time periods with the gas meter mounting address and reporting time. By combining the gas composition information, the current operating signal strength at the meter, and the temperature and pressure inside the meter, the standard condition signal strength of the metering signal can be calculated. This standard condition signal strength can then be used as a criterion for judging whether the gas meter signal strength has attenuated, avoiding misjudgments caused by relying solely on gain data.

[0131] The remote service system can determine the minimum threshold based on the current standard signal strength of the meter, and trigger an alarm if the signal falls below the threshold.

[0132] Based on the current standard signal strength and installation address of the meter, the remote business system can perform a horizontal comparison of all gas meters under the same gate station, screen for meters with abnormal signal strength attenuation, and issue timely alarms.

[0133] Based on the current standard condition signal strength and the historical standard condition signal strength of the meter, the remote business system can draw a signal strength attenuation curve for a single meter, screen for meters with abnormal signal strength attenuation based on the signal strength attenuation curve, and issue timely alarms.

[0134] In addition, the remote service system can record and mark time periods when meters may exhibit abnormalities. Gas companies can then adjust and correct the cumulative gas consumption during these marked abnormal periods, improving the accuracy of cumulative gas consumption and avoiding billing disputes with users.

[0135] This application embodiment combines an ultrasonic gas meter with a remote business system, using the ultrasonic metering signal waveform as a basis to judge signal quality. This effectively identifies abnormalities such as gas metering module malfunctions, external strong electromagnetic interference / gas turbulence interference, etc., and provides timely alarms, improving the accuracy of ultrasonic signal monitoring, thereby improving the accuracy of gas metering and reducing gas metering disputes.

[0136] Figure 7 This is a schematic diagram of the structure of a signal monitoring device provided in an embodiment of this application. Figure 7 As shown, the image processing device 700 includes a data acquisition module 701 and a signal anomaly monitoring module 702.

[0137] The data acquisition module 701 is used to acquire the signal monitoring data of the ultrasonic gas meter, which includes the ultrasonic signal waveform and / or ultrasonic signal intensity reported by the ultrasonic gas meter.

[0138] The signal anomaly monitoring module 702 is used to monitor the ultrasonic signal waveform and / or ultrasonic signal intensity for anomalies based on the signal monitoring data of the ultrasonic gas meter, and to issue an anomaly alarm.

[0139] In one optional implementation, when monitoring the ultrasonic signal waveform for anomalies based on the signal monitoring data of the ultrasonic gas meter and issuing an anomaly alarm, the signal anomaly monitoring module 702 is specifically used for:

[0140] Calculate the similarity between the ultrasonic signal waveform reported by each ultrasonic gas meter under the same gas pipeline network and the reference waveform; based on the similarity between the ultrasonic signal waveform reported by each ultrasonic gas meter and the reference waveform, select the first gas meter with abnormal similarity; issue the first alarm message, which indicates that the ultrasonic signal waveform of the first gas meter is abnormal.

[0141] In one optional implementation, when selecting the first gas meter with an abnormal similarity based on the similarity between the ultrasonic signal waveform reported by each ultrasonic gas meter and the reference waveform, the signal anomaly monitoring module 702 is specifically used for:

[0142] Ultrasonic gas meters with a similarity score less than the waveform similarity threshold are selected as key monitoring targets. The key monitoring targets that show abnormal ultrasonic signal waveforms in N consecutive monitoring tests are identified as the first gas meter with abnormal ultrasonic signal waveforms, where N is a positive integer. And / or, the similarity scores are sorted, the difference between any two adjacent similarity scores is calculated, and the first gas meter with abnormal similarity is selected based on the difference between any two adjacent similarity scores.

[0143] In one alternative implementation, the signal anomaly monitoring module 702 is further used for:

[0144] The ultrasound signal waveforms with a similarity greater than the waveform similarity threshold to the reference waveform are sorted, and the ultrasound signal waveform in the middle position of the sorting result is taken as the new reference waveform and the reference waveform is updated.

[0145] In one optional implementation, when monitoring the ultrasonic signal waveform for anomalies based on the signal monitoring data of the ultrasonic gas meter and issuing an anomaly alarm, the signal anomaly monitoring module 702 is specifically used for:

[0146] Based on the ultrasonic signal waveforms reported by ultrasonic gas meters located in the same gas pipeline network, calculate the signal-to-noise ratio (SNR) of each ultrasonic gas meter; based on the SNR of each ultrasonic gas meter, identify the second gas meter with an abnormal SNR; issue a second alarm message indicating that the SNR of the ultrasonic signal of the second gas meter is abnormal.

[0147] In one optional implementation, when monitoring the ultrasonic signal waveform for anomalies based on the signal monitoring data of the ultrasonic gas meter and issuing an anomaly alarm, the signal anomaly monitoring module 702 is specifically used for:

[0148] Based on the ultrasonic signal waveforms reported by ultrasonic gas meters located in the same gas pipeline network, calculate the envelope curve of each ultrasonic signal waveform; based on the envelope curves of each ultrasonic signal waveform, identify the third gas meter with an abnormal envelope curve shape; issue a third alarm message, indicating that the envelope curve shape of the ultrasonic signal waveform of the third gas meter is abnormal.

[0149] In one optional implementation, when monitoring the ultrasonic signal waveform for anomalies based on the signal monitoring data of the ultrasonic gas meter and issuing an anomaly alarm, the signal anomaly monitoring module 702 is specifically used for:

[0150] For any ultrasonic gas meter, acquire the historical waveforms reported by the ultrasonic gas meter within a historical time period; based on the ultrasonic signal waveforms reported by the ultrasonic gas meter and the historical waveforms, determine the quality change curve of the ultrasonic signal of the ultrasonic gas meter; based on the quality change curve, screen out ultrasonic gas meters with abnormal signal quality and issue corresponding alarm information.

[0151] In one optional implementation, when determining the quality change curve of the ultrasonic signal of the ultrasonic gas meter based on the ultrasonic signal waveform reported by the ultrasonic gas meter and historical waveforms, and filtering out ultrasonic gas meters with abnormal signal quality based on the quality change curve and issuing corresponding alarm information, the signal anomaly monitoring module 702 is specifically used for:

[0152] Calculate the similarity between the ultrasonic signal waveform reported by the ultrasonic gas meter and the historical waveform and the reference waveform, and determine the similarity change curve; if the ultrasonic signal waveform of the ultrasonic gas meter is determined to be abnormal according to the similarity change curve, issue a fourth alarm message, which indicates that the ultrasonic signal waveform of the ultrasonic gas meter is abnormal; and / or, calculate the signal-to-noise ratio (SNR) corresponding to the ultrasonic signal waveform reported by the ultrasonic gas meter and the historical waveform, and determine the SNR change curve; if the SNR change curve is determined to be abnormal according to the SNR, issue a fifth alarm message, which indicates that the SNR of the ultrasonic gas meter is abnormal.

[0153] In one optional implementation, the signal monitoring data further includes: the gas temperature and pressure inside the ultrasonic gas meter, the reference waveform and the corresponding gas gate station information, and the gas quality composition information of the gas gate station. When monitoring for abnormal ultrasonic signal intensity based on the signal monitoring data of the ultrasonic gas meter and issuing an abnormal alarm, the signal abnormality monitoring module 702 is specifically used for:

[0154] Based on the ultrasonic signal intensity, gas temperature and pressure reported by the ultrasonic gas meter, and the gas quality composition information of the corresponding gas gate station, the standard condition signal intensity of the ultrasonic gas meter is calculated; based on the ultrasonic signal intensity reported by the ultrasonic gas meters within the gas supply range of the same gas gate station, the sixth gas meter with abnormal ultrasonic signal intensity is selected; a sixth alarm message is issued, indicating that the ultrasonic signal intensity of the sixth gas meter is abnormal.

[0155] In one optional implementation, when monitoring the ultrasonic signal strength for anomalies based on the signal monitoring data of the ultrasonic gas meter and issuing an anomaly alarm, the signal anomaly monitoring module 702 is specifically used for:

[0156] For any ultrasonic gas meter, obtain the historical signal strength reported by the ultrasonic gas meter within a historical period; determine the signal attenuation curve of the ultrasonic gas meter based on the ultrasonic signal strength reported by the ultrasonic gas meter and the historical signal strength; based on the signal attenuation curve, filter out ultrasonic gas meters with abnormal signal attenuation and issue corresponding alarm information.

[0157] In one alternative implementation, when acquiring signal monitoring data from the ultrasonic gas meter, the data acquisition module 701 is further configured to:

[0158] It receives and stores the ultrasonic signal waveform, ultrasonic signal intensity, gas temperature and pressure inside the meter, which are reported periodically by the ultrasonic gas meter; it acquires and stores the standard signal intensity and original signal waveform of the ultrasonic gas meter at the time of manufacture, the meter address and the corresponding gas gate station information; and it receives the gas quality composition information of each gas gate station reported periodically by the gas gate station quality monitoring system.

[0159] The signal monitoring device provided in this embodiment can execute the method provided in the above method embodiment. Its implementation principle and technical effect are similar, and will not be described in detail here.

[0160] Figure 8 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Figure 8 As shown, the electronic device 800 includes a memory 801, a processor 802, and a transceiver 803. The memory 801 stores a computer program, and the processor 802 executes the computer program to implement the methods of any of the above embodiments. A communication link exists between the memory 801 and the processor 802. For example, the memory 801, processor 802, and transceiver 803 can communicate via a communication bus 804.

[0161] Optionally, the aforementioned processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. The general-purpose processor can be a microprocessor or any conventional processor. The steps in the method embodiments disclosed in this application can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor.

[0162] This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the methods in any of the above method embodiments.

[0163] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the methods in any of the above method embodiments.

[0164] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0165] The order of the embodiments described above is merely for illustrative purposes and does not represent the superiority or inferiority of the embodiments. Furthermore, some processes described in the above embodiments and accompanying drawings include multiple operations appearing in a specific order. However, it should be clearly understood that these operations may not be executed in the order they appear herein, or may be executed in parallel. The sequence numbers are merely used to distinguish different operations, and the sequence numbers themselves do not represent any execution order. Additionally, these processes may include more or fewer operations, and these operations may be executed sequentially or in parallel. It should be noted that the descriptions such as "first," "second," etc., in this document are used to distinguish different messages, devices, modules, etc., and do not represent a sequential order, nor do they limit "first" and "second" to different types. "Multiple" means two or more, unless otherwise explicitly specified.

[0166] Other embodiments of this application will readily conceive of by those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and embodiments are to be considered exemplary only, and the true scope and spirit of this application are indicated by the following claims. It should be understood that this application is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims. Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application and are not intended to limit it; although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to depart from the scope of the technical solutions of the embodiments of this application.

Claims

1. A signal monitoring method, characterized in that, include: Acquire signal monitoring data from the ultrasonic gas meter, wherein the signal monitoring data includes the ultrasonic signal waveform and / or ultrasonic signal intensity reported by the ultrasonic gas meter; Based on the signal monitoring data of the ultrasonic gas meter, abnormalities are monitored in the ultrasonic signal waveform and / or the ultrasonic signal intensity, and an abnormality alarm is issued.

2. The method according to claim 1, characterized in that, The step of monitoring the ultrasonic signal waveform for abnormalities based on the signal monitoring data of the ultrasonic gas meter and issuing an abnormality alarm includes: Calculate the similarity between the ultrasonic signal waveform reported by the ultrasonic gas meter located in the same gas pipeline network and the reference waveform; Based on the similarity between the ultrasonic signal waveform reported by each ultrasonic gas meter and the reference waveform, the first gas meter with abnormal similarity is selected. A first alarm message is issued, indicating that the ultrasonic signal waveform of the first gas meter is abnormal.

3. The method according to claim 2, characterized in that, The step of filtering out the first gas meter with abnormal similarity based on the similarity between the ultrasonic signal waveform reported by each of the ultrasonic gas meters and the reference waveform includes: Ultrasonic gas meters with a similarity less than the waveform similarity threshold are selected as key monitoring targets. The key monitoring targets that show abnormal ultrasonic signal waveforms for N consecutive times are identified as the first gas meter with abnormal ultrasonic signal waveforms, where N is a positive integer. And / or, The similarities are sorted, the difference between any two adjacent similarities is calculated, and the first gas meter with an abnormal similarity is selected based on the difference between any two adjacent similarities.

4. The method according to claim 3, characterized in that, Also includes: The ultrasound signal waveforms with a similarity greater than the waveform similarity threshold to the reference waveform are sorted, and the ultrasound signal waveform in the middle position of the sorting result is taken as the new reference waveform to update the reference waveform.

5. The method according to claim 1, characterized in that, The step of monitoring the ultrasonic signal waveform for abnormalities based on the signal monitoring data of the ultrasonic gas meter and issuing an abnormality alarm includes: Based on the ultrasonic signal waveforms reported by ultrasonic gas meters located in the same gas pipeline network, calculate the signal-to-noise ratio of each ultrasonic gas meter. Based on the signal-to-noise ratio of each ultrasonic gas meter, the second gas meter with an abnormal signal-to-noise ratio is selected. A second alarm message is issued, indicating that the signal-to-noise ratio of the ultrasonic signal of the second gas meter is abnormal.

6. The method according to claim 1, characterized in that, The step of monitoring the ultrasonic signal waveform for abnormalities based on the signal monitoring data of the ultrasonic gas meter and issuing an abnormality alarm includes: Based on the ultrasonic signal waveforms reported by ultrasonic gas meters located in the same gas pipeline network, calculate the envelope curves of each ultrasonic signal waveform. Based on the envelope curves of each ultrasonic signal waveform, the third gas meter with abnormal envelope curve morphology is selected. A third alarm message is issued, indicating that the envelope curve shape of the ultrasonic signal waveform of the third gas meter is abnormal.

7. The method according to claim 1, characterized in that, The step of monitoring the ultrasonic signal waveform for abnormalities and issuing an alarm based on the signal monitoring data from the ultrasonic gas meter includes: For any of the ultrasonic gas meters, obtain the historical waveforms reported by the ultrasonic gas meter within a historical time period; Based on the ultrasonic signal waveform reported by the ultrasonic gas meter and the historical waveform, determine the quality change curve of the ultrasonic signal of the ultrasonic gas meter; Based on the quality change curve, ultrasonic gas meters with abnormal signal quality are selected and corresponding alarm messages are issued.

8. The method according to claim 7, characterized in that, The process involves determining the ultrasonic signal quality variation curve of the ultrasonic gas meter based on the ultrasonic signal waveform reported by the ultrasonic gas meter and the historical waveform; filtering out ultrasonic gas meters with abnormal signal quality based on the quality variation curve; and issuing corresponding alarm information, including: Calculate the similarity between the ultrasonic signal waveform reported by the ultrasonic gas meter and the historical waveform and the reference waveform, and determine the change curve of the similarity; if the ultrasonic signal waveform of the ultrasonic gas meter is determined to be abnormal according to the change curve of the similarity, issue a fourth alarm message, the fourth alarm message indicating that the ultrasonic signal waveform of the ultrasonic gas meter is abnormal. And / or, Calculate the signal-to-noise ratio (SNR) corresponding to the ultrasonic signal waveform reported by the ultrasonic gas meter and the historical waveform, and determine the SNR variation curve; if the SNR variation curve indicates that the ultrasonic gas meter has an abnormal SNR, then issue a fifth alarm message, which indicates that the ultrasonic gas meter has an abnormal SNR.

9. The method according to claim 1, characterized in that, The signal monitoring data also includes: the gas temperature and pressure inside the ultrasonic gas meter, the reference waveform and the corresponding gas gate station information, as well as the gas quality composition information of the gas gate station. The step of monitoring the ultrasonic signal intensity for abnormalities based on the signal monitoring data of the ultrasonic gas meter and issuing an abnormal alarm includes: The standard condition signal strength of the ultrasonic gas meter is calculated based on the ultrasonic signal strength, gas temperature and pressure reported by the ultrasonic gas meter, and the gas quality composition information of the corresponding gas gate station. Based on the ultrasonic signal strength reported by ultrasonic gas meters within the same gas gate station's gas supply range, the sixth gas meter with abnormal ultrasonic signal strength is selected. A sixth alarm message is issued, indicating that the ultrasonic signal strength of the sixth gas meter is abnormal.

10. The method according to claim 1, characterized in that, The step of monitoring the ultrasonic signal intensity for abnormalities based on the signal monitoring data of the ultrasonic gas meter and issuing an abnormal alarm includes: For any of the ultrasonic gas meters, obtain the historical signal strength reported by the ultrasonic gas meter within a historical time period; The signal attenuation curve of the ultrasonic gas meter is determined based on the ultrasonic signal intensity reported by the ultrasonic gas meter and the historical signal intensity. Based on the signal attenuation curve, ultrasonic gas meters with abnormal signal attenuation are selected, and corresponding alarm messages are issued.

11. The method according to any one of claims 1-10, characterized in that, The acquisition of signal monitoring data from the ultrasonic gas meter includes: Receive and store the ultrasonic signal waveform, ultrasonic signal intensity, gas temperature and pressure inside the meter reported periodically by the ultrasonic gas meter; Acquire and store the standard signal strength and original signal waveform of the ultrasonic gas meter at the time of its manufacture, the meter mounting address and the corresponding gas gate station information; Receive gas quality composition information from the gas gate station's gas quality monitoring system, which is periodically reported by the system.

12. An electronic device, characterized in that, include: Memory, processor, and transceiver; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory to implement the method as described in any one of claims 1-11.

13. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of claims 1-11.

Images