CN113432805B - Wireless monitoring method applied to water supply pipeline leakage wireless monitoring device - Google Patents
Wireless monitoring method applied to water supply pipeline leakage wireless monitoring device Download PDFInfo
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Abstract
The invention provides a wireless monitoring method applied to a wireless leakage monitoring device of a water supply pipeline, which comprises a piezoelectric acceleration sensor, a power supply management module, a system control module, a signal conditioning module, a vibration signal acquisition module, a data storage module and a wireless data transmission module, wherein the piezoelectric acceleration sensor is fixed on the outer wall of the monitored water supply pipeline, the power supply management module supplies power for the system control module, the signal conditioning module, the vibration signal acquisition module, the data storage module and the wireless data transmission module, the piezoelectric acceleration sensor is connected with the signal conditioning module, the signal conditioning module is connected with the vibration signal acquisition module, and the system control module is respectively connected with the vibration signal acquisition module, the wireless data transmission module and the data storage module. The wireless monitoring method applied to the wireless monitoring device for the leakage of the water supply pipeline realizes online accurate detection of the leakage of the water supply pipeline and improves the leakage detection efficiency.
Description
Technical Field
The invention relates to the field of pipeline detection, in particular to a wireless monitoring method applied to a water supply pipeline leakage wireless monitoring device.
Background
The existing water supply pipeline leakage detection technology generally adopts a special equipment method, and specifically, signal parameter indexes such as sound, infrared spectrum, pressure and the like are collected by professional leakage detection personnel by using pipeline leakage detection equipment. Such as the patent names: a pressure pipeline leakage detection listening device (application number: 202020809839.0) discloses that a vehicle-mounted filter leak detector is used for picking up pipeline leakage sound along a water supply pipeline, and the pipeline leakage is detected through the leak detector and manual listening.
Disclosure of Invention
In order to overcome the defects of the prior art, one of the purposes of the invention is to provide a wireless monitoring device for detecting the leakage of a water supply pipeline, which can solve the problems that the existing method for detecting the leakage of the pipeline through a leak detector and artificial listening has complex operation and depends on artificial experience, and the early tiny leakage of the water supply pipeline cannot be found in time.
The invention also aims to provide a wireless monitoring method for water supply pipeline leakage, which can solve the problems that the existing method for detecting pipeline leakage through a leak detector and artificial listening has complex operation and depends on artificial experience, and early tiny leakage of a water supply pipeline cannot be found in time.
One of the purposes of the invention is realized by adopting the following technical scheme:
a wireless monitoring device for water supply pipeline leakage comprises a piezoelectric acceleration sensor, a power supply management module, a system control module, a signal conditioning module, a vibration signal acquisition module, a data storage module and a data wireless transmission module, wherein the piezoelectric acceleration sensor is fixed on the outer wall of a monitored water supply pipeline;
the piezoelectric acceleration sensor converts an acoustic emission signal sent by the outer wall of a water supply pipeline into a current signal, the piezoelectric acceleration sensor transmits the current signal to the signal conditioning module, the signal conditioning module amplifies the current signal and converts the current signal into an analog voltage signal, the signal conditioning module sends the analog voltage signal to the vibration signal acquisition module, the vibration signal acquisition module converts the analog voltage signal into a digital signal, the vibration signal acquisition module takes the digital signal as sample signal data corresponding to the monitored water supply pipeline, the system control module operates a preset pipeline leakage detection algorithm to calculate and process the sample signal data to obtain a leakage detection result, and stores the leakage detection result and the sample signal data in the data storage module, and when the leakage detection result indicates that leakage exists, the system control module sends alarm information to a monitoring platform through the data wireless transmission module.
And the system further comprises a human-computer interaction module, wherein the human-computer interaction module is connected with the system control module and is used for setting sampling parameters and inquiring a leakage detection result.
Further, the system control module is a digital signal processor of model TMS320F 28335.
Furthermore, the power supply management module also comprises a rechargeable lithium battery used for providing electric energy for the power supply management module, and the rechargeable lithium battery is electrically connected with the power supply management module.
The second purpose of the invention is realized by adopting the following technical scheme:
a wireless monitoring method for water supply pipeline leakage is applied to a wireless water supply pipeline leakage detection device in the application, and comprises the following steps:
acquiring sample signal data, and acquiring sample signal data which is input by a vibration signal acquisition module and corresponds to a monitored water supply pipeline, wherein the sample signal data is obtained by sequentially carrying out amplification processing and voltage conversion processing on a current signal acquired by a piezoelectric acceleration sensor through a signal conditioning module and carrying out digital signal conversion processing on the vibration signal acquisition module;
calculating the mean value of the permutation entropies, dividing the sample signal data into a plurality of frames of sub-sample signal data, respectively calculating the permutation entropies of each frame of sub-sample signal data corresponding to the autocorrelation function, and calculating the mean value of the permutation entropies of the sample signal data corresponding to the autocorrelation function according to the permutation entropies of each frame of sub-sample signal data corresponding to the autocorrelation function;
calculating power spectral density, and calculating the power spectral density of the sample signal data according to an average periodogram method to obtain the bandwidth and the central frequency of a main frequency component in the sample signal data;
and detecting leakage, namely taking the mean value of the permutation entropies, the bandwidth and the central frequency as corresponding characteristic parameters of the sample signal data, and inputting the characteristic parameters serving as characteristic vectors into a preset SVM model for recognition to obtain a leakage detection result.
Further, when the leakage detection result is that leakage exists, alarm information is sent to the monitoring platform through the data wireless transmission module.
Further, the obtaining of the sample signal data further includes obtaining current sampling time corresponding to the sample signal data, further including data dynamic storage, matching the characteristic parameters corresponding to the sample signal data with packet tags of different data packets in the data storage module, if a corresponding packet tag is matched, using the matched corresponding packet tag as a target packet tag, combining the characteristic parameters corresponding to the sample signal data, the leak detection result and the current sampling time into a current sample data group to be stored in a data packet corresponding to the target packet tag, if a corresponding packet tag is not matched, creating a new data packet, using the characteristic parameter and the leakage detection result corresponding to the sample signal data as a packet label of the new data packet, and combining the characteristic parameter and the leakage detection result corresponding to the sample signal data and the current sampling time into a current sample data group to be stored in the new data packet.
Further, before combining the characteristic parameter, the leak detection result and the current sampling time corresponding to the sample signal data into a current sample data group to be stored in the data packet corresponding to the target packet tag, a group inner space is judged, whether the group inner space in the data packet corresponding to the target packet tag is full is judged, if yes, the historical sample data group with the earliest sample sampling time in the data packet corresponding to the target packet tag is deleted, and if not, the characteristic parameter, the leak detection result and the current sampling time corresponding to the sample signal data are combined into a current sample data group to be stored in the data packet corresponding to the target packet tag.
Further, before creating the new data packet, whether the number of the data packets reaches a threshold value is judged, if yes, the new data packet is created after the data packet containing the most historical sample data groups or the data packet with the earliest average sample sampling time is deleted, and if not, the new data packet is directly created.
Further, the acquiring of the sample signal data further comprises acquiring time domain data corresponding to the sample signal data, when the corresponding grouping label is matched, after combining the characteristic parameter, the leakage detection result and the current sampling time corresponding to the sample signal data into a current sample data group and storing the current sample data group in a data grouping corresponding to a target grouping label, deleting the time domain data corresponding to the sample signal data, and reporting the characteristic parameter, the leakage detection result and the current sampling time corresponding to the sample signal data to the monitoring platform through the data wireless transmission module;
when the corresponding grouping label is not matched, a new data grouping is created, the characteristic parameter and the leakage detection result corresponding to the sample signal data are used as the grouping label of the new data grouping, the characteristic parameter, the leakage detection result and the current sampling time corresponding to the sample signal data are combined into a current sample data group, the current sample data group is stored in the new data grouping, the characteristic parameter, the leakage detection result, the current sampling time combination and the time domain data corresponding to the sample signal data are reported to a monitoring platform through a data wireless transmission module, and the time domain data corresponding to the sample signal data in the data storage module are deleted after the uploading is successful.
Compared with the prior art, the invention has the beneficial effects that: according to the wireless detection method for the leakage of the water supply pipeline, the current signals collected by the piezoelectric acceleration sensor are processed by the signal conditioning module and the vibration signal collecting module to obtain digital signals, the digital signals serve as sample signal data, characteristic parameters corresponding to the sample signal data are calculated, and the characteristic parameters serve as characteristic vectors and are led into the preset SVM model for recognition, so that the leakage of the water supply pipeline is accurately detected on line, and the leakage detection efficiency is improved.
The foregoing description is only an overview of the technical solutions of the present invention, and in order to make the technical solutions of the present invention more clearly understood and to implement them in accordance with the contents of the description, the following detailed description is given with reference to the preferred embodiments of the present invention and the accompanying drawings. The detailed description of the present invention is given in detail by the following examples and the accompanying drawings.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the invention without limiting the invention. In the drawings:
FIG. 1 is a schematic block diagram of a water supply pipeline leakage wireless monitoring device according to the present invention;
FIG. 2 is a circuit diagram of a charge amplifying circuit in a signal conditioning module of a wireless monitoring device for water supply pipeline leakage according to the present invention;
FIG. 3 is a circuit diagram of a dual T power frequency trap in a signal conditioning module of the wireless monitoring device for water supply pipeline leakage according to the present invention;
FIG. 4 is a circuit diagram of an anti-aliasing low-pass filter in a signal conditioning module of a wireless water supply pipeline leakage monitoring device according to the invention;
FIG. 5 is a flow chart of a method for wirelessly monitoring leakage of a water supply pipeline according to the present invention.
Detailed Description
The present invention will be further described with reference to the accompanying drawings and the detailed description, and it should be noted that any combination of the embodiments or technical features described below can be used to form a new embodiment without conflict.
As shown in FIG. 1, a wireless monitoring device that water supply pipeline leaked in this application, including piezoelectricity acceleration sensor, power management module, system control module, signal conditioning module, vibration signal collection module, data storage module, data wireless transmission module and human-computer interaction module, piezoelectricity acceleration sensor fixes and is being monitored water supply pipeline outer wall, power management module does system control module signal conditioning module vibration signal collection module data storage module data wireless transmission module and the power supply of human-computer interaction module, piezoelectricity acceleration sensor with signal conditioning module connects, signal conditioning module with vibration signal collection module connects, system control module respectively vibration signal collection module data wireless transmission module, The data storage module is connected with the human-computer interaction module.
In this embodiment, the rechargeable lithium battery is electrically connected to the power management module and is used for providing electric energy to the power management module. The power management module comprises a voltage detection circuit and a system working voltage conversion circuit, the voltage detection circuit monitors the voltage of the whole wireless monitoring device except the piezoelectric acceleration sensor, the detection result is reported as system state data, and the system working voltage conversion circuit outputs 1.8V, 2.5V and 3.3V of the working voltage required by the system by using a two-way output LDO chip. The system control module adopts a digital signal processor with the model number of TMS320F28335, is used for scheduling control and data transmission of functional modules such as data acquisition, storage, communication and the like, and operates a preset pipeline leakage detection algorithm to perform leakage detection. The signal conditioning module comprises a charge amplifying circuit, an anti-aliasing low-pass filter and a double-T power frequency trap, and is specifically described as follows: the charge amplifying circuit is composed of an operational amplifier circuit including an operational amplifier OP1 and an operational amplifier OP2, and one of the circuits is taken as an example, as shown in fig. 2, the circuit is an operational amplifier circuit including an operational amplifier OP1, two input ends of the operational amplifier OP1 are respectively connected in series with resistors R1 and R2 and connected with two charge signal output ends of the piezoelectric acceleration sensor, an output end of the operational amplifier OP1 is connected with an input end of the double-T trap, a feedback capacitor C1 is used for storing charges input by the piezoelectric acceleration sensor and converting the charges into voltages and amplifying the voltages by ten times, resistors R1 and R2 are used for inputting current limit and limiting lower limit frequency of frequency response, a feedback resistor R3 is used for limiting upper limit frequency of frequency response, and a non-inverting input end of the charge amplifying circuit is simultaneously connected with 2.5V to raise the output to a positive voltage; the double-T power frequency trap is used for filtering a 50Hz power frequency interference signal of a space electromagnetic field coupling system and comprises a basic double-T-shaped network and an in-phase amplifying circuit, as shown in figure 3, the input of the double-T power frequency trap is connected with the output of a charge amplifying circuit, the output of the double-T power frequency trap is connected with the input of an anti-aliasing low-pass filter, a Q value non-adjustable double-T-shaped trap circuit consisting of a resistor R6, a resistor R7, a resistor R8, a capacitor C2, a capacitor C3 and a capacitor C4 is used for filtering a 50Hz power frequency signal, the in-phase amplifying circuit consisting of an operational amplifier OP3 is used for positive feedback of the double-T network, the Q value of the filter is adjustable, and the amplification coefficient of the filter is determined by the ratio of the resistor R10 and the R9; the anti-aliasing low-pass filter is used for filtering high-frequency noise in a vibration signal, a circuit diagram is shown in fig. 4, the input end of the anti-aliasing low-pass filter is connected with the output end of the double-T power frequency trap, the output end of the anti-aliasing low-pass filter is connected with the input end of the vibration signal acquisition module, a second-order RC low-pass filter circuit formed by resistors R11 and R12, capacitors C5 and C6 is used for filtering the high-frequency noise, an in-phase amplification circuit formed by an operational amplifier OP4 is used for providing a feedback signal, the gain and impedance conversion of the filter are improved, the filtered signal is transmitted to an ADC without distortion, the gain of the filter in the circuit is 1, and the cut-off frequency is 5 KHz.
The wireless data transmission module consists of an NB-IoT communication module and a module power supply control circuit, wherein the NB-IoT communication module is used for reporting data to be sent out in a system control module to a monitoring platform, reporting a characteristic parameter calculation result, a leakage detection result and a system state to the monitoring platform according to a preset period, and performing supplementary report and historical data query; the module power supply control circuit is used for turning off the module power supply in the non-data reporting time, so that the overall power consumption of the system is reduced. The man-machine interaction module in the embodiment is composed of a liquid crystal screen, three reed switches are used as non-contact keys for control and setting, parameters such as sampling period, retransmission and reissue times are set, and the man-machine interaction module can also be used for inquiring information such as system state data, historical storage data and system parameters.
When leakage detection is carried out on a monitored water supply pipeline, the piezoelectric acceleration sensor converts an acoustic emission signal sent by the outer wall of the water supply pipeline into a current signal, the piezoelectric acceleration sensor transmits the current signal to the signal conditioning module, the signal conditioning module amplifies and converts the current signal into an analog voltage signal, the signal conditioning module sends the analog voltage signal to the vibration signal acquisition module, the vibration signal acquisition module converts the analog voltage signal into a digital signal, the vibration signal acquisition module takes the digital signal as sample signal data corresponding to the monitored water supply pipeline, the system control module operates a preset pipeline leakage detection algorithm to carry out operation processing on the sample signal data to obtain a leakage detection result, and stores the leakage detection result and the sample signal data in the data storage module, when the leakage detection result indicates that leakage exists, the system control module sends alarm information to a monitoring platform through the data wireless transmission module; in this embodiment, in order to reduce the storage load of the entire apparatus, a dynamic storage algorithm is used for storing the sample signal data, specifically:
in the embodiment, historical sample signal data stored in a data storage module is divided into a plurality of groups to obtain a plurality of data groups, each group sets rated storage capacity according to a preset capacity rule, characteristic parameters and leakage detection results of the sample signal data are used as grouping labels of each data group, after the periodic sampling of the pipe wall vibration signal of the water supply pipeline is completed once and the leakage result is calculated, the characteristic parameters corresponding to the sample signal data are matched with the grouping labels of different data groups in the data storage module, if the corresponding grouping labels are matched, the matched corresponding grouping labels are used as target grouping labels, the characteristic parameters, the leakage detection results and the current sampling time corresponding to the sample signal data are combined into a current sample data group to be stored in the data group corresponding to the target grouping labels, and if the corresponding grouping labels are not matched, creating a new data packet, using the characteristic parameter and the leakage detection result corresponding to the sample signal data as a packet label of the new data packet, and combining the characteristic parameter and the leakage detection result corresponding to the sample signal data and the current sampling time into a current sample data group to be stored in the new data packet. Before the characteristic parameters, the leakage detection results and the current sampling time corresponding to the sample signal data are combined into a current sample data group to be stored in the data grouping corresponding to the target grouping label, a group inner space is judged, whether the group inner space in the data grouping corresponding to the target grouping label is full is judged, if yes, the historical sample data group with the earliest sample sampling time in the data grouping corresponding to the target grouping label is deleted, and if not, the characteristic parameters, the leakage detection results and the current sampling time corresponding to the sample signal data are combined into the current sample data group to be stored in the data grouping corresponding to the target grouping label. And before the new data packet is created, judging whether the number of the data packets reaches a threshold value, if so, deleting the data packet containing the most historical sample data groups or the data packet with the earliest average sample sampling time, and then creating the new data packet, and if not, directly creating the new data packet.
The method comprises the steps of obtaining sample signal data, and also comprises the steps of obtaining time domain data corresponding to the sample signal data, in the dynamic data storage process, combining characteristic parameters corresponding to the sample signal data, a leakage detection result and current sampling time into a current sample data set to be stored in a data packet corresponding to a target packet tag when a corresponding packet tag is matched, deleting the time domain data corresponding to the sample signal data, and reporting the characteristic parameters corresponding to the sample signal data, the leakage detection result and the current sampling time to a monitoring platform through a data wireless transmission module;
when the corresponding grouping label is not matched, a new data grouping is created, the characteristic parameter and the leakage detection result corresponding to the sample signal data are used as the grouping label of the new data grouping, the characteristic parameter, the leakage detection result and the current sampling time corresponding to the sample signal data are combined into a current sample data group, the current sample data group is stored in the new data grouping, the characteristic parameter, the leakage detection result, the current sampling time combination and the time domain data corresponding to the sample signal data are reported to a monitoring platform through a data wireless transmission module, and the time domain data corresponding to the sample signal data in the data storage module are deleted after the uploading is successful. The dynamic data storage mechanism in the embodiment can effectively reduce the reporting of abnormal sampling data, reduce the total power consumption of the device, and reduce the communication and operation loads of the server.
As shown in fig. 5, the present application further provides a wireless monitoring method for water supply pipeline leakage, which specifically includes the following steps:
and acquiring sample signal data, wherein the system control module acquires the sample signal data which is input by the vibration signal acquisition module and corresponds to the monitored water supply pipeline. The sample signal data is a digital signal, and the specific generation process is as follows: the piezoelectric acceleration sensor converts the acoustic emission signal that water supply pipe outer wall sent into current signal, and piezoelectric acceleration sensor conveys current signal to signal conditioning module, signal conditioning module enlargies current signal and converts analog voltage signal into, signal conditioning module with analog voltage signal send to vibration signal acquisition module, vibration signal acquisition module converts analog voltage signal into digital signal, vibration signal acquisition module will digital signal regard as and monitor the sample signal data that water supply pipe corresponds and send to system control module. In this embodiment, the method further includes obtaining a current sampling time corresponding to the sample signal data and time domain data.
Calculating the mean value of the permutation entropies, dividing the sample signal data into a plurality of frames of sub-sample signal data, respectively calculating the permutation entropies of each frame of sub-sample signal data corresponding to the autocorrelation function, and calculating the mean value of the permutation entropies of the sample signal data corresponding to the autocorrelation function according to the permutation entropies of each frame of sub-sample signal data corresponding to the autocorrelation function.
And calculating the power spectral density, and calculating the power spectral density of the sample signal data according to an average periodogram method to obtain the bandwidth and the central frequency of the main frequency component in the sample signal data.
And detecting leakage, namely taking the mean value of the permutation entropies, the bandwidth and the central frequency as corresponding characteristic parameters of the sample signal data, and inputting the characteristic parameters serving as characteristic vectors into a preset SVM model for recognition to obtain a leakage detection result. The preset SVM model is obtained after historical sample data training of leakage of a plurality of monitoring pipelines, corresponding sample data training can be carried out according to different monitored water supply pipelines, and different leakage detection models suitable for different monitored pipelines are obtained. And when the leakage detection result is that leakage exists, alarm information is sent to the monitoring platform through the data wireless transmission module.
And dynamically storing the data, namely matching the characteristic parameters corresponding to the sample signal data with packet tags of different data packets in a data storage module, taking the matched corresponding packet tag as a target packet tag if the corresponding packet tag is matched, further judging a group inner space, namely judging whether the group inner space in the data packet corresponding to the target packet tag is full, deleting the historical sample data group with the earliest sample sampling time in the data packet corresponding to the target packet tag if the group inner space in the data packet corresponding to the target packet tag is full, and combining the characteristic parameters corresponding to the sample signal data, the leakage detection result and the current sampling time into a current sample data group to be stored in the data packet corresponding to the target packet tag if the group inner space in the data packet corresponding to the target packet tag is not full. If the corresponding grouping label is not matched, judging whether the number of the data groups reaches a threshold value, if so, deleting the data group containing the most historical sample data groups or the data group with the earliest average sample sampling time, then creating a new data group, if not, directly creating the new data group, after creating the new data group, taking the characteristic parameters and the leakage detection result corresponding to the sample signal data as the grouping label of the new data group, and combining the characteristic parameters, the leakage detection result and the current sampling time corresponding to the sample signal data into a current sample data group to be stored in the new data group. In the above step, when the corresponding grouping tag is matched, after the characteristic parameter, the leakage detection result and the current sampling time corresponding to the sample signal data are combined into a current sample data group and stored in the data grouping corresponding to the target grouping tag, the time domain data corresponding to the sample signal data are deleted, and the characteristic parameter, the leakage detection result and the current sampling time corresponding to the sample signal data are reported to the monitoring platform through the data wireless transmission module;
when the corresponding grouping label is not matched, a new data grouping is created, the characteristic parameter and the leakage detection result corresponding to the sample signal data are used as the grouping label of the new data grouping, the characteristic parameter, the leakage detection result and the current sampling time corresponding to the sample signal data are combined into a current sample data group, the current sample data group is stored in the new data grouping, the characteristic parameter, the leakage detection result, the current sampling time combination and the time domain data corresponding to the sample signal data are reported to a monitoring platform through a data wireless transmission module, and the time domain data corresponding to the sample signal data in the data storage module are deleted after the uploading is successful.
According to the wireless detection method for the leakage of the water supply pipeline, a current signal acquired by a piezoelectric acceleration sensor is processed by a signal conditioning module and a vibration signal acquisition module to obtain a digital signal, the digital signal is used as sample signal data, characteristic parameters corresponding to the sample signal data are calculated, and the characteristic parameters are led into a preset SVM model as characteristic vectors to be identified, so that the leakage of the water supply pipeline is accurately detected on line, the leakage detection efficiency is improved, dynamic grouping storage is performed locally, repeated data storage is reduced, under the condition that long-term monitoring data are stored, the data transmission quantity during periodic reporting and historical data query is reduced, the storage space utilization rate and the data transmission stability are improved, and the long-term online monitoring of the leakage of the water supply pipeline is realized; the method can collect corresponding simulated leakage sample data to perform online model training aiming at different monitored water supply pipelines and site environments, so as to obtain different leakage detection algorithm models, thereby improving the universal applicability of different water supply pipelines and different monitoring environments.
The foregoing is merely a preferred embodiment of the invention and is not intended to limit the invention in any manner; those skilled in the art can readily practice the invention as shown and described in the drawings and detailed description herein; however, those skilled in the art should appreciate that they can readily use the disclosed conception and specific embodiments as a basis for designing or modifying other structures for carrying out the same purposes of the present invention without departing from the scope of the invention as defined by the appended claims; meanwhile, any equivalent changes, modifications and evolutions made to the above embodiments according to the substantial technology of the present invention are still within the protection scope of the technical solution of the present invention.
Claims (9)
1. A wireless monitoring method applied to a wireless monitoring device for water supply pipeline leakage comprises a piezoelectric acceleration sensor, a power supply management module, a system control module, a signal conditioning module, a vibration signal acquisition module, a data storage module and a wireless data transmission module, the piezoelectric acceleration sensor is fixed on the outer wall of the monitored water supply pipeline, the power management module supplies power to the system control module, the signal conditioning module, the vibration signal acquisition module, the data storage module and the data wireless transmission module, the piezoelectric acceleration sensor is connected with the signal conditioning module, the signal conditioning module is connected with the vibration signal acquisition module, the system control module is respectively connected with the vibration signal acquisition module, the data wireless transmission module and the data storage module; the piezoelectric acceleration sensor converts an acoustic emission signal sent by the outer wall of a water supply pipeline into a current signal, the piezoelectric acceleration sensor transmits the current signal to the signal conditioning module, the signal conditioning module amplifies the current signal and converts the current signal into an analog voltage signal, the signal conditioning module sends the analog voltage signal to the vibration signal acquisition module, the vibration signal acquisition module converts the analog voltage signal into a digital signal, the vibration signal acquisition module takes the digital signal as sample signal data corresponding to the monitored water supply pipeline, the system control module operates a preset pipeline leakage detection algorithm to calculate and process the sample signal data to obtain a leakage detection result, and stores the leakage detection result and the sample signal data in the data storage module, when the leakage detection result indicates that leakage exists, the system control module sends alarm information to a monitoring platform through the data wireless transmission module; the method is characterized in that: the wireless monitoring method comprises the following steps:
acquiring sample signal data, and acquiring sample signal data which is input by a vibration signal acquisition module and corresponds to a monitored water supply pipeline, wherein the sample signal data is obtained by sequentially carrying out amplification processing and voltage conversion processing on a current signal acquired by a piezoelectric acceleration sensor through a signal conditioning module and carrying out digital signal conversion processing on the vibration signal acquisition module;
calculating the mean value of the permutation entropies, dividing the sample signal data into a plurality of frames of sub-sample signal data, respectively calculating the permutation entropies of each frame of sub-sample signal data corresponding to the autocorrelation function, and calculating the mean value of the permutation entropies of the sample signal data corresponding to the autocorrelation function according to the permutation entropies of each frame of sub-sample signal data corresponding to the autocorrelation function;
calculating power spectral density, and calculating the power spectral density of the sample signal data according to an average periodogram method to obtain the bandwidth and the central frequency of a main frequency component in the sample signal data;
and detecting leakage, namely taking the mean value of the permutation entropies, the bandwidth and the central frequency as corresponding characteristic parameters of the sample signal data, and inputting the characteristic parameters serving as characteristic vectors into a preset SVM model for recognition to obtain a leakage detection result.
2. The wireless monitoring method for the water supply pipeline leakage wireless monitoring device according to claim 1, wherein the wireless monitoring method comprises the following steps: and when the leakage detection result indicates that leakage exists, sending alarm information to a monitoring platform through the data wireless transmission module.
3. The wireless monitoring method for the water supply pipeline leakage wireless monitoring device according to claim 1, wherein the wireless monitoring method comprises the following steps: the method comprises the steps of obtaining sample signal data, obtaining current sampling time corresponding to the sample signal data, dynamically storing the sample signal data, matching characteristic parameters corresponding to the sample signal data with grouping labels of different data groups in a data storage module, if the corresponding grouping labels are matched, using the matched corresponding grouping labels as target grouping labels, combining the characteristic parameters corresponding to the sample signal data, a leakage detection result and the current sampling time into a current sample data group to be stored in a data group corresponding to the target grouping labels, and if the corresponding grouping labels are not matched, creating a new data packet, using the characteristic parameter and the leakage detection result corresponding to the sample signal data as a packet label of the new data packet, and combining the characteristic parameter and the leakage detection result corresponding to the sample signal data and the current sampling time into a current sample data group to be stored in the new data packet.
4. A wireless monitoring method for a water supply pipeline leakage wireless monitoring device according to claim 3, wherein: before the characteristic parameters, the leakage detection results and the current sampling time corresponding to the sample signal data are combined into a current sample data group to be stored in the data grouping corresponding to the target grouping label, a group inner space is judged, whether the group inner space in the data grouping corresponding to the target grouping label is full is judged, if yes, the historical sample data group with the earliest sample sampling time in the data grouping corresponding to the target grouping label is deleted, and if not, the characteristic parameters, the leakage detection results and the current sampling time corresponding to the sample signal data are combined into the current sample data group to be stored in the data grouping corresponding to the target grouping label.
5. The wireless monitoring method for the water supply pipeline leakage wireless monitoring device according to claim 4, wherein the wireless monitoring method comprises the following steps: and before the new data packet is created, judging whether the number of the data packets reaches a threshold value, if so, deleting the data packet containing the most historical sample data groups or the data packet with the earliest average sample sampling time, and then creating the new data packet, and if not, directly creating the new data packet.
6. A wireless monitoring method for a water supply pipeline leakage wireless monitoring device according to claim 4, wherein: the method comprises the steps of obtaining sample signal data, and also comprises the steps of obtaining time domain data corresponding to the sample signal data, when the corresponding grouping labels are matched, combining characteristic parameters corresponding to the sample signal data, a leakage detection result and current sampling time into a current sample data group and storing the current sample data group in a data grouping corresponding to a target grouping label, deleting the time domain data corresponding to the sample signal data, and reporting the characteristic parameters corresponding to the sample signal data, the leakage detection result and the current sampling time to a monitoring platform through a data wireless transmission module;
when the corresponding grouping label is not matched, a new data grouping is created, the characteristic parameter and the leakage detection result corresponding to the sample signal data are used as the grouping label of the new data grouping, the characteristic parameter, the leakage detection result and the current sampling time corresponding to the sample signal data are combined into a current sample data group, the current sample data group is stored in the new data grouping, the characteristic parameter, the leakage detection result, the current sampling time combination and the time domain data corresponding to the sample signal data are reported to a monitoring platform through a data wireless transmission module, and the time domain data corresponding to the sample signal data in the data storage module are deleted after the uploading is successful.
7. The wireless monitoring method for the water supply pipeline leakage wireless monitoring device according to claim 1, wherein the wireless monitoring method comprises the following steps: the system is characterized by further comprising a human-computer interaction module, wherein the human-computer interaction module is connected with the system control module and is used for setting sampling parameters and inquiring leakage detection results.
8. The wireless monitoring method for the water supply pipeline leakage wireless monitoring device according to claim 1, wherein the wireless monitoring method comprises the following steps: the system control module is a digital signal processor of model TMS320F 28335.
9. The wireless monitoring method for the water supply pipeline leakage wireless monitoring device according to claim 1, wherein the wireless monitoring method comprises the following steps: the power supply management module is electrically connected with the rechargeable lithium battery.
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