Concrete pumping state monitoring device and method based on sound-sensitive sensor

Abstract

The invention provides a concrete pumping state monitoring device and method based on a sound-sensitive sensor. The concrete pumping state monitoring device and method are used for solving the technical problem that concrete is blocked in the concrete pumping process of existing building construction. The monitoring device comprises a plurality of sound-sensitive sensors, a data acquisition device and a remote control platform, the sound-sensitive sensors are uniformly distributed at a plurality of key positions of the pump pipe, the sound-sensitive sensors are connected with the data acquisition device, and the data acquisition device is connected with the remote control platform. The invention further discloses a concrete pumping state monitoring method based on the sound-sensitive sensor. A plurality of data acquisition terminals are adopted to monitor the whole pump pipe, the pumping state of concrete is recognized, blockage is output according to characteristics, and blockage position information is output. Real-time monitoring and fault diagnosis can be carried out on the concrete pump pipe in the concrete pumping process, and safety and high efficiency of the pump pipe in the using process are guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of concrete pumping, and in particular to a concrete pumping state monitoring device and method based on an acoustic sensor. Background Art

[0002] With the development of the construction industry and the widespread application of concrete pumping technology, the safety of pump pipes and whether they become clogged during concrete pumping have gradually become important issues in construction site management. Concrete pumping status monitoring is a crucial step in ensuring construction quality and efficiency in construction projects. During the concrete pumping process, the pump pipes may become clogged. Traditional concrete pump pipe monitoring methods rely primarily on manual inspection and routine maintenance, making real-time monitoring and accurate diagnosis difficult. These methods suffer from low efficiency, slow response, and the inability to locate faults in real time. Therefore, there is an urgent need for a technology that can automatically detect concrete pump pipes and provide efficient, real-time monitoring.

[0003] Existing sensor technology for concrete pumping status monitoring typically uses pressure sensors, flow sensors, and vibration sensors to monitor pressure, flow rate, and vibration in real time during the pumping process. These sensors provide precise data to help determine whether pumping is normal and prevent blockages, wear, and other failures, thereby improving construction efficiency and safety. However, sensors are susceptible to interference in complex construction environments, which can lead to data drift or errors. Therefore, the accuracy and stability of sensor data still need to be further improved, especially in harsh construction environments.

[0004] The application of Internet of Things (IoT) technology in concrete pumping monitoring is revolutionizing construction projects. By combining sensors, data communications, and cloud computing, it enables real-time monitoring, data analysis, and intelligent management of the pumping process. This not only improves construction efficiency and safety but also provides strong support for the digitalization and intelligent management of construction projects. In the future, as technology continues to develop, the IoT will play an even greater role in pumping monitoring, propelling the construction industry to new heights.

[0005] The utility model patent with application number 202021083069.2 discloses a device for monitoring the state of concrete in a mixer truck based on sound recognition, including a processor, a microphone, a preprocessing module and a memory. The microphone is fixedly installed in the tank of the mixer truck, and the microphone is connected to the processor through the preprocessing module, and the processor is connected to the memory. The above utility model uses the original sound signal of the concrete state in the mixer truck collected by the microphone to quickly judge the concrete state through sound recognition. There is no need for the operator to conduct real-time test monitoring of the concrete state, thereby realizing real-time judgment of the concrete state in the mixer truck, improving the quality of the concrete mixture, ensuring pumping construction, reducing engineering quality risks, and improving production efficiency. However, the above patent only involves the monitoring of the concrete state in one mixer truck, and cannot monitor the pumping state of multiple pump trucks at the same time, and cannot locate the pumping position of the fault in real time. The above device is applied to the concrete pumping process of construction construction, rather than concrete transport pump trucks. Summary of the Invention

[0006] To address the problem of concrete blockage during existing concrete pumping processes in construction, this paper proposes a concrete pumping status monitoring device and method based on acoustic sensors. This device enables real-time monitoring and fault diagnosis of concrete pump pipes during concrete pumping, ensuring the safety and efficiency of the pump pipes during use. The present invention utilizes multiple data acquisition terminals to monitor the entire pump pipe, identifying the concrete pumping status and outputting blockage information based on the characteristics, along with the location of the blockage.

[0007] In order to achieve the above-mentioned purpose, the technical solution of the present invention is implemented as follows: a concrete pumping status monitoring device based on acoustic sensors includes several acoustic sensors, data acquisition equipment, and a remote control platform. The acoustic sensors are evenly distributed at multiple key positions of the pump pipe, the acoustic sensors are connected to the data acquisition equipment, and the data acquisition equipment is connected to the remote control platform.

[0008] The remote control platform includes an MQTT server, a local terminal, a cloud server and a mobile terminal. The data acquisition device is connected to the MQTT server, the MQTT server is connected to the local terminal, the local terminal is connected to the cloud server, and the cloud server is connected to the mobile terminal.

[0009] The data acquisition device has a wireless transmission function. The data acquisition device uploads the collected data to the MQTT server in real time through the wireless network, and the MQTT server sends the collected data to the local terminal.

[0010] The MQTT server is a data transfer terminal based on the client-server message publish / subscribe transmission protocol. The MQTT server continuously sends collected data to the local terminal. The collected data includes the device number + sound intensity voltage value, and the sending frequency is 10 pieces / second; the local terminal stores the data collected by all data acquisition devices, and filters, extracts features and compares them according to the device number bound to the data acquisition device to obtain data calculation results.

[0011] The cloud server is the interactive transit between the mobile terminal and the local terminal, responsible for sending group information and usage information to the local terminal, and sending the data calculation results obtained by the local terminal to the mobile terminal; the mobile terminal binds the device number of the currently used data acquisition device through the app, marks the usage location and sends it to the local terminal, and receives the calculation results of the local terminal for display.

[0012] The data acquisition device includes a shell, which is provided with a control power button, an antenna and a type C charging port. A controller is provided in the shell. The controller is connected to the control power supply through the control power button, and the control power supply is connected to the type C charging port. The controller is respectively connected to the analog acquisition module and the wireless communication module, the analog acquisition module is connected to the acoustic sensor, and the wireless communication module is connected to the antenna.

[0013] The local terminal is provided with a signal processing unit and an alarm system, and the signal processing unit is connected to the alarm system; the signal processing unit is connected to the MQTT server, and the signal processing unit performs spectrum analysis on the sound signal collected by the sound sensor and compares the correlation coefficient with the normal sound signal, and judges whether the sound change is within the normal range according to the set threshold value, and determines whether the pump tube is blocked. If the decibel value exceeds the normal value of the set threshold value, the alarm system is triggered, and the alarm system sends a control message to the cloud server, and the cloud server sends an alarm message to the mobile terminal;

[0014] The mobile terminal continuously receives the calculation results of the local terminal, and the calculation results directly display the abnormal value and the device number.

[0015] The cloud server is connected to a database; the database is a local MYSQL database that stores the calculation results.

[0016] A monitoring method for a concrete pumping state monitoring device based on an acoustic sensor, the steps of which are as follows:

[0017] Step 1: Initialization: The data acquisition device comes with a unique identity code when it leaves the factory, so no encoding is required. The mobile terminal enters the identity code of the data acquisition device as the code for binding;

[0018] Step 2: After the mobile terminal obtains access rights to the cloud server, it sends the written information to the cloud server, and the cloud server determines the construction site information and equipment information of the data acquisition equipment;

[0019] Step 3: The local terminal receives the data from the data acquisition device and the binding information sent by the mobile terminal, and groups the data acquisition devices according to the binding information input by the mobile terminal;

[0020] Step 4: Send MQTT protocol signals to the MQTT server according to the grouped device numbers to obtain the sound signals collected by the corresponding data acquisition devices;

[0021] Step 5: Perform spectrum transformation on the acquired sound signal to obtain spectrum characteristics. The spectrum characteristics are compared with the normal healthy sound model to obtain a calculation result. Based on the calculation result, it is determined whether the pump tube corresponding to the device number is blocked. The acquired sound signal and the calculation result are stored in the database. If the calculation result is abnormal, an abnormality list is sent and transmitted to the cloud server.

[0022] Step 6: The cloud server and the local server remain online, and the calculation results of the local server are synchronized to the mobile terminal in real time. The mobile terminal parses the received calculation results and displays them and draws trend charts.

[0023] The spectrum transformation is a Fourier transform, which selects data every minute and performs a Fourier transform on the sound signal to obtain the corresponding spectrum characteristics;

[0024] Remove noise from spectrum features based on frequency characteristics to obtain valid data, sort multiple data acquisition devices in time series, perform wavelet transform on valid data, extract localized characteristics of non-stationary signals, and capture transient features in sound signals;

[0025] The Pearson correlation coefficient of the spectral characteristics is compared with the normal healthy sound model. The calculation formula of the Pearson correlation coefficient is:

[0026]

[0027] Where n is the sample size, x i 、y i is the value of the data point sample, x is the intensity signal, and y is the frequency signal; and are the means of x and y respectively;

[0028] The normal healthy sound model is trained through historical data;

[0029] The cloud server processes the exception list and calculation results, generates a trend chart for data display, and displays it on the mobile terminal; the monitoring screen on the mobile terminal includes operating status and warning information. The operating status includes whether the data acquisition device is transmitting data, and the warning information includes normal, abnormal, and abnormal location.

[0030] Compared with the prior art, the present invention has the following beneficial effects: the sound sensor monitors the sound changes inside the pump pipe in real time, and transmits the data to the data acquisition device, which uses an MQTT server, a local terminal, a cloud server and a mobile terminal. The MQTT server realizes the uplink and downlink interaction of the data collected at the acquisition end. The local terminal calculates and outputs the data collected at the acquisition end and can continuously update the data samples to improve the recognition accuracy and the mining of the data value. The cloud server enables the mobile terminal to access the results calculated by the local terminal. Through data processing in the local terminal, the status of the pump pipe can be monitored in real time, potential faults can be discovered in time, and corresponding measures can be taken. The present invention can effectively improve the safety and reliability of the construction process through real-time monitoring of the concrete pump pipe, reduce the blind spots of manual inspection, and take measures quickly in the event of a fault to avoid serious losses. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0032] Figure 1 Schematic diagram of the structure of the monitoring device of the present invention.

[0033] Figure 2 Flowchart of the monitoring method of the present invention.

[0034] In the figure, 1 is the acoustic sensor, 2 is the data acquisition device, 3 is the MQTT server, 4 is the local terminal, 5 is the cloud server, 6 is the mobile terminal, and 7 is the database. DETAILED DESCRIPTION

[0035] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without creative work are within the scope of protection of the present invention.

[0036] Example 1

[0037] like Figure 1 As shown, a concrete pumping status monitoring device based on acoustic sensors includes several acoustic sensors 1, a data acquisition device 2, and a remote control platform. The acoustic sensors 1 are connected to the data acquisition device 2, which is in turn connected to the remote control platform. The remote control platform includes an MQTT server 3, a local terminal 4, a cloud server 5, and a mobile terminal 6. The data acquisition device 2 is connected to the MQTT server 3, which is in turn connected to the local terminal 4, which is in turn connected to the cloud server 5, which is in turn connected to the mobile terminal 6. The cloud server 5 is connected to a database 7. To effectively monitor the status of the pump pipe, acoustic sensors 1 are installed at various key locations along the pipe, such as the pump head, elbow, and end. The acoustic sensors 1 monitor acoustic changes within the pipe in real time and transmit the acoustic signal data to the data acquisition device. The acoustic sensors 1 are used to collect real-time acoustic data from the concrete pump pipe, primarily in decibels. The acoustic sensors can detect acoustic changes within the pipe, providing comprehensive data support for pump pipe status monitoring. The acoustic sensors 1 are the self-developed SM2406 model. Data acquisition device 2 is used to receive sound data collected by the acoustic sensor and upload the collected sound signals to the MQTT server. Data acquisition device 2 has wireless transmission capabilities, allowing real-time data upload to the remote control platform to ensure data immediacy and accuracy. The collected data first goes to MQTT server 3, which is a data transfer terminal based on the client-server message publish / subscribe transmission protocol, and then sends the data to local terminal 4. MQTT server 3 is a data transfer terminal based on the client-server message publish / subscribe transmission protocol. All online acoustic sensor data is downloaded according to ID number.

[0038] The MQTT server 3 continuously sends collected dynamic data to the local terminal 4. The data format includes the device number + sound intensity voltage value, and the transmission frequency is 10 pieces / second. The data is directly transmitted back in the form of number + value, without repeated correspondence. The transmitted data is set on the MQTT server, which acts as a data interaction bridge. The advantage of using the MQQT protocol is that it takes up less resources and can connect to more collection terminals with the same configuration. The local terminal 4 stores the data of all collection terminals (data collection devices) and filters, extracts features, and compares them according to the device number bound to the data collection device 2 to obtain data calculation results. The cloud server 5 is the interactive relay between the mobile terminal and the local terminal 4. It is responsible for sending grouping information and usage information to the local terminal 4, and at the same time, sending the data calculation results obtained by the local terminal 4 to the mobile terminal 6. The grouping information and usage information specifically include a monitoring task, which consists of several data collection devices, and the location where the task is executed. The mobile terminal 6 binds the currently used device number through the app, marks the usage location, and sends it to the local terminal 4. At the same time, it receives the calculation results of the local terminal 4 and displays them. The database is a local MYSQL database, which stores the calculation results for remote terminal calls.

[0039] Data acquisition device 2 includes a housing equipped with a power button, an antenna, and a Type-C charging port. A controller is housed within the housing. The controller is connected to a power supply via the power button, which is used to start and stop the data acquisition device. The power supply is connected to the Type-C charging port, through which the power supply is charged. The controller is connected to an analog acquisition module and a wireless communication module. The analog acquisition module is connected to a sound sensor and converts the sound signal collected by the sensor into a digital signal, representing the sound intensity voltage value, and transmits it to the controller. The wireless communication module is connected to the antenna and transmits the sound data from the controller to a wireless network. The wireless communication module uses a 4G card for data transmission; data transmission is impossible without a 4G card. The analog acquisition module uses the self-developed SM2406 model. A 4G card is a mobile SIM card, and the controller model is IO-441. The control power supply is a low-cost DC9V, stable and reliable product commonly available on the market. The controller's output signal is executed by a relay connected to the controller.

[0040] The local terminal 4 is provided with a signal processing unit and an alarm system, and the signal processing unit is connected to the alarm system. The signal processing unit performs spectrum analysis on the sound signal collected by the acoustic sensor and compares the correlation coefficient with the normal sound signal. It determines whether the sound change is within the normal range based on the set threshold value and determines whether the pump tube is blocked. If the decibel value exceeds the normal value of the preset threshold, the alarm system will be triggered immediately to sound an alarm and send the alarm signal to the mobile terminal, which can see the prompt information. When a pump tube abnormality is detected, the alarm system will immediately send a control message to the cloud server, and the cloud server will send an alarm message to the mobile terminal. The user can receive the abnormal message using the mobile terminal, reminding the user to take appropriate measures.

[0041] Mobile terminal 6 continuously receives the calculation results from the local terminal, which directly displays the abnormal value and the device number of the acoustic sensor. The device number is the location of the pump pipe anomaly. Users can access the cloud server's webpage through the mobile terminal to ensure that they know which pump pipe is faulty. The operating status of the concrete pump pipe can be monitored in real time, and the user will be notified when an anomaly occurs.

[0042] Through the remote control platform's cloud server 5, managers can access real-time pump and pipeline data and conduct data analysis at any time using mobile terminals 6. The remote control platform stores data and transmits historical trend analysis results to the cloud server, helping managers identify potential risk factors and predict pump and pipeline status. If a fault is detected, managers can view fault location information through the remote control platform's mobile terminal and instruct on-site staff to take emergency measures to minimize the impact of the fault on the construction schedule.

[0043] Example 2

[0044] A method for monitoring the concrete pumping state based on an acoustic sensor, the steps of which are as follows:

[0045] Step 1: The identity code of the data acquisition device is used as the device code, and the mobile terminal enters the device code of the data acquisition device for binding;

[0046] Step 2: After the user obtains access rights to the cloud server, he can send the written information to the cloud server, and the cloud server will know the construction site information and equipment information.

[0047] Step 3: The local terminal receives the data from the data acquisition device and the binding information sent by the mobile terminal, and groups the data acquisition devices according to the binding information input by the mobile terminal.

[0048] Devices are grouped according to the device number entered by the mobile terminal. The local terminal reads the construction site and equipment group once every 1 second, knowing where the equipment is being used and who to notify when an anomaly is detected. The collected data is then processed according to the data processing flow based on the data collection device number in the bound device group.

[0049] Step 4: Send an MQTT protocol signal to the MQTT server 3 according to the grouped device number to obtain the sound signal data collected by the corresponding data acquisition device.

[0050] Step 5. Perform spectrum transformation on the acquired sound signal to obtain spectrum characteristics. Use the spectrum characteristics to compare with the normal healthy sound model to obtain the calculation result. According to the calculation result, determine whether the pump tube corresponding to the device number is blocked, and store the acquired sound signal and calculation result in the local MYSQL database; if the calculation result is abnormal, it will be sent to the exception list and transmitted to the cloud server.

[0051] The collected data is deeply analyzed, and the sound data is comprehensively analyzed. First, the short-time Fourier transform (STFT) is used to select data per minute (600 items), and the sound signal is Fourier transformed to obtain the corresponding spectrum characteristics. Calculation process:

[0052] In the case of discrete frequency, its Fourier transform The calculation formula is:

[0053]

[0054] Where x(t) is the original sound signal received, and t indicates the time stamp of the original data; represents the spectral characteristics of the signal in the frequency domain, is the frequency.

[0055] When the original samples are discrete at different frequencies, the calculation formula for their Fourier transform (DFT) is:

[0056]

[0057] Where x[n] is the time series of the sound signals with different frequencies, and N is the length of the discrete signal, the number of sampling points. The sound signals processed by data acquisition device 2 are only processed with different frequencies, not with the same frequency. The original signal cannot be processed with the same frequency.

[0058] According to the frequency characteristics, the data is de-noised (35-56Hz), and the data converted in the previous step is put into the filter. After filtering, the data is de-noised to obtain valid data. Multiple terminals under the time series are sorted and the wavelet transform of the valid data is performed. When extracting non-stationary signals, it has better localization characteristics, captures the transient characteristics in the sound signal, and sorts the data acquisition equipment. Only in this way can the flow state of the entire pipe be known. The wavelet change here processes the filtered data. The non-stationary signal is obtained through the wavelet transform. The Pearson correlation coefficient is compared with the normal health model. The process is as follows:

[0059] The correlation coefficient calculation formula is r(x,y), where and are the means of x and y respectively.

[0060]

[0061] In this application, n is the sample size, x is i 、y i is the value of the data point sample, x is the intensity signal, and y is the frequency signal.

[0062] If x=(1,2,3,4,5),Y=(2,4,6,8,10), we get According to the above calculation, r(x,y) = 1, indicating a normal state. Setting the correlation value to 0.6, a correlation coefficient ≥ 0.6 indicates a healthy state, while a correlation coefficient < 0.6 indicates an abnormal state. This comparison can accurately predict potential blockages in the pump tubing. The normal health model is trained using historical data.

[0063] The historical sound data stored in the local MYSQL database is read through the device number and sent to the cloud server.

[0064] Step 6: The cloud server and the local server remain online, and the result data calculated by the local server is synchronized to the mobile terminal in real time. The mobile terminal parses the received data and displays it and draws a trend chart.

[0065] The cloud server processes the anomaly list and calculation results, generates a data trend chart, and displays it on the mobile terminal. The monitoring screen on the mobile terminal includes operating status and warning information. The operating status includes whether the data acquisition device is transmitting data, and the warning information includes normal, abnormal, and abnormal location.

[0066] The cloud server can access the database, which stores three types of data: mobile terminal access rights information, calculation results, and raw data. The calculation results and historical raw data obtained by the local terminal are stored in the database.

[0067] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A concrete pumping state monitoring device based on an acoustic sensor, characterized in that: The system comprises a plurality of acoustic sensors (1), a data acquisition device (2), and a remote control platform. The acoustic sensors (1) are evenly distributed at a plurality of key positions of the pump pipe. The acoustic sensors (1) are connected to the data acquisition device (2), and the data acquisition device (2) is connected to the remote control platform.

2. The concrete pumping state monitoring device based on acoustic sensor according to claim 1 is characterized in that: The remote control platform comprises an MQTT server (3), a local terminal (4), a cloud server (5) and a mobile terminal (6); the data acquisition device (2) is connected to the MQTT server (3), the MQTT server (3) is connected to the local terminal (4), the local terminal (4) is connected to the cloud server (5), and the cloud server (5) is connected to the mobile terminal (6).

3. The concrete pumping state monitoring device based on acoustic sensor according to claim 2 is characterized in that: The data acquisition device (2) has a wireless transmission function. The data acquisition device (2) uploads the collected data to the MQTT server (3) in real time via the wireless network, and the MQTT server (3) sends the collected data to the local terminal (4).

4. The concrete pumping state monitoring device based on acoustic sensor according to claim 3 is characterized in that: The MQTT server (3) is a data transfer terminal based on a client-server message publishing / subscribing transmission protocol. The MQTT server (3) continuously sends collected data to the local terminal (4). The collected data includes a device number and a sound intensity voltage value, and the sending frequency is 10 pieces per second. The local terminal (4) stores the data collected by all data acquisition devices (2), and performs screening, feature extraction and comparison according to the device number bound to the data acquisition device (2) to obtain data calculation results.

5. The concrete pumping state monitoring device based on acoustic sensor according to claim 4 is characterized in that: The cloud server (5) is an interactive relay between the mobile terminal and the local terminal (4), and is responsible for sending group information and usage information to the local terminal (4), and at the same time sending the data calculation results obtained by the local terminal (4) to the mobile terminal (6); the mobile terminal (6) binds the device number of the currently used data acquisition device (2) through the app, marks the usage location and sends it to the local terminal (4), and at the same time receives the calculation results of the local terminal (4) for display.

6. The concrete pumping state monitoring device based on an acoustic sensor according to any one of claims 1 to 5, characterized in that: The data acquisition device (2) comprises a shell, on which a control power button, an antenna and a Type C charging port are provided. A controller is provided in the shell, the controller is connected to the control power supply via the control power button, the control power supply is connected to the Type C charging port, the controller is connected to the analog quantity acquisition module and the wireless communication module respectively, the analog quantity acquisition module is connected to the acoustic sensor (1), and the wireless communication module is connected to the antenna.

7. The concrete pumping state monitoring device based on acoustic sensor according to claim 6 is characterized in that: The local terminal (4) is provided with a signal processing unit and an alarm system, and the signal processing unit is connected to the alarm system; the signal processing unit is connected to the MQTT server (3), and the signal processing unit performs spectrum analysis on the sound signal collected by the sound sensor and compares the correlation coefficient with the normal sound signal, and judges whether the sound change is within the normal range according to the set threshold value, and determines whether the pump tube is blocked. If the decibel value exceeds the normal value of the set threshold value, the alarm system is triggered, and the alarm system sends a control message to the cloud server (5), and the cloud server (5) sends an alarm message to the mobile terminal (6); The mobile terminal (6) continuously receives the calculation results of the local terminal (4), and the calculation results directly display the abnormal value and the device number.

8. The concrete pumping state monitoring device based on an acoustic sensor according to any one of claims 1 to 5 and 7, characterized in that: The cloud server (5) is connected to a database (7); the database is a local MYSQL database that stores calculation results.

9. The monitoring method of the concrete pumping state monitoring device based on the acoustic sensor according to claim 8, characterized in that: The steps are as follows: Step 1: Initialization: The data acquisition device comes with a unique identity code when it leaves the factory, so no encoding is required. The mobile terminal enters the identity code of the data acquisition device as the code for binding; Step 2: After the mobile terminal obtains access rights to the cloud server, it sends the written information to the cloud server, and the cloud server determines the construction site information and equipment information of the data acquisition equipment; Step 3: The local terminal receives the data from the data acquisition device and the binding information sent by the mobile terminal, and groups the data acquisition devices according to the binding information input by the mobile terminal; Step 4: Send MQTT protocol signals to the MQTT server according to the grouped device numbers to obtain the sound signals collected by the corresponding data acquisition devices; Step 5: Perform spectrum transformation on the acquired sound signal to obtain spectrum characteristics, compare the spectrum characteristics with the normal healthy sound model to obtain a calculation result, determine whether the pump tube corresponding to the device number is blocked based on the calculation result, and store the acquired sound signal and calculation result in a database; If the calculation result is abnormal, an abnormal list will be sent to the cloud server; Step 6: The cloud server and the local server remain online, and the calculation results of the local server are synchronized to the mobile terminal in real time. The mobile terminal parses the received calculation results and displays them and draws trend charts.

10. The monitoring method according to claim 9, characterized in that: The spectrum transformation is a Fourier transform, which selects data every minute and performs a Fourier transform on the sound signal to obtain the corresponding spectrum characteristics; Remove noise from spectrum features based on frequency characteristics to obtain valid data, sort multiple data acquisition devices in time series, perform wavelet transform on valid data, extract localized characteristics of non-stationary signals, and capture transient features in sound signals; The Pearson correlation coefficient of the spectral characteristics is compared with the normal healthy sound model. The calculation formula of the Pearson correlation coefficient is: Where n is the sample size, x i 、y i is the value of the data point sample, x is the intensity signal, and y is the frequency signal; and are the means of x and y respectively; The normal healthy sound model is trained through historical data; The cloud server processes the exception list and calculation results, generates a trend chart for data display, and displays it on the mobile terminal; the monitoring screen on the mobile terminal includes operating status and warning information. The operating status includes whether the data acquisition device is transmitting data, and the warning information includes normal, abnormal, and abnormal location.

Images