A water pump set fault early warning method and system based on an internet of things sensor

Abstract

The application discloses a water pump group fault early warning method and system based on an Internet of Things sensor, belongs to the technical field of water pump fault early warning, and specifically comprises the following steps: collecting sensing data of all water pump devices through sensing devices arranged at key positions of the water pump group; dividing independent pipe sections based on a pipe network topological structure and calculating fluid coupling strength coefficients of the pipe sections through the sensing data; generating an environment adaptive matching degree by combining a vibration main frequency of a target device with a basic frequency matching degree of pipe pressure pulsation main frequency and the coupling coefficient; if the environment adaptive matching degree is greater than or equal to a preset matching degree threshold, distinguishing between body abnormalities and conduction resonance by performing a rotating speed deviation test; if it is conduction resonance, maintaining flow stability by cooperative speed regulation of devices on the shortest conveying path; and if it is a body abnormality, issuing a fault early warning. The application realizes accurate fault early warning and risk mitigation by considering the coupling relationship between water pump devices.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of water pump fault early warning, in particular to a water pump set fault early warning method and system based on Internet of Things sensors. BACKGROUND

[0002] In the fields of industrial production, municipal water supply, etc., as the core equipment for fluid transportation, the stable operation of the water pump set is directly related to the energy efficiency and safety of the entire system. Once a fault occurs, it may not only cause production interruption and water supply stagnation, but also trigger a chain of problems such as equipment damage and energy consumption surge, so it is crucial to conduct timely and effective fault early warning on the water pump set.

[0003] At present, the traditional water pump set fault early warning method mainly relies on monitoring the vibration, temperature and other parameters of a single device, and determines whether the device is abnormal by setting a fixed threshold. However, the water pump set is often formed by multiple devices working cooperatively through a complex pipe network, and there is not only fluid power coupling between devices, but also vibration conduction through the base and other structures. When the system is abnormal, it is difficult to quickly distinguish whether the problem is caused by device degradation or external coupling, which further affects the timeliness and effectiveness of subsequent maintenance decisions. In addition, the traditional early warning system lacks dynamic response and compensation mechanisms for coupled interference, and when resonance or other coupling abnormalities occur, it cannot alleviate the risk through coordinated control, which may exacerbate equipment wear and tear and reduce system operation stability.

[0004] Therefore, how to break through the limitations of traditional early warning methods, fully consider the coupling relationship between devices in the water pump set and the influence of the pipe network structure, accurately distinguish between intrinsic faults and conduction interference, and improve the accuracy and reliability of fault early warning, has become a technical problem to be solved in the current water pump set operation and maintenance field. SUMMARY

[0005] The purpose of the present application is to provide a water pump set fault early warning method and system based on Internet of Things sensors, which solves the following technical problems:

[0006] Therefore, how to break through the limitations of traditional early warning methods, fully consider the coupling relationship between devices in the water pump set and the influence of the pipe network structure, accurately distinguish between intrinsic faults and conduction interference, and improve the accuracy and reliability of fault early warning, has become a technical problem to be solved in the current water pump set operation and maintenance field.

[0007] The purpose of the present application can be achieved by the following technical solutions:

[0008] In a first aspect, a water pump set fault early warning method based on Internet of Things sensors includes the following steps:

[0009] S1, collecting sensing data of all water pump devices through sensing devices arranged at key mechanical parts of each device in the water pump group, wherein the sensing data comprises device vibration spectrum and fluid pressure pulsation characteristic data;

[0010] S2, obtaining the pipe network topology of the water pump group, and constructing and solving a fluid coupling strength matrix of each pipe section based on the fluid pressure pulsation characteristic data to obtain fluid coupling strength coefficients of each pipe section;

[0011] S3, when the vibration spectrum energy of any water pump device exceeds a preset warning value, the water pump device is marked as a target device, the vibration main frequency of the target device and the pressure pulsation main frequency of the directly connected pipeline thereof are extracted, and the environment adaptive matching degree of the target device is calculated based on the fluid coupling strength coefficients of the connected pipeline;

[0012] S4, if the environment adaptive matching degree is greater than or equal to a preset matching degree threshold, the adjacent devices directly connected with the target device through the pipeline are controlled to perform speed deviation, the vibration amplitude deviation value of the target device before and after the speed deviation is synchronously obtained, if the deviation value is greater than a preset difference threshold, a conduction resonance warning is generated, and if the deviation value is less than or equal to the preset difference threshold, a body abnormality warning is generated;

[0013] S5, when the body abnormality warning is generated, a device fault warning is issued, and when the conduction resonance warning is generated, no device fault warning is issued and a coordinated speed regulation of linkage compensation is performed.

[0014] As a further scheme of the application, in the S2, the specific process of the fluid coupling strength coefficient is:

[0015] Based on the pipe network topology of the water pump group, independent pipe sections are divided according to the actual connection path of the pipeline, the inlet end water pump device and the outlet end water pump device of each pipe section are recorded, and the topological association index of the pipe section, the inlet end water pump device and the outlet end water pump device is established;

[0016] The ratio of the pressure pulsation amplitude of the outlet end water pump device to the pressure pulsation amplitude of the inlet end water pump device is collected to obtain a pressure transmission gain value;

[0017] Taking the pipe section as an index, the pressure transmission gain values of each pipe section are arranged according to the pipe section connection relationship in the pipe network topology to generate a fluid coupling strength matrix of each pipe section;

[0018] The fluid coupling strength matrix of each pipe section is normalized, the characteristic vector value corresponding to the maximum eigenvalue of the normalized fluid coupling strength matrix is solved, and the characteristic vector value is taken as the fluid coupling strength coefficient of the pipe section.

[0019] As a further scheme of the present application, in the S3, the target device is further configured to: acquire a connection position of the target device; if the target device is in a series connection position, acquire fluid coupling intensity coefficients of the target device and an outlet associated pipe segment, and select a maximum fluid coupling intensity coefficient of the associated pipe segment as a fluid coupling intensity coefficient corresponding to the target device;

[0020] If the target device is in a parallel connection position, acquire fluid coupling intensity coefficients of all pipe segments associated with the target device and lengths of the pipe segments, and calculate a comprehensive coefficient by weighted average of the lengths of the pipe segments, and take the comprehensive coefficient as the fluid coupling intensity coefficient corresponding to the target device.

[0021] As a further scheme of the present application, in the S3, the specific calculation process of the environment adaptive matching degree is:

[0022] ;

[0023] ;

[0024] Wherein, f1 is a vibration main frequency of the target device, f2 is a pressure pulsation main frequency of a directly connected pipeline, k is a fluid coupling intensity coefficient corresponding to the target device, a is a preset unit coefficient, p is a basic frequency matching degree, and P is an environment adaptive matching degree.

[0025] As a further scheme of the present application, in the S4, the specific process of executing the rotating speed offset is:

[0026] Among all the devices having a direct pipeline connection with the target device, an upstream water pump device directly conveying fluid to the target device is selected as a main regulating device;

[0027] Among pipe network branches to which the main regulating device belongs, a water pump device indirectly connected with the main regulating device through a continuous pipe segment and having no direct pipeline connection is selected as a speed-up device;

[0028] The main regulating device reduces the rotating speed by a fixed speed reduction reference value and acquires a flow change amount after the speed reduction, and generates a real-time rotating speed adjustment instruction of the speed-up device based on the flow change amount and adjusts the rotating speed of the speed-up device.

[0029] As a further scheme of the present application, if there are more than two upstream water pump devices, a pipe segment fluid coupling intensity coefficient between any upstream water pump device and the target device is acquired, and all the upstream water pump devices are sorted in descending order according to the pipe segment fluid coupling intensity coefficients;

[0030] The rotating speed offset is executed in the descending order, and if the vibration amplitude deviation of the target device exceeds a threshold value after the rotating speed offset of any upstream water pump device, the upstream water pump device is marked as a main source device, and a conduction resonance warning is generated.

[0031] As a further scheme of the present application: in the S4, if the environmental self-adaptive matching degree is less than a preset matching degree threshold, the adjacent device rigidly connected with the target device is controlled to perform a rotational speed offset, a vibration amplitude deviation value of the target device before and after the rotational speed offset is synchronously acquired, if the deviation value is greater than a preset deviation threshold, a conduction resonance warning is generated, and if the deviation value is less than or equal to the preset deviation threshold, a body abnormality warning is generated.

[0032] As a further scheme of the present application: in the S5, the specific process of the cooperative speed regulation for performing the linkage compensation is as follows:

[0033] Based on the water pump group pipe network topology structure, all the delivery paths from the autonomous source device to the final fluid delivery point through the target device are acquired, and the unit initial delivery flow of each delivery path before performing the rotational speed offset is acquired;

[0034] The steady-state flow ratio of each delivery path is calculated, and the steady-state flow ratio is a ratio of the initial delivery flow of the path to a sum of initial delivery flows of all paths;

[0035] A global flow control model is established, the steady-state flow ratio is taken as a flow distribution weight of each path, when the path where the main source device is located performs the rotational speed offset, a flow variation of the path is monitored in real time, the flow variation of the path of the main source device is inversely distributed according to the weight proportion of the remaining paths, and a target compensation flow of all the delivery paths is obtained;

[0036] A local closed-loop controller is constructed for each delivery path, the target compensation flow is taken as a set value, and a real-time acquired path delivery flow is taken as a feedback value; a rotational speed adjustment instruction is generated according to an output of the closed-loop controller, the rotational speed adjustment instruction is distributed to all the water pump devices in the delivery path according to a preset weight, and each water pump device is driven to synchronously adjust the rotational speed.

[0037] In a second aspect, a water pump group fault early warning system based on an Internet of Things sensor is used to implement the water pump group fault early warning method based on the Internet of Things sensor, and the system comprises:

[0038] A data acquisition module is configured to acquire sensing data of all the water pump devices through sensing devices deployed at key mechanical parts of the water pump group, wherein the sensing data comprises device vibration spectrum and fluid pressure pulsation characteristic data;

[0039] A data analysis module is configured to acquire a water pump group pipe network topology structure, and construct and solve a fluid coupling strength matrix of each pipe section based on the fluid pressure pulsation characteristic data, to obtain a fluid coupling strength coefficient of each pipe section;

[0040] The correlation matching module is configured to, when vibration spectrum energy of any water pump device exceeds a preset alert value, mark the water pump device as a target device, extract a vibration main frequency of the target device and a pressure pulsation main frequency of a directly connected pipeline of the target device, and calculate an environment adaptive matching degree of the target device based on a fluid coupling strength coefficient of the connected pipeline.

[0041] The alarm generating module is configured to, if the environment adaptive matching degree is greater than or equal to a preset matching degree threshold, control an adjacent device directly connected to the target device through a pipeline to perform speed deviation, synchronously acquire a vibration amplitude deviation value of the target device before and after the speed deviation, if the deviation value is greater than a preset difference threshold, generate a conducted resonance alarm, and if the deviation value is less than or equal to the preset difference threshold, generate a body abnormality alarm.

[0042] The processing optimization module is configured to, when the body abnormality alarm is generated, issue a device fault warning, and when the conducted resonance alarm is generated, not issue the device fault warning and perform coordinated speed regulation of linkage compensation.

[0043] The present application has the following advantages:

[0044] The present application collects vibration spectrum, base vibration transmission characteristics and fluid pressure pulsation characteristics of key parts of a water pump group by deploying sensors, calculates a fluid coupling strength coefficient in combination with a pipeline network topological structure, determines a coupling coefficient corresponding to a target device in a differentiated manner for different connection positions such as series connection and parallel connection, corrects a frequency matching degree to obtain an environment adaptive matching degree, and identifies coupling correlation between devices generated through fluid and base, thereby breaking through the limitation of traditional single device monitoring that ignores mutual influence between devices, accurately distinguishing whether device vibration abnormality is caused by a body problem or external conducted resonance, greatly reducing the probability of misjudging conducted interference as a body fault, and significantly improving the accuracy of fault warning.

[0045] Meanwhile, when identifying that there may be conducted resonance, the present application sequentially performs speed deviation on upstream water pump devices in order of fluid coupling strength coefficient, and quickly locates a main source device causing resonance in combination with speed regulation test of base rigid connection devices, confirms resonance abnormality, performs coordinated speed regulation of each path device according to a steady-state flow rate proportion based on a global flow rate control model to maintain stable flow rate, ensures that the overall fluid delivery is not affected when handling faults, maintains system operation stability and energy efficiency while ensuring accurate fault warning, and realizes accurate fault warning and risk mitigation. BRIEF DESCRIPTION OF DRAWINGS

[0046] The present application will be further described below with reference to the accompanying drawings.

[0047] Figure 1 is a flowchart of a water pump group fault warning method based on an Internet of Things sensor according to an embodiment of the present application.

[0048] Figure 2 Figure 1 is a structural schematic diagram of a water pump set fault early warning system based on an Internet of Things sensor according to an embodiment of the present application. DETAILED DESCRIPTION

[0049] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative work fall within the scope of protection of the present application.

[0050] Embodiment one

[0051] Please refer to Figure 1 The present application is a water pump set fault early warning method based on an Internet of Things sensor, which comprises the following steps:

[0052] S1, collecting sensing data of all water pump devices through sensing devices deployed at key mechanical parts of the water pump set, wherein the sensing data comprises device vibration spectrum and fluid pressure pulsation characteristic data.

[0053] S2, obtaining a water pump set pipe network topology structure, and constructing and solving a fluid coupling strength matrix of each pipe section based on the fluid pressure pulsation characteristic data to obtain fluid coupling strength coefficients of each pipe section.

[0054] In step S2 of the present embodiment, the specific process of the fluid coupling strength coefficient is as follows:

[0055] Based on the water pump set pipe network topology structure, independent pipe sections are divided according to the actual connection path of the pipeline, the inlet end water pump device and the outlet end water pump device of each pipe section are recorded, and a topological association index of the pipe section, the inlet end water pump device and the outlet end water pump device is established;

[0056] The ratio of the pressure pulsation amplitude of the outlet end water pump device to the pressure pulsation amplitude of the inlet end water pump device is collected to obtain a pressure transmission gain value;

[0057] Taking the pipe section as an index, the pressure transmission gain values of each pipe section are arranged according to the pipe section connection relationship in the pipe network topology to generate a fluid coupling strength matrix of each pipe section;

[0058] The fluid coupling strength matrix of each pipe section is normalized, the characteristic vector value corresponding to the maximum eigenvalue of the normalized fluid coupling strength matrix is solved, and the characteristic vector value is taken as the fluid coupling strength coefficient of the pipe section.

[0059] Based on the water pump group pipe network topology, independent pipe sections are divided according to the actual connection path of the pipe, the inlet end water pump equipment and the outlet end water pump equipment of each pipe section are recorded, and the topological association index of the pipe section, the inlet end water pump equipment and the outlet end water pump equipment is established. For example, if there are water pump A, water pump B and water pump C in the water pump group, water pump A is connected to water pump B through a pipe, and water pump B is connected to water pump C through another pipe. The two pipes can be divided into two independent pipe sections. The inlet end of the first pipe section is water pump A, and the outlet end is water pump B. The inlet end of the second pipe section is water pump B, and the outlet end is water pump C. The first pipe section is associated with (water pump A, water pump B), and the second pipe section is associated with (water pump B, water pump C) to form an index. This is because the actual connection path of the pipe in the pipe network determines the transmission path of the fluid from one water pump to another. Dividing independent pipe sections and recording the specific equipment connected by each pipe can clearly define the specific equipment connected by each pipe, providing a basis for subsequent analysis of the transmission relationship between equipment. The ratio of the pressure fluctuation amplitude of the outlet end water pump equipment to the pressure fluctuation amplitude of the inlet end water pump equipment is collected to obtain the pressure transmission gain value. For example, for the first pipe section, the pressure fluctuation amplitude at water pump A (i.e. the size of the pressure fluctuation of the fluid at the outlet of water pump A when it is running) and the pressure fluctuation amplitude at water pump B (i.e. the size of the pressure fluctuation of the fluid at the inlet of water pump B) are collected. The pressure fluctuation amplitude of water pump B is divided by the pressure fluctuation amplitude of water pump A, and the result is the pressure transmission gain value of the first pipe section. This is because the pressure fluctuation will be transmitted from the inlet end water pump to the outlet end water pump as the fluid flows in the pipe. The ratio of the two can reflect the transmission ability of the pipe section to the pressure fluctuation. The larger the ratio, the stronger the effect of the pipe section on the transmission of the pressure fluctuation. The pressure transmission gain values of each pipe section are arranged according to the connection relationship of the pipe sections in the pipe network topology to generate a fluid coupling strength matrix of each pipe section. For example, in the above example, the pipe network topology is water pump A-first pipe section-water pump B-second pipe section-water pump C, and the connection relationship of the pipe sections is that the outlet end of the first pipe section and the inlet end of the second pipe section are both water pump B. Therefore, the pressure transmission gain values of the first pipe section and the second pipe section are filled in the corresponding positions in the matrix in the order of connection, forming a matrix. This is because the connection relationship of the pipe network topology determines the mutual influence between the pipe sections. Arranging the matrix in this way can intuitively reflect the transmission path of the fluid coupling in the entire pipe network and the association between the pipe sections.The fluid coupling strength matrix of each pipe section is normalized, the eigenvector value corresponding to the maximum eigenvalue of the normalized fluid coupling strength matrix is solved, and the eigenvector value is taken as the fluid coupling strength coefficient of the pipe section. For example, the pressure transfer gain value in each matrix is adjusted according to certain rules (such as divided by the maximum value of all values in the matrix) to make all numerical values in the same order of magnitude, complete normalization, and then calculate the maximum eigenvalue of the normalized matrix and the eigenvector corresponding to the eigenvalue. The values in the vector are respectively taken as the fluid coupling strength coefficients of the two pipe sections. This is because normalization can eliminate the dimensional influence of the original size difference of the pressure transfer gain value of different pipe sections, so that the coupling strength of each pipe section is comparable, and the eigenvector corresponding to the maximum eigenvalue can reflect the most significant coupling relationship in the matrix. Using it as a coefficient can effectively quantify the key degree of each pipe section in fluid coupling.

[0060] Precise quantification of the fluid coupling strength of different pipe sections in the water pump group can clearly capture the coupling relationship between devices caused by fluid flow, and the fluid coupling strength coefficient quantifies the ability of pressure pulsation and vibration transmission in different pipe sections. The value directly reflects the strength of the fluid coupling influence between the two devices through the pipe section - the higher the coefficient, the easier it is for the pressure pulsation or vibration of the upstream device to be transmitted to the downstream device through fluid, and the more significant the coupling relationship between the two; the lower the coefficient, the weaker the transmission ability, and the smaller the mutual influence between devices caused by fluid.

[0061] The basic frequency matching degree only reflects the similarity of the target device vibration main frequency and the direct communication pipeline pressure pulsation main frequency, but cannot reflect whether this frequency correlation is caused by the device itself or fluid coupling transmission. The environment adaptive matching degree obtained by combining the fluid coupling strength coefficient correction can combine the frequency matching degree and the coupling influence strength between devices: when the coupling strength is high, if the frequency matching degree is also high, it means that the vibration of the target device is more likely to be transmitted by other devices through fluid coupling (i.e. transmission resonance); when the coupling strength is low, even if the frequency has some matching, it is more likely that the target device itself has an intrinsic abnormality (because under weak coupling, external transmitted vibration is difficult to cause significant frequency correlation), which provides a reliable quantitative basis for subsequent judgment of whether the device vibration abnormality is caused by the intrinsic problem of the device itself or the transmission of other devices through fluid coupling. The fluid coupling strength coefficient obtained can help the system analyze the vibration spectrum of the device, combine the coupling strength to correct the frequency matching degree, more accurately distinguish intrinsic abnormalities and transmission resonance, thereby improving the accuracy of fault warning, avoiding misjudgment of transmission interference as intrinsic failure, and ensuring the reliability of the warning result.

[0062] S3, when the vibration spectrum energy of any water pump equipment exceeds the preset warning value, the water pump equipment is marked as a target equipment, the vibration main frequency of the target equipment and the pressure pulsation main frequency of the directly connected pipeline are extracted, and the environment adaptive matching degree of the target equipment is calculated based on the fluid coupling strength coefficient of the connected pipeline.

[0063] In step S3 of the embodiment, the following is further included:

[0064] The connection position of the target equipment is obtained. If the target equipment is in a series connection position, the fluid coupling strength coefficients of the associated pipe sections of the inlet and outlet of the target equipment are obtained, and the fluid coupling strength coefficient of the largest associated pipe section is selected as the fluid coupling strength coefficient corresponding to the target equipment.

[0065] If the target equipment is in a parallel connection position, the fluid coupling strength coefficients and lengths of all pipe sections associated with the target equipment are obtained, the comprehensive coefficient is calculated by length-weighted average of each pipe section, and the comprehensive coefficient is taken as the fluid coupling strength coefficient corresponding to the target equipment.

[0066] It can be understood that because the water pump equipment in different connection positions is affected by fluid coupling in different ways in the pipe network, the strong coupling of a certain pipe section may play a dominant role in series connection, and the influence of multiple pipe sections needs to be considered comprehensively in parallel connection. The initial or final position is only affected by a single pipe section. According to the characteristics of different positions, the corresponding coefficient is selected, which can make the fluid coupling strength coefficient more consistent with the actual coupling state of the equipment. Avoid the distortion of the coefficient caused by the difference in connection mode, ensure that the coefficient can truly reflect the degree of fluid coupling influence on the target equipment, and provide a reliable quantitative basis for subsequent calculation of the environment adaptive matching degree. The accurate environment adaptive matching degree is the key to distinguish whether the equipment vibration anomaly is an intrinsic problem or a transmission resonance. It is essential to realize accurate pump set fault warning, which can improve the accuracy of warning and reduce false positives.

[0067] The specific calculation process of the comprehensive coefficient is as follows:

[0068] ;

[0069] Where ki is the fluid coupling strength coefficient of the i-th pipe section associated with the target equipment, and Li is the length of the i-th pipe section associated with the target equipment.

[0070] In step S3 of the embodiment, the specific calculation process of the environment adaptive matching degree is as follows:

[0071] ;

[0072] ;

[0073] Wherein, f1 is the vibration main frequency of the target device, f2 is the pressure pulsation main frequency of the direct connection pipeline, k is the fluid coupling strength coefficient corresponding to the target device, a is a preset unit coefficient, p is the basic frequency matching degree, and P is the environmental adaptive matching degree.

[0074] S4, if the environmental adaptive matching degree is greater than or equal to the preset matching degree threshold, the speed of the adjacent device directly connected with the target device is controlled to be offset, the vibration amplitude deviation value of the target device before and after the speed offset is obtained, if the deviation value is greater than the preset difference threshold, a conduction resonance alarm is generated; if the deviation value is less than or equal to the preset difference threshold, a body abnormality alarm is generated.

[0075] In step S4 of the embodiment, the specific process of speed offset is as follows:

[0076] Among all the devices directly connected with the target device, the upstream water pump device directly conveying fluid to the target device is selected as the main regulating device;

[0077] Among the pipe network branch to which the main regulating device belongs, the water pump device indirectly connected with the main regulating device through a continuous pipe section and without direct pipeline connection is selected as the speed-up device;

[0078] The main regulating device reduces the speed by a fixed speed reduction reference value and obtains the flow change value after the speed reduction, generates the real-time speed adjustment instruction of the speed-up device based on the flow change value, and adjusts the speed of the speed-up device.

[0079] The upstream water pump device directly conveying fluid to the target device is selected as the master device, such as if the target device is water pump M, the devices directly connected to it by pipelines are water pump N and water pump P, wherein the outlet of water pump N is connected to the inlet of water pump M by a pipeline (i.e. N conveys fluid to M), and the outlet of water pump M is connected to the inlet of water pump P by a pipeline (i.e. M conveys fluid to P), then water pump N directly conveying fluid to M is the upstream device and is selected as the master device, because the fluid conveying state of the upstream water pump device directly affects the fluid pressure and flow received by the target device, adjusting the rotating speed of such devices can more directly change the fluid coupling effect on the target device, thereby facilitating the observation of the vibration change of the target device; then in the pipe network branch to which the master device belongs, select the water pump device indirectly connected to the master device through a continuous pipe section and without direct pipeline connection as the speed-up device, for example, the master device is water pump N, and the connection relationship of the pipe network branch to which it belongs is N→Q→R→S, wherein N and Q are directly connected by a pipeline, Q and R are directly connected by a pipeline, R and S are directly connected by a pipeline, and N and R, N and S are not directly connected by a pipeline, then R and S are indirectly connected to the master device N through a continuous pipe section and without direct pipeline connection, and can be selected as the speed-up device, because such indirectly connected devices and the master device belong to the same branch, adjusting the rotating speed of the speed-up device can compensate for the flow fluctuation caused by the rotating speed change of the master device, and at the same time, since there is no direct pipeline connection, the speed-up device will not produce direct fluid coupling interference with the master device, avoiding affecting the test results; then the master device reduces the rotating speed according to a fixed speed reduction reference value and obtains the flow change after speed reduction, and generates real-time rotating speed adjustment instructions for the speed-up device based on the flow change and adjusts the rotating speed of the speed-up device, for example, the master device N reduces the rotating speed according to a fixed speed reduction reference value (such as reducing a certain rotating speed unit each time), and the flow of the branch is monitored by a sensing device to reduce a certain amount, and the system will calculate the rotating speed value that the speed-up device (such as R and S) needs to increase according to the reduced flow change, generate adjustment instructions to make R and S increase the corresponding rotating speed, to compensate for the flow loss caused by the speed reduction of the master device, because the speed reduction of the master device will reduce the amount of fluid conveyed to the target device, which may change the fluid coupling strength on the target device, and the rotating speed increase of the speed-up device can compensate for the flow and maintain the stability of fluid conveying in the entire branch, to ensure that the overall operation state of the system will not be disturbed by the flow fluctuation when testing the vibration change of the target device.

[0080] By adjusting the speed of the upstream master device that delivers fluid to the target device, the fluid coupling effect on the target device can be changed, and the vibration changes are observed to determine whether the vibration anomaly is caused by the upstream device. At the same time, by adjusting the speed of the speed-up device connected to the same branch, the flow can be compensated when the master device is slowed down, avoiding the imbalance of the overall flow of the system affecting normal operation. It can not only accurately test the possibility of conduction resonance, but also maintain the stable operation of the pump group, avoiding system failure caused by testing. The vibration changes after speed deviation can accurately distinguish whether the vibration anomaly of the target device is caused by the upstream device or the target device itself. Finally, accurate fault warning is essential to ensure that the system is not misjudged as a fault when there is a conduction resonance, and the accuracy of the warning is improved, and the stability of the system during testing is ensured.

[0081] It is worth noting that when the target device is in the initial connection position, the subsequent steps are not performed, and the speed deviation of the adjacent device that is rigidly connected with the target device is controlled. It can be understood that the fluid pressure pulsation can only propagate from the pump to the downstream of the pipe network, and cannot be conducted in reverse to the upstream pump. The speed deviation of the downstream device cannot affect the vibration state of the initial position pump through fluid coupling. Therefore, when the target device is in the initial connection position, there is no fluid resonance effect.

[0082] In another preferred embodiment of the present application, if there are more than two upstream water pump devices, the fluid coupling strength coefficient between any upstream water pump device and the target device is obtained, and all upstream water pump devices are sorted in descending order according to the fluid coupling strength coefficient.

[0083] The speed deviation is performed in descending order, and if the vibration amplitude deviation of the target device exceeds the threshold value after any upstream water pump device performs the speed deviation, the upstream water pump device is marked as the main source device, and a conduction resonance warning is generated.

[0084] It can be understood that when there are multiple upstream water pump devices, the vibration anomaly of the target device may be caused by one or more devices through fluid coupling, and the influence degree of different upstream devices is different due to the different coupling strength of the pipe section. Sorting in descending order of coupling strength can focus on the devices that are more likely to have a significant impact, avoid blind detection, efficiently and accurately locate the main source device of the conduction resonance, and avoid the confusion caused by mixing multiple upstream devices. Clearly identify the specific upstream source of the vibration anomaly of the target device to provide an accurate basis for subsequent generation of conduction resonance warning and execution of linkage compensation. Finally, accurate fault warning is essential. By accurately identifying the main source device, it can be ensured that the system is not misjudged as a fault when there is a conduction resonance, and the accuracy of the warning and the stability of the system operation are improved.

[0085] In step S4 of the embodiment, the following is also included:

[0086] If the environment adaptive matching degree is less than the preset matching degree threshold, the control adjacent devices rigidly connected with the target device through the base to perform a rotational speed offset, synchronously acquire a vibration amplitude deviation value of the target device before and after the rotational speed offset, if the deviation value is greater than a preset difference threshold, a conduction resonance warning is generated; if the deviation value is less than or equal to the preset difference threshold, a body abnormality warning is generated.

[0087] If the environment adaptive matching degree is less than the preset matching degree threshold, it means that the vibration main frequency of the target device and the pressure pulsation main frequency of the directly connected pipeline have a low matching degree, and the fluid coupling induced resonance is less likely to occur. At this time, it is necessary to consider whether the vibration is conducted through the rigid connection of the base. For example, the target device is water pump A, and the environment adaptive matching degree is calculated to be less than the preset value, which means that the resonance caused by fluid coupling is less likely to occur, and it is necessary to check the adjacent devices rigidly connected with the water pump A. The control of these adjacent devices to perform a rotational speed offset, that is, to determine which devices are connected with the target device through the rigid base, for example, water pump A and water pump B are installed on the same whole cast iron base, and they are adjacent devices connected through the rigid base. At this time, the control of water pump B to adjust the rotational speed by a certain amplitude (such as reducing or increasing the fixed rotational speed), while synchronously collecting the vibration amplitude of water pump A before and after the rotational speed offset of water pump B, and calculating the deviation value of the two, because the rigid base will transmit the vibration, the change of the rotational speed of the adjacent device will change the frequency and amplitude of its own vibration, and if the vibration of the target device is affected by the conduction of the base, the vibration amplitude will change significantly with the change of the rotational speed of the adjacent device. If the deviation value is greater than the preset difference threshold, it means that the vibration amplitude of the target device has changed significantly due to the change of the rotational speed of the adjacent device, that is, the vibration abnormality is likely to be transmitted from the adjacent device through the rigid base, and a conduction resonance warning is generated. If the deviation value is less than or equal to the preset difference threshold, it means that the change of the rotational speed of the adjacent device has little effect on the vibration of the target device, and the vibration abnormality is more likely to come from the target device itself, and a body abnormality warning is generated, because when the vibration is conducted through the rigid base, the change of the motion state of the adjacent device will directly affect the vibration of the target device, and when the body is abnormal, the change of the rotational speed of the external device will not significantly affect the vibration.

[0088] Because the transmission path of vibration not only has fluid coupling, but also can be transmitted through mechanical structures such as rigid base, when the environmental self-adaptive matching degree is low, the mechanical transmission influence caused by the rigid connection of the base needs to be excluded after excluding the resonance dominated by fluid coupling, and it is ensured that no possible resonance source is missed. The advantage is that different vibration transmission paths are comprehensively covered, and misjudgment caused by only focusing on fluid coupling and ignoring mechanical transmission is avoided. By checking the adjacent equipment of the base rigid connection, the vibration abnormality of the target equipment is further distinguished as a problem of itself or a resonance through mechanical structure transmission, and the comprehensiveness of fault judgment is ensured. Finally, it is crucial to realize accurate fault early warning, which can accurately identify the problem source in various possible vibration transmission scenarios, and improve the reliability and accuracy of early warning.

[0089] S5, when the ontology abnormality alarm is generated, the device fault early warning is issued; when the transmission resonance alarm is generated, the device fault early warning is not issued and the cooperative speed regulation of linkage compensation is performed.

[0090] In step S5 of the embodiment, the specific process of the cooperative speed regulation of linkage compensation is as follows:

[0091] Based on the water pump group pipe network topology, all transmission paths from the autonomous source device to the final fluid delivery point through the target device are obtained, and the unit initial transmission flow of each transmission path before performing speed offset is obtained;

[0092] The steady-state flow ratio of each transmission path is calculated, and the steady-state flow ratio is the ratio of the initial transmission flow of the path to the sum of the initial transmission flows of all paths;

[0093] A global flow control model is established, the steady-state flow ratio is taken as the flow distribution weight of each path, when the path of the main source device performs speed offset, the flow change amount of the path is monitored in real time, the flow change amount of the path of the main source device is inversely distributed according to the weight proportion of the remaining paths, and the target compensation flow of all transmission paths is obtained;

[0094] A local closed-loop controller is constructed for each transmission path, the target compensation flow is taken as the set value, and the real-time collected path transmission flow is taken as the feedback value; the speed adjustment instruction is generated according to the output of the closed-loop controller, the speed adjustment instruction is distributed to all water pump devices in the transmission path according to the preset weight, and each water pump device is driven to adjust the speed synchronously.

[0095] Based on the pump group pipe network topology, all delivery paths from the autonomous source device to the final fluid delivery point through the target device are obtained, such as the main source device being water pump A, the target device being water pump B, and the final fluid delivery point being a water tank. There are three paths after being sorted: A→B→C→water tank, A→B→D→water tank, and A→B→water tank. The unit initial delivery flow of each path before executing the speed offset is obtained, which is assumed to be 20, 30, and 50 (unit: certain flow unit) respectively. The steady-state flow ratio of each delivery path is calculated, that is, the ratio of the initial flow of each path to the sum of the initial flows of all paths. The sum of the three paths is 20+30+50=100, so the ratios are 20%, 30%, and 50% respectively. This is because the initial flow reflects the natural flow distribution state of each path when the system is stably running, and the ratio can reflect the share weight of each path in the overall delivery. A global flow control model is established, and these steady-state flow ratios are used as the flow distribution weights of each path. When the path where the main source device is located (assuming it is the A→B→water tank path where the main source device A is located) executes the speed offset, the flow change of the path is monitored in real time. For example, the flow of the path decreases by 10 units due to the speed offset. At this time, the 10 units of change need to be allocated in the opposite direction according to the weight proportion of the remaining paths (that is, the remaining paths need to increase the flow to compensate). The total weight of the remaining paths is 20%+30%=50%, so the A→B→C→water tank path needs to compensate 10×(20% / 50%)=4 units, and the A→B→D→water tank path needs to compensate 10×(30% / 50%)=6 units. The target compensation flow of all delivery paths is obtained. This is because the reverse allocation according to the weight can ensure that the flow adjustment of each path conforms to the original share ratio, avoiding the disruption of the overall balance due to the change of a single path. A local closed-loop controller is constructed for each delivery path, with the target compensation flow as the set value (such as 4 units for the A→B→C→water tank path) and the real-time collected path delivery flow as the feedback value. For example, the current flow of the path is only increased by 2 units, and the controller will calculate the deviation. The speed adjustment instruction is generated according to the output of the closed-loop controller (such as the need to increase the speed to increase the flow by 2 units), and the instruction is distributed to all water pump devices in the path according to the preset weight. Assuming that the adjustment weights of water pumps A, B, and C in the A→B→C→water tank path are 30%, 20%, and 50% respectively, then A bears 30% of the speed increase, B bears 20%, and C bears 50%. Drive each device to adjust the speed synchronously. This is because the influence of different devices in the path on the flow is different, and the allocation according to the weight can make the flow adjustment more accurate, and the synchronous adjustment can avoid the flow fluctuation caused by the mutual interference between devices.

[0096] When the path where the main source device is located performs speed deviation, the flow change thereof will affect other parallel paths through pressure coupling of the pipe network. If only a single path is adjusted, it is easy to cause flow imbalance of other paths. Based on initial steady-state proportional distribution compensation, the flow adjustment of each path can conform to the original sharing rule of the system. The speed deviation of the path where the main source device is located can eliminate the transmission resonance, and the collaborative compensation of other paths can maintain the overall flow stability and avoid excessive fluctuation of pipe network transportation. While dealing with the transmission resonance problem, the stable supply of the pump set to the final fluid delivery point is ensured, and the normal operation of the system is not affected. The system can balance fault handling and fluid delivery stability in complex pipe network structure, and improve the practicality and adaptability of the scheme.

[0097] Embodiment two

[0098] As shown in Figure 2 The present application also includes a water pump set fault early warning system based on Internet of Things sensors, which is used to implement the water pump set fault early warning method based on Internet of Things sensors in the above embodiment, and includes:

[0099] A data acquisition module is configured to collect sensing data of all water pump devices through sensing devices deployed at key mechanical parts of the water pump set, wherein the sensing data includes device vibration spectrum and fluid pressure pulsation characteristic data.

[0100] A data analysis module is configured to obtain the pipe network topology of the water pump set, and construct and solve a fluid coupling strength matrix of each pipe section based on the fluid pressure pulsation characteristic data to obtain fluid coupling strength coefficients of each pipe section.

[0101] An association matching module is configured to, when the vibration spectrum energy of any water pump device exceeds a preset warning value, mark the water pump device as a target device, extract the vibration main frequency of the target device and the pressure pulsation main frequency of the directly connected pipeline thereof, and calculate the environmental adaptive matching degree of the target device based on the fluid coupling strength coefficients of the connected pipeline.

[0102] An alarm generation module is configured to, if the environmental adaptive matching degree is greater than or equal to a preset matching degree threshold, control the adjacent devices directly connected with the target device to perform speed deviation, synchronously obtain the vibration amplitude deviation value of the target device before and after the speed deviation, and if the deviation value is greater than a preset difference threshold, generate a transmission resonance alarm; and if the deviation value is less than or equal to the preset difference threshold, generate a body abnormality alarm.

[0103] A processing optimization module is configured to, when the body abnormality alarm is generated, issue a device fault early warning; and when the transmission resonance alarm is generated, not issue a device fault early warning and perform collaborative speed regulation of linkage compensation.

[0104] The above has been described in detail one embodiment of the present application, but the content is only the preferred embodiment of the present application, cannot be considered for limiting the scope of the present application. Any equivalent changes and improvements made in the scope of the present application, should still belong to the scope of the present application.

Claims

1. A water pump set failure early warning method based on an Internet of Things sensor, characterized in that, The method comprises the following steps: S1, collecting sensing data of all water pump devices through sensing devices arranged at key mechanical parts of each device in the water pump group, wherein the sensing data comprises device vibration spectrum and fluid pressure pulsation characteristic data; S2, obtaining the pipe network topology of the water pump group, and constructing and solving a fluid coupling strength matrix of each pipe section based on the fluid pressure pulsation characteristic data to obtain fluid coupling strength coefficients of each pipe section; S3, when the vibration spectrum energy of any water pump device exceeds a preset warning value, the water pump device is marked as a target device, the vibration main frequency of the target device and the pressure pulsation main frequency of the directly connected pipeline are extracted, and the environmental adaptive matching degree of the target device is calculated based on the fluid coupling strength coefficient of the connected pipeline; S4, if the environmental adaptive matching degree is greater than or equal to a preset matching degree threshold, the adjacent devices directly connected to the target device are controlled to perform speed deviation, the vibration amplitude deviation value of the target device before and after the speed deviation is obtained synchronously, if the deviation value is greater than a preset difference threshold, a conduction resonance warning is generated, and if the deviation value is less than or equal to the preset difference threshold, a body abnormality warning is generated; S5, when the body abnormality warning is generated, a device fault warning is issued, and when the conduction resonance warning is generated, no device fault warning is issued and a coordinated speed regulation of linkage compensation is performed. 2.The water pump set fault early warning method based on the Internet of Things sensor of claim 1, wherein, In S2, the specific process of solving the fluid coupling strength coefficient is as follows: Based on the pipe network topology of the water pump group, independent pipe sections are divided according to the actual connection path of the pipeline, the inlet end water pump device and the outlet end water pump device of each pipe section are recorded, and the topological association index of the pipe section, the inlet end water pump device and the outlet end water pump device is established; The ratio of the pressure pulsation amplitude of the outlet end water pump device to the pressure pulsation amplitude of the inlet end water pump device is collected to obtain a pressure transmission gain value; Taking the pipe section as an index, the pressure transmission gain values of the pipe sections are arranged according to the pipe section connection relationship in the pipe network topology to generate a fluid coupling strength matrix of each pipe section; The fluid coupling strength matrix of each pipe section is normalized, the characteristic vector value corresponding to the maximum eigenvalue of the normalized fluid coupling strength matrix is solved, and the characteristic vector value is taken as the fluid coupling strength coefficient of the pipe section. 3.The water pump set fault early warning method based on the Internet of Things sensor of claim 1, wherein, In S3, the connection position of the target device is obtained, if the target device is in a series connection position, the fluid coupling strength coefficients of the inlet and outlet associated pipe sections of the target device are obtained, the fluid coupling strength coefficient of the largest associated pipe section is selected as the fluid coupling strength coefficient corresponding to the target device; If the target device is in a parallel connection position, the fluid coupling strength coefficients and lengths of all pipe sections associated with the target device are obtained, the comprehensive coefficient is calculated by weighted average according to the lengths of the pipe sections, and the comprehensive coefficient is taken as the fluid coupling strength coefficient corresponding to the target device.

4. The water pump set fault early warning method based on the Internet of Things sensor according to claim 3, characterized in that, In S3, the specific calculation process of the environmental adaptive matching degree is as follows: ； ； Wherein, f1 is the vibration main frequency of the target device, f2 is the pressure pulsation main frequency of the directly connected pipeline, k is the fluid coupling strength coefficient corresponding to the target device, a is a preset unit coefficient, p is a basic frequency matching degree, and P is an environmental adaptive matching degree. 5.The water pump set fault early warning method based on the Internet of Things sensor of claim 1, wherein, In S4, the specific process of performing speed deviation is as follows: In all devices connected to the target device through a direct pipeline, the upstream water pump device directly delivering fluid to the target device is selected as the master device; In the pipe network branch to which the master device belongs, the water pump device indirectly connected to the master device through a continuous pipe section without a direct pipeline connection is selected as the speed-up device; The master device reduces the speed by a fixed speed reduction reference value and obtains the flow change after speed reduction, generates a real-time speed adjustment instruction for the speed-up device based on the flow change, and adjusts the speed of the speed-up device.

6. The water pump set failure early warning method based on the Internet of Things sensor according to claim 5, characterized in that, If there are more than two upstream water pump devices, the pipe section fluid coupling strength coefficient between any upstream water pump device and the target device is obtained, and all upstream water pump devices are sorted in descending order according to the pipe section fluid coupling strength coefficient; The speed offset is performed in the descending order, and if the vibration amplitude deviation of the target device exceeds the threshold value after any upstream water pump device performs the speed offset, the upstream water pump device is marked as the master source device, and a conducted resonance warning is generated.

7. The water pump set failure early warning method based on an Internet of Things sensor according to claim 1, characterized in that, In S4, if the environmental self-adaptive matching degree is less than the preset matching degree threshold, the speed offset is performed on the adjacent device connected to the target device through a rigid base, the vibration amplitude deviation value of the target device before and after the speed offset is obtained, and if the deviation value is greater than the preset difference threshold, a conducted resonance warning is generated. If the deviation value is less than or equal to the preset difference threshold, a body abnormality warning is generated. 8.The water pump set fault early warning method based on the Internet of Things sensor of claim 6, wherein, In S5, the specific process of the cooperative speed regulation for linkage compensation is as follows: Based on the pump group pipe network topology, all delivery paths from the master source device through the target device to the final fluid delivery point are obtained, and the unit initial delivery flow of each delivery path before the speed offset is performed is obtained; The steady-state flow ratio of each delivery path is calculated, which is the ratio of the initial delivery flow of the path to the sum of the initial delivery flows of all paths; A global flow control model is established, and the steady-state flow ratio is used as the flow distribution weight of each path. When the path of the master source device performs the speed offset, the flow change of the path is monitored in real time, and the flow change of the path of the master source device is inversely distributed according to the weight proportion of the remaining paths to obtain the target compensation flow of all delivery paths; A local closed-loop controller is constructed for each delivery path, with the target compensation flow as the set value and the real-time collected path delivery flow as the feedback value. The speed adjustment instruction is generated according to the output of the closed-loop controller, and the speed adjustment instruction is distributed to all water pump devices in the delivery path according to the preset weight, to drive the water pump devices to adjust the speed synchronously.

9. A water pump set fault early warning system based on Internet of Things sensors, for implementing the water pump set fault early warning method based on Internet of Things sensors in any one of claims 1-8, characterized in that, It includes: A data acquisition module for collecting sensing data of all water pump devices through sensing devices deployed at key mechanical parts of the water pump group devices, wherein the sensing data includes device vibration spectrum and fluid pressure pulsation characteristic data; A data analysis module for obtaining the pump group pipe network topology, and constructing and solving a fluid coupling strength matrix of each pipe section based on the fluid pressure pulsation characteristic data to obtain the fluid coupling strength coefficient of each pipe section; The correlation matching module is configured to, when vibration spectrum energy of any water pump device exceeds a preset alert value, mark the water pump device as a target device, extract a vibration main frequency of the target device and a pressure pulsation main frequency of a directly connected pipeline of the target device, and calculate an environment adaptive matching degree of the target device based on a fluid coupling strength coefficient of the connected pipeline; The alarm generation module is configured to, if the environment adaptive matching degree is greater than or equal to a preset matching degree threshold, control an adjacent device directly connected to the target device through a pipeline to perform a rotating speed offset, synchronously acquire a vibration amplitude deviation value of the target device before and after the rotating speed offset, if the deviation value is greater than a preset deviation threshold, generate a conducted resonance alarm, if the deviation value is less than or equal to the preset deviation threshold, generate a body abnormality alarm; The processing optimization module is configured to, when the body abnormality alarm is generated, issue a device fault early warning, and when the conducted resonance alarm is generated, not issue the device fault early warning and perform a coordinated speed regulation of linkage compensation.

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