Intelligent water pump driving system, method, equipment, medium and product

Abstract

The invention discloses a water pump intelligent driving system, method and device, a medium and a product, and relates to the technical field of water pump control. The driving detection unit is used for detecting operation parameters of the water pump, and the operation parameters at least comprise electrical parameters, mechanical vibration parameters, temperature parameters and hydraulic parameters; the edge calculation unit is used for receiving the operation parameters transmitted and detected by the driving detection unit, performing multi-source information fusion and intelligent analysis, generating a frequency control instruction according to an analysis result and sending the frequency control instruction to the variable frequency driving unit; and the remote control unit is in communication connection with the edge calculation unit and used for receiving a user instruction, sending the user instruction to the edge calculation unit and receiving and displaying the system state information and the early warning information from the edge calculation unit. According to the application, the operation efficiency of the water pump can be improved, and the energy waste can be reduced.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of water pump control, in particular to a water pump intelligent driving system, method, equipment, medium and product. BACKGROUND

[0002] As a core power and fluid conveying equipment, water pumps account for a significant proportion of global industrial total electricity consumption. For a long time, many key pump stations, water supply systems and water pumps in process flow have relied on traditional control schemes with mature technology but low efficiency. These schemes generally adopt the basic mode of "asynchronous motor running at constant speed combined with mechanical valve regulation". In this mode, the motor always runs at a fixed speed (such as the rated speed corresponding to 50Hz), and when the system required flow or pressure changes, the operator adjusts the opening of the pump outlet valve by hand or electrically to change the pipeline resistance characteristics to meet the working condition requirements. This "pump throttling" operation mode causes a large amount of electric energy to be wasted on the throttling loss of the valve, resulting in very low system overall operating efficiency and serious energy waste. Moreover, the existing water pump unit control system is an "information island", and all operations and state monitoring must rely on personnel on site. The operator cannot remotely obtain real-time key information such as the operating efficiency and health status of the water pump, and daily operation and maintenance completely relies on regular on-site inspection, and the equipment condition is judged by experience methods such as "listening, looking and touching". This mode has high labor intensity, strong subjectivity, cannot realize predictive maintenance, and has low management efficiency. SUMMARY

[0003] The purpose of the present application is to provide a water pump intelligent driving system, method, equipment, medium and product, which can improve the operating efficiency of the water pump and reduce energy waste.

[0004] To achieve the above purpose, the present application provides the following solutions: In a first aspect, the present application provides a water pump intelligent driving system, comprising: a variable frequency driving unit, the variable frequency driving unit being used for controlling the switch and operating power of the water pump; a driving detection unit, the driving detection unit being used for detecting operating parameters of the water pump, the operating parameters at least including electrical parameters, mechanical vibration parameters, temperature parameters and hydraulic parameters; an edge computing unit, the edge computing unit being used for receiving the detected operating parameters transmitted by the driving detection unit, performing multi-source information fusion and intelligent analysis, and generating a frequency control instruction according to the analysis result and sending the frequency control instruction to the variable frequency driving unit; a remote control unit, the remote control unit being in communication connection with the edge computing unit, used for receiving user instructions and sending the user instructions to the edge computing unit, and receiving and displaying system state information and early warning information from the edge computing unit.

[0005] Optionally, the edge computing unit comprises a multi-source information fusion module and an intelligent analysis module, wherein: The multi-source information fusion module is configured to perform fusion processing on the operation parameters from the drive detection unit. The intelligent analysis module is internally provided with an energy efficiency calculation model and a health assessment model, configured to calculate the operation efficiency of the water pump and assess the mechanical health state of the water pump in real time based on the fusion-processed data, and generate the frequency control instruction or warning information based on the assessment results.

[0006] Optionally, the drive detection unit comprises: An electrical parameter acquisition board configured to acquire three-phase current and voltage of the water pump motor. A vibration sensor installed on a bearing seat or a motor housing of the water pump and configured to acquire a vibration signal. A temperature sensor installed on a winding of the motor and / or a bearing seat of the water pump and configured to acquire a temperature signal. A pressure sensor and a flow meter installed on an inlet and / or outlet pipeline of the water pump and configured to acquire a pressure signal and a flow signal, respectively. Each sensor, the electrical parameter acquisition board, and the flow meter are connected to the edge computing unit through a signal conditioning circuit and a communication bus.

[0007] Optionally, the variable frequency drive unit is a frequency converter dedicated to driving a permanent magnet synchronous motor and adopts an open-loop sensorless vector control method; the variable frequency drive unit comprises: A rectifier circuit, a DC bus, an inverter circuit, and a control board, wherein the rectifier circuit, the DC bus, and the inverter circuit are connected in sequence, and an output end of the inverter circuit is connected to the water pump motor; the control board is connected to the DC bus and the inverter circuit through signal acquisition lines and drive lines, respectively, and is configured to execute a synchronous vector control algorithm, monitor internal electrical parameters in real time, and upload the internal electrical parameters to the edge computing unit.

[0008] Optionally, the remote control unit comprises: A host computer application software, a mobile terminal application software, and a voice interaction module; wherein the mobile terminal application software supports near-field communication with the edge computing unit through Bluetooth; and the voice interaction module is integrated with a voice recognition chip and is configured to realize local voice wake-up and instruction recognition.

[0009] Optionally, the water pump intelligent drive system further comprises a power distribution and protection unit, and the power distribution and protection unit comprises: The main circuit breaker, the AC reactor and the filter device; the input end of the main circuit breaker is connected with an external power supply, and the output end is connected to the input end of the variable frequency driving unit through the AC reactor and the filter device in sequence, for providing power access, short circuit protection and harmonic suppression.

[0010] In a second aspect, the present application provides a water pump intelligent driving method, comprising: The driving detection unit collects multi-dimensional operation data of the water pump unit in real time; The edge computing unit receives the operation state data, and performs multi-source information fusion and intelligent analysis, the intelligent analysis including real-time energy efficiency evaluation and optimization based on an energy efficiency calculation model, and mechanical fault prediction and health degree evaluation based on a health evaluation model; The edge computing unit generates optimized frequency control instructions and early warning information according to the results of intelligent analysis; The edge computing unit sends the frequency control instructions to the variable frequency driving unit to adjust the motor speed of the water pump, forming a closed-loop control; at the same time, the edge computing unit sends the early warning information to the remote control unit for display.

[0011] In a third aspect, the present application provides a computer device, comprising a memory, a processor, a computer program stored in the memory and executable on the processor, and the processor executes the computer program to realize the steps of the water pump intelligent driving system method according to any one of the above.

[0012] In a fourth aspect, the present application provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to realize the steps of the water pump intelligent driving system method according to any one of the above.

[0013] In a fifth aspect, the present application provides a computer program product, comprising a computer program, and the computer program is executed by a processor to realize the steps of the water pump intelligent driving system method according to any one of the above.

[0014] According to the specific embodiments provided by the present application, the following technical effects are disclosed: This application provides an intelligent pump drive system, method, device, medium, and product. First, a drive detection unit detects the pump's operating parameters. Then, an edge computing unit analyzes the pump's real-time operating parameters. Finally, a variable frequency drive unit adjusts the motor's operating power to precisely match dynamically changing load demands. This fundamentally eliminates the high-energy-consumption mode of traditional "constant speed operation + valve throttling," directly solving the problem of "extremely low energy efficiency" in existing technologies. The energy-saving effect is significant, and operating costs are greatly reduced. Simultaneously, the remote control unit enables remote system control, allowing managers to monitor system status, analyze historical data, and remotely issue start / stop and parameter setting commands from anywhere in the world via computer or mobile phone. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a schematic diagram of the functional modules of a water pump intelligent drive system according to an embodiment of this application; Figure 2 This is a flowchart illustrating the operation of an intelligent water pump drive system according to one embodiment of this application. Figure 3 A flowchart illustrating a smart pump driving method provided in an embodiment of this application; Figure 4 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application. Detailed Implementation

[0017] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0018] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0019] In one exemplary embodiment, such as Figure 1 As shown, a smart pump drive system is provided, comprising: A variable frequency drive unit for controlling the switching and operating power of the water pump; A drive detection unit for detecting operating parameters of the water pump, the operating parameters including at least electrical parameters, mechanical vibration parameters, temperature parameters, and hydraulic parameters; An edge computing unit for receiving the detected operating parameters transmitted by the drive detection unit, performing multi-source information fusion and intelligent analysis, and generating control instructions according to the analysis results and sending the control instructions to the variable frequency drive unit; A remote control unit in communication connection with the edge computing unit, for receiving user (in this embodiment, a management personnel) instructions and sending the instructions to the edge computing unit, and receiving and displaying system state information and early warning information from the edge computing unit.

[0020] In this embodiment, the edge computing unit is used to analyze real-time working condition parameters of the water pump, and then the motor speed of the water pump is continuously adjusted to accurately match the dynamically changing load demand, thereby fundamentally abandoning the high energy consumption mode of the traditional "constant speed operation + valve throttling", directly solving the "extremely low energy efficiency" of the prior art, and significantly saving energy and greatly reducing operating costs.

[0021] As an optional embodiment, the edge computing unit includes a multi-source information fusion module and an intelligent analysis module, wherein: The multi-source information fusion module is used to perform fusion processing on the operating parameters from the drive detection unit; The intelligent analysis module has an energy efficiency calculation model and a health assessment model built in, for calculating the operating efficiency of the water pump and assessing the mechanical health state of the water pump in real time based on the fusion-processed data, and generating the frequency control instructions or early warning information based on the assessment results.

[0022] In the present application, the core processor board of the edge computing unit adopts a Huawei Atlas 200 AI acceleration module, which integrates CPU and AI processing cores (GPU / NPU) and has strong edge-side AI inference capability. It is equipped with 8GB LPDDR4 memory and expands a 500GB SATA SSD solid state disk (such as Samsung 860 EVO) for storing high-frequency acquisition time series data such as vibration waveforms and temperature sequences, providing support for historical data analysis and model training.

[0023] In the embodiment of the application, the edge computing unit is configured with an RS-485 communication board (such as a CAN, HAT, etc. commercially available expansion board), connected through the GPIO pin of the core processor, forming a Modbus-RTU master station. The bus connects the frequency conversion drive unit and each sensor / acquisition board in the drive detection unit, for real-time reading of motor current, voltage, output frequency, and vibration, temperature, pressure, flow, etc. data, while issuing frequency setting values.

[0024] In the embodiment of the application, the core processor board is installed with a Quectel RM500Q 5G module (through a Mini PCI-E interface) and an Intel AX200 Wi-Fi 6 / Bluetooth 5.0 module (through an M.2 interface). The 5G / Wi-Fi is used for stable and high-speed data interaction with the cloud server of the remote control unit; the Bluetooth supports on-site operation and maintenance personnel to perform near-field wireless configuration, debugging and data viewing through a mobile phone App.

[0025] In the embodiment of the application, the edge computing unit runs an embedded Linux system, on which a multi-source information fusion module and an intelligent analysis module are deployed, wherein: The multi-source information fusion module is used to perform time synchronization, dimension normalization and feature extraction on data from different sensors and different physical dimensions (current-A, vibration-mm / s, temperature-℃, pressure-kPa, flow-m 3 / h) to form a unified "state vector" describing the current comprehensive state of the system.

[0026] The intelligent analysis module includes an energy efficiency calculation model and a health assessment model, wherein: The energy efficiency calculation model calculates the instantaneous operating efficiency η of the water pump in real time. According to the formula: η = (QHρg) / (3600P 输入 ), the operating efficiency of the water pump can be obtained by detecting the flow, pressure, input power, etc. Wherein Q is the actual flow (m 3 / h), H is the actual lift (m, converted from the pressure difference at the inlet and outlet), ρ is the fluid density (kg / m 3 ), g is the acceleration of gravity (m / s 2 ), P 输入 is the motor input power (KW, calculated from the output electrical parameters of the frequency converter). The edge computing unit continuously monitors the efficiency η and compares it with the stored optimal efficiency curve of the water pump model. When the operating point deviates from the high efficiency area, the model will calculate the fine frequency command to make the system return to the high efficiency point operation.

[0027] The health assessment model adopts a combination of a rule-based expert system and a lightweight machine learning model (such as a model for pattern recognition of vibration spectrum features) to perform health assessment. For example, the time-domain signals collected by the vibration sensor are subjected to fast Fourier transform (FFT) to obtain a frequency spectrum; the amplitude variation of a specific frequency band (such as bearing pass frequency, impeller pass frequency) is analyzed, for example, a threshold rule is set: when the amplitude of the bearing characteristic frequency exceeds 50% of the baseline value for consecutive cycles, a “suspected bearing wear” warning is triggered; when the amplitude of the 1x frequency corresponding to the unbalanced force significantly increases, a “rotor imbalance” warning is triggered. For another example, the rate of change of the temperature of the bearing and winding is monitored. Under normal circumstances, the temperature rises after startup and tends to be stable. If it is found that the temperature abnormally rises during stable operation, or the temperature rise rate is much higher than that of the same type of historical working conditions, it may indicate bearing lubrication failure or winding insulation problem, triggering the corresponding warning.

[0028] In the constant pressure water supply mode, the edge computing unit compares the outlet pressure Pactual with the set value Pset, and calculates the current most energy-efficient frequency instruction Fset eff through the built-in PID combined with the AI optimization algorithm.

[0029] In the embodiments of the present application, according to η (pump efficiency) = QHpg / 3600 , the flow rate, pressure, input power, and the running efficiency of the pump can be obtained. Table 1 is the data detected from the actual work of the water pump: Table 1 Water pump efficiency under different flow rates

[0030] In the embodiments of the present application, the vibration signals of the water pump with model number 80-50-200 are analyzed, and the difference between the rotational frequency amplitude ΦA and the bearing characteristic frequency amplitude ΦB is calculated. The preset rule is: if ΦA-ΦB ≤ 0.5 mm / s (green light zone), the operation is normal; if 0.5 mm / s < ΦA-ΦB < 0.7 mm / s (yellow light zone), it is prompted that “the bearing is slightly worn, and attention is suggested”; if ΦA-ΦB ≥ 0.7 mm / s (red light zone), a high-priority alarm of “the bearing is severely worn, and shutdown for maintenance is suggested” is immediately generated.

[0031] In the embodiments of the present application, the user inputs new working condition requirements (such as flow rate 145 m 3 / h, head 118 m) through the App of the remote control unit. The edge computing unit calculates the frequency instruction Fset eff according to the water pump similarity law: Q1 / Q2=n1 / n2, H1 / H2=(n1 / n2) 2, wherein Q1 represents the flow rate of the water pump under the first working condition, Q2 represents the flow rate of the water pump under the second working condition, n1 represents the rotating speed of the water pump under the first working condition, n2 represents the rotating speed of the water pump under the second working condition, H1 represents the head of the water pump under the first working condition, and H2 represents the head of the water pump under the second working condition. In combination with the known best efficiency point parameters (such as a flow rate of 120 m 3 / h, a head of 82 m, and a rotating speed of 2950 r / min), the target rotating speed required to meet the new working condition is quickly calculated to be about 3600 r / min, and a corresponding frequency instruction is generated.

[0032] In the embodiment of the application, the edge computing unit delivers the finally determined frequency instruction Fset to the variable frequency drive unit through the Modbus bus, the variable frequency drive unit adjusts the output, and the rotating speed of the motor is changed. The working condition of the water pump changes, and the new state data is detected and fed back, forming a closed loop.

[0033] In this implementation, by integrating the drive detection unit (multiple types of sensors such as vibration and temperature) and the edge computing unit (built-in health assessment model), the mechanical health status of the water pump can be monitored in real time. Through intelligent analysis of data such as vibration spectrum characteristics and temperature change trends, potential risks can be identified at the fault inception stage (such as slight wear of the bearing and slight imbalance of the rotor), and early warnings can be issued. This changes the maintenance mode from “after-the-fact maintenance” or “regular maintenance” to “predictive maintenance”, allowing users to schedule planned maintenance before the equipment is severely damaged, directly addressing the shortcomings of the prior art “single protection function and passivity”, and maximizing the avoidance of unplanned downtime to ensure production continuity.

[0034] In the embodiment of the application, the optimized and lightweight deep reinforcement learning (DRL) model can be deployed in the edge computing unit, wherein the input of the model is the aforementioned “state vector” (calculated by the multi-source information fusion module), including the set pressure P_set, the actual pressure P_actual, the actual flow rate Q_actual, the current frequency F_current, the motor current I_motor, the vibration V_vibration, and the bearing temperature T_bearing. The output of the model is the optimal frequency setting value F_set or the frequency adjustment amount ΔF. The goal of the model is to maximize the long-term cumulative reward (the reward function can be defined as the score of efficient operation minus the score of equipment loss) under the premise of meeting the process requirements (such as constant pressure). The edge computing unit uses the model to make real-time decisions, which can achieve adaptive energy-saving control.

[0035] As an optional implementation, the drive detection unit includes: An electrical parameter acquisition board for acquiring three-phase current and voltage of the water pump motor; A vibration sensor is installed on the bearing seat or motor housing of the water pump to collect vibration signals. A temperature sensor is installed on the winding of the motor and / or the bearing seat of the water pump to collect temperature signals. A pressure sensor and a flow meter are installed on the inlet and / or outlet pipe of the water pump to collect pressure signals and flow signals, respectively. Each sensor is connected to the edge computing unit through a signal conditioning circuit and a communication bus.

[0036] In the embodiments of the present application, the drive detection unit is a distributed sensor network system, which is the physical basis for the system to realize "state perception" and "predictive maintenance".

[0037] In the embodiments of the present application, the electrical parameter acquisition board adopts an open-type current transformer and a voltage sampling circuit, which is installed on the power cable from the frequency converter to the motor, or directly uses the internal communication of the frequency converter to obtain high-precision electrical parameters. The three-phase current, voltage, power factor, etc. are uploaded through the RS-485 bus in the Modbus-RTU protocol.

[0038] In the embodiments of the present application, the vibration sensor adopts an industrial-grade piezoelectric vibration acceleration sensor, which is installed in the vertical and horizontal directions of the non-drive end bearing seat of the water pump and the drive end housing of the motor. The signal is converted to a 4-20 mA or direct digital signal for uploading.

[0039] In the embodiments of the present application, the temperature sensor adopts a PT100 platinum resistance temperature sensor, which is embedded in the internal stator winding of the motor (pre-buried) and installed on the outer surface of the bearing seat of the water pump. The signal is converted to a standard signal by a temperature transmitter.

[0040] In the embodiments of the present application, the pressure sensor and the flow meter are installed on the inlet and / or outlet pipe of the water pump to output a 4-20 mA standard signal.

[0041] In the embodiments of the present application, all sensor signals are finally collected into the signal acquisition module in the cabinet (which can be integrated on the expansion IO board of the edge computing unit), and after unified processing, they are uploaded to the edge computing unit.

[0042] As an optional implementation, the frequency conversion drive unit is a frequency converter dedicated to driving a permanent magnet synchronous motor, which adopts an open-loop sensorless vector control method; the frequency conversion drive unit comprises: a rectifier circuit, a DC bus, an inverter circuit, and a control board, wherein the rectifier circuit, the DC bus, and the inverter circuit are connected in sequence, and the output end of the inverter circuit is connected with the water pump motor; the control board is connected with the DC bus and the inverter circuit through signal acquisition lines and drive lines, respectively, and the control board is used to execute a synchronous vector control algorithm, and to monitor internal electrical parameters in real time and upload them to the edge computing unit.

[0043] In the embodiment of the present application, the rectifier circuit is used as the input end of the frequency conversion driving unit, for converting three-phase alternating current of the power supply into direct current. The direct current bus capacitor is used for filtering and energy storage. The inverter circuit comprises an IGBT module, for converting the direct current into three-phase alternating current with adjustable frequency and voltage.

[0044] In the embodiment of the present application, the control board monitors the direct current bus voltage and the inverter output current, receives external instructions through the communication line, and sends PWM signals to control the IGBT of the inverter circuit through the driving line, so as to realize accurate control of the entire energy conversion process in a closed loop (at the internal algorithm level).

[0045] In the embodiment of the present application, the control board executes an advanced synchronous vector control algorithm, estimates the rotor position and speed in real time through accurate mathematical calculation of the motor model, and realizes high-precision torque and speed control without the need to install a mechanical encoder. This improves the system reliability and reduces the installation and maintenance complexity.

[0046] In the embodiment of the present application, the frequency conversion driving unit not only receives instructions from the edge computing unit, but also feeds back key operating parameters in the unit, such as the direct current bus voltage, the inverter output current, the IGBT module temperature and other parameters, to the edge computing unit in real time. These parameters participate in the system-level energy management analysis and overall health diagnosis.

[0047] In the embodiment of the present application, the motor can be slowly accelerated by controlling the output frequency to smoothly rise from 0 Hz to the target value, and the starting impact is completely eliminated.

[0048] In this implementation, the soft start and soft stop of the motor are realized through the frequency conversion driving unit. The starting current can be limited within 1.2 times of the rated current, and the severe impact of 5-7 times of the starting current on the power grid and mechanical parts (bearings, shaft seals, impellers) during direct start at power frequency is completely eliminated. During operation, the torque output is smooth, and water power fluctuations and mechanical stress mutations are avoided. This directly solves the problem of "extensive control and serious equipment wear" in the prior art, effectively reduces the equipment failure rate, significantly prolongs the service life of the water pump unit, and improves the operation reliability.

[0049] As an optional implementation, the remote control unit comprises: The upper computer application software, the mobile terminal application software and the voice interaction module; wherein the mobile terminal application software supports near field communication with the edge computing unit through Bluetooth; the voice interaction module is integrated with a voice recognition chip, for realizing local voice wake-up and instruction recognition.

[0050] In the embodiments of the application, the remote control unit includes a cloud server, the cloud server is deployed on an Internet cloud platform, is responsible for receiving and storing massive historical data from multiple edge computing units, running more complex AI models (such as long-term training, optimization and application of a DRL model), and providing a Web version of a host computer software to a manager. The software interface of the host computer application software can display the real-time state, efficiency curve, health score and alarm list of all connected water pumps, support historical data query, report generation and remote parameter setting.

[0051] As an optional implementation, an AI model (such as a DRL model) can be deployed in the cloud or the host computer application software to realize autonomous intelligent operation of the water pump, and the specific control process includes: The edge computing unit collects all input parameters at a frequency of several times per second, and the input parameters include demand parameters and operating state parameters. The edge unit packs the processed state data and sends it to the trained AI model. The AI model calculates the optimal frequency command according to the current state and issues the optimal frequency command to the edge computing unit. The edge unit performs safety check (such as amplitude limiting) on the command and issues it to the frequency drive unit through the communication bus (Modbus). The frequency drive unit drives the water pump motor to operate at a new frequency, changing the water pump operating condition.

[0052] In the embodiments of the application, the inputs of the AI model are the real-time operating state parameters and demand parameters of the water pump, including but not limited to: actual pressure at the outlet of the water pump, actual flow rate at the outlet of the water pump, current output frequency of the frequency converter, three-phase current of the motor, total vibration intensity of the water pump, bearing temperature of the water pump, winding temperature of the water pump motor, real-time operating efficiency of the water pump, system set pressure, system set flow rate and system set liquid level.

[0053] As an optional implementation, the optimal frequency command can include the following forms: directly outputting a frequency setting value, a frequency increment, and a PID parameter adaptive control command. Among them, directly outputting a frequency setting value is the most direct way, and a frequency increment means increasing or decreasing a value based on the last frequency, which is more smooth. In addition, the PID parameter adaptive control command means outputting a set of optimized PID parameters to the edge computing unit, so that the PID controller of the edge computing unit uses these new parameters to run, realizing adaptive control.

[0054] In the embodiments of the present application, the mobile terminal application software (App) supports Android and iOS systems. In addition to the basic monitoring function of the cloud upper computer, it also supports direct connection with the on-site edge computing unit through Bluetooth. After the management personnel arrive at the pump house, they can perform on-site debugging, parameter reading and manual control through the App Bluetooth connection, without the need to open the control cabinet or operate the touch screen, which is convenient and safe.

[0055] In the embodiments of the present application, all key data, analysis results and alarm information are uploaded to the cloud of the remote control unit and the App through the 5G / Wi-Fi module of the edge computing unit. The management personnel can remotely monitor and receive early warnings. For example, after receiving a yellow light warning, they can arrange for short-term planned maintenance to avoid sudden shutdown.

[0056] In the embodiments of the present application, the voice interaction module is integrated on the field control cabinet panel. A low-power AI voice chip such as CI1302 can be used. The chip has a built-in wake-up word and command word recognition model, which can communicate with the main control MCU of the edge computing unit through the UART interface. For example, the user can say "start the water pump" or "set the pressure to 50 meters". After the system recognizes the instruction, it will execute and provide voice feedback, providing convenience for on-site operation.

[0057] In this implementation, by integrating the remote control unit, the supporting upper computer and the mobile terminal application software, and using the edge computing unit as the Internet of Things gateway, all key operation data, state information and early warning alarms can be transmitted in real time to the management platform. The management personnel can monitor the system status, analyze historical data and remotely issue start / stop and parameter setting instructions through a computer or a mobile phone anywhere in the world. The Bluetooth function of the mobile terminal application software also provides a convenient on-site debugging method, directly solving the problems of "system isolation and difficult operation and maintenance" and "lack of remote management capability" in the prior art, greatly reducing the dependence on artificial on-site inspection, reducing the operation and maintenance labor cost, and realizing the modernization and intelligentization of operation and maintenance management.

[0058] As an optional implementation, it further includes a power distribution and protection unit, which includes: A main circuit breaker, an AC reactor and a filter device. The input end of the main circuit breaker is connected to an external power source, and the output end is connected to the input end of the frequency conversion driving unit through the AC reactor and the filter device in sequence, for providing power access, short circuit protection and harmonic suppression.

[0059] In the embodiments of the present application, the main circuit breaker is used to provide manual isolation function and short circuit protection function. The AC reactor is connected in series between the main circuit breaker and the input terminal of the frequency conversion driving unit, for suppressing the inrush current when the frequency converter is closed, reducing the pollution of high-order harmonics generated by the frequency converter rectifier circuit to the power grid (harmonic suppression), and buffering when the power grid voltage fluctuates.

[0060] In the embodiments of the present application, the filter device adopts an EMI filter, which is installed after the AC reactor and before the input terminal of the frequency converter, for filtering out high-frequency interference from the power grid and preventing high-frequency switching noise generated by the frequency converter from being conducted to the power grid, thereby meeting the electromagnetic compatibility (EMC) requirements.

[0061] In the embodiments of the present application, the power distribution and protection unit further comprises an anti-reverse diode, which is connected in parallel with a DC bus circuit inside the frequency conversion driving unit. The anti-reverse diode prevents regenerative energy generated after the motor turns into a generator when the water pump is stopped due to inertia or is pushed back by high fluid from flowing back into the rectification part of the frequency converter, thereby protecting the power device.

[0062] Based on the same inventive concept, the embodiments of the present application also provide a water pump intelligent driving method for implementing the above-mentioned water pump intelligent driving system. The implementation scheme for solving the problem provided by the method is similar to the implementation scheme described in the above system, and therefore the specific limitations in one or more water pump intelligent driving method embodiments provided below can refer to the limitations of the water pump intelligent driving system described above, which will not be described here again.

[0063] In one exemplary embodiment, as shown in Figures 2-3 a water pump intelligent driving method is provided, which specifically comprises: Step 201, collecting multi-dimensional running parameters of the water pump unit in real time through the driving detection unit; Step 202, the edge computing unit receives the running state data and performs multi-source information fusion and intelligent analysis, the intelligent analysis includes real-time energy efficiency evaluation and optimization based on an energy efficiency calculation model, and mechanical fault prediction and health degree evaluation based on a health evaluation model; Step 203, the edge computing unit generates optimized frequency control instructions and warning information according to the results of intelligent analysis; Step 204, issuing the frequency control instructions to the frequency conversion driving unit to adjust the motor speed of the water pump to form a closed-loop control; at the same time, the warning information is sent to the remote control unit for display.

[0064] As an optional implementation, the water pump intelligent driving method further comprises: Step 205, the remote control unit receives user instructions and sends the instructions to the edge computing unit, the edge computing unit generates frequency control instructions and issues them to the frequency conversion driving unit, and the frequency conversion control unit controls the switch and operating power of the water pump, thereby realizing remote control.

[0065] In one exemplary embodiment, a computer device is provided, which may be a server or a terminal, and its internal structure diagram may be as follows. Figure 4 As shown, this computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The database stores intelligent pump drive data. The I / O interfaces are used for exchanging information between the processor and external devices. The communication interface is used for communication with external terminals via a network connection. When the computer program is executed by the processor, it implements an intelligent pump drive method.

[0066] Those skilled in the art will understand that Figure 4 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0067] In one exemplary embodiment, a computer device is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above-described method embodiments.

[0068] In one exemplary embodiment, a computer-readable storage medium is provided storing a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0069] In one exemplary embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0070] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0071] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer readable storage medium, and when the computer program is executed, the processes of the above-mentioned embodiments of the methods can be included. Any reference to a memory, a database or other medium used in the embodiments provided in the present application can include at least one of a non-volatile and a volatile memory. The non-volatile memory can include a read-only memory (ROM), a magnetic tape, a floppy disk, a flash memory, an optical storage, a high-density embedded non-volatile memory, a resistive random access memory (ReRAM), a magnetoresistive random access memory (MRAM), a ferroelectric random access memory (FRAM), a phase change memory (PCM), a graphene memory, etc. The volatile memory can include a random access memory (RAM) or an external cache memory, etc. As an illustration but not limitation, the RAM can be in various forms, such as a static random access memory (SRAM) or a dynamic random access memory (DRAM), etc.

[0072] The database involved in the embodiments provided in the present application can include at least one of a relational database and a non-relational database. The non-relational database can include a distributed database based on a blockchain, etc., without being limited thereto. The processor involved in the embodiments provided in the present application can be a general-purpose processor, a central processing unit, a graphics processing unit, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., without being limited thereto.

[0073] The technical features of the above embodiments can be combined arbitrarily. In order to make the description concise, all possible combinations of the technical features in the above embodiments are not described, however, as long as the combinations of the technical features do not exist contradictory, they should be considered as the scope of the present application.

[0074] The principles and implementation modes of the present application are described by using specific examples in the present application. The above embodiments are only used to help understand the method and its core idea of the present application; meanwhile, for those skilled in the art, according to the idea of the present application, the specific implementation mode and application range can be changed. In conclusion, the content of the present application should not be understood as a limitation.

Claims

1. A smart pump drive system, characterized in that, The intelligent pump drive system includes: A variable frequency drive unit, which is used to control the switching on and off of the water pump and its operating power; A drive detection unit is used to detect the operating parameters of the water pump, which include at least electrical parameters, mechanical vibration parameters, temperature parameters, and hydraulic parameters. An edge computing unit is used to receive the operating parameters detected by the drive detection unit, perform multi-source information fusion and intelligent analysis, and generate frequency control commands based on the analysis results and send them to the frequency conversion drive unit. A remote control unit, which is communicatively connected to the edge computing unit, is used to receive user commands and send them to the edge computing unit, as well as to receive and display system status information and early warning information from the edge computing unit.

2. The intelligent pump drive system according to claim 1, characterized in that, The edge computing unit includes a multi-source information fusion module and an intelligent analysis module, wherein: The multi-source information fusion module is used to fuse the operating parameters from the drive detection unit; The intelligent analysis module has a built-in energy efficiency calculation model and a health assessment model, which are used to calculate the pump operating efficiency and assess the pump mechanical health status in real time based on the fused data, and generate the frequency control command or early warning information based on the assessment results.

3. The intelligent pump drive system according to claim 1, characterized in that, The drive detection unit includes: Electrical parameter acquisition board, used to acquire the three-phase current and voltage of the water pump motor; Vibration sensors are installed in the bearing housing or motor housing of water pumps to collect vibration signals; Temperature sensors are installed in the windings of motors and / or the bearing housings of water pumps to collect temperature signals. Pressure sensors and flow meters are installed in the inlet and / or outlet pipes of the water pump to collect pressure signals and flow signals, respectively. Each sensor, electrical parameter acquisition board, and flow meter is connected to the edge computing unit via a signal conditioning circuit and a communication bus.

4. The intelligent pump drive system according to claim 1, characterized in that, The variable frequency drive unit is a frequency converter specifically designed for driving permanent magnet synchronous motors, employing an open-loop sensorless vector control method; the variable frequency drive unit includes: The system includes a rectifier circuit, a DC bus, an inverter circuit, and a control board. The rectifier circuit, DC bus, and inverter circuit are connected in sequence, and the output terminal of the inverter circuit is connected to the water pump motor. The control board is connected to the DC bus and the inverter circuit through signal acquisition lines and drive lines, respectively. The control board is used to execute a synchronous vector control algorithm and monitor internal electrical parameters in real time and upload them to the edge computing unit.

5. The intelligent pump drive system according to claim 1, characterized in that, The remote control unit includes: The system includes host computer application software, mobile application software, and a voice interaction module; wherein the mobile application software supports near-field communication with the edge computing unit via Bluetooth; and the voice interaction module integrates a voice recognition chip for local voice wake-up and command recognition.

6. The intelligent pump drive system according to claim 1, characterized in that, The intelligent pump drive system also includes a power distribution and protection unit, which comprises: The main circuit breaker, AC reactor, and filter components are provided. The input terminal of the main circuit breaker is connected to an external power source, and the output terminal is connected to the input terminal of the frequency converter drive unit in sequence through the AC reactor and the filter components, which are used to provide power input, short-circuit protection, and harmonic suppression.

7. A method for intelligently driving a water pump, characterized in that, The intelligent pump driving method includes: The multi-dimensional operating parameters of the water pump unit are collected in real time through the drive detection unit; The edge computing unit receives the operating status data and performs multi-source information fusion and intelligent analysis. The intelligent analysis includes real-time energy efficiency assessment and optimization based on the energy efficiency calculation model, and mechanical fault prediction and health assessment based on the health assessment model. The edge computing unit generates optimized frequency control commands and early warning information based on the results of intelligent analysis; The edge computing unit sends the frequency control command to the variable frequency drive unit to adjust the motor speed of the water pump, forming a closed-loop control; at the same time, the edge computing unit sends the early warning information to the remote control unit for display.

8. A computer device, comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor executes the computer program to implement the steps of the intelligent pump drive method of claim 7.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the intelligent pump drive method of claim 7.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the intelligent pump drive method of claim 7.

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