Integrated intelligent flow sensor and dynamic compensation system and method thereof

Abstract

The invention discloses an integrated intelligent flow sensor and a dynamic compensation system and method thereof.The sensor is of an integrated flow channel structure, a flow sensor, a temperature sensor and a pressure sensor are integrated, and compact design and signal isolation are achieved; the system calls a fluid physical property database by synchronously collecting three-parameter signals, and dynamically calculates the fluid density based on real-time temperature and pressure data; according to the method, the volume flow under the original working condition is dynamically compensated, and the high-precision volume flow and the directly-output mass flow are obtained. Flow measurement is fundamentally upgraded into'multi-parameter-material flow 'conversion based on the physical principle, and high-precision measurement is still guaranteed when the fluid state fluctuates.

Description

Technical Field

[0001] This invention belongs to the field of industrial process control, and specifically relates to an integrated intelligent flow sensor and its dynamic compensation system and method. Background Technology

[0002] In industrial process control, energy management, water monitoring, and HVAC systems, fluid flow rate, temperature, and pressure are three fundamental and interrelated physical parameters. Synchronous and accurate monitoring of these parameters is of paramount importance. System efficiency assessment: For example, in a cooling system, knowing only the water flow rate is insufficient to assess heat dissipation efficiency. The inlet and outlet water temperatures and system pressure must be considered to calculate the actual heat removed.

[0003] Process control optimization: In chemical processes, the reaction rate is closely related to the fluid temperature and pressure. It is necessary to adjust the flow rate in real time according to these parameters to ensure the stability and safety of the reaction.

[0004] Energy consumption metering and billing: For compressible fluids such as steam and compressed air, their energy transfer capacity (enthalpy) is strongly dependent on temperature and pressure. Measuring only volumetric flow rate is insufficient to accurately measure energy consumption; mass flow rate or heat must be calculated through temperature and pressure compensation.

[0005] Equipment health and fault early warning: Abnormal wear of pumps or valves, pipeline blockage or leakage often cause characteristic changes in the relationship between flow rate, pressure, and temperature. Simultaneous monitoring of these three parameters helps in early diagnosis and early warning.

[0006] However, traditional technical solutions typically employ discrete sensors—i.e., independent flow meters, temperature sensors, and pressure transmitters—for measurement. This approach suffers from inherent drawbacks such as low system integration, complex installation, high cost, poor signal synchronization, and difficulties in data correlation analysis. In particular, the data "time lag" caused by differences in installation location and response time between different sensors severely impacts the accuracy of advanced control and diagnostic algorithms based on multi-parameter fusion.

[0007] The existing solution has the following problems: Lack of crucial pressure parameters: This is the most fundamental deficiency. Without pressure information, the system cannot determine the fluid's density and phase (such as whether it is near its boiling point or undergoing vaporization). For gases or vapors, pressure is the primary factor determining density; for liquids, their physical properties can also undergo subtle but critical changes under high pressure.

[0008] The flow compensation model is overly simplistic: Existing solutions primarily compensate for temperature, and the models are typically simple linear or polynomial fits, failing to establish a high-precision physical compensation model that integrates temperature and pressure based on fluid property equations (such as equations of state). Therefore, the output "flow rate" is essentially an uncorrected "operating condition volumetric flow rate," rather than a "standard condition volumetric flow rate" or "mass flow rate."

[0009] Inability to directly output mass flow rate: Users cannot directly obtain the core parameter characterizing the amount of matter transported—mass flow rate. This is a critical limitation in scenarios such as energy trading and chemical reaction metering.

[0010] Limited application scope: Due to the lack of pressure and advanced compensation, it is difficult to accurately apply to gas flow measurement, steam metering, high-pressure liquid systems, or processes with large changes in fluid properties.

[0011] The level of intelligence needs to be improved: the diagnostic function is limited to single-parameter over-limit alarms and lacks an intelligent fault diagnosis model based on the linkage relationship of three parameters: flow, temperature and pressure.

[0012] Therefore, the above problems urgently need to be solved. Summary of the Invention

[0013] Purpose of the Invention: To overcome the above shortcomings, the purpose of this invention is to provide an integrated intelligent flow sensor and its dynamic compensation system and method. A compact flow channel and sensing structure integrating three sensors is designed, achieving high physical integration of the three-parameter sensing units and effective electrical signal isolation, satisfying the dual requirements of "integration" and "high precision." A dynamic flow compensation algorithm based on fluid property library and real-time TP fusion is designed, fundamentally upgrading flow measurement from a simple "frequency-velocity" conversion to a "multi-parameter-mass flow" conversion based on physical principles. Through density calculation using real-time TP fusion, the influence of fluid property changes on the measurement is dynamically corrected, thus ensuring high accuracy of volumetric flow rate even with significant fluctuations in fluid temperature and pressure. For the first time in this type of integrated sensor, direct and reliable mass flow rate output is achieved.

[0014] Technical Solution: To achieve the above objectives, this invention provides an integrated intelligent flow sensor, comprising a three-sensor integrated structure, a signal conditioning circuit, an embedded processing unit, a configurable output module, and a human-machine interaction module arranged sequentially. The three-sensor integrated structure includes: a high-strength integrated flow channel body made of high-strength engineering plastic or stainless steel, the flow channel body having a built-in vortex generator and a pre-reserved sealing installation interface in the flow channel wall; a flow sensor installed downstream of the vortex generator; a temperature sensor inserted obliquely into the central region of the flow channel through a sealing sleeve in the flow channel wall; and a pressure sensor connected to the flow channel through a micro pressure tap, with the sensor chip encapsulated in a metal isolation chamber and sealed and installed in the flow channel wall. The embedded processing unit has a built-in dynamic compensation algorithm engine and an intelligent diagnostic rule base. By adopting a high-strength integrated flow channel body, the three measuring points of vortex shedding, temperature, and pressure are integrated into a single mechanical body. This avoids the need for additional piping, flanges, and installation space required for the separate installation of three independent sensors, significantly reducing the material and installation costs of system integration and shrinking the overall size. At the same time, the three sensors sense the fluid state within the same flow channel at almost the same moment, ensuring the accuracy and timeliness of temperature and pressure data used to compensate for the current flow rate data from a physical perspective. This solves the compensation error caused by different locations and asynchronous times in distributed installations.

[0015] Furthermore, the signal conditioning circuit adopts a partitioned isolation design, with each signal conditioning unit powered by an independent LDO and electromagnetically and thermally isolated through a shield or grounding isolation strip. For the weak pC-level charge signal output by the flow sensor, a charge-to-voltage conversion circuit with a precision operational amplifier, an active second-order bandpass filter, and a hysteresis comparator shaping circuit are configured. For the temperature sensor signal, a quad operational amplifier precision constant current drive and differential amplifier circuit with four integrated operational amplifiers are configured. For the pressure sensor signal, an excitation circuit with a REF5030 precision voltage reference, an INA333 zero-drift instrumentation amplifier circuit, a PGA280 programmable gain amplifier circuit, and an LTC1562 fourth-order switched capacitor anti-aliasing filter circuit are configured. By employing an independent LDO power supply and a shield / grounding isolation strip, electrical crosstalk between the piezoelectric charge signal, platinum resistance signal, and pressure sensor circuitry that may contain digital noise is eliminated, ensuring the purity of the vortex street signal, which is particularly susceptible to being submerged. At the same time, three signals are designed so that each signal is processed under its optimal conditioning path, maximizing the signal-to-noise ratio and ensuring the quality of subsequent digital processing from an electrical perspective.

[0016] Furthermore, the configurable output module supports custom configuration of two output channels, which can be configured as a switch quantity over-limit alarm output associated with any measured parameter, a 0-10V / 4-20mA analog quantity output proportional to any parameter, or a pulse quantity output related to mass flow rate / cumulative quantity. The human-machine interface module supports switching of main display parameters and dynamic switching of measurement units for each parameter. Each output channel can be associated with any parameter, and the type can be configured between switch quantity, analog quantity, and pulse quantity. The same sensor can be adapted to various downstream devices such as DCS systems, PLCs, and alarms without hardware modifications, meeting different application scenarios such as flow meters, calorimeters, and batch control. It also supports dynamic switching of measurement units, allowing field engineers to quickly adjust according to their habits or project requirements, improving the product's international versatility and ease of use.

[0017] Furthermore, the embedded processing unit is a microcontroller running a real-time operating system. Through multi-task scheduling, it achieves synchronous signal acquisition, dynamic compensation algorithm calculation, output control, intelligent diagnosis, human-machine interaction, and communication functions. Tasks include a highest-priority synchronous acquisition task triggered by a 1ms hardware timer interrupt, a 10ms-period algorithm core task, a 20ms-period timer-triggered output control task, a 50ms-period semaphore-triggered diagnostic task, a 100ms-period timer-triggered display task, a 50ms-period timer-triggered key scanning task, and a serial port interrupt-triggered communication task. Using a real-time operating system and triggering the highest-priority acquisition task with a 1ms hardware interrupt ensures stable and lossless acquisition of the vortex shear frequency signal, guaranteeing accurate flow measurement without pulse loss. Simultaneously, scheduling acquisition, algorithm, output, diagnosis, and display tasks according to different cycles ensures intensive computation of the core algorithm on a resource-constrained MCU without hindering human-machine interaction and communication, achieving a balance between intelligence and real-time performance.

[0018] Furthermore, the intelligent diagnostic rule base includes diagnostic rules based on a three-parameter linkage relationship: when a sharp drop in flow rate is detected and a simultaneous surge in pressure is detected, it is determined that the downstream valve is closed or the pipeline is blocked; when a normal flow rate is detected but the temperature rises abnormally and the pressure drops abnormally, it is determined that the pump efficiency has decreased or cavitation has occurred; when a rule is triggered, an alarm signal is output and diagnostic prompts are displayed. Based on the three-parameter linkage relationship, the diagnostic rules mean that sensors no longer passively output data, but can actively understand the system operating conditions behind the data, providing early warnings, greatly enhancing the added value of the product and making it a key node in predictive maintenance.

[0019] This invention also provides a dynamic compensation system based on the integrated intelligent flow sensor, comprising a signal synchronous acquisition module, a density real-time calculation engine, a flow compensation and derivative calculation module connected in sequence, and a fluid property database bidirectionally connected to the density real-time calculation engine; the signal synchronous acquisition module is used to synchronously capture flow vortex frequency signals, temperature signals, and pressure signals and perform timestamp alignment, and transmit the aligned signal data to the density real-time calculation engine and the flow compensation and derivative calculation module; the density real-time calculation engine is used for real-time density calculation; the fluid property database pre-stores the physical property parameters and state equations of common fluids such as water, air, nitrogen, common oils, and saturated steam, and supports user-defined fluid parameter input; the flow compensation and derivative calculation module is used for flow compensation and derivative calculations. A standardized, programmable data processing pipeline was established, encompassing synchronous acquisition, database querying, and real-time computation. The synchronous acquisition module resolved the fundamental problem of time mismatch in multi-source data. Through hardware timer interrupts and software timestamp alignment, it ensured that the data used to calculate density and flow rate reflected the fluid state at the same instant. The fluid property database greatly improved the system's adaptability. When a new fluid appeared, no hardware or core code modifications were required; expansion could be achieved simply by updating the database.

[0020] Furthermore, the real-time density calculation engine employs differentiated logic for different fluids: for incompressible liquids, the density ρ(T) is calculated based on a temperature lookup table or fitted formula, and an isothermal compressibility coefficient is introduced for minor pressure correction; for compressible fluids, the density is calculated based on the formula ρ=P / (Z*R*T), where Z is the compressibility factor obtained based on pre-stored data or empirical formulas, R is the gas constant, T is the temperature, and P is the pressure. This upgrades flow measurement from a simple frequency and velocity conversion to a multi-parameter, mass flow conversion based on physical principles. Through real-time TP fusion density calculation, the influence of fluid property changes on the measurement is dynamically corrected, thus ensuring high accuracy of volumetric flow rate even with significant fluctuations in fluid temperature and pressure. For the first time in this type of integrated sensor, direct and reliable mass flow rate output is achieved.

[0021] Furthermore, the flow compensation and derivation calculation module performs the following steps: S1: Calculate the original operating condition volumetric flow rate Qv_raw=K*f based on the vortex shedding frequency f and the factory-calibrated instrument coefficient K; S2: Obtain the high-precision operating condition volumetric flow rate Qv=Qv_raw*(ρ_cal / ρ_curr) by using the ratio of the fluid density ρ_cal during calibration to the current real-time density ρ_curr; S3: Calculate the mass flow rate Qm=Qv*ρ_curr; S4: For gaseous fluids, calculate the standard condition volumetric flow rate Qn=Qm / ρ_n by combining the gas density ρ_n under standard conditions.

[0022] This invention also provides a dynamic compensation method based on the integrated intelligent flow sensor, comprising the following steps: S1: Synchronously acquiring the vortex shedding frequency signal, temperature signal, and pressure signal of the fluid through the integrated three-sensor structure; S2: Obtaining a timestamp-aligned effective digital signal through signal conditioning and digital preprocessing; S3: Calling the fluid property database and obtaining the current fluid density based on real-time temperature and pressure data through a real-time density calculation engine; S4: Compensating for flow rate and calculating Qv, Qm, and optional Qn through a flow compensation and derived calculation module; S5: Outputting parameter signals according to the configuration, while simultaneously displaying measurement results and diagnostic information; S6: Obtaining calibration coefficients in the production process through two-point calibration and multi-point calibration methods and storing them in non-volatile memory. A complete, closed-loop, and efficient sensing, decision-making, and output workflow is defined, starting from physical signal acquisition to final result output and system maintenance, forming a complete lifecycle management closed loop from on-site operation back to production manufacturing, ensuring the reliability and predictability of system operation.

[0023] As can be seen from the above technical solution, the present invention has the following beneficial effects: 1. The present invention discloses an integrated intelligent flow sensor and its dynamic compensation system and method. It designs a compact flow channel and sensing structure that integrates three sensors, realizes the high integration of the three-parameter sensing unit in physical space and the effective isolation of electrical signals, and meets the dual requirements of "integration" and "high precision". 2. This invention discloses an integrated intelligent flow sensor and its dynamic compensation system and method. It designs a dynamic flow compensation algorithm based on the fusion of a fluid property library and real-time flow measurement (TP), fundamentally upgrading flow measurement from a simple "frequency-velocity" conversion to a "multi-parameter-mass flow" conversion based on physical principles. Through density calculation using real-time TP fusion, the influence of fluid property changes on the measurement is dynamically corrected, thus ensuring high accuracy of volumetric flow rate even with significant fluctuations in fluid temperature and pressure. Furthermore, it achieves direct and reliable mass flow rate output for the first time in this type of integrated sensor. 3. This invention provides an integrated intelligent flow sensor and its dynamic compensation system and method. By designing dynamic unit switching, it greatly improves the international adaptability and user experience of the product; the reconfigurable output channel enables a single sensor to adapt to more diverse control system interface requirements; the correlation diagnostic function utilizes the advantage of three-parameter information redundancy, providing value far exceeding that of single-parameter alarms, realizing a leap from "monitoring" to "insight", and improving the product's intelligence level and added value. Attached Figure Description

[0024] Figure 1 This is a schematic diagram of the architecture of an integrated intelligent flow sensor according to the present invention; Figure 2 This is a schematic diagram of the architecture of the dynamic compensation system based on the integrated intelligent flow sensor of the present invention; Figure 3 This is a schematic diagram illustrating the steps of the dynamic compensation method based on the integrated intelligent flow sensor of the present invention. Detailed Implementation

[0025] Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain the present invention, and should not be construed as limiting the present invention. Example

[0026] In this embodiment, as Figure 1 This invention discloses an integrated intelligent flow sensor, comprising a three-sensor integrated structure, a signal conditioning circuit, an embedded processing unit, a configurable output module, and a human-machine interaction module arranged sequentially. The three-sensor integrated structure includes: a high-strength integrated flow channel body made of high-strength engineering plastic or stainless steel, the flow channel body having a built-in vortex generator and a pre-reserved sealing installation interface in the flow channel wall; a flow sensor installed downstream of the vortex generator; a temperature sensor inserted obliquely into the central region of the flow channel through a sealing sleeve in the flow channel wall; and a pressure sensor connected to the flow channel through a micro pressure tap, with the sensor chip encapsulated in a metal isolation chamber and sealed and installed in the flow channel wall. The embedded processing unit has a built-in dynamic compensation algorithm engine and an intelligent diagnostic rule base.

[0027] Specifically, the integrated flow channel body can be processed using high-strength engineering plastics such as PPS or SUS304 stainless steel; the flow sensor is preferably an electro-ceramic vortex detector probe; the temperature sensor is preferably a PT1000 platinum resistance thermometer; and the pressure sensor is preferably a MEMS piezoresistive pressure sensor.

[0028] In particular, a ceramic capacitive pressure sensor can also be used as an alternative. It uses a ceramic diaphragm to form a capacitor. Pressure causes deformation, which changes the capacitance and is converted into a digital signal by a dedicated ASIC.

[0029] In this embodiment, the signal conditioning circuit adopts a partitioned isolation design. Each signal conditioning unit is powered by an independent LDO and is electromagnetically and thermally isolated through a shield or grounding isolation strip. For the weak pC-level charge signal output by the flow sensor, a charge-to-voltage conversion circuit with a precision operational amplifier, an active second-order bandpass filter, and a hysteresis comparator shaping circuit are configured. For the temperature sensor signal, a quad operational amplifier precision constant current drive and differential amplifier circuit with four integrated operational amplifiers are configured. For the pressure sensor signal, an excitation circuit with a REF5030 precision voltage reference, an INA333 zero-drift instrumentation amplifier circuit, a PGA280 programmable gain amplifier circuit, and an LTC1562 fourth-order switched capacitor anti-aliasing filter circuit are configured.

[0030] Specifically, the precision operational amplifier can be implemented using the TLC2264.

[0031] Specifically, the active second-order bandpass filter can be implemented using a multi-feedback MFB or Sallen-Key topology. Its high-pass section (fchigh = 1Hz) employs an RC high-pass network, the core purpose of which is to filter out ultra-low frequency drift and quasi-static pressure interference caused by temperature changes and slow stress deformation of the pipeline, while simultaneously isolating low-frequency mechanical vibrations of the pipeline (such as pump foundation vibration) that may be coupled through the piezoelectric effect. Its low-pass section (fclow = 5kHz) employs an RC low-pass network, designed to filter out high-frequency switching power supply noise, radio frequency interference (RFI), and digital circuit crosstalk. The cutoff frequency of 5kHz is significantly higher than the maximum vortex shedding frequency (typically <2kHz) in common industrial fluid measurements, providing ample noise suppression margin while ensuring signal integrity.

[0032] Specifically, the hysteresis comparator shaping circuit can be implemented using a Schmitt trigger, with the following parameter settings: Positive threshold (V) th+ ): +50mV; Negative threshold (V th- -50mV; Hysteresis width (V) hys ): 100mV (i.e., V) th+ -V th- ); The filtered analog sine / quasi-sine wave signal is fed into the comparator. When the signal rises above +50mV, the comparator output flips to a high level; the output only flips to a low level when the signal falls below -50mV.

[0033] The hysteresis effect effectively eliminates the output jitter caused by residual noise near the threshold point, ensuring that only one clean, steep-edge square wave pulse is generated per vortex cycle.

[0034] Specifically, the four-channel integrated operational amplifier can be implemented using the LM324KAPWR.

[0035] In this embodiment, the configurable output module supports custom configuration of two output channels, which can be configured as a switch quantity over-limit alarm output associated with any measured parameter, a 0-10V / 4-20mA analog quantity output proportional to any parameter, or a pulse quantity output related to mass flow rate / cumulative quantity; the human-machine interaction module supports switching of main display parameters and dynamic switching of measurement units for each parameter.

[0036] Specifically, the two output channels are OUT1 and OUT2, respectively; the measured parameters include at least the operating volume flow rate Qv, mass flow rate Qm, temperature T, and pressure P; the measurement units for each parameter include at least the flow rate units such as m³ / h, L / min, kg / h, etc., the temperature units such as ℃ / ℉, and the pressure units such as kPa / bar / psi.

[0037] In this embodiment, the embedded processing unit is a microcontroller (MCU) running a real-time operating system (FreeRTOS) and implementing functions such as synchronous signal acquisition, dynamic compensation algorithm calculation, output control, intelligent diagnosis, human-computer interaction, and communication through multi-task scheduling. The tasks include the highest priority synchronous acquisition task triggered by a 1ms hardware timer interrupt, the algorithm core task with a 10ms cycle, the output control task triggered by a 20ms timer, the diagnostic task triggered by a 50ms semaphore, the display task triggered by a 100ms timer, the key scanning task triggered by a 50ms timer, and the communication task triggered by a serial port interrupt.

[0038] In this embodiment, the intelligent diagnostic rule base includes diagnostic rules based on a three-parameter linkage relationship: when a sharp drop in flow rate is detected and a sudden increase in pressure is detected simultaneously, it is determined that the downstream valve is closed or the pipeline is blocked; when a normal flow rate is detected but the temperature rises abnormally and the pressure drops abnormally, it is determined that the pump efficiency has decreased or cavitation has occurred; when a rule is triggered, an alarm signal is output and diagnostic prompt information is displayed.

[0039] Specifically, when a diagnostic message such as "Fault:Clogging" is displayed, it indicates that the system has detected a blockage or clogging fault.

[0040] In this embodiment, the present invention also discloses a dynamic compensation system based on the integrated intelligent flow sensor, such as... Figure 2The system includes a signal synchronization acquisition module, a real-time density calculation engine, a flow compensation and derivative calculation module, and a fluid property database bidirectionally connected to the real-time density calculation engine. The signal synchronization acquisition module synchronously captures flow vortex frequency signals, temperature signals, and pressure signals, aligns them with timestamps, and transmits the aligned signal data to the real-time density calculation engine and the flow compensation and derivative calculation module. The real-time density calculation engine performs real-time density calculations. The fluid property database pre-stores the physical property parameters and equations of state for common fluids such as water, air, nitrogen, common oils, and saturated steam, and supports user-defined fluid parameter input. The flow compensation and derivative calculation module performs flow compensation and derivative calculations.

[0041] In this embodiment, the real-time density calculation engine adopts differentiated logic for different fluids: for incompressible liquids, the density ρ(T) is calculated based on a table or fitting formula according to the temperature, and an isothermal compressibility coefficient is introduced for minor pressure correction; for compressible fluids, the density is calculated based on the formula ρ=P / (Z*R*T), where Z is the compressibility factor obtained based on pre-stored data or empirical formulas, R is the gas constant, T is the temperature, and P is the pressure.

[0042] Specifically, the incompressible liquid includes, but is not limited to, water; the compressible fluid includes, but is not limited to, gas and steam.

[0043] In this embodiment, the flow compensation and derivation calculation module performs the following steps: S1: Calculate the original operating condition volumetric flow rate Qv_raw=K*f based on the vortex shedding frequency f and the factory-calibrated instrument coefficient K; S2: Obtain the high-precision operating condition volumetric flow rate Qv=Qv_raw*(ρ_cal / ρ_curr) by using the ratio of the fluid density ρ_cal during calibration to the current real-time density ρ_curr; S3: Calculate the mass flow rate Qm=Qv*ρ_curr; S4: For gaseous fluids, calculate the standard condition volumetric flow rate Qn=Qm / ρ_n by combining the gas density ρ_n under standard conditions.

[0044] Specifically, the fluid density during calibration is typically the density of water at 20°C and normal pressure; the standard state is 0°C and 1 atm.

[0045] In this embodiment, the present invention also discloses a dynamic compensation method based on the integrated intelligent flow sensor, such as... Figure 3The process includes the following steps: S1: Synchronously acquire the vortex shedding frequency signal, temperature signal, and pressure signal of the fluid through the integrated three-sensor structure; S2: Obtain a timestamp-aligned effective digital signal through signal conditioning and digital preprocessing; S3: Call the fluid property database and obtain the current fluid density based on real-time temperature and pressure data through a real-time density calculation engine; S4: Complete flow compensation and calculation of Qv, Qm, and optional Qn through the flow compensation and derived calculation module; S5: Output parameter signals according to the configuration, and simultaneously display measurement results and diagnostic information; S6: In the production process, obtain calibration coefficients through two-point calibration and multi-point calibration methods and store them in non-volatile memory.

[0046] Specifically, the preprocessing described in S2 includes, but is not limited to, flow anti-pulse interference average filtering, temperature Kalman filtering, and pressure sliding window average filtering; the non-volatile memory can be implemented using, for example, AT25010B.

[0047] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements can be made without departing from the principle of the present invention, and these improvements should also be considered within the scope of protection of the present invention.

Claims

1. An integrated intelligent flow sensor, characterized in that, The system includes a three-sensor integrated structure, a signal conditioning circuit, an embedded processing unit, a configurable output module, and a human-machine interaction module arranged sequentially. The three-sensor integrated structure includes: a high-strength integrated flow channel body made of high-strength engineering plastic or stainless steel, with a built-in vortex generator and a pre-reserved sealing installation interface in the flow channel wall; a flow sensor installed downstream of the vortex generator; a temperature sensor inserted obliquely into the central region of the flow channel through a sealing sleeve in the flow channel wall; and a pressure sensor connected to the flow channel through a micro pressure tap, with the sensor chip encapsulated in a metal isolation chamber and sealed and installed in the flow channel wall. The embedded processing unit has a built-in dynamic compensation algorithm engine and an intelligent diagnostic rule base.

2. The integrated intelligent flow sensor according to claim 1, characterized in that, The signal conditioning circuit adopts a partitioned isolation design. Each signal conditioning unit is powered by an independent LDO and is electromagnetically and thermally isolated through a shield or grounding isolation strip. For the weak pC-level charge signal output by the flow sensor, a charge-to-voltage conversion circuit with a precision operational amplifier, an active second-order bandpass filter, and a hysteresis comparator shaping circuit are configured. For the temperature sensor signal, a quad operational amplifier precision constant current drive and differential amplifier circuit with four integrated operational amplifiers are configured. For the pressure sensor signal, an excitation circuit with a REF5030 precision voltage reference, an INA333 zero-drift instrumentation amplifier circuit, a PGA280 programmable gain amplifier circuit, and an LTC1562 fourth-order switched capacitor anti-aliasing filter circuit are configured.

3. The integrated intelligent flow sensor according to claim 1, characterized in that, The configurable output module supports custom configuration of two output channels, which can be configured as a switch quantity over-limit alarm output associated with any measured parameter, a 0-10V / 4-20mA analog quantity output proportional to any parameter, or a pulse quantity output related to mass flow rate / cumulative quantity; the human-machine interaction module supports switching of main display parameters and dynamic switching of measurement units for each parameter.

4. The integrated intelligent flow sensor according to claim 1, characterized in that, The embedded processing unit is a microcontroller that runs a real-time operating system and uses multi-task scheduling to achieve functions such as synchronous signal acquisition, dynamic compensation algorithm calculation, output control, intelligent diagnosis, human-computer interaction, and communication. The tasks include the highest priority synchronous acquisition task triggered by a 1ms hardware timer interrupt, the algorithm core task with a 10ms cycle, the output control task triggered by a 20ms timer, the diagnostic task triggered by a 50ms semaphore, the display task triggered by a 100ms timer, the key scanning task triggered by a 50ms timer, and the communication task triggered by a serial port interrupt.

5. The integrated intelligent flow sensor according to claim 1, characterized in that, The intelligent diagnostic rule base includes diagnostic rules based on a three-parameter linkage relationship: when a sharp drop in flow rate is detected and a sudden increase in pressure is detected simultaneously, it is determined that the downstream valve is closed or the pipeline is blocked; when a normal flow rate is detected but the temperature rises abnormally and the pressure drops abnormally, it is determined that the pump efficiency has decreased or cavitation has occurred; when a rule is triggered, an alarm signal is output and diagnostic prompt information is displayed.

6. A dynamic compensation system based on the integrated intelligent flow sensor according to any one of claims 1-5, characterized in that, It includes a signal synchronous acquisition module, a density real-time calculation engine, a flow compensation and derivative calculation module connected in sequence, and a fluid property database that is bidirectionally connected to the density real-time calculation engine; The signal synchronization acquisition module is used to synchronously capture the flow vortex frequency signal, temperature signal and pressure signal and perform timestamp alignment, and then transmit the aligned signal data to the density real-time calculation engine and the flow compensation and derivative calculation module. The real-time density calculation engine is used for real-time density calculation. The fluid property database pre-stores the physical property parameters and equations of state for common fluids such as water, air, nitrogen, common oils, and saturated steam, and supports user-defined fluid parameter input. The flow compensation and derivative calculation module is used for flow compensation and derivative calculation.

7. The dynamic compensation system according to claim 6, characterized in that, The real-time density calculation engine employs differentiated logic for different fluids: for incompressible liquids, the density ρ(T) is calculated based on a table or fitted formula according to the temperature, and an isothermal compressibility coefficient is introduced for minor pressure correction; for compressible fluids, the density is calculated based on the formula ρ=P / (Z*R*T), where Z is the compressibility factor obtained based on pre-stored data or empirical formulas, R is the gas constant, T is the temperature, and P is the pressure.

8. The dynamic compensation system according to claim 6, characterized in that, The flow compensation and derived calculation module performs the following steps: S1: Based on the vortex shedding frequency f and the factory-calibrated instrument coefficient K, calculate the original operating condition volumetric flow rate Qv_raw=K*f; S2: By using the ratio of the fluid density ρ_cal at calibration to the current real-time density ρ_curr, the high-precision operating condition volumetric flow rate Qv = Qv_raw*(ρ_cal / ρ_curr) is obtained; S3: Calculate the mass flow rate Qm = Qv * ρ_curr; S4: For gaseous fluids, calculate the standard volumetric flow rate Qn = Qm / ρ_n by combining the gas density ρ_n under standard conditions.

9. A dynamic compensation method based on the integrated intelligent flow sensor as described in claim 6, characterized in that, Includes the following steps: S1: The three-sensor integrated structure is used to synchronously acquire the vortex shedding frequency signal, temperature signal and pressure signal of the fluid; S2: After signal conditioning and digital preprocessing, a valid digital signal with timestamp alignment is obtained; S3: Call the fluid property database and obtain the current fluid density based on real-time temperature and pressure data through the real-time density calculation engine; S4: The flow compensation and calculation of Qv, Qm, and optional Qn are completed through the flow compensation and derived calculation module; S5: Output parameter signals according to the configuration, and simultaneously display measurement results and diagnostic information; S6: In the production process, calibration coefficients are obtained through two-point calibration and multi-point calibration methods and stored in non-volatile memory.

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