Bit-based strain bridge online fault detection system and method

Abstract

This invention belongs to the field of strain gauge sensors and discloses an online fault detection system and method for a strain gauge bridge based on BIT. The invention comprises a full-bridge strain gauge, a constant current excitation unit, a multiplexing unit, a signal acquisition unit, and a processing and analysis unit. The constant current excitation unit outputs a fault detection current to the target bridge arm resistor, and the multiplexing unit switches the conduction path of the fault detection current in different bridge arm resistors, allowing the fault detection current to flow directionally through the target bridge arm resistor. Simultaneously, the signal acquisition unit acquires the dynamic response signal of the bridge circuit generated by the target bridge arm resistor under the action of the fault detection current in real time. The processing and analysis unit sequentially controls the four bridge arm resistors to poll and detect faults, thereby achieving online automatic detection and precise location of latent faults in the four bridge arm resistors of the strain gauge bridge without affecting the normal measurement function of the strain gauge bridge.

Description

Technical Field

[0001] This invention belongs to the field of strain gauge sensors, specifically relating to an online fault detection system and method for a strain gauge bridge based on BIT. Background Technology

[0002] Strain gauge bridges, as high-precision stress measurement circuits, are widely used in industrial force measurement, structural health monitoring, aerospace load testing, bridge monitoring, and weighing systems. In practical applications, multiple resistance strain gauges are typically attached to the surface of the structure being measured, forming a full-bridge or half-bridge measurement circuit. By sensing the resistance changes caused by structural deformation, a differential voltage signal is output, which is then amplified and converted from analog to digital for strain analysis and condition assessment. Due to its advantages of high sensitivity, fast response speed, and simple structure, this type of detection method has become an important technical means in the field of engineering measurement.

[0003] However, during long-term operation, strain gauges and their bridge circuit connections are susceptible to factors such as changes in ambient temperature, mechanical vibration, material aging, bonding processes, and solder joint reliability. This can lead to faults in the bridge arm resistors, such as localized debonding, poor contact, cold solder joints, resistance drift, or even open circuits. Initially, these faults typically do not cause complete failure of the measurement system. Instead, they manifest gradually as increased measurement errors, zero-point drift, decreased sensitivity, or deterioration in long-term stability, thus affecting the system's measurement accuracy and operational safety.

[0004] In existing technologies, the main methods for detecting the condition of strain gauge bridges include manual calibration, offline resistance measurement, and temperature compensation correction. For example, some systems periodically apply standard loads to calibrate the output results to determine if the sensor is malfunctioning; some solutions identify obvious open-circuit or short-circuit faults by detecting changes in the resistance of the bridge arms; and some technologies use temperature compensation algorithms to reduce the impact of environmental temperature drift. While these methods can improve measurement accuracy to some extent, they generally require shutdown for testing or rely on external standard operating conditions, making it difficult to meet the real-time monitoring needs of strain gauge bridges operating online for extended periods in practical engineering projects.

[0005] Furthermore, existing detection methods based on resistance changes primarily target significant electrical anomalies, lacking effective identification capabilities for latent faults such as loose strain gauge adhesion, localized detachment, thermal conductivity degradation, and abnormal structural stress transmission. Existing online monitoring technologies focus more on the overall equipment operating status and lack a dedicated mechanism for individually locating and detecting the resistance of each of the four arms of a strain gauge bridge, making it difficult to accurately determine the specific faulty arm. In addition, while some parameter analysis-based detection schemes can improve detection accuracy, they often require changes to the bridge circuit excitation method, the addition of extra detection equipment, or the use of complex data processing algorithms, resulting in high system complexity, poor real-time performance, and high engineering implementation costs. Summary of the Invention

[0006] The purpose of this invention is to overcome the technical problem in the prior art of accurately detecting and locating latent faults in the resistance of the four arms of a strain gauge bridge online, and to provide a strain gauge bridge online fault detection system and method based on BIT.

[0007] To achieve the above objectives, the present invention adopts the following technical solution: A strain gauge bridge, the strain gauge bridge consisting of four resistors R 1. R 2. R 3. R Composed of 4, each value is equal to R 0; A constant current excitation unit is connected to the strain gauge bridge and is used to provide the strain gauge bridge with working excitation current and fault detection current. A multi-channel switching unit is connected to a constant current excitation unit and a strain full bridge, respectively, and is used to switch the conduction path of the fault detection current in different bridge arm resistors, so that the fault detection current flows directionally through the target bridge arm resistor. The signal acquisition unit is connected to the bridge output terminal of the strain gauge bridge and is used to acquire the bridge dynamic response signal generated by the target bridge arm resistance under the action of the fault detection current. The processing and analysis unit is connected to the multiplexing unit and the signal acquisition unit respectively. It is used to control the multiplexing unit to select each bridge arm resistor as the target bridge arm resistor in sequence, and to determine whether the corresponding bridge arm resistor is faulty based on the bridge dynamic response signal.

[0008] A further improvement of the present invention is that the constant current excitation unit is connected to a programmable constant current source to output a fault detection current of constant amplitude to the target bridge arm resistor.

[0009] A further improvement of the present invention is that the multiplexing unit includes several analog switches, which are used to combine to form several different bridge arm resistor conduction paths.

[0010] A further improvement of the present invention is that the signal acquisition unit includes an instrumentation amplifier and an analog-to-digital converter, the instrumentation amplifier is connected to the analog-to-digital converter, and the analog-to-digital converter is a high-precision 24-bit analog-to-digital converter.

[0011] Secondly, the present invention provides a BIT-based online fault detection method for strain gauge bridges, comprising the following steps: The constant current excitation unit is controlled to output fault detection current to the strain gauge bridge. The control multiplexing unit switches the conduction path of the fault detection current in different bridge arm resistors, so that the fault detection current flows in a directional manner through the target bridge arm resistor. Collect the bridge dynamic response signal generated by the target bridge arm resistance under the action of fault detection current; Determine whether the target bridge arm resistor is faulty based on the bridge dynamic response signal; The control multiplexing unit sequentially switches the remaining bridge arm resistors as the target bridge arm resistors, repeats the fault detection process, and obtains the fault detection results corresponding to the bridge arm resistors of the strain gauge bridge.

[0012] A further improvement of the present invention is that the bridge dynamic response signal includes the temperature rise response signal generated by the target bridge arm resistor during the heating stage and the cooling response signal after the fault detection current is stopped.

[0013] A further improvement of this invention is that the specific method for determining whether the target bridge arm resistance is faulty based on the bridge dynamic response signal is as follows: The dynamic response signal of the bridge is acquired and analyzed to obtain the heating response signal and the cooling response signal. Model fitting is performed on the heating response signal and the cooling response signal to extract the heating time constant and the cooling time constant; The heating time constant and cooling time constant are compared with a preset threshold range to determine whether the target bridge arm resistor is faulty.

[0014] A further improvement of this invention is that, when fitting the heating response signal and the cooling response signal to the model, an exponential approach model is used to fit the heating response signal, and an exponential decay model is used to fit the cooling response signal.

[0015] A further improvement of the present invention is that, when determining whether the target bridge arm resistor is faulty, if either the heating time constant or the cooling time constant exceeds the corresponding preset threshold range, the target bridge arm resistor is determined to be faulty; if both the heating time constant and the cooling time constant are within the corresponding preset threshold range, the target bridge arm resistor is determined to be in normal working condition.

[0016] A further improvement of this invention is that, after obtaining the fault detection results corresponding to the resistance of each bridge arm of the strain gauge bridge, the fault detection results are uploaded, and the preset threshold range corresponding to the heating time constant and cooling time constant of the target bridge arm resistance is dynamically updated based on the fault detection results.

[0017] Compared with the prior art, the present invention has the following beneficial effects: This invention, by setting up a strain gauge bridge, a constant current excitation unit, a multiplexing unit, a signal acquisition unit, and a processing and analysis unit, utilizes the constant current excitation unit to output a fault detection current to the target bridge arm resistor, and the multiplexing unit switches the conduction path of the fault detection current in different bridge arm resistors, enabling the fault detection current to flow directionally through the target bridge arm resistor. Simultaneously, the signal acquisition unit collects the bridge circuit dynamic response signal generated by the target bridge arm resistor under the action of the fault detection current in real time, and the processing and analysis unit sequentially controls the four bridge arm resistors to poll and detect faults. Thus, without affecting the normal measurement function of the strain gauge bridge, it achieves online automatic detection and precise location of latent faults in the four bridge arm resistors of the strain gauge bridge. This effectively solves the technical problems of existing technologies that make it difficult to detect adhesion abnormalities, local debonding, and thermal conduction degradation faults in real time, and are unable to locate specific faulty bridge arms, improving detection efficiency, fault identification accuracy, and long-term system reliability. Attached Figure Description

[0018] Figure 1 This is a system diagram of the present invention; Figure 2 This is a flowchart of the present invention; Figure 3 for R 1. Self-test schematic diagram; Figure 4 for R 2. Self-test schematic diagram; Figure 5 for R 3. Self-test schematic diagram; Figure 6 for R 4. Self-test schematic diagram; Figure 7 This is the circuit schematic diagram of the present invention. Detailed Implementation

[0019] To further understand the content of this invention, the invention will be described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the embodiments are merely illustrative and not limiting of the invention.

[0020] Example 1: See Figure 1 A BIT-based strain gauge bridge online fault detection system includes: A strain gauge bridge, the strain gauge bridge consisting of four resistors R 1. R 2. R 3. R Composed of 4, each value is equal to R 0; The four bridge arms are preferably constructed using resistance strain gauges to form a full bridge structure, which is used to output a bridge differential signal that reflects the stress state of the structure.

[0021] A constant current excitation unit, connected to a strain gauge bridge, provides both operating excitation current and fault detection current to the strain gauge bridge. Its dual-mode current output design allows for both measurement and self-testing, enabling online monitoring without system shutdown.

[0022] A multi-channel switching unit is connected to a constant current excitation unit and a strain gauge bridge, respectively, and is used to switch the conduction path of the fault detection current in different bridge arm resistors so that the fault detection current flows directionally through the target bridge arm resistor.

[0023] A signal acquisition unit, connected to the bridge output of the strain gauge bridge, is used to acquire the dynamic response signal of the bridge circuit generated by the target bridge arm resistance under the action of fault detection current. Due to differences in the bonding quality of the target bridge arms, their thermal diffusion capabilities vary, resulting in significant differences in the dynamic response curves.

[0024] The processing and analysis unit is connected to the multiplexing unit and the signal acquisition unit respectively. It is used to control the multiplexing unit to select each bridge arm resistor as the target bridge arm resistor in sequence, and to determine whether the corresponding bridge arm resistor is faulty based on the bridge dynamic response signal.

[0025] This embodiment, by setting up a constant current excitation unit, a multi-channel switching unit, a signal acquisition unit, and a processing and analysis unit, can output fault detection current to the target bridge arm resistor without affecting the normal measurement function of the strain gauge bridge, and collect the corresponding bridge dynamic response signal in real time, thereby realizing online automatic fault detection of the strain gauge bridge, avoiding the problems of long detection cycle and high maintenance cost of traditional shutdown calibration and manual detection methods.

[0026] Example 2: See Figure 2 The BIT-based online fault detection method for strain gauge bridges includes the following steps: S1 controls the constant current excitation unit to output fault detection current to the strain gauge bridge.

[0027] S2 controls the multiplexing unit to switch the conduction path of the fault detection current in different bridge arm resistors, so that the fault detection current flows directionally through the target bridge arm resistor.

[0028] S3, collects the bridge dynamic response signal generated by the target bridge arm resistance under the action of fault detection current.

[0029] S4. Determine whether the target bridge arm resistor is faulty based on the bridge dynamic response signal.

[0030] S5 controls the multiplexing unit to sequentially switch the remaining bridge arm resistors as the target bridge arm resistors, repeatedly executes the fault detection process, and obtains the fault detection results corresponding to the bridge arm resistors of the strain gauge bridge.

[0031] Example 3: This embodiment includes a strain gauge bridge, a constant current excitation unit, a multiplexing unit, a signal acquisition unit, and a processing and analysis unit, which are cascaded in sequence. Its core working principle is based on the integration of thermal conduction physics and the principle of bridge measurement, and is quantitatively described through a mathematical model.

[0032] Based on the system schematic diagram, the specific working steps of this embodiment are as follows: I. Constant Current Excitation Control and Static Baseline Calibration: After the system powers on, the MCU first initializes all hardware modules. The system then enters the baseline calibration phase: under no-excitation detection current conditions, the static offset voltage of the bridge is measured. Including background noise. All subsequent dynamic measurements need to be compensated, and the compensation formula is as follows:

[0033] After baseline calibration is completed, the system is capable of outputting a high-precision constant detection current.

[0034] II. Directional Pulse Heating and Dynamic Signal Acquisition of Bridge Arm: The system works in conjunction with integrated chips IC1 and IC2 via an external constant current source to convert physical resistance into a self-heating temperature-sensing resistor. IC1 incorporates an operational amplifier, an analog-to-digital converter (ADC), and two constant current sources, IDAC0 and IDAC1 (each capable of outputting 2mA current). By controlling the internal switch array of the chip, the conduction path can be precisely switched.

[0035] Targeted detection strain gauges For example: the switch inside the system control IC1 Close, will Grounding, in IC2 Following Connect the switch and simultaneously disconnect the switch at the lower end of the control bridge. At this time, IDAC0 and IDAC1 jointly output a constant 4mA detection current. Injected through the AIN+ / IOUT ports, the dominant current path is: current source IDAC0 / IDAC1 land.

[0036] During the duration Under the pulsed Joule thermal shock, It becomes the dominant heat-generating element, and its instantaneous temperature rise Satisfies the first-order thermodynamic differential equation:

[0037] in, For the heat capacity of the strain gauge, Let be the total thermal resistance from the strain gauge to the environment. The solution to the equation is: Among them, thermal time constant .exist to During this period, the ADC samples the bridge output in real time at a synchronous frequency. If the strain gauge experiences faults such as debonding, heat cannot be effectively conducted ( A significant increase in temperature will cause a non-negligible change in its resistance due to the temperature rise. This could lead to an imbalance between the bridge and the road.

[0038] III. Analytical Derivation and Fault Space Mapping of Bridge Imbalance Response: To achieve accurate fault location, the system established an analytical mapping model between dynamic signals and the four specific physical locations of the entire bridge. Assuming four bridge arm strain gauges ( The initial nominal resistance of all is When the system is subjected to stress and deformed, and all gauges are properly bonded, the change in resistance of each strain gauge is... At this point, the theoretical bridge output voltage is zero.

[0039] In BIT self-test mode, the target bridge arm experiences an additional resistance change due to directional self-heating. Based on the voltage divider principle, when any strain gauge malfunctions (i.e., its resistance changes relative to the others while remaining in their current state), the bridge circuit will generate an abnormal output voltage with a specific polarity: like The corresponding strain gauge malfunctions and causes a relative resistance change, resulting in a change in the bridge circuit output voltage:

[0040] like The corresponding strain gauge malfunctions and causes a relative resistance change, resulting in a change in the bridge circuit output voltage:

[0041] like The corresponding strain gauge malfunctions and causes a relative resistance change, resulting in a change in the bridge circuit output voltage:

[0042] like The corresponding strain gauge malfunctions and causes a relative resistance change, resulting in a change in the bridge circuit output voltage:

[0043] The imbalanced output is used as the sensing input signal, with a gain of [value missing]. Amplified by an operational amplifier, and then passed through For a 2-bit ADC to perform analog-to-digital conversion, the expression for its final output signal is uniformly defined as follows:

[0044] The system sequentially switches the dominant current path using a combination of multiple switches, based on the output signal in the above formula. The positive and negative polarity and amplitude characteristics of the temperature rise response are compared with... to The specific spatial locations have achieved a one-to-one physical correspondence.

[0045] IV. Temperature Rise Feature Extraction and State Judgment Localization: The processing and analysis unit will collect the data. The sequence is treated as a temperature rise response curve and fitted using algorithms such as the least squares method. The heating section data is fitted into an exponentially approaching model. The cooling section data was fitted to an exponential decay model. The system thus extracts the steady-state amplitude of the heating / cooling section ( ), thermal time constant ( Area under the curve Characterized by total heat and time constant ratio and goodness of fit Features such as these are extracted. The system will then extract the feature vector. The fault status is determined by comparing the fault status with the typical threshold under known good conditions and using a multi-feature joint weighted score.

[0046] Subsequently, the embedded processing unit packages and uploads the raw data, fitted features, and local decision results to the host computer. The host computer then establishes a long-term time series database based on the feature vectors. By plotting single-value-movement range The control chart identifies the slow drift trend of parameters and dynamically calculates more reasonable statistical thresholds based on historical data, which are then sent to the embedded unit to achieve environmental adaptation. Finally, the system integrates multi-dimensional data to generate a comprehensive diagnostic report covering the real-time status of strain gauges, time-series change curves of characteristic parameters, SPC early warning information, and subsequent maintenance suggestions for the equipment.

[0047] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A BIT-based strain gauge bridge online fault detection system, characterized in that, include: A strain gauge bridge, the strain gauge bridge consisting of four resistors R 1. R 2. R 3. R Composed of 4, each value is equal to R 0; A constant current excitation unit is connected to the strain gauge bridge and is used to provide the strain gauge bridge with working excitation current and fault detection current. A multi-channel switching unit is connected to a constant current excitation unit and a strain full bridge, respectively, and is used to switch the conduction path of the fault detection current in different bridge arm resistors, so that the fault detection current flows directionally through the target bridge arm resistor. The signal acquisition unit is connected to the bridge output terminal of the strain gauge bridge and is used to acquire the bridge dynamic response signal generated by the target bridge arm resistance under the action of the fault detection current. The processing and analysis unit is connected to the multiplexing unit and the signal acquisition unit respectively. It is used to control the multiplexing unit to select each bridge arm resistor as the target bridge arm resistor in sequence, and to determine whether the corresponding bridge arm resistor is faulty based on the bridge dynamic response signal.

2. The online fault detection system for a BIT-based strain gauge bridge according to claim 1, characterized in that, The constant current excitation unit is connected to a programmable constant current source to output a fault detection current of constant amplitude to the target bridge arm resistor.

3. The online fault detection system for a BIT-based strain gauge bridge according to claim 1, characterized in that, The multiplexing unit includes several analog switches, which are used to combine to form several different bridge arm resistor conduction paths.

4. The online fault detection system for a BIT-based strain gauge bridge according to claim 1, characterized in that, The signal acquisition unit includes an instrumentation amplifier and an analog-to-digital converter (ADC). The instrumentation amplifier is connected to the ADC, which is a high-precision 24-bit ADC.

5. A BIT-based online fault detection method for strain gauge bridges, based on the BIT-based online fault detection system for strain gauge bridges as described in claim 1, characterized in that, Includes the following steps: The constant current excitation unit is controlled to output fault detection current to the strain gauge bridge. The control multiplexing unit switches the conduction path of the fault detection current in different bridge arm resistors, so that the fault detection current flows in a directional manner through the target bridge arm resistor. Collect the bridge dynamic response signal generated by the target bridge arm resistance under the action of fault detection current; Determine whether the target bridge arm resistor is faulty based on the bridge dynamic response signal; The control multiplexing unit sequentially switches the remaining bridge arm resistors as the target bridge arm resistors, repeats the fault detection process, and obtains the fault detection results corresponding to the bridge arm resistors of the strain gauge bridge.

6. The online fault detection method for a BIT-based strain gauge bridge according to claim 5, characterized in that, The bridge dynamic response signal includes the temperature rise response signal generated by the target bridge arm resistance during the heating phase and the cooling response signal after the fault detection current stops.

7. The online fault detection method for a BIT-based strain gauge bridge according to claim 5, characterized in that, The specific method for determining whether the target bridge arm resistor is faulty based on the bridge dynamic response signal is as follows: The dynamic response signal of the bridge is acquired and analyzed to obtain the heating response signal and the cooling response signal. Model fitting is performed on the heating response signal and the cooling response signal to extract the heating time constant and the cooling time constant; The heating time constant and cooling time constant are compared with a preset threshold range to determine whether the target bridge arm resistor is faulty.

8. The online fault detection method for a BIT-based strain gauge bridge according to claim 7, characterized in that, When fitting the heating response signal and the cooling response signal to the model, the exponential approach model is used to fit the heating response signal, and the exponential decay model is used to fit the cooling response signal.

9. The online fault detection method for a BIT-based strain gauge bridge according to claim 7, characterized in that, When determining whether the target bridge arm resistor is faulty, if either the heating time constant or the cooling time constant exceeds the corresponding preset threshold range, the target bridge arm resistor is determined to be faulty; if both the heating time constant and the cooling time constant are within the corresponding preset threshold range, the target bridge arm resistor is determined to be in normal working condition.

10. The online fault detection method for a BIT-based strain gauge bridge according to claim 5, characterized in that, After obtaining the fault detection results corresponding to the resistance of each bridge arm of the strain gauge bridge, the fault detection results are uploaded, and the preset threshold range corresponding to the heating time constant and cooling time constant of the target bridge arm resistance is dynamically updated based on the fault detection results.

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