Intelligent monitoring and re-tightening system and method based on pre-tightening force closed-loop control

Abstract

The application provides an intelligent monitoring and retightening system based on pre-tightening force closed-loop control, comprising: a perception layer including a plurality of wireless pre-tightening force sensing nodes, each of which is one-to-one corresponding to each bolt; an execution layer including: a ring track mechanism; a mobile automatic tightening robot slidingly assembled on the ring track mechanism and capable of walking along the ring track mechanism, the mobile automatic tightening robot being provided with a tightening module to perform tightening operation on the nut; and a control layer in communication connection with the perception layer and the execution layer, receiving the measured pre-tightening force uploaded by the perception layer, generating a retightening decision instruction according to the measured pre-tightening force and a target pre-tightening force value, and driving the mobile automatic tightening robot to perform tightening operation on the nut according to the retightening decision instruction. The system provides a three-layer architecture of the perception layer, the execution layer and the control layer, and realizes online perception, intelligent diagnosis and active intervention of the bolt retightening state.

Description

Technical Field

[0001] This invention relates to the field of condition monitoring and intelligent maintenance technology for bolts in industrial equipment, and in particular to an intelligent monitoring and re-tightening system and method based on preload closed-loop control. Background Technology

[0002] In rotary pressure filter equipment, the sealing packing material experiences wear and consumption during long-term operation. Manual monitoring suffers from problems such as untimely monitoring, heavy workload, and operational safety risks. An online intelligent monitoring and automatic re-tightening system based on preload closed-loop control can effectively solve these problems, providing timely and accurate processing. Existing online monitoring solutions use strain gauge sensors, but these have the following limitations: strain gauges require drilling for installation, weakening bolt strength; they are prone to drift under temperature fluctuations; they cannot integrate a re-tightening actuator, only monitoring without intervention; wired wiring is difficult, and maintenance is challenging. Another patent, CN202510999844.X, proposes a "method and system for monitoring and identifying loose fan bolts based on acoustic emission technology," but it can only qualitatively determine "whether it is loose," cannot quantify axial force, and lacks re-tightening capability. (Invention Content)

[0003] To address the shortcomings of the existing technologies, this invention provides an intelligent monitoring and re-tightening system and method based on preload closed-loop control. The system provides a three-layer architecture consisting of a sensing layer, an execution layer, and a control layer, enabling online sensing, intelligent diagnosis, and proactive intervention of bolt re-tightening status.

[0004] This invention provides an intelligent monitoring and re-tightening system based on preload closed-loop control, comprising:

[0005] The equipment flange is equipped with multiple bolts, and each bolt is fitted with a nut.

[0006] The sensing layer includes multiple wireless preload sensing nodes, each of which is installed on each bolt to collect the measured preload of each bolt.

[0007] The execution layer includes:

[0008] A ring track mechanism is fixed to the outer circumferential surface of the equipment flange;

[0009] A mobile automatic tightening robot is slidably mounted on the circular track mechanism and can move along the circular track mechanism. The mobile automatic tightening robot is equipped with a tightening module to perform tightening operations on the nut.

[0010] The control layer is communicatively connected to the perception layer and the execution layer, respectively. It is used to receive the measured preload force uploaded by the perception layer, generate a re-tightening decision command based on the measured preload force and the target preload force value, and drive the mobile automatic tightening robot to perform a tightening operation on the nut according to the re-tightening decision command.

[0011] In one embodiment of the present invention, the wireless preload sensing node includes:

[0012] A piezoelectric ultrasonic sensor chip is embedded in the head end face of the bolt and is used to emit ultrasonic waves into the bolt body and receive the reflected echoes.

[0013] A temperature sensor, integrated with the piezoelectric ultrasonic sensing chip, is used to collect the current measured temperature of the environment where the bolt is located.

[0014] The piezoelectric ultrasonic sensor chip is a bidirectional transceiver structure, and the head end face is provided with a reflective surface or uses the bolt center hole as a reflection path.

[0015] The measured preload is calculated based on the longitudinal wave travel time difference and calibration coefficient of the ultrasonic wave propagating along the bolt shank. The calculation formula is as follows:

[0016]

[0017] Where F is the preload, For longitudinal wave acoustic time difference, These are calibration coefficients; the calibration coefficients, after temperature compensation, are calculated according to the formula... Correction, among which As the benchmark calibration coefficient, Temperature-corrected slope This represents the deviation between the current measured temperature and the standard temperature.

[0018] In one embodiment of the present invention, the wireless preload sensing node further comprises:

[0019] A miniature battery-powered module is used to power the sensing nodes;

[0020] The wireless communication module is electrically connected to the piezoelectric ultrasonic sensing chip and the temperature sensor, and is used to wirelessly transmit the collected measured preload force and the current measured temperature to the control layer.

[0021] The wireless communication module supports LoRa, ZigBee, or 5G NR-RedCap low-power wide-area communication protocols.

[0022] In one embodiment of the present invention, the mobile automatic tightening robot includes:

[0023] The mobile automatic tightening robot includes:

[0024] The drive mechanism includes:

[0025] An annular slider is slidably mounted on the annular track mechanism and can travel along the annular track mechanism;

[0026] A linear slide rail is fixedly installed on the annular sliding member;

[0027] A linear slider is slidably mounted on the linear slide rail and can move laterally along the linear slide rail;

[0028] A tightening module is fixedly installed on the linear slider via a connecting bracket and moves together with the linear slider. The tightening module 222 includes:

[0029] A servo tightening shaft is fixedly installed on the end of the connecting bracket away from the linear sliding member, and is used to output tightening torque;

[0030] A floating sleeve is installed at the output end of the servo tightening shaft and is used for automatic positioning and fitting into the nut.

[0031] In one embodiment of the present invention, the control layer includes:

[0032] The central control cabinet has a built-in programmable logic controller, an industrial Ethernet switch, and a data server. The programmable logic controller is electrically connected to the execution layer via signal lines and outputs control commands.

[0033] The programmable logic controller establishes a data link with the wireless communication module of the sensing layer through the industrial Ethernet switch and receives data uploaded by the wireless preload sensing node.

[0034] In one embodiment of the present invention, the control layer includes:

[0035] The host computer software platform, installed on an engineering workstation or maintenance terminal, communicates with the data server and includes:

[0036] The real-time monitoring module is used to display the measured preload of each bolt on the display screen in a bolt ring topology diagram, and to distinguish different states with different color codes;

[0037] The intelligent diagnostic module has a dynamic preload lower limit and predicts the loosening trend of bolts based on time trend data;

[0038] The task scheduling module is used to generate re-tightening work orders and supports multiple task modes such as single-point re-tightening, batch re-tightening, timed inspection, and event-triggered re-tightening.

[0039] The closed-loop execution module is used to generate robot path planning instructions, control the mobile automatic tightening robot to inspect along the optimal path, skip bolts with measured preload force greater than or equal to the target preload force value, and perform re-tightening on bolts with measured preload force less than the target preload force value.

[0040] The verification module is used to read the measured preload of the bolt again after the bolt has been retightened, and to verify whether the measured preload after retightening is stable within the preset deviation range of the target preload value. If it is, the retightening verification is deemed to have passed; otherwise, the retightening verification is deemed to have failed and the bolt is marked as a failed retightening bolt.

[0041] The tightening process monitoring module is used to monitor the current and axial reaction force of the tightening module in real time. When the current exceeds the safety threshold, it triggers an emergency stop command and alarms.

[0042] The report generation and traceability module is used to output a retightening test report that includes bolt identification, measured preload before retightening, measured preload after retightening, target preload value, final torque value, temperature, timestamp, equipment ID, and operating robot number.

[0043] Another aspect of the present invention provides an online intelligent monitoring and automatic re-tightening method employing the system described above, comprising:

[0044] Collect the measured preload force of each bolt;

[0045] Based on the measured preload and target preload values, a re-tightening decision command is generated, and the mobile automatic tightening robot is driven to perform a tightening operation on the nut according to the re-tightening decision command.

[0046] In one embodiment of the present invention, the step of generating a re-tightening decision command based on the measured preload and the target preload value, and driving the mobile automatic tightening robot to perform a tightening operation on the nut according to the re-tightening decision command, includes:

[0047] The measured preload of each bolt is compared with the preset warning threshold and alarm threshold, wherein the warning threshold and the alarm threshold are different proportions of the target preload value, and the alarm threshold is lower than the warning threshold, and the warning threshold is less than the target preload value.

[0048] When the measured preload is less than the alarm threshold, a re-tightening decision instruction is generated. The re-tightening decision instruction includes a target bolt list and the target preload value corresponding to each bolt. The target bolt list includes bolts whose measured preload is less than the alarm threshold.

[0049] The mobile automatic tightening robot executes the re-tightening decision command, walks along the circular track mechanism to the position of the target bolt, the tightening module performs the tightening operation on the nut of the target bolt, and when the measured pre-tightening force after re-tightening reaches the preset deviation range of the target pre-tightening force value, the robot is instructed to stop, thus completing the re-tightening.

[0050] In one embodiment of the present invention, when the measured pretension force is less than the warning threshold and greater than or equal to the alarm threshold, it is marked as a warning state and an alarm message is pushed, but the re-tightening decision instruction is not generated.

[0051] When the measured preload is less than the alarm threshold, an alarm state is marked and an alarm is triggered, and the re-tightening decision command is generated at the same time.

[0052] In one embodiment of the present invention, the triggering condition for generating the complex tightening decision instruction includes at least one of the following:

[0053] A time-based strategy is implemented, setting fixed time periods for full inspection and including bolts with currently measured preload force lower than the warning threshold in the target bolt list.

[0054] The event strategy forces a re-inspection after equipment start-up / shutdown, overheating, or abnormal vibration, and includes all bolts in the target bolt list.

[0055] The prediction strategy, based on historical data, fits a relaxation curve and includes bolts with a predicted remaining life value lower than a preset time threshold in the target bolt list.

[0056] The manual command strategy involves remotely initiating a re-tightening command via the maintenance terminal to add the specified bolts to the target bolt list.

[0057] In one embodiment of the present invention, when any bolt is in an alarm state and the duration exceeds a preset duration, the bolt is preferentially included in the target bolt list.

[0058] In one embodiment of the present invention, the tightening operation employs a segmented tightening strategy, including:

[0059] During the rapid tightening phase, the tightening operation is performed at the first rotation speed, and the measured preload is adjusted to the first preset ratio of the target preload value.

[0060] During the servo slow tightening stage, the tightening operation is performed at the second speed, and the measured pre-tightening force is adjusted from the first preset ratio of the target pre-tightening force value to the second preset ratio. The second speed is less than the first speed, and the second preset ratio is greater than the first preset ratio but less than 1.

[0061] During the closed-loop tightening stage of axial force, the tightening operation is performed at a preset torque change rate. The measured preload is gradually approached from the second preset ratio of the target preload value to the target preload value. When the measured preload reaches the preset deviation range of the target preload value, the system switches to holding mode and records the final torque value of the process.

[0062] In one embodiment of the present invention, the mobile automatic tightening robot performs tightening operations on the target bolts in the re-tightening decision instruction sequentially according to the optimal path, and skips bolts whose current measured preload is greater than or equal to the target preload value.

[0063] In one embodiment of the present invention, when the measured preload after re-tightening reaches a preset deviation range of the target preload value, a shutdown command is issued. After re-tightening is completed, the process further includes:

[0064] Once the pressure holding stage begins, and the pressure holding time is not less than the preset time, the actual preload of the bolt is read again. If the actual preload after re-tightening is stable within the preset deviation range of the target preload value, the re-tightening verification is deemed successful; otherwise, the re-tightening verification is deemed unsuccessful and the bolt is marked as a failed re-tightening bolt.

[0065] As can be seen from the above solutions, the advantages of the present invention are:

[0066] The intelligent monitoring and re-tightening system and method based on preload closed-loop control provided by this invention uses wireless preload sensing nodes in the sensing layer, each corresponding to a bolt, to directly collect the measured preload of each bolt, achieving high-precision direct measurement of the preload. The control layer receives the measured preload uploaded from the sensing layer and automatically generates a re-tightening decision command, driving a mobile automatic tightening robot, slidably mounted on a circular track mechanism, to move along the circular track mechanism to the target bolt position. The tightening module then performs the tightening operation on the nut. The entire re-tightening process requires no manual intervention and responds rapidly. By receiving the measured preload of the current bolt from the sensing layer in real time during the re-tightening process, the control layer achieves precise re-tightening control with the measured preload as the sole closed-loop variable. Attached Figure Description

[0067] Figure 1 This is a schematic diagram of the overall architecture of an intelligent monitoring and re-tightening system based on preload closed-loop control provided in an embodiment of the present invention;

[0068] Figure 2 This is a schematic diagram of the execution layer structure;

[0069] Figure 3 Cross-sectional view of the bolt sensor mounting structure;

[0070] Figure 4 This is a flowchart illustrating an online intelligent monitoring and automatic re-tightening method provided in one embodiment;

[0071] Figure 5 This is a schematic diagram of the specific process for step S2.

[0072] The attached figures are labeled as follows:

[0073] 1-Sensing layer, 11-Sensing node, 111-Piezoelectric ultrasonic sensing chip, 112-Temperature sensor, 113-Miniature battery power supply module, 114-Wireless communication module, 12-Resin encapsulation;

[0074] 2-Execution layer, 21-Circular track mechanism, 22-Mobile automatic tightening robot, 221-Drive mechanism, 2211-Circular slider, 2212-Linear slider, 2213-Linear slide rail, 222-Tightening module, 2221-Servo tightening shaft, 2222-Floating sleeve, 223-Connecting bracket, 224-Industrial camera;

[0075] 3-Control Layer, 31-Central Control Cabinet, 311-Programmable Logic Controller, 312-Industrial Ethernet Switch, 313-Data Server, 32-Host Computer Software Platform, 321-Real-time Monitoring Module, 322-Intelligent Diagnosis Module, 323-Task Scheduling Module, 324-Closed-Loop Operation Execution Module, 325-Verification Module, 326-Tightening Process Monitoring Module, 327-Report Generation and Traceability Module;

[0076] 4- Bolt, 41- Head end face, 42- Bolt rod. Detailed Implementation

[0077] It should be noted that, in this invention, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus.

[0078] In the absence of further restrictions, an element defined by the phrase "comprising a..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0079] Example 1:

[0080] See Figure 1 , Figure 2 , Figure 3 , Figure 1This is a schematic diagram of the overall architecture of an intelligent monitoring and re-tightening system based on preload closed-loop control, provided in an embodiment of the present invention. Figure 2 This is a schematic diagram of the execution layer structure; Figure 3 Cross-sectional view of the bolt sensor mounting structure.

[0081] An intelligent monitoring and re-tightening system based on preload closed-loop control includes: a device flange (not shown in the figure), on which multiple bolts are installed, and each bolt is fitted with a nut; and a sensing layer 1, an execution layer 2, and a control layer 3.

[0082] The sensing layer 1 includes multiple wireless preload sensing nodes 11, each of which is installed on each bolt to collect the measured preload of each bolt.

[0083] The execution layer 2 includes: a ring track mechanism 21, fixed to the outer peripheral surface of the equipment flange; and a mobile automatic tightening robot 22, which is slidably mounted on the ring track mechanism 21 and can move along the ring track mechanism 21. The mobile automatic tightening robot 22 is equipped with a tightening module 222 to perform tightening operations on the nuts on the bolts.

[0084] The control layer 3 is communicatively connected to the perception layer 1 and the execution layer 2, respectively, and is used to receive the measured preload force uploaded by the perception layer, generate a re-tightening decision command based on the measured preload force and the target preload force value, and drive the mobile automatic tightening robot to perform a tightening operation on the nut according to the re-tightening decision command.

[0085] refer to Figure 3 As shown, the wireless preload sensing node 11 includes: a piezoelectric ultrasonic sensing chip 111, a temperature sensor 112, a micro battery power supply module 113, and a wireless communication module 114. The piezoelectric ultrasonic sensing chip 111 is embedded in the head end face 41 of the bolt 4 and is used to emit ultrasonic waves to the bolt shank 42 and receive the reflected echoes.

[0086] Temperature sensor 112 is integrated with the piezoelectric ultrasonic sensor chip 111 in the same sensing unit, for example, placed on the side of the piezoelectric ultrasonic sensor chip 111, and also embedded in the head end face of the bolt 4, for collecting the current measured temperature of the environment where the bolt is located. A micro battery power supply module 113 powers the piezoelectric ultrasonic sensor chip 111, temperature sensor 112, and wireless communication module 114; the wireless communication module 114 is electrically connected to the piezoelectric ultrasonic sensor chip 111 and temperature sensor 112, for wirelessly transmitting the collected measured preload force and current measured temperature to the control layer. Preferably, the wireless communication module supports low-power wide-area communication protocols such as LoRa, ZigBee, or 5G NR-RedCap. The piezoelectric ultrasonic sensor chip 111 is 1.2 mm thick and 8 mm in diameter, and is glued to the head end face 41 with epoxy resin; the temperature sensor 112 uses a PT100 platinum resistance thermometer with an accuracy of ±0.2℃. The 113 micro battery power supply module uses a 3.7 V / 60 mAh lithium polymer battery, and the wireless communication module uses the 114ESP32-C3-MINI-1 wireless module, which supports LoRa and Bluetooth 5.0.

[0087] The wireless preload sensor node 11 can be installed on each bolt 4 by resin sealing 12. The wireless preload sensor node 11 can be adapted to different types of bolts such as M8 to M120.

[0088] In a preferred embodiment, the piezoelectric ultrasonic sensor chip is a bidirectional transceiver structure, and the head end face is provided with a reflective surface or the bolt center hole is used as a reflection path to permanently integrate the piezoelectric ultrasonic sensor chip 111 onto the bolt head end face, forming a "sensor-bolt integrated unit" to avoid secondary installation errors.

[0089] Specifically, the measured preload is calculated based on the longitudinal wave travel time difference of the ultrasonic wave propagating along the bolt shank and a calibration coefficient. The preload is obtained through calibration conversion of the change in ultrasonic wave travel time within the bolt shank, enabling direct and continuous monitoring of the bolt's true axial force. The calculation formula is as follows:

[0090]

[0091] Where F is the preload, For longitudinal wave acoustic time difference, These are calibration coefficients; the calibration coefficients, after temperature compensation, are calculated according to the formula... Correction, among which As the benchmark calibration coefficient, Temperature-corrected slope This represents the deviation between the current measured temperature and the standard temperature.

[0092] The calibration coefficient is corrected by temperature, which enables high-precision measurement over a wide temperature range (-40℃ to +125℃).

[0093] In this embodiment, the sensing layer uses a piezoelectric ultrasonic sensor chip to directly measure the change in ultrasonic propagation time within the bolt shank. After calibration and conversion, the true axial force of the bolt is obtained, replacing the traditional torque method that indirectly calculates the preload through torque value. This fundamentally eliminates systematic errors caused by factors such as differences in thread friction coefficient and fluctuations in end-face friction coefficient. At the same time, the three-dimensional calibration model of "acoustic time difference - temperature - axial force" eliminates temperature drift through dual-frequency compensation, achieving a measurement error ≤ ±3% FS and a repeatability error ≤ 3% within the range of -40℃ to +125℃.

[0094] refer to Figure 2 As shown, the mobile automatic tightening robot 22 includes: a drive mechanism 221 and a tightening module 222. The drive mechanism 221 can move along the annular track mechanism 21.

[0095] The drive mechanism 221 includes an annular slider 2211, a linear slider 2212, and a linear slide rail 2213. The annular slider 2211 is slidably mounted on the annular track mechanism 21 and can travel along the annular track mechanism. The linear slide rail 2213 is fixedly mounted on the annular slider 2211. The linear slider 2212 is slidably mounted on the linear slide rail 2213 and can move laterally along the linear slide rail 2213.

[0096] The tightening module 222 is fixedly installed below the linear slider 2212 via a connecting bracket 223 and moves together with the linear slider 2212. Specifically, the tightening module 222 includes: a servo tightening shaft 2221, fixedly installed on the end of the connecting bracket 223 away from the linear slider 2212, used to output tightening torque; and a floating sleeve 2222 installed on the output end of the servo tightening shaft 2221, used for automatic positioning and fitting onto the nut assembled with the bolt 4. The servo tightening shaft has a range of 10–100 N·m and an accuracy of ±1% FS.

[0097] The mobile automatic tightening robot 22 is also equipped with an industrial camera 224, which is fixedly installed at the end of the connecting bracket 223, close to the floating sleeve 2222, to identify the bolt position and confirm the tightening status. In addition, the bolt can be illuminated by a ring-shaped LED light source, which, together with the industrial camera, can identify the bolt center positioning accuracy to ±0.05 mm.

[0098] In addition, a high-precision torque sensor and an angle sensor (not shown in the figure) can be further installed at the output end of the servo tightening shaft 2221.

[0099] The floating sleeve has three-dimensional fine-tuning capabilities in the lateral, axial, and angular directions. In a preferred embodiment, the floating sleeve 2222 has an internal elastic element, such as a spring (not shown in the figure), allowing the sleeve to compress / extend axially. When the floating sleeve contacts the nut assembled with the bolt 4, the spring compression absorbs the height difference, ensuring a tight fit between the floating sleeve 2222 and the nut end face. The floating sleeve 2222 is mounted on the output end of the servo tightening shaft 2221. Preferably, the floating sleeve 2222 and the output end of the servo tightening shaft are connected via a spherical or elastic element, allowing a small angular deflection between the sleeve axis and the tightening shaft axis to compensate for the angular deviation of the bolt axis. Furthermore, the lateral movement of the linear slider along the linear guide rail synchronously drives the lateral movement of the floating sleeve 2222. In this case, adjusting the axial and angular directions of the floating sleeve by the elastic element is a passive fine-tuning.

[0100] In another preferred embodiment, the tightening module is equipped with an electric-servo composite floating mechanism (not shown in the figure). The electric-servo composite floating mechanism is located between the connecting bracket 223 and the servo tightening shaft 2221, or integrated inside the servo tightening shaft 2221, so that the entire tightening module or the tightening shaft itself has active axial movement and angular deflection capabilities, for example, setting the axial floating stroke to 5-15 mm and the radial floating angle to ±2°. In this case, the tightening module supports two tightening modes: "constant torque" and "constant axial force". In the constant axial force mode, the tightening module constructs a dual closed-loop control of torque and axial force according to the re-tightening decision command. When the measured pre-tightening force reaches the preset deviation range of the target pre-tightening force value, the motor power is immediately cut off and the module is locked to prevent overload.

[0101] Further reference Figure 1 As shown, the control layer 3 includes a central control cabinet 31 housing a programmable logic controller (PLC) 311, an industrial Ethernet switch 312, and a data server 313. The PLC 311 is electrically connected to the execution layer 2 via signal lines and outputs control commands. The PLC 311 establishes a data link with the wireless communication module of the sensing layer 1 through the industrial Ethernet switch 312, and receives data uploaded by the wireless preload sensor node 11. The data server 313 uses SQLite local + MySQL cloud synchronization, supporting real-time / historical queries.

[0102] Control layer 3 also includes: a host computer software platform 32, installed on an engineering workstation or maintenance terminal, communicating with the data server, and comprising:

[0103] The real-time monitoring module 321 displays the measured preload of each bolt on the screen in a bolt ring topology diagram, and uses different colors to distinguish different states. For example, green / yellow / red correspond to different levels such as compliance, warning, and alarm.

[0104] The intelligent diagnostic module 322 has a dynamic preload lower limit, for example... And based on time trend data, the loosening trend of bolts is predicted.

[0105] The task scheduling module 323 is used to generate re-tightening work orders and supports multiple task modes such as single-point re-tightening, batch re-tightening, timed inspection, and event-triggered re-tightening.

[0106] The closed-loop execution module 324 is used to generate robot path planning instructions, control the mobile automatic tightening robot to inspect along the optimal path, skip bolts with measured preload greater than or equal to the target preload value, and perform re-tightening on bolts with measured preload less than the target preload value.

[0107] The verification module 325 is used to read the measured preload of the bolt again after the bolt has been retightened, and to verify whether the measured preload after retightening is stable within the preset deviation range of the target preload value. If so, the retightening verification is deemed to have passed; otherwise, the retightening verification is deemed to have failed and the bolt is marked as a failed retightening bolt.

[0108] The tightening process monitoring module 326 is used to monitor the current and axial reaction force of the tightening module in real time. When the current exceeds the safety threshold, it triggers an emergency stop command and alarms.

[0109] The report generation and traceability module 327 is used to output a re-tightening test report containing bolt identification, measured pre-tightening force before re-tightening, measured pre-tightening force after re-tightening, target pre-tightening force value, final torque value, temperature, timestamp, equipment ID, and operating robot number.

[0110] In addition, the control layer reserves industrial communication interfaces such as OPC UA, Modbus TCP, and Profinet, supporting integration with factory MES systems and possessing industrial Internet of Things (IIoT) access capabilities.

[0111] In addition, in one embodiment, a human-machine safety protection mechanism is further provided, including: a physical fence set in the robot's walking area, a photoelectric gate installed at the entrance of the physical fence, and an obstacle avoidance sensor installed on the drive mechanism.

[0112] In practical applications, the above system is suitable for, but not limited to, the following equipment: inlet and outlet flanges of large compressors in the petrochemical industry, main shaft flanges and gearbox connections of wind turbine generators, turbine top covers and generator flanges of hydropower / thermal power equipment, and coupler and bogie connection structures of rail transit locomotives. Bolt rings can be circular or polygonal, and the number of bolts supported ranges from 6 to 64. The system replaces traditional periodic manual inspections with online automatic monitoring, significantly reducing downtime and improving equipment availability. The mobile automatic tightening robot has a short single tightening operation time, significantly improving efficiency compared to manual tightening and reducing manual inspection and maintenance costs. After tightening, it automatically generates a tightening report containing bolt identification, measured pre-tightening force before tightening, measured pre-tightening force after tightening, target pre-tightening force value, final torque value, temperature, timestamp, equipment ID, and operating robot number, enabling full-process data traceability and facilitating equipment management and maintenance decisions.

[0113] Example 2:

[0114] refer to Figure 4 As shown, Figure 4 A flowchart illustrating an online intelligent monitoring and automatic re-tightening method according to one embodiment is shown.

[0115] An online intelligent monitoring and automatic re-tightening method using the above system includes the following steps:

[0116] Step S1: Collect the measured preload force of each bolt.

[0117] Step S2: Generate a re-tightening decision command based on the measured preload and target preload values, and drive the mobile automatic tightening robot to perform tightening operation on the nut according to the re-tightening decision command.

[0118] In a preferred implementation, refer to Figure 5 , Figure 5 A schematic diagram of the specific process for step S2 is shown.

[0119] The steps of generating a re-tightening decision command based on the measured preload and target preload values, and driving the mobile automatic tightening robot to perform a tightening operation on the nut according to the re-tightening decision command, include:

[0120] Step S21: Compare the measured preload of each bolt with preset warning thresholds and alarm thresholds. The warning threshold and alarm threshold are both different proportions of the target preload value, with the alarm threshold being lower than the warning threshold and the warning threshold being less than the target preload value. For example, the warning threshold is set to 90% of the target preload value, and the alarm threshold is set to 70% of the target preload value.

[0121] Step S22: When the measured preload is less than the alarm threshold, a re-tightening decision instruction is generated. The re-tightening decision instruction includes a target bolt list and the target preload value corresponding to each bolt. The target bolt list includes bolts whose measured preload is less than the alarm threshold.

[0122] Step S23: The mobile automatic tightening robot executes the re-tightening decision command, walks along the circular track mechanism to the position of the target bolt, the tightening module performs a tightening operation on the nut of the target bolt, and when the measured pre-tightening force after re-tightening reaches the preset deviation range of the target pre-tightening force value, the robot is instructed to stop, thus completing the re-tightening.

[0123] In addition, when the measured pre-tightening force is less than the warning threshold but greater than or equal to the alarm threshold, it is marked as a warning state and an alarm message is pushed, but the re-tightening decision instruction is not generated.

[0124] When the measured preload is less than the alarm threshold, an alarm state is marked and an alarm is triggered, and the re-tightening decision command is generated at the same time.

[0125] When the measured preload is greater than the warning threshold, it is in a normal state. At this time, the measured preload reaches the preset deviation range of the target preload value, that is, the measured preload is equal to or within the preset deviation range of the target preload value, and no re-tightening is required.

[0126] In a preferred implementation, the triggering condition for generating the complex tightening decision instruction includes at least one of the following:

[0127] A time-based strategy is implemented, which involves setting fixed time periods for full inspection, such as daily or weekly, and including bolts with a current measured preload force lower than the warning threshold in the target bolt list.

[0128] The event strategy forces a re-inspection after equipment start-up / shutdown, overheating, or abnormal vibration, and includes all bolts in the target bolt list.

[0129] The prediction strategy, based on historical data and fitting relaxation curves, includes bolts with remaining life prediction values ​​below a preset time threshold in the target bolt list, that is, bolts with insufficient service life are given priority for re-tightening.

[0130] The manual command strategy involves remotely initiating a re-tightening command via the maintenance terminal to add the specified bolts to the target bolt list.

[0131] In a preferred implementation, when any bolt is in an alarm state for a duration exceeding a preset duration, that bolt is preferentially included in the target bolt list.

[0132] In a preferred implementation, the tightening operation employs a segmented tightening strategy, including:

[0133] During the rapid tightening phase, the tightening operation is performed at a first rotational speed, adjusting the measured preload to a first preset ratio of the target preload value. For example, the first rotational speed is set to 50 rpm, and the first preset ratio is set to 70%. By rapidly tightening to 70% of the target preload, efficiency is improved.

[0134] During the servo slow tightening phase, tightening is performed at a second rotational speed. The measured preload is adjusted from a first preset ratio to a second preset ratio of the target preload value. The second rotational speed is less than the first rotational speed, and the second preset ratio is greater than the first preset ratio but less than 1. For example, the second rotational speed is set to ≤10 rpm, and the second preset ratio is set to 90%. Servo slow tightening reduces inertial fluctuations.

[0135] During the closed-loop tightening phase of the axial force, the tightening operation is performed at a preset torque change rate. The measured preload gradually approaches the target preload value from a second preset percentage of the target preload value. When the measured preload reaches the preset deviation range of the target preload value, the system switches to holding mode, and the final torque value of this process is recorded. For example, the target preload value is approached at a preset torque change rate of 2 N*m / s, and when it reaches the ±2% range of the target preload value, the system switches to holding mode.

[0136] The mobile automatic tightening robot sequentially tightens the target bolts in the re-tightening decision command according to the optimal path, skipping bolts whose current measured preload is greater than or equal to the target preload value. At this time, the mobile automatic tightening robot obtains the geometric coordinates of each target bolt on the equipment flange based on the target bolt list in the re-tightening decision command, and plans its travel path based on its current position to determine the optimal path. It then sequentially travels along the circular track mechanism to the position of each target bolt to perform the tightening operation, skipping bolts whose current measured preload has reached or exceeded the target preload value.

[0137] In a preferred implementation, when the measured preload after re-tightening reaches the preset deviation range of the target preload value, the machine is stopped. After re-tightening is completed, the process further includes: entering the pressure holding stage, and after the pressure holding time is not less than a preset time, such as 2 seconds, the measured preload of the bolt is read again. If the measured preload after re-tightening is stable within the preset deviation range of the target preload value, the re-tightening verification is deemed to have passed; otherwise, the re-tightening verification is deemed to have failed and the bolt is marked as a failed re-tightening bolt.

[0138] It should be noted that this method implementation can be implemented in conjunction with the above-described system implementation. The relevant technical details mentioned in the above system implementation remain valid in this method implementation, and will not be repeated here to avoid repetition.

[0139] The embodiments of the present invention have been described above with reference to the accompanying drawings. However, the present invention is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of the present invention without departing from the spirit and scope of the claims, and all of these forms are within the protection scope of the present invention.

Claims

1. An intelligent monitoring and re-tightening system based on preload closed-loop control, characterized in that, include: The equipment flange is equipped with multiple bolts, and each bolt is fitted with a nut. The sensing layer includes multiple wireless preload sensing nodes, each of which is installed on each bolt to collect the measured preload of each bolt. The execution layer includes: A ring track mechanism is fixed to the outer circumferential surface of the equipment flange; A mobile automatic tightening robot is slidably mounted on the circular track mechanism and can move along the circular track mechanism. The mobile automatic tightening robot is equipped with a tightening module to perform tightening operations on the nut. The control layer is communicatively connected to the perception layer and the execution layer, respectively. It is used to receive the measured preload force uploaded by the perception layer, generate a re-tightening decision command based on the measured preload force and the target preload force value, and drive the mobile automatic tightening robot to perform a tightening operation on the nut according to the re-tightening decision command.

2. The system according to claim 1, characterized in that, The wireless preload sensing node includes: A piezoelectric ultrasonic sensor chip is embedded in the head end face of the bolt and is used to emit ultrasonic waves into the bolt body and receive the reflected echoes. A temperature sensor, integrated with the piezoelectric ultrasonic sensing chip, is used to collect the current measured temperature of the environment where the bolt is located. The piezoelectric ultrasonic sensor chip is a bidirectional transceiver structure, and the head end face is provided with a reflective surface or uses the bolt center hole as a reflection path. The measured preload is calculated based on the longitudinal wave travel time difference and calibration coefficient of the ultrasonic wave propagating along the bolt shank. The calculation formula is as follows: Where F is the preload, For longitudinal wave acoustic time difference, These are calibration coefficients; the calibration coefficients, after temperature compensation, are calculated according to the formula... Correction, among which As the benchmark calibration coefficient, Temperature-corrected slope This represents the deviation between the current measured temperature and the standard temperature.

3. The system according to claim 2, characterized in that, The wireless preload sensing node also includes: A miniature battery-powered module is used to power the sensing nodes; The wireless communication module is electrically connected to the piezoelectric ultrasonic sensing chip and the temperature sensor, and is used to wirelessly transmit the collected measured preload force and the current measured temperature to the control layer. The wireless communication module supports LoRa, ZigBee, or 5G NR-RedCap low-power wide-area communication protocols.

4. The system according to claim 1, characterized in that, The mobile automatic tightening robot includes: The drive mechanism includes: An annular slider is slidably mounted on the annular track mechanism and can travel along the annular track mechanism; A linear slide rail is fixedly installed on the annular sliding member; A linear slider is slidably mounted on the linear slide rail and can move laterally along the linear slide rail; A tightening module is fixedly mounted on a linear sliding member via a connecting bracket and moves together with the linear sliding member. The tightening module includes: A servo tightening shaft is fixedly installed on the end of the connecting bracket away from the linear sliding member, and is used to output tightening torque; A floating sleeve is installed at the output end of the servo tightening shaft and is used for automatic positioning and fitting into the nut.

5. The system according to claim 4, wherein the control layer comprises: The central control cabinet has a built-in programmable logic controller, an industrial Ethernet switch and a data server. The programmable logic controller is electrically connected to the execution layer through signal lines and outputs control commands. The programmable logic controller establishes a data link with the wireless communication module of the sensing layer through the industrial Ethernet switch and receives data uploaded by the wireless preload sensing node.

6. The system according to claim 5, wherein the control layer comprises: The host computer software platform, installed on an engineering workstation or maintenance terminal, communicates with the data server and includes: The real-time monitoring module is used to display the measured preload of each bolt on the display screen in a bolt ring topology diagram, and to distinguish different states with different color codes; The intelligent diagnostic module has a dynamic preload lower limit and predicts the loosening trend of bolts based on time trend data; The task scheduling module is used to generate re-tightening work orders and supports multiple task modes such as single-point re-tightening, batch re-tightening, timed inspection, and event-triggered re-tightening. The closed-loop execution module is used to generate robot path planning instructions, control the mobile automatic tightening robot to inspect along the optimal path, skip bolts with measured preload force greater than or equal to the target preload force value, and perform re-tightening on bolts with measured preload force less than the target preload force value. The verification module is used to read the measured preload of the bolt again after the bolt has been retightened, and to verify whether the measured preload after retightening is stable within the preset deviation range of the target preload value. If it is, the retightening verification is deemed to have passed; otherwise, the retightening verification is deemed to have failed and the bolt is marked as a failed retightening bolt. The tightening process monitoring module is used to monitor the current and axial reaction force of the tightening module in real time. When the current exceeds the safety threshold, it triggers an emergency stop command and alarms. The report generation and traceability module is used to output a retightening test report that includes bolt identification, measured preload before retightening, measured preload after retightening, target preload value, final torque value, temperature, timestamp, equipment ID, and operating robot number.

7. An online intelligent monitoring and automatic re-tightening method using the system described in any one of claims 1 to 6, characterized in that, include: Collect the measured preload force of each bolt; Based on the measured preload and target preload values, a re-tightening decision command is generated, and the mobile automatic tightening robot is driven to perform a tightening operation on the nut according to the re-tightening decision command.

8. The method according to claim 7, characterized in that, The steps of generating a re-tightening decision command based on the measured preload and target preload values, and driving the mobile automatic tightening robot to perform a tightening operation on the nut according to the re-tightening decision command, include: The measured preload of each bolt is compared with the preset warning threshold and alarm threshold, wherein the warning threshold and the alarm threshold are different proportions of the target preload value, and the alarm threshold is lower than the warning threshold, and the warning threshold is less than the target preload value. When the measured preload is less than the alarm threshold, a re-tightening decision instruction is generated. The re-tightening decision instruction includes a target bolt list and the target preload value corresponding to each bolt. The target bolt list includes bolts whose measured preload is less than the alarm threshold. The mobile automatic tightening robot executes the re-tightening decision command, walks along the circular track mechanism to the position of the target bolt, the tightening module performs the tightening operation on the nut of the target bolt, and when the measured pre-tightening force after re-tightening reaches the preset deviation range of the target pre-tightening force value, the robot is instructed to stop, thus completing the re-tightening.

9. The method according to claim 8, characterized in that, When the measured preload force is less than the warning threshold but greater than or equal to the alarm threshold, it is marked as a warning state and an alarm message is pushed, but the re-tightening decision instruction is not generated. When the measured preload is less than the alarm threshold, an alarm state is marked and an alarm is triggered, and the re-tightening decision command is generated at the same time.

10. The method according to claim 9, characterized in that, The triggering conditions for generating the complex tightening decision instruction include at least one of the following: A time-based strategy is implemented, setting fixed time periods for full inspection and including bolts with currently measured preload force lower than the warning threshold in the target bolt list. The event strategy forces a re-inspection after equipment start-up / shutdown, overheating, or abnormal vibration, and includes all bolts in the target bolt list. The prediction strategy, based on historical data, fits a relaxation curve and includes bolts with a predicted remaining life value lower than a preset time threshold in the target bolt list. The manual command strategy involves remotely initiating a re-tightening command via the maintenance terminal to add the specified bolts to the target bolt list.

11. The method according to claim 9 or 10, characterized in that, When any bolt is in an alarm state for a duration exceeding a preset time, that bolt will be preferentially included in the target bolt list.

12. The method according to claim 11, characterized in that, The tightening operation employs a segmented tightening strategy, including: During the rapid tightening phase, the tightening operation is performed at the first rotation speed, and the measured preload is adjusted to the first preset ratio of the target preload value. During the servo slow tightening stage, the tightening operation is performed at the second speed, and the measured pre-tightening force is adjusted from the first preset ratio of the target pre-tightening force value to the second preset ratio. The second speed is less than the first speed, and the second preset ratio is greater than the first preset ratio but less than 1. During the closed-loop tightening stage of axial force, the tightening operation is performed at a preset torque change rate. The measured preload is gradually approached from the second preset ratio of the target preload value to the target preload value. When the measured preload reaches the preset deviation range of the target preload value, the system switches to holding mode and records the final torque value of the process.

13. The method according to claim 8, characterized in that, The mobile automatic tightening robot performs tightening operations on the target bolts in the re-tightening decision command in sequence according to the optimal path, and skips bolts whose current measured preload is greater than or equal to the target preload value.

14. The method according to claim 8, characterized in that, When the measured preload after retightening reaches the preset deviation range of the target preload value, the machine is stopped. After retightening, the process also includes: Once the pressure holding stage begins, and the pressure holding time is not less than the preset time, the actual preload of the bolt is read again. If the actual preload after re-tightening is stable within the preset deviation range of the target preload value, the re-tightening verification is deemed successful; otherwise, the re-tightening verification is deemed unsuccessful and the bolt is marked as a failed re-tightening bolt.

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