Offline automatic detection system and method for adjustable pallet fork forklift

Abstract

The invention discloses an off-line automatic detection system and method for an adjustable pallet fork forklift, relates to the technical field of forklifts, and aims at solving the technical problems that manual detection is low in efficiency and large in error, and an existing automatic system is not targeted and needs intrusive transformation. The E2 simulates a handle signal to generate a CAN instruction sequence of fork action and whole vehicle movement, and drives the E1 to control the hydraulic solenoid valve and the motor to execute action; meanwhile, pressure, temperature and stroke data are collected in real time, the minimum value and the maximum value of the pressure are updated through a dynamic extreme value tracking algorithm, and the action time and the movement distance are accurately calculated. And after the proximity switch K1 / K2 is triggered, the E2 is forced to shut down through a high-priority CAN message, so that the safety is ensured. And the interactive instrument M1 sets parameters, automatically stores detection data, and compares the detection data with a preset standard to generate a judgment report. Full-process automatic detection is achieved, the method is suitable for multiple vehicle types, hardware transformation is not needed, and an efficient and reliable scheme is provided for quality inspection of the electric forklift.

Description

Technical Field

[0001] The present invention relates to the technical field of forklifts, and in particular to an adjustable fork forklift off-line automatic detection system and method thereof. Background Art

[0002] In the production process of industrial vehicles, off-line detection is a very important link, especially for electric industrial products such as fork-adjustable electric forklifts with certain risks. Such electric products with certain risks have strict requirements for parameters such as the running duration of single actions, the hydraulic system pressure during the action process, and the temperature of the motor after continuous actions. Once unqualified, serious safety hazards may occur. The actions of small fork-adjustable electric forklifts include six basic actions: fork opening, fork retraction, fork lifting, fork lowering, vehicle forward movement, and vehicle backward movement. The main off-line detection items include the running time, running speed, vehicle hydraulic system pressure, motor temperature, power consumption, etc. of these six actions. Specifically, after the electric forklift is off-line, it is necessary to detect whether the durations of the four actions of fork lifting, fork lowering, fork opening, and fork retraction meet the requirements. Both too fast and too slow durations are unqualified. The speeds of vehicle forward movement and vehicle backward movement need to be within a certain range. Both too fast and too slow speeds do not meet the standards. The hydraulic system pressure value during the vehicle running process should also be within a certain range. Too large a system pressure will increase energy consumption, and too small a system pressure may make the vehicle powerless and unable to complete normal work. Data such as motor temperature and power consumption also reflect the performance of the vehicle and should meet the standards.

[0003] The prior art has significant limitations: Manual detection depends on the reaction speed of quality inspectors, and the recording error of the fork lifting time is too large, with low detection efficiency and insufficient result credibility; for example, the Chinese invention patent authorization document CN113341939B discloses a vehicle off-line detection system and method, and although this solution reduces manual intervention, its design does not meet the special requirements of fork-adjustable electric forklifts. It can neither accurately obtain the extreme value of hydraulic pressure (such as the dynamic change of pressure from the initial value to pressure build-up), nor can it automatically calculate the fork action time difference (Δt). In addition, such a system needs to modify the vehicle hardware (such as installing sensors or controllers), which damages the original vehicle structure and increases the adaptation cost. Summary of the Invention

[0004] The present invention aims to solve the technical defects of low efficiency and large errors in manual detection of forklift trucks with adjustable forks, as well as the non-targeted and invasive transformation of existing automated detection systems. By connecting an external controller E2 to the original vehicle CAN bus and reserved diagnostic interface, pressure, temperature, and travel data are obtained in real time. The external controller E2 simulates the handle signal and sends a full-action instruction sequence to the vehicle controller E1 to achieve automated control of fork lifting / lowering / spreading / retracting and vehicle forward / backward movement. At the same time, combined with the dynamic extreme value tracking algorithm, the hydraulic pressure data is analyzed in real time during the fork movement, the minimum pressure value X1 and the maximum pressure value X2 are dynamically updated, and the action time Δt is accurately calculated to eliminate manual recording errors. In addition, magnetic proximity switches K1 / K2 are used to monitor the vehicle movement boundary in real time. After the trigger signal, the instruction is forced to interrupt and the machine stops to avoid collision risks during automatic detection. Finally, the interactive instrument M1 automatically stores the detection data and compares it with the preset standard to generate a judgment result, forming a non-invasive and fully closed-loop detection process, significantly improving the detection accuracy and efficiency, and ensuring vehicle safety and compliance.

[0005] The present invention provides an automated detection system for off-line forklift trucks with adjustable forks, which includes: an external controller E2 that sends action instructions to the vehicle controller E1 through the CAN bus; proximity switches K1 and K2 that are connected to the DI port of the external controller E2 and send signals to the external controller E2; an interactive instrument M1 that communicates bidirectionally with the external controller E2 through the CAN bus, sends setting information or start signals to the external controller E2, and displays the data sent by the external controller E2; and a vehicle controller E1 that transmits real-time data to the external controller E2 through the CAN bus.

[0006] Preferably, the interactive instrument M1 is connected to the external controller E2 through the CAN bus and sends a detection start instruction and action parameters to the external controller E2. The external controller E2 is connected to the vehicle controller E1 through the CAN bus, simulates the vehicle handle function, and sends CAN instructions for fork lifting / lowering, spreading / retracting, and vehicle forward / backward movement to the vehicle controller E1. The vehicle controller E1 controls the oil pump motor and the traveling motor to drive the hydraulic solenoid valve to act according to the received CAN instructions to complete vehicle execution.

[0007] Preferably, the external controller E2 sends a CAN instruction sequence for fork lifting-lowering-spreading-retracting in a cycle according to the received parameters, and records the motor temperature after each cycle. The vehicle controller E1 controls the oil pump motor to drive the hydraulic solenoid valve in each cycle, and feedbacks the maximum system pressure value X2 and the action time Δt to the external controller E2 through the CAN bus when the fork is lifted to the limit position.

[0008] Preferably, the vehicle controller E1 collects the detection data of the pressure sensor and the temperature sensor in real time through the DI port and the CAN bus; the external controller E2 receives the detection data sent by the vehicle controller E1 through the CAN bus and analyzes and processes it; the interactive instrument M1 receives the data processed by the external controller E2 through the CAN bus, displays it in real time in tabular form, and stores the data in the local memory.

[0009] Preferably, the proximity switches K1 and K2 are respectively installed at the front end and the rear end of the vehicle, and their output ends are connected to the DI port of the external controller E2 to detect the distance between the vehicle and the obstacle. When the proximity switch K1 or K2 is triggered, a high-level signal is output to the DI port of the external controller E2; after receiving the high-level signal, the external controller E2 immediately cuts off the CAN instruction sent to the vehicle controller E1 and sends an emergency shutdown command to the vehicle controller E1 through the CAN bus; according to the shutdown command, the vehicle controller E1 controls the oil pump motor and the traveling motor to power off and reset, and the hydraulic solenoid valve closes.

[0010] Preferably, the proximity switches K1 and K2 are magnetically mounted and are respectively adsorbed on the fork end and the rear end of the frame. When the vehicle moves forward or backward beyond the preset boundary, K1 or K2 is triggered and outputs a high-level signal to the DI port of the external controller E2; after receiving the high-level signal, the external controller E2 interrupts the current CAN instruction loop and sends a reset instruction to the vehicle controller E1 through the CAN bus; when the vehicle controller E1 executes the reset instruction, it turns off the power supply of the oil pump motor and the traveling motor and restores the hydraulic solenoid valve to its initial state.

[0011] The present invention proposes an automatic detection method for the off-line of an adjustable fork forklift. This method is applied to any one of the above-mentioned automatic detection systems for the off-line of an adjustable fork forklift. The method includes: driving the vehicle to move according to the received CAN instruction sequence, and respectively collecting the hydraulic system pressure data and the vehicle moving stroke data in real time through the pressure sensor and the encoder, and transmitting the data through the CAN bus; dynamically updating the minimum and maximum values of the pressure data according to the sending time and the initial pressure of the fork lifting instruction, and calculating the fork action time and the forward / backward distance; repeating the execution of the action instruction according to the preset number of cycles, recording the motor temperature and power consumption after each cycle ends, and storing the data in tabular form.

[0012] Preferably, according to the received parameters, the method generates a CAN instruction sequence according to the preset communication protocol, sets the detection parameters, including the default duration of the fork action, the number of cycles, and the vehicle forward / backward speed threshold, and transmits the parameters through the CAN bus.

[0013] Preferably, when the proximity switch K1 or K2 is detected to be triggered, the method stops issuing CAN instructions according to the trigger signal, sends an emergency stop instruction through the CAN bus, and cuts off the power supply of the oil pump motor and the traveling motor according to the stop instruction, and resets the hydraulic solenoid valve.

[0014] Preferably, the method compares the stored detection data with a preset standard. If all the data are within the threshold range, the vehicle is determined to be qualified; otherwise, it is determined to be unqualified.

[0015] The present invention has the following beneficial effects:

[0016] 1. By directly connecting the external controller E2 to the reserved diagnostic interface of the whole vehicle, reusing the original vehicle CAN bus and sensors (such as pressure, temperature, stroke, etc.), there is no need to modify the vehicle hardware or install additional equipment, which is suitable for different models of fork-adjustable electric forklifts, reducing the deployment cost and improving the system flexibility.

[0017] 2. The external controller E2 automatically generates a sequence of fork action instructions (lifting, lowering, opening, retracting) and vehicle movement instructions (forward, backward), replacing manual operation, eliminating human errors, reducing the detection error of fork action time, and improving the detection efficiency.

[0018] 3. Adopting the dynamic pressure extreme value update algorithm (X1 / X2) combined with timestamp marking (t1 / t2), it can capture the pressure change trend of the hydraulic system in real time and accurately calculate the action time Δt, solving the problem that traditional detection cannot reflect the dynamic pressure characteristics and improving the data accuracy.

[0019] 4. By using the magnetic proximity switches K1 / K2 to monitor the vehicle movement boundary in real time, the instruction is immediately interrupted and forced to stop after the trigger signal, avoiding collision accidents caused by vehicle out-of-control during the automatic detection process, and significantly improving the safety.

[0020] 5. The interactive instrument M1 automatically stores the detection data (Δt, X2, ΔS, temperature, power consumption), and intuitively displays it in tabular form, supports one-key export and automatic comparison with the preset standard, realizing unmanned operation in the whole process from detection to determination, and reducing manual intervention.

[0021] 6. The system adjusts the detection parameters (such as the number of cycles n, action duration t) through software configuration, and can adapt to new vehicle models or update detection standards without hardware modification, reducing the maintenance cost. Description of the Drawings

[0022] Figure 1 is a schematic diagram of the system wiring of the present invention, where 1 is the vehicle controller E1, 2 is the external controller E2, 3 is the interactive instrument M1, 4 is the proximity switch K1, and 5 is the proximity switch K2;

[0023] Figure 2 It is a schematic diagram of the system principle of the present invention;

[0024] Figure 3 It is a schematic diagram of the method flow of the present invention. Specific Embodiments

[0025] Embodiment 1

[0026] According to Figure 1 As shown, the present invention provides an adjustable fork lift truck off-line automatic detection system. Its core components include an external controller E2, a vehicle controller E1, an interactive instrument M1, and proximity switches K1 and K2. The external controller E2 is bidirectionally connected to the interactive instrument M1 through the CAN bus, and at the same time establishes a CAN communication link with the vehicle controller E1 through the diagnostic interface reserved for the vehicle. Both the vehicle controller E1 and the interactive instrument M1 are powered by the original vehicle battery, without the need for additional power supply, avoiding increasing the vehicle load. The proximity switches K1 and K2 are installed in a magnetic adsorption manner, respectively fixed at the end of the fork and the rear end of the vehicle frame, and their output ends are directly connected to the DI (digital input) port of the external controller E2 through cables, for real-time monitoring of the vehicle movement boundary.

[0027] The external controller E2 serves as the control center of the system, undertaking functions such as instruction generation, data processing, and safety protection. It receives the detection parameters (such as the default duration t of fork movement and the number of cycles n) sent by the interactive instrument M1 through the CAN bus, and generates a CAN instruction sequence for fork lifting, lowering, spreading, retracting, and vehicle forward and backward movement based on the preset communication protocol. These instructions are transmitted to the vehicle controller E1 through the diagnostic interface, simulating the control signals of the vehicle handle. After parsing the instructions, the vehicle controller E1 drives the oil pump motor (MO1) and the traveling motor (MO2) to work through the DO (digital output) port, and at the same time controls the power-on and power-off of the lift solenoid valve and the lower solenoid valve of the hydraulic system, so as to accurately execute the fork actions and vehicle movement.

[0028] During the execution of fork actions, the vehicle controller E1 collects the data of the pressure sensor (PRE) and the temperature sensor (TEMP) in real time through the DI port, including the hydraulic system pressure Xn, the motor temperature, and the battery power, and transmits the data back to the external controller E2 through the CAN bus. The external controller E2 performs dynamic extreme value tracking processing on the pressure data: records the initial pressure X0 and the time stamp t1 when sending the fork lifting instruction, then continuously receives the real-time pressure Xn, and dynamically updates the minimum value X1 and the maximum value X2. When it detects that Xn reaches a new maximum value X2 new, records the time stamp t2 and calculates the action time Δt = t2 - t1. For the vehicle forward / backward movement, the external controller E2 sends a movement instruction lasting 60 seconds, and calculates the movement distance ΔS = S2 - S1 through the travel data S fed back by the vehicle controller E1.

[0029] Proximity switches K1 and K2, as safety protection modules, are connected to the external controller E2 through the DI ports. When the vehicle moves forward or backward beyond the preset boundary (such as approaching an obstacle or the edge of the detection area), K1 or K2 is triggered and outputs a high-level signal to E2. The external controller E2 immediately interrupts the current instruction loop and sends an emergency stop command to the vehicle controller E1 through the CAN bus. The vehicle controller E1 then cuts off the power supply of the oil pump motor and the traveling motor, and resets the hydraulic solenoid valve to the closed state to ensure that the vehicle stops.

[0030] The interactive instrument M1 receives the detected data (including Δt, X2, ΔS, temperature, and power consumption) processed by the external controller E2 through the CAN bus and displays it in tabular form on the screen interface in real time. The detected data is automatically stored in the local memory of the instrument and supports being exported to the computer through the USB or network interface for automatic comparison with the preset standard to generate a conformity report. The instrument interface is designed as a three-level menu: the main interface displays the real-time detection status, the setting interface is used to adjust the action duration and the number of cycles, and the result interface shows the stored historical data and the determination conclusion.

[0031] When the system executes the complete detection process, the external controller E2 repeatedly sends the forklift fork action sequence (lifting - lowering - spreading - retracting) and the vehicle movement commands (forward - backward) according to the preset number of cycles n. After each cycle, the motor temperature and power consumption are recorded until all cycles are completed. All the data is summarized by the interactive instrument M1 to generate a detection report, realizing the full-process automation from parameter setting, action execution, data acquisition to result determination.

[0032] The fully automatic offline detection system of the present invention realizes seamless integration with the forklift truck with adjustable forks through a non-intrusive design. Based on the original CAN bus of the vehicle and the reserved diagnostic interface, the external controller E2 directly reuses hardware resources such as pressure sensors, temperature sensors, and encoders without modifying the original electrical architecture of the vehicle, significantly reducing the system deployment complexity and cost. Through the instruction simulation function of the external controller E2, the system can accurately reproduce the manual operation process, generate standardized forklift fork action sequences and vehicle movement commands, and completely eliminate the detection errors caused by inconsistent manual operations. At the same time, the dynamic extreme value tracking algorithm (X1 / X2 update and Δt calculation) combined with the real-time data feedback mechanism enables the detection accuracy of key parameters such as the hydraulic system pressure and action time to far exceed the error levels of ±0.5 seconds and ±2 MPa of traditional manual detection, providing a reliable data basis for vehicle performance evaluation.

[0033] In addition, the system's closed-loop safety protection mechanism and intelligent data management further enhance the reliability and efficiency of the detection process. The magnetic proximity switches K1 / K2 are directly connected to the DI ports of the external controller E2 through hardwired signals to ensure a quick response when the vehicle approaches the boundary. The forced shutdown command is transmitted through high-priority CAN messages to avoid delays caused by bus congestion. The modular design of the interactive instrument M1 supports real-time visualization, local storage, and one-key export of detection data, automatically generates a judgment report in combination with preset standards, and significantly shortens the single detection cycle from 30 minutes in the traditional manual mode. This system has passed the adaptation verification for multiple vehicle models and can be compatible with different specifications of fork-adjustable electric forklifts only by adjusting parameters through software configuration, with broad industrial application prospects.

[0034] Embodiment 2

[0035] According to Figure 2 shown, this embodiment details the connection architecture and data transmission logic of the CAN bus in the present invention. As Figure 2 shown, the external controller E2 accesses the original vehicle CAN bus network through the diagnostic interface reserved by the whole vehicle. The CAN-H (high-level line) and CAN-L (low-level line) of the diagnostic interface are respectively connected to the CAN transceiver pins of the external controller E2 to form a communication link with the vehicle controller E1 and the interactive instrument M1. The vehicle controller E1 serves as the main node on the CAN bus, and its CAN interface is directly connected in parallel with the vehicle internal CAN network. The interactive instrument M1, as an external device, is interconnected with the external controller E2 through an independent CAN channel to form a dual-channel communication structure: the first channel (E2-E1) is used for instruction issuance and sensor data feedback, and the second channel (E2-M1) is used for detection parameter setting and result feedback. The two channels achieve data isolation and priority scheduling through the routing module inside the external controller E2 to avoid bus overload.

[0036] The power supply of the vehicle controller E1 is directly supplied by the vehicle battery through the B+ (power supply positive) and B- (power supply negative) lines. The CAN transceiver terminal of it is set with a resistor to match the vehicle CAN network and ensure signal integrity. The power supply of the external controller E2 is also taken from the battery B+ / B-, but its power supply line is independent of the vehicle controller E1 and is protected against overcurrent through a fuse and a relay to prevent the detection system failure from affecting the vehicle main circuit. The power supply of the interactive instrument M1 is connected through the power output terminal of the external controller E2 and is regulated by the internal power supply module of E2 to output direct current for M1 to use, thus avoiding interference with the vehicle power supply system by directly taking power from the battery.

[0037] In the design of the CAN communication protocol, the external controller E2 and the vehicle controller E1 adopt the standard CAN 2.0B protocol and define the following key messages:

[0038] 1. Instruction message, sent from E2 to E1, including fork movement instructions (lifting, lowering, opening, retracting) and vehicle movement instructions (forward, backward), encoding action type, duration, and cycle identifier in the data field.

[0039] 2. Sensor data message, sent from E1 to E2, including hydraulic system pressure Xn, motor temperature, battery charge, and travel data S, storing each parameter value segmented by byte in the data field.

[0040] 3. Status message, sent from E1 to E2, feedback solenoid valve status, motor operation flag, and fault code.

[0041] 4. Interactive instruction message, sent from M1 to E2, transmitting detection parameters (duration t, cycle number n) and start / stop commands.

[0042] 5. Result message, sent from E2 to M1, including processed detection data (Δt, X2, ΔS, temperature, power consumption) and safety event records.

[0043] The external controller E2 listens for sensor data messages and status messages through the CAN bus, parses pressure, temperature, and travel data in real time, and updates extreme values X1 / X2 and calculates Δt, ΔS based on a preset algorithm. At the same time, E2 encapsulates the processed data into a result message and sends it to M1. After receiving it, M1 parses and refreshes the display interface. When proximity switch K1 or K2 is triggered, E2 immediately stops sending instruction messages and inserts a high-priority emergency stop message to E1, forcing the vehicle controller E1 to perform a power-off reset operation.

[0044] In the physical layer design, CAN-H and CAN-L lines use twisted pair shielded wires, and the shielding layer is grounded at a single point to the battery B-, effectively suppressing electromagnetic interference. The bus transmission rate is set to 250 kbps, meeting the real-time requirements. The CAN interface module of the external controller E2 has a built-in error detection and retransmission mechanism. When a bus error frame is detected, it automatically retransmits unacknowledged messages to ensure reliable transmission of instructions and data.

[0045] The interactive instrument M1 communicates with the external controller E2 through the second CAN channel (independent of the vehicle CAN network) to avoid conflicts with the vehicle's original messages. The interface operation instructions of M1 (such as parameter modification, start detection) are sent to E2 through the interactive instruction message, and E2 updates the internal control logic after response. During the detection process, M1 requests E2 to send result messages at a 100 ms cycle to achieve real-time data refresh. After the detection is completed, M1 exports the stored CAN raw data (including timestamp, message ID, and data field) to the computer through the USB interface for quality inspection personnel to review and archive.

[0046] In this embodiment, through a hierarchical CAN bus architecture, dual-channel communication design, and strict protocol specifications, efficient coordination of instructions, data, and safety signals is achieved, ensuring the stable operation of the system in a complex industrial environment.

[0047] In this embodiment, through a hierarchical CAN bus architecture and dual-channel communication design, efficient compatibility between the detection system and the vehicle's original control network is achieved. The external controller E2 serves as a data hub, isolating the detection parameter setting and result feedback traffic through an independent channel (E2-M1) to avoid bus contention with the vehicle control instructions (E2-E1), ensuring the real-time nature of critical action instructions. The custom message structure of the CAN 2.0B protocol (such as instruction messages and sensor data messages) precisely divides data types and priorities. Combined with a high transmission rate and the physical layer design of twisted pair shielded cables, a very high message transmission success rate can still be maintained in a complex electromagnetic environment. In addition, the error detection and retransmission mechanism built into the external controller E2 can automatically repair communication anomalies caused by interference, further enhancing the system's reliability.

[0048] The CAN bus design of the present invention demonstrates significant advantages in industrial scenarios. Through the reuse of the vehicle diagnostic interface and independent power supply design, the system can be deployed without damaging the vehicle's original wiring harness, greatly reducing the adaptation time. The second CAN channel of the interactive instrument M1 supports seamless docking with external devices (such as computers and cloud servers) to achieve remote monitoring and big data analysis of detection data. Actual tests show that the system fully meets the stringent requirements of the off-line detection of forklift trucks with adjustable forks. This design provides a standardized communication framework for the intelligent detection of industrial vehicles and has the technical potential to be extended to other vehicle models (such as reach trucks and tractors).

[0049] Embodiment 3

[0050] According to Figure 3As shown in the figure, the present invention proposes an off-line automatic detection method for an adjustable fork forklift. At the start of the detection, the operator sets detection parameters through the interactive instrument M1, including the default duration t of the fork movement (such as the lifting / lowering time), the number of cycles n, and the vehicle forward / backward speed threshold. After the setting is completed, M1 sends the parameters to the external controller E2 through the CAN bus. According to the received parameters, the external controller E2 generates a fork movement instruction sequence (lifting → lowering → opening → retracting) and a vehicle movement instruction (forward → backward) according to the preset CAN communication protocol, and encapsulates the instructions into a CAN message (ID: 0x100) and sends it to the vehicle controller E1 through the diagnostic interface. After parsing the instructions, the vehicle controller E1 controls the oil pump motor MO1 to drive the hydraulic solenoid valve to act through the DO port, or controls the walking motor MO2 to drive the vehicle to move. At the same time, it collects the hydraulic system pressure data Xn of the pressure sensor (PRE), the motor temperature data of the temperature sensor (TEMP), and the stroke data S of the encoder through the DI port in real time, and sends the above data back to the external controller E2 in real time through the CAN bus (ID: 0x200).

[0051] During the execution of the fork lifting action, the external controller E2 records the instruction sending time point t1 and the initial pressure X0, and continuously receives the pressure data Xn, dynamically comparing Xn with the current minimum value X1 and the maximum value X2. If Xn < X1, then update X1 to Xn; if Xn > X2, then update X2 to Xn and record the new time point t2. When the fork is lifted to the limit position (the pressure reaches the pressure holding state), calculate the action time Δt = t2 - t1, and record the final pressure maximum value X2 at the same time. For the fork lowering, opening and retracting actions, the same strategy is used to calculate the action time and pressure extreme values. In the vehicle forward / backward action, the external controller E2 sends a moving instruction for 60 seconds, and calculates the moving distance ΔS = S2 - S1 according to the starting stroke S1 and the ending stroke S2 fed back by E1, and checks whether the speed is within the preset threshold range.

[0052] The safety protection mechanism runs through the entire detection process. When the vehicle approaches the boundary obstacle during forward or backward movement, the magnetic proximity switch K1 or K2 is triggered, and a high-level signal is output to the DI port of the external controller E2. E2 immediately interrupts the current CAN instruction issuance and sends an emergency stop instruction to E1 through the CAN bus (ID: 0x600). After receiving the stop instruction, the vehicle controller E1 cuts off the power supply of the oil pump motor MO1 and the walking motor MO2, and resets the hydraulic solenoid valve to the closed state to ensure that the vehicle stops immediately and avoid the risk of collision.

[0053] The detection system repeats the fork actions sequence and the vehicle movement instructions according to the preset number of cycles n. After each cycle ends, the external controller E2 obtains the motor temperature and power consumption data from the vehicle controller E1, and encapsulates the processed detection results (Δt, X2, ΔS, temperature, power consumption) into a CAN message (ID: 0x500) and sends it to the interactive instrument M1. M1 displays the data in tabular form in real time, and stores the complete record in the local memory, and supports exporting to the computer through the USB interface. Finally, the system automatically compares the exported detection data with the preset standards (such as the allowable error of Δt is ±0.1 second, the pressure range of X2 is 20 - 30 MPa, and the temperature threshold is ≤80°C). If all parameters are within the threshold range, the vehicle is judged to be qualified; if any parameter exceeds the limit, it is marked as unqualified and a fault report is generated.

[0054] The entire detection process requires no manual intervention. From parameter setting, instruction execution, data acquisition to result determination, it is fully automated through the CAN bus and the external controller E2. The interactive instrument M1 provides a visual operation interface, supports historical data query, parameter dynamic adjustment and report printing functions, significantly improves the detection efficiency and consistency, and completely solves the problems of large errors and long time consumption in traditional manual detection.

[0055] The full-automatic offline detection method of the present invention realizes the accurate capture and efficient determination of the key performance parameters of the fork-adjustable electric forklift through the dynamic extreme value tracking algorithm and the closed-loop control logic. The external controller E2 analyzes the hydraulic pressure data in real time during the fork action, dynamically updates the minimum value X1 and the maximum value X2, and accurately calculates the action time Δt in combination with the timestamp marks (t1 / t2), greatly reducing the error of ±0.5 seconds in traditional manual detection and significantly improving the pressure detection accuracy. The vehicle movement distance ΔS is double-checked through the encoder travel data and the instruction duration, ensuring that the comprehensive error of speed and distance measurement is significantly better than the measurement results of manual use of a rangefinder or stopwatch. At the same time, the non-invasive design enables the system to reuse the sensor data through the CAN bus without modifying the original vehicle hardware, adapting to the detection requirements of different vehicle models.

[0056] In actual production line tests, this method demonstrates excellent reliability and stability. Taking a certain model of fork-adjustable electric forklift as an example, 10 full-cycle detections (including fork actions, vehicle movement, and safety trigger tests) are continuously executed. The system successfully captures all pressure extreme value changes and action time deviations. The emergency stop mechanism triggered by the proximity switch completes command interruption and motor power-off within 50 ms, effectively avoiding multiple simulated collision risks. The automatic determination function of the interactive instrument M1 significantly compresses the time for generating the detection results of a single vehicle from 15 minutes of manual processing, and supports batch export and cloud synchronization, providing a core tool for the digital management of the production line. This method has passed the ISO 13849 functional safety certification and is applicable to high-paced industrial environments, setting a new technical benchmark for the quality control of electric forklifts.

Claims

1. An automatic detection system for the offline of a forklift with adjustable forks, characterized in that, The system includes: An external controller E2 that sends action instructions to the vehicle controller E1 via the CAN bus; Proximity switches K1 and K2, connected to the DI port of the external controller E2, and sending signals to the external controller E2; An interactive instrument M1 communicates bidirectionally with the external controller E2 via the CAN bus, sends setting information or start signals to the external controller E2, and displays the data sent by the external controller E2; A vehicle controller E1 transmits real-time data to the external controller E2 via the CAN bus.

2. The automatic inspection system for the off-line adjustable fork forklift according to claim 1, characterized in that, The interactive instrument M1 is connected to the external controller E2 via the CAN bus and sends a detection start instruction and action parameters to the external controller E2; the external controller E2 is connected to the vehicle controller E1 via the CAN bus, simulates the function of the vehicle handle, and sends CAN instructions for fork lifting / lowering, opening / closing, and vehicle forward / backward to the vehicle controller E1; the vehicle controller E1 controls the oil pump motor and the traveling motor to drive the hydraulic solenoid valve to act according to the received CAN instructions to complete vehicle execution.

3. An automatic detection system for the offline of a forklift with adjustable forks according to claim 1 or 2, characterized in that, The external controller E2 sends a CAN instruction sequence for fork lifting-lowering-opening-closing in a cycle according to the received parameters, and records the motor temperature after each cycle; the vehicle controller E1 controls the oil pump motor to drive the hydraulic solenoid valve in each cycle, and feedbacks the maximum system pressure X2 and the action time Δt to the external controller E2 via the CAN bus when the fork is lifted to the limit position.

4. An automatic detection system for the offline of a forklift with adjustable forks according to claim 1, characterized in that The vehicle controller E1 real-time collects the detection data of the pressure sensor and the temperature sensor via the DI port and the CAN bus; the external controller E2 receives the detection data sent by the vehicle controller E1 via the CAN bus and analyzes and processes it; the interactive instrument M1 receives the data processed by the external controller E2 via the CAN bus, displays it in real time in tabular form, and stores the data in the local memory.

5. An automatic detection system for the off-line of a forklift with adjustable forks according to claim 1, characterized in that, The proximity switches K1 and K2 are respectively installed at the front end and the rear end of the vehicle, and their output ends are connected to the DI port of the external controller E2 to detect the distance between the vehicle and the obstacle. When the proximity switch K1 or K2 is triggered, a high-level signal is output to the DI port of the external controller E2; after receiving the high-level signal, the external controller E2 immediately cuts off the CAN instructions sent to the vehicle controller E1 and sends an emergency stop command to the vehicle controller E1 via the CAN bus; the vehicle controller E1 controls the oil pump motor and the traveling motor to power off and reset, and the hydraulic solenoid valve closes.

6. An automatic detection system for the offline of a forklift with adjustable forks according to claim 1 or 5, characterized in that, The proximity switches K1 and K2 are magnetically mounted, respectively adsorbed on the fork end and the rear end of the vehicle frame. When the vehicle moves forward or backward beyond the preset boundary, K1 or K2 is triggered and outputs a high-level signal to the DI port of the external controller E2; after receiving the high-level signal, the external controller E2 interrupts the current CAN instruction loop and sends a reset instruction to the vehicle controller E1 through the CAN bus; when the vehicle controller E1 executes the reset instruction, it shuts off the power supply of the oil pump motor and the traveling motor and restores the hydraulic solenoid valve to its initial state.

7. An automated detection method for the off-line of a forklift with adjustable forks, the method being applied to the automated detection system for the off-line of a forklift with adjustable forks according to any one of claims 1 to 6, characterized in that, The method includes: Driving the vehicle to move according to the received CAN instruction sequence, and respectively collecting the hydraulic system pressure data and the vehicle moving travel data in real time through the pressure sensor and the encoder, and transmitting the data through the CAN bus; Dynamically updating the minimum and maximum values of the pressure data according to the sending time and the initial pressure of the fork lifting instruction, and calculating the fork action time and the forward / backward distance; Repeating the execution of the action instruction according to the preset number of cycles, recording the motor temperature and power consumption after each cycle, and storing the data in tabular form.

8. An automated inspection method for the off-line adjustable forklift forks according to claim 7, characterized in that, The method generates a CAN instruction sequence according to the received parameters according to the preset communication protocol, sets the detection parameters, including the default duration of the fork action, the number of cycles, and the vehicle forward / backward speed threshold, and transmits the parameters through the CAN bus.

9. An automated inspection method for the offline of a forklift with adjustable forks according to claim 7 or 8, characterized in that When detecting that the proximity switch K1 or K2 is triggered, the method stops issuing CAN instructions according to the trigger signal, sends an emergency stop instruction through the CAN bus, and cuts off the power supply of the oil pump motor and the traveling motor according to the stop instruction, and resets the hydraulic solenoid valve.

10. An automatic detection method for the offline of a forklift with adjustable forks according to claim 7 or 8, characterized in that, The method compares the stored detection data with the preset standard. If all the data are within the threshold range, the vehicle is determined to be qualified; otherwise, it is determined to be unqualified.

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