Implementation method of dual-channel speed measurement, detection equipment and transportation equipment

Abstract

The invention discloses a dual-channel speed measurement implementation method, detection equipment and transportation equipment, and the method comprises the steps: carrying out the distance measurement of a target object through a laser detection module, and measuring the acceleration of the target object through an acceleration detection module; and then receiving the distance data transmitted by the first transmission module and the acceleration data transmitted by the second transmission module through a judgment output module, and determining a speed measurement result of the target object. The speed of the target object is measured through double-channel data fusion of laser ranging and acceleration detection, the speed of the target object is verified through laser ranging and acceleration detection by using two different measurement principles, and the method has the advantages that the reliability of a measurement system is improved, and common cause failure is avoided.

Description

Technical Field

[0001] This disclosure generally relates to the field of speed measurement technology, and specifically to a method for implementing dual-channel speed measurement, a detection device, and a transportation device. Background Technology

[0002] For applications requiring high security and reliability, a "1oo2" system architecture is typically used to enhance security. Its core principle lies in achieving a high level of security integrity through dual redundancy design.

[0003] Currently, the speed of a target object is often measured using two devices with the same measurement method. However, both devices are prone to measurement failure due to the same factor, resulting in a "common cause failure" problem. Therefore, a new speed measurement method is needed to solve this problem. Summary of the Invention

[0004] In view of the above-mentioned defects or deficiencies in the prior art, it is desirable to provide a method for implementing dual-channel speed measurement, a detection device, and a transport device, which can solve the common cause failure problem caused by the same device measuring the same object.

[0005] A first aspect provides a method for implementing dual-channel velocity measurement, the method being applied to a detection device, the detection device including a laser detection module, an acceleration detection module, and a judgment output module, the laser detection module being electrically connected to the judgment output module via a first transmission module, and the acceleration detection module being electrically connected to the judgment output module via a second transmission module, the method comprising: The laser detection module measures the distance to the target object to obtain distance data of the target object relative to the laser detection module. The acceleration of the target object is measured by the acceleration detection module to obtain acceleration data. The judgment output module receives the distance data through the first transmission module and the acceleration data through the second transmission module, and determines the velocity measurement result of the target object based on the distance data and the acceleration data.

[0006] The dual-channel velocity measurement method provided in this application measures the distance to a target object using a laser detection module and the acceleration of the target object using an acceleration detection module. Then, a judgment output module receives the distance data from the first transmission module and the acceleration data from the second transmission module to determine the velocity measurement result of the target object. By fusing laser ranging and acceleration detection data into dual-channel data, the velocity of the target object is measured. The use of two different measurement principles to verify the velocity of the target object improves the reliability of the measurement system and avoids common-cause failures.

[0007] The second aspect provides a detection device, which includes a laser detection module, an acceleration detection module, and a judgment output module. The laser detection module is electrically connected to the judgment output module through a first transmission module, and the acceleration detection module is electrically connected to the judgment output module through a second transmission module. The laser detection module is used to measure the distance to the target object and obtain the distance data of the target object relative to the laser detection module; The acceleration detection module is used to measure the acceleration of the target object and obtain acceleration data; The judgment output module is used to receive the distance data through the first transmission module and the acceleration data through the second transmission module, and to determine the velocity measurement result of the target object based on the distance data and the acceleration data.

[0008] The third aspect provides a transportation device on which the detection device provided in the second aspect is installed; The detection device is used to emit a laser into the pit where the transport equipment is located during the movement of the transport equipment, and to determine the distance data of the transport equipment relative to the pit based on the laser. The detection device is also used to measure the acceleration of the transport equipment during its movement and obtain acceleration data. The detection device is also used to determine the speed measurement result of the transport equipment based on the distance data and the acceleration data. Attached Figure Description

[0009] Other features, objects, and advantages of this application will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings: Figure 1 This application provides a schematic diagram of the structure of a testing device; Figure 2 A flowchart illustrating the steps of a dual-channel velocity measurement method provided in this application; Figure 3 A flowchart illustrating the steps of a dual-channel velocity measurement method provided in this application; Figure 4 A schematic diagram of another testing device provided in this application; Figure 5 A flowchart illustrating the steps of a dual-channel velocity measurement method provided in this application; Figure 6 A flowchart illustrating the steps of a dual-channel velocity measurement method provided in this application; Figure 7 This is a structural schematic diagram of an elevator device provided in this application.

[0010] Figure label: 100. Testing equipment; 10. Laser detection module; 11. Acceleration detection module; 12. First transmission module; 13. Second transmission module; 14. Judgment output module; 15. Monitoring module. Detailed Implementation

[0011] The present application will now be described in further detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and not intended to limit it. Furthermore, it should be noted that, for ease of description, only the parts relevant to the invention are shown in the accompanying drawings.

[0012] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. This application will now be described in detail with reference to the accompanying drawings and embodiments.

[0013] In existing technologies, high safety integrity systems often employ dual redundancy designs to improve reliability. However, traditional solutions rely on sensors with the same measurement principle, such as using two accelerometers simultaneously. When affected by environmental factors such as external vibration or electromagnetic interference, both sensors may fail simultaneously, leading to a common-cause failure risk. For example, in elevator car speed monitoring scenarios, if both accelerometers experience data drift simultaneously due to abnormal vibrations in the car, the system will be unable to identify the true speed, posing a safety hazard.

[0014] To address the aforementioned problems, the inventors discovered that the root cause of common-cause failure lies in redundant units using the same method to measure physical quantities. Combining sensors with different measurement principles, such as acquiring velocity data through two independent pathways—distance change rate and acceleration integral—can effectively reduce the probability of common-cause failure. Based on this idea, a dual-channel velocity measurement implementation method was designed.

[0015] Before describing the implementation method of dual-channel velocity measurement provided in this application, the structure of the detection device for implementing the method of this application will be described first.

[0016] like Figure 1 As shown, the detection device 100 provided in this application includes a laser detection module 10, an acceleration detection module 11, and a judgment output module 14. The laser detection module 10 is electrically connected to the judgment output module 14 through a first transmission module 12, and the acceleration detection module 11 is electrically connected to the judgment output module 14 through a second transmission module 13.

[0017] The laser detection module 10 refers to a device that measures distance by emitting laser light and receiving reflected signals. This can be implemented using devices such as lidar, time-of-flight sensors, or laser sensors. Its function is to provide an independent measurement data source based on optical principles. The acceleration detection module 11 refers to a device that obtains acceleration information by detecting changes in inertial force. This can be implemented using devices such as MEMS accelerometers or piezoelectric sensors. Its function is to provide an independent measurement data source based on kinematic principles.

[0018] The first transmission module 12 and the second transmission module 13 refer to the physical channels for data communication, which can be implemented using RS-485 bus, CAN bus, wireless communication module, or transmission circuit. Their function is to ensure that the data transmission paths of different measurement modules are isolated from each other. The judgment output module 14 refers to the control unit with data processing capabilities, which can be implemented using embedded microprocessor, FPGA chip, sampling sensor, etc. Its function is to improve measurement reliability through dual-channel data fusion.

[0019] Based on the above description of the structure of the detection device 100, the implementation method of the dual-channel speed measurement provided in this application will be explained below, such as... Figure 2 As shown, the method includes the following steps: Step S20: The laser detection module 10 measures the distance to the target object to obtain the distance data of the target object relative to the laser detection module 10; The laser detection module 10 is used to measure the distance to a target object using optical principles. For example, the laser detection module 10 uses a 905 nm pulsed laser diode in conjunction with a photodetector. The laser detection module 10 emits a laser beam towards the target object or other objects capable of measuring the distance to the target object, receives the reflected signal, and then calculates the distance data of the target object relative to the laser detection module 10 using the time between the emitted light speed and the received reflected signal, as well as the speed of light itself. The laser detection module 10 is independent of inertial sensors, avoiding interference from mechanical vibrations on the measurement data.

[0020] For example, if the detection equipment is installed on the elevator car, and the goal is to measure the distance between the elevator car and the pit to determine the elevator car's position, this can be achieved by using a laser emitter to emit laser pulses to the pit at a fixed sampling frequency, then receiving the time difference of the reflected signals from the pit to calculate the real-time distance value, forming a time-distance sequence. This allows the calculation of the distance between the elevator car and the pit. In this case, the target object is the pit. Since the laser detection module 10 is installed on the elevator car, the distance between the elevator car and the pit can be equivalent to the distance between the laser detection module 10 and the pit.

[0021] Step S30: Measure the acceleration of the target object through the acceleration detection module 11 to obtain acceleration data; The acceleration detection module 11 refers to a sensor unit that measures the acceleration of a target's motion, such as a MEMS accelerometer or a piezoelectric sensor. This acceleration detection module does not depend on the external optical environment and can operate normally in darkness or smoke conditions.

[0022] For example, during the up-and-down movement of the elevator car, the acceleration detection module 11 can continuously collect the acceleration data of the elevator car, and output the acceleration time series after filtering.

[0023] In step S40, the output module 14 determines the speed measurement result of the target object based on the distance data received by the first transmission module 12 and the acceleration data received by the second transmission module 13.

[0024] The judgment output module 14 receives distance data and acceleration data through different channels (first transmission module 12 and second transmission module 13), respectively. It then converts the distance and acceleration data into data with the same dimensions for judgment, enabling the judgment output module 14 to make judgments based on the same standard and improving the accuracy of the judgment. For example, the judgment output module 14 can process the distance and velocity data according to the relationship between distance data and velocity, and the relationship between acceleration data and velocity, respectively, to obtain two different velocity data sets. The processed velocity data is then used to determine the velocity measurement result of the target object.

[0025] This application constructs independent measurement channels using two different physical principles: laser ranging and acceleration measurement. For example, in a dusty environment in an elevator shaft, the laser ranging result may fail due to reduced visibility, but the acceleration module can still function normally. Conversely, when the elevator car is subjected to strong electromagnetic interference, the acceleration data may be abnormal, but the operation of the laser detection module remains unaffected. This heterogeneous redundancy design significantly reduces the probability of common-cause failure.

[0026] Through the above technical solution, this application effectively solves the common-cause failure problem of similar sensor redundancy systems. For example, in elevator speed monitoring scenarios, when one sensor fails due to environmental factors, the system can automatically switch to another sensor to maintain normal operation, while simultaneously detecting abnormal states in a timely manner through data comparison. This dual-channel heterogeneous measurement mechanism improves the overall reliability of the system while ensuring measurement accuracy.

[0027] In an optional embodiment, such as Figure 3 As shown, Figure 3 An optional method embodiment for determining the velocity measurement result of a target object, provided as an exemplary embodiment of this application, includes the following steps: Step S301: Perform target processing on the distance data and acceleration data to obtain first velocity data and second velocity data. Target processing is the operation of processing the distance data and acceleration data into the same physical quantity. Since the final calculation required by this application is the velocity of the target object, and the distance and acceleration data of the target object are obtained through different detection principles, the distance and acceleration data must be processed to obtain the corresponding velocity data in order to determine the velocity measurement result of the target object.

[0028] Target processing refers to converting the original measurement data of different physical quantities into velocity data of the same physical quantity. This target processing makes the measurement results of two different principles comparable, thus providing a basis for subsequent deviation judgment.

[0029] Optionally, the first velocity data can be obtained by differential processing of distance data and the second velocity data can be obtained by integral processing of acceleration data.

[0030] Differential processing refers to converting the rate of change of distance data over time into velocity data. This can be achieved using numerical differentiation algorithms or difference calculations. For example, instantaneous velocity can be obtained by calculating the distance difference between two adjacent time points and dividing by the time interval. Integral processing refers to converting acceleration data accumulated over time into velocity data. This can be achieved using numerical integration algorithms or the trapezoidal integral method. For example, the velocity change can be obtained by multiplying the acceleration data by the time interval and summing the results. By performing differential and integral processing on the raw data of different physical quantities separately, velocity information can be derived from two independent data sources, avoiding the error propagation caused by a single data processing method.

[0031] Step S302: Determine whether there is a deviation between the first speed data and the second speed data; if there is a deviation, proceed to step S303; if there is no deviation, proceed to step S304. Step S303: Determine that the velocity measurement result of the target object is invalid; Step S304: Use the first speed data or the second speed data as the speed measurement result of the target object.

[0032] Here, deviation refers to the degree of difference between two speed data sets (i.e., the degree of difference between the first speed data set and the second speed data set). For example, a preset threshold range can be used for judgment, or the difference between the two can be directly calculated to determine the deviation. This judgment mechanism is used to identify data anomalies and avoid erroneous results output due to the failure of a single measurement source.

[0033] For example, distance data is acquired through a laser ranging module, and acceleration data is collected through an accelerometer. Distance data is converted into velocity values ​​through differentiation, and acceleration data is converted into velocity values ​​through integration. The two velocity data are input to the judgment output module 14 for real-time comparison. When the difference between the two exceeds a preset threshold, the measurement result is deemed unreliable and marked as invalid; if the difference is within the allowable range, either velocity value (first velocity data or second velocity data) is output as the final result. Thus, through dual independent data processing paths and a cross-validation mechanism, the risk of data failure due to a single factor is effectively avoided.

[0034] This application significantly reduces the probability of common-cause failure by using heterogeneous data sources of laser ranging and inertial measurement, combined with complementary data processing methods of differentiation and integration. For example, when elevator vibration causes accelerometer drift, laser ranging data can still provide reliable velocity information; conversely, when the laser is blocked, inertial measurement data can still maintain the normal operation of the system.

[0035] Through the above technical solution, this application achieves real-time self-checking and fault-tolerant processing of speed measurement results. It promptly stops erroneous output when abnormal data is detected and provides reliable speed values ​​when the data is consistent. This solution is particularly suitable for high-safety scenarios such as elevator car speed monitoring, avoiding the risk of misjudgment due to sensor failure and ensuring that the system maintains effective monitoring functionality even in the event of a single sensor failure.

[0036] In an optional embodiment, such as Figure 4 As shown, the detection device 100 also includes a monitoring module 15, and the first transmission module 12 and the second transmission module 13 are electrically connected to the judgment output module 14 through the monitoring module 15.

[0037] Combination Figure 4 This application provides an optional embodiment of a novel dual-channel velocity measurement method, such as... Figure 5 As shown, an embodiment of this method includes the following steps: Step S501: The operating status of the first transmission module 12 and the second transmission module 13 are monitored by the monitoring module 15 to obtain the first monitoring data and the second monitoring data. The monitoring module 15 is a hardware unit used to monitor the operating status of the first transmission module 12 and the second transmission module 13 in real time. The monitoring module 15 can be implemented using, for example, a monitoring circuit, a transmission module with a heartbeat packet detection mechanism or a cyclic redundancy check algorithm, etc., to determine whether the data transmission between the laser detection module 10 and the judgment output module 14 is normal, and whether the data transmission between the acceleration detection module 11 and the judgment output module 14 is normal. The operating status of the first transmission module 12 includes, for example, its power-off state, current state, voltage state, CPU state, and throughput state; similarly, the operating status of the second transmission module 13 includes, for example, the power-off state, current state, voltage state, CPU state, and throughput state of the first transmission module 12.

[0038] The first transmission module 12 refers to the physical channel for data communication, which can be implemented using RS-485 bus, CAN bus, wireless communication module, transmission circuit, etc. Its function is to ensure that the data transmission paths of different measurement modules are isolated from each other. The first transmission module 12 carries the communication link for laser detection data and is used to transmit the digital signals generated by distance measurement.

[0039] Similarly, the second transmission module 13 refers to the physical channel for data communication, which can be implemented using RS-485 bus, CAN bus, wireless communication module, transmission circuit, etc. Its function is to ensure that the data transmission paths of different measurement modules are isolated from each other. The second transmission module 13 refers to the communication link carrying acceleration data, used to transmit the analog signal output by the acceleration sensor.

[0040] Step S502: Determine the velocity measurement result of the target object based on the first monitoring data, the second monitoring data, the distance data, and the acceleration data.

[0041] For example, during system operation, the monitoring module 15 continuously monitors the voltage fluctuations, data packet loss rate, or clock synchronization status of the first transmission module 12, generating first monitoring data containing status codes. Additionally, the monitoring module 15 also synchronously monitors the noise interference level, signal delay, or number of checksum errors of the second transmission module 13, generating second monitoring data containing status indicators. When the judgment output module 14 receives distance and acceleration data, it first parses the status codes in the first monitoring data and the status indicators in the second monitoring data, and then determines the velocity measurement result of the target object based on the parsing results combined with the distance and acceleration data.

[0042] This application utilizes a status monitoring module to perform real-time diagnostics on heterogeneous transmission channels, achieving fault isolation at the physical layer. When an anomaly occurs in one transmission channel, it can automatically switch to another normal channel to continue operation, avoiding the problem of system-wide failure due to a single fault.

[0043] Through the above technical solution, this application effectively solves the measurement interruption problem caused by common-cause failure in traditional redundant systems. In the elevator speed monitoring scenario, if the laser detection module 10 malfunctions due to external environmental stress or internal circuit abnormalities, the system can automatically switch to the integration mode of the acceleration detection module 11 to maintain speed calculation; if the internal circuit of the acceleration detection module 11 malfunctions, the system can switch to the ranging differential mode of the laser detection module 10 to continue working. This dynamic channel switching mechanism significantly improves the system's continuous operation capability under complex working conditions and ensures the reliability of speed monitoring in safety-critical areas.

[0044] like Figure 6 As shown, this application provides an optional method embodiment for determining the velocity measurement result of a target object, which includes the following steps: Step S601: If the first monitoring data is abnormal, the distance data is determined to be invalid. Then, the acceleration data is integrated to obtain the second velocity data, and the second velocity data is used as the velocity measurement result of the target object. The first monitoring data refers to the monitoring results of the detection module 15 on the operating status of the first transmission module 12. For example, it can be achieved by detecting signal transmission delay or data packet loss rate, and is used to determine the validity of the distance data transmitted by the first transmission module 12. Integration processing refers to converting acceleration data into velocity data by accumulating it over time. Specifically, it can be implemented using the trapezoidal integral method or the Simpson integral method, and is used to generate alternative velocity data based on acceleration data when distance data fails.

[0045] For example, if the first transmission module 12 experiences signal delay or data loss, the judgment output module 14 may mark the first monitoring data as abnormal. In this case, the distance data is considered unreliable, and the judgment output module 14 may instead generate second velocity data as the final measurement result by integrating the acceleration data.

[0046] Step S602: If the second monitoring data is abnormal, the acceleration data is determined to be invalid. The distance data is differentiated to obtain the first velocity data, and the first velocity data is used as the velocity measurement result of the target object. The second monitoring data refers to the monitoring results obtained by the monitoring module 15 after detecting the operating status of the second transmission module 13. Specifically, it can be achieved by detecting voltage fluctuations or the number of communication interruptions, and is used to determine the validity of the acceleration data.

[0047] Differential processing refers to calculating instantaneous velocity based on the rate of change of distance data over time. Specifically, it can be implemented using the central difference method or the forward difference method, and is used to generate alternative velocity data when acceleration data becomes invalid.

[0048] For example, if the second transmission module 13 experiences a voltage abnormality or communication interruption, the judgment output module 14 may mark the second monitoring data as abnormal. At this time, the acceleration data is considered unreliable, and the judgment output module 14 may instead generate the first velocity data as the final measurement result by differential processing of the distance data.

[0049] Step S603: If both the first monitoring data and the second monitoring data are normal, then determine the velocity measurement result of the target object based on the distance data and acceleration data.

[0050] If both transmission modules are functioning normally, the output module 14 can perform cross-validation of the two data sources and select the consistent speed result for output.

[0051] Compared with existing technologies, redundant devices using the same measurement method are prone to simultaneous failure of both channels due to the same interference factor. This solution avoids the problem of overall measurement failure due to a single transmission failure by independently monitoring the status of the transmission module and dynamically switching the data source.

[0052] Through the above technical solution, this application can automatically switch to a valid data source when some data transmission is abnormal, ensuring the continuity and reliability of speed measurement results. It is especially suitable for scenarios with extremely high requirements for safety and redundancy, such as elevator equipment, and effectively reduces the risk of common cause failure.

[0053] Optionally, this application further proposes a technical solution whereby the judgment output module 14 outputs error information or target data containing error markers after determining that the velocity measurement result of the target object is invalid. The target data is distance data and / or acceleration data.

[0054] Here, error messages refer to signals indicating abnormalities in velocity measurement results. These can be implemented using preset error codes or warning signals, such as transmitting the abnormal status via digital signals. Error markers are identifiers appended to the raw data. These can be implemented using specific bits in the data frame or independent check fields, such as adding an abnormality flag to the distance data header to distinguish it from normal data. Target data refers to raw measurement data that has not been completely discarded. Specifically, it can include at least one of the distance data from the laser detection module 10 or the acceleration data from the acceleration detection module 11. For example, acceleration data can be retained for subsequent analysis when the transmission link is abnormal.

[0055] For example, when the deviation between the first velocity data and the second velocity data exceeds a preset threshold, the judgment output module 14 will trigger an error handling mechanism. At this time, the error information is sent to an external monitoring system through the communication interface, for example, by notifying the host computer to handle the anomaly in the form of an interrupt signal. At the same time, the distance data or acceleration data containing the error mark is cached in the storage unit, for example, retaining the original velocity data and acceleration data with an added error mark, for maintenance personnel to retrieve and analyze. If both the laser detection module 10 and the acceleration detection module 11 malfunction simultaneously, both types of data are marked and error information is output.

[0056] Compared to existing technologies, which typically only discard abnormal data or stop output, making it impossible for the system to distinguish between occasional interference and hardware failures, this solution actively outputs error information and labeled data, enabling external systems to quickly identify the type of anomaly. For example, error labels can distinguish between sensor failure and transmission link interruption, while retaining the original data to provide a basis for fault tracing.

[0057] Through the above technical solution, this application can avoid the misuse of invalid speed data leading to control command errors. For example, when the elevator braking system receives invalid speed data, it can directly adopt the safety mode. At the same time, the erroneously marked target data provides effective information for offline diagnosis. For example, maintenance personnel can use the marked data to locate abnormal sampling cycles in the laser detection module 10, thus shortening equipment maintenance time.

[0058] The structure of the testing device 100 provided in this application has been described above. Combined with the above description of the implementation method of dual-channel speed measurement, the function of each module of the testing device 100 can be understood, and will not be repeated here.

[0059] Another aspect of this application provides a transportation device, which is, for example, a... Figure 7 The elevator equipment shown can also be a lift, ladder, hoist, etc. The transportation equipment is equipped with detection equipment 100. The detection device 100 is used to emit a laser into the pit where the transport equipment is located during the movement of the transport equipment, and to determine the distance data of the transport equipment relative to the pit based on the laser. The detection device 100 is also used to measure the acceleration of the transport equipment during its movement and obtain acceleration data; The detection device 100 is also used to determine the speed measurement results of the transport equipment based on distance data and acceleration data.

[0060] The detection device 100 refers to an integrated device comprising a laser detection module 10, an acceleration detection module 11, a transmission module, and a judgment output module 14. For example, it can be implemented using an embedded sensor module combined with a data processing unit, used to simultaneously acquire distance and acceleration information. The laser detection module 10 is a sensor based on the principle of optical ranging, specifically implemented using a pulsed laser emitter and receiver, calculating distance changes by measuring the time difference of laser reflection. The acceleration detection module 11 is a sensor based on an inertial measurement unit, for example, implemented using a triaxial accelerometer combined with a signal conditioning circuit, acquiring acceleration data by detecting changes in the inertial force of the elevator car.

[0061] Specifically, during the operation of the transport equipment, the laser detection module 10 continuously emits laser pulses into the pit and calculates the real-time distance between the transport equipment and the pit by receiving the time difference of the reflected signals, thus generating distance data. Simultaneously, the acceleration detection module 11 collects the acceleration signals generated by the movement of the transport equipment in real time, generating acceleration data.

[0062] Optionally, the detection device 100 can convert distance data into first velocity data through differential processing, and acceleration data into second velocity data through integral processing, and determine the speed measurement result of the elevator car based on the first velocity data and the second velocity data. The two velocity data are compared and verified. If the deviation is within a preset threshold range or the two are consistent, the first velocity data or the second velocity data is output as the effective speed measurement result for the transportation equipment; if the deviation exceeds the threshold or there is a difference between the two, an error handling mechanism is triggered.

[0063] In some specific embodiments, the sampling frequency of the laser detection module 10 can be set to, for example, 1 kHz, and the data acquisition period of the acceleration detection module 11 can be set to, for example, 0.1 ms. Differentiation and integration operations can be implemented using the trapezoidal integration method or the Simpson integration method. When the transmission module malfunctions, the velocity calculation is performed preferentially using the unaffected sensor data.

[0064] Compared to existing technologies, dual-sensor systems using the same measurement principle are prone to simultaneous failure due to common factors such as environmental vibration and electromagnetic interference. This solution combines sensors based on two different physical principles—optical ranging and inertial measurement—to achieve heterogeneous redundancy at the data acquisition level, effectively reducing the risk of failure due to common factors. Simultaneously, a cross-validation mechanism using differential and integral operations enhances the reliability of speed calculations.

[0065] Through the above technical solution, this application enables independent speed measurement via dual channels during the operation of transportation equipment. If the laser detection module 10 fails due to obstruction, for example, by foreign objects in the pit, the speed monitoring function can still be maintained by the data obtained from the acceleration detection module 11. Conversely, if the acceleration detection module 11 drifts due to mechanical impact, the laser detection module 10 can provide an accurate speed reference. The complementary design of the two measurement methods significantly improves the fault tolerance and safety level of the transportation equipment speed monitoring system.

[0066] This application further proposes a transportation device, on which a detection device 100 is installed. The detection device 100 is used to emit a laser towards the pit in the space where the transportation device is located during the movement of the transportation device, and to determine the distance data of the transportation device relative to the pit based on the laser. The detection device 100 is also used to measure the acceleration of the transportation device during the movement of the transportation device and to obtain acceleration data. Specifically, the detection device 100 is used to perform differential processing on the distance data to obtain first velocity data, and to perform integral processing on the acceleration data to obtain second velocity data, and to determine the velocity measurement result of the transportation device based on the first velocity data and the second velocity data.

[0067] Differential processing refers to calculating the slope of the distance data over time, which can be achieved using numerical differential algorithms, such as the central difference method or the three-point formula, thus converting the rate of change of distance into velocity data. Integral processing refers to calculating the cumulative amount of acceleration data over time, which can be achieved using the trapezoidal integral method or Simpson's integral method, thus converting the continuous effect of acceleration into velocity data. The first and second velocity data represent velocity values ​​derived from different physical quantities, respectively. Comparing the deviation between the two can verify the reliability of the measurement results.

[0068] Specifically, when the transport equipment is running, the laser detection module 10 continuously emits pulsed lasers into the pit and receives reflected signals, obtaining real-time distance data with millimeter-level accuracy by calculating the time of flight of the light waves. The acceleration detection module 11 uses a three-axis MEMS sensor to collect the acceleration information of the car's movement, and the sampling frequency can be set to 100Hz. The distance data is processed by differentiation to generate a first velocity curve, and the acceleration data is processed by integration to generate a second velocity curve. When the fluctuation range of the two velocity curves is within a preset threshold, the judgment output module 14 outputs any set of data as a valid velocity value; if the deviation between the two exceeds the threshold, an abnormal alarm mechanism is triggered. Furthermore, the operating status of the first transmission module 12 and the second transmission module 13 can be monitored in real time, for example, through CRC check or heartbeat packet detection, to ensure the integrity of the data transmission channel.

[0069] Compared to existing technologies, traditional dual-redundant velocity measurement systems, which use sensors based on the same principle (e.g., dual radar speed measuring devices), are prone to simultaneous failure due to electromagnetic interference or mechanical vibration. This solution, by fusing heterogeneous data sources from optical ranging and inertial measurement, utilizes the mathematical complementarity of differential and integral algorithms to physically avoid the risk of common-cause failure. Simultaneously, the independent monitoring mechanism of the transmission channel can distinguish the source of data anomalies. For example, when the laser detection module 10 fails due to dust obstruction, the system can automatically switch to the acceleration integration mode of the acceleration detection module 11 to maintain velocity monitoring functionality.

[0070] Through the above technical solution, this application solves the common-cause failure problem caused by homogeneous sensors in traditional redundant measurement systems, and realizes a heterogeneous redundancy design for the speed monitoring system of transportation equipment. By cross-validating two independent calculation paths, optical ranging differentiation and inertial integration, the reliability of speed data is improved. At the same time, fault isolation is achieved by utilizing transmission channel status monitoring, ensuring that the basic speed measurement function can still be maintained when a single sensor fails, thereby meeting the reliability requirements of redundant systems in transportation equipment safety standards.

[0071] The above description is merely a preferred embodiment of this application and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of the invention involved in this application is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the inventive concept. For example, technical solutions formed by substituting the above features with (but not limited to) technical features with similar functions disclosed in this application.

Claims

1. A method for implementing dual-channel velocity measurement, the method being applied to a detection device, the detection device comprising a laser detection module, an acceleration detection module, and a judgment output module, wherein the laser detection module is electrically connected to the judgment output module via a first transmission module, and the acceleration detection module is electrically connected to the judgment output module via a second transmission module, characterized in that... The method includes: The laser detection module measures the distance to the target object to obtain distance data of the target object relative to the laser detection module. The acceleration of the target object is measured by the acceleration detection module to obtain acceleration data. The judgment output module receives the distance data through the first transmission module and the acceleration data through the second transmission module, and determines the velocity measurement result of the target object based on the distance data and the acceleration data.

2. The method according to claim 1, characterized in that, Determining the velocity measurement result of the target object based on the distance data and the acceleration data includes: The distance data and the acceleration data are subjected to target processing to obtain first velocity data and second velocity data. The target processing is the operation of processing the distance data and the acceleration data into the same physical quantity. Determine whether there is a deviation between the first speed data and the second speed data; If the aforementioned deviation exists, the velocity measurement result of the target object is determined to be invalid; If the deviation does not exist, the first speed data or the second speed data shall be used as the speed measurement result of the target object.

3. The method according to claim 2, characterized in that, The target processing of the distance data and the acceleration data includes: The first velocity data is obtained by differentiating the distance data; The acceleration data is integrated to obtain the second velocity data.

4. The method according to claim 1, characterized in that, The detection device further includes a monitoring module, and the method further includes: The monitoring module monitors the operating status of the first transmission module and the second transmission module to obtain first monitoring data and second monitoring data. Determining the velocity measurement result of the target object based on the distance data and the acceleration data includes: The velocity measurement result of the target object is determined based on the first monitoring data, the second monitoring data, the distance data, and the acceleration data.

5. The method according to claim 4, characterized in that, Determining the velocity measurement result of the target object based on the first monitoring data, the second monitoring data, the distance data, and the acceleration data includes: If the first monitoring data is abnormal, the distance data is determined to be invalid. Then, the acceleration data is integrated to obtain the second velocity data, and the second velocity data is used as the velocity measurement result of the target object. If the second monitoring data is abnormal, the acceleration data is determined to be invalid. The distance data is then differentiated to obtain the first velocity data, which is used as the velocity measurement result of the target object. If both the first monitoring data and the second monitoring data are normal, the velocity measurement result of the target object is determined based on the distance data and the acceleration data.

6. The method according to claim 2, characterized in that, The method further includes: After determining that the velocity measurement result of the target object is invalid, the judgment output module outputs an error message or target data containing an error mark, wherein the target data is the distance data and / or the acceleration data.

7. A testing device, characterized in that, The detection device includes a laser detection module, an acceleration detection module, and a judgment output module. The laser detection module is electrically connected to the judgment output module through a first transmission module, and the acceleration detection module is electrically connected to the judgment output module through a second transmission module. The laser detection module is used to measure the distance to the target object and obtain the distance data of the target object relative to the laser detection module; The acceleration detection module is used to measure the acceleration of the target object and obtain acceleration data; The judgment output module is used to receive the distance data through the first transmission module and the acceleration data through the second transmission module, and to determine the velocity measurement result of the target object based on the distance data and the acceleration data.

8. The detection device according to claim 7, characterized in that, The detection device further includes a monitoring module, and the first transmission module and the second transmission module are electrically connected to the judgment output module through the monitoring module; The monitoring module is used to monitor the operating status of the first transmission module and the second transmission module, and obtain first monitoring data and second monitoring data. The judgment output module is further configured to receive the first monitoring data and the second monitoring data, and determine the velocity measurement result of the target object based on the first monitoring data, the second monitoring data, the distance data and the acceleration data.

9. A transportation device, characterized in that, The transport equipment is equipped with the detection equipment described in claims 7-8; The detection device is used to emit a laser into the pit where the transport equipment is located during the movement of the transport equipment, and to determine the distance data of the transport equipment relative to the pit based on the laser. The detection device is also used to measure the acceleration of the transport equipment during its movement and obtain acceleration data. The detection device is also used to determine the speed measurement result of the transport equipment based on the distance data and the acceleration data.

10. The transport equipment according to claim 9, characterized in that, The detection device is specifically used to perform differential processing on the distance data to obtain first speed data, and to perform integral processing on the acceleration data to obtain second speed data, and to determine the speed measurement result of the transport device based on the first speed data and the second speed data.

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