Remote operation and maintenance methods and devices for intelligent weighing equipment

Abstract

This application provides a remote operation and maintenance method and apparatus for intelligent weighing equipment. The method includes: acquiring initial acquisition data collected by a signal acquisition device and initial operating data corresponding to the intelligent weighing instrument; the initial acquisition data includes a initial dual-path force measurement data from a dual-redundant sensor and initial signal trigger data from a vehicle separator; preprocessing the initial acquisition data and initial operating data respectively to obtain target acquisition data and target operating data; determining a target state frame based on the target acquisition data and target operating data, and sending the target state frame to the operation and maintenance application layer; receiving a target remote control command from the operation and maintenance application layer in response to the target state frame; and controlling the weighing sensing layer to perform fault recovery operations according to the target remote control command to achieve rapid diagnosis and recovery. Through end-to-end data acquisition and closed-loop processing of remote commands, the efficiency of remote diagnosis and rapid recovery of weighing equipment is improved.

Description

Technical Field

[0001] This application relates to the field of intelligent weighing technology, and in particular to a remote operation and maintenance method and device for intelligent weighing equipment. Background Technology

[0002] Currently, highway entrance and exit weighing systems generally employ a traditional architecture using analog sensors and local instruments. These devices lack IP-based networking capabilities and remote status monitoring, resulting in the following significant drawbacks: when equipment malfunctions, the system cannot detect and accurately locate the fault in real time, relying on manual discovery by toll collectors, thus delaying appropriate action; toll collectors lack professional maintenance skills and can only wait for manufacturer technicians to arrive, leading to prolonged interruptions in weighing operations, causing lane congestion, and severely reducing traffic efficiency. Furthermore, the system lacks lightweight remote handling methods, resulting in high maintenance costs, slow response times, and poor reliability, making it difficult to meet the rigid requirements of 24 / 7 uninterrupted rapid weighing and efficient traffic flow at highway entrances and exits.

[0003] Therefore, improving the efficiency of remote diagnostics and rapid recovery of weighing equipment is an urgent issue that needs to be addressed. Summary of the Invention

[0004] This application provides a remote operation and maintenance method and apparatus for intelligent weighing equipment. By encapsulating the end-to-end device data of each device in the weighing sensing layer into a target status frame and remotely sending it to the operation and maintenance application layer, the remote control commands are received and fault recovery operations are executed, thereby improving the efficiency of remote diagnosis and rapid recovery of weighing equipment.

[0005] In a first aspect, embodiments of this application provide a remote operation and maintenance method for intelligent weighing equipment, applied to the control center layer of a remote operation and maintenance system. The system further includes a weighing sensing layer and an operation and maintenance application layer. The control center layer includes an intelligent weighing instrument; the weighing sensing layer includes *a* dual-redundant sensors, a vehicle separator, and a signal acquisition unit, where *a* is an integer greater than 1. The method includes: Acquire the initial acquisition data collected by the signal acquisition device and the initial operating data corresponding to the intelligent weighing instrument; the initial acquisition data includes a initial dual-path force measurement data of the a dual-redundant sensors and the initial signal triggering data of the vehicle separator; The initial acquisition data and the initial operation data are preprocessed to obtain the target acquisition data and the target operation data; The target status frame is determined based on the target collected data and the target running data, and the target status frame is sent to the operation and maintenance application layer; Receive the target remote control command fed back by the operation and maintenance application layer in response to the target status frame; According to the target remote control command, the weighing sensing layer is controlled to perform fault recovery operations to achieve rapid diagnosis and recovery.

[0006] Secondly, embodiments of this application provide a remote operation and maintenance device for intelligent weighing equipment, applied to the control center layer of a remote operation and maintenance system. The system further includes a weighing sensing layer and an operation and maintenance application layer. The control center layer includes an intelligent weighing instrument; the weighing sensing layer includes *a* dual-redundant sensors, a vehicle separator, and a signal collector, where *a* is an integer greater than 1; the device includes an acquisition module, a processing module, a determination module, a receiving module, and a control module, wherein: The acquisition module is used to acquire the initial acquisition data collected by the signal acquisition device and the initial operating data corresponding to the intelligent weighing instrument; the initial acquisition data includes a initial dual-path force measurement data of the a dual-redundant sensors and the initial signal triggering data of the vehicle separator; The processing module is used to preprocess the initial acquisition data and the initial running data respectively to obtain the target acquisition data and the target running data; The determining module is used to determine a target status frame based on the target collected data and the target running data, and send the target status frame to the operation and maintenance application layer; The receiving module is used to receive the target remote control command fed back by the operation and maintenance application layer in response to the target status frame; The control module is used to control the weighing sensing layer to perform fault recovery operations according to the target remote control command, so as to achieve rapid diagnosis and recovery.

[0007] Thirdly, embodiments of this application provide an electronic device, including a processor, a memory, a communication interface, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor, and the programs include instructions for performing steps in any method of the first aspect of this application.

[0008] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program for electronic data interchange, wherein the computer program causes a computer to perform some or all of the steps described in any method of the first aspect of this application.

[0009] Fifthly, embodiments of this application provide a computer program product, wherein the computer program product includes a non-transitory computer-readable storage medium storing a computer program operable to cause a computer to perform some or all of the steps described in any method of the first aspect of this application. The computer program product may be a software installation package.

[0010] By implementing the embodiments of this application, the end-to-end device data of each device in the weighing sensing layer is encapsulated into a target status frame and remotely sent to the operation and maintenance application layer, thereby receiving feedback remote control commands and performing fault recovery operations, which improves the efficiency of remote diagnosis and rapid recovery of weighing equipment. Attached Figure Description

[0011] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0012] Figure 1 This is a schematic diagram of the composition of a remote operation and maintenance system provided in an embodiment of this application; Figure 2 This is a system architecture diagram of a remote operation and maintenance system provided in an embodiment of this application; Figure 3 This is a schematic diagram of the structure of a dual-redundant sensor provided in an embodiment of this application; Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application; Figure 5 This is a flowchart illustrating a remote operation and maintenance method for an intelligent weighing device provided in an embodiment of this application; Figure 6 This is a schematic diagram of a data acquisition process provided in an embodiment of this application; Figure 7 This is a schematic diagram of a process for determining a target state frame provided in an embodiment of this application; Figure 8 This is a functional module block diagram of a remote operation and maintenance device for an intelligent weighing equipment provided in an embodiment of this application. Detailed Implementation

[0013] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present application.

[0014] The terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or apparatuses.

[0015] It should be understood that the term "and / or" in this document is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this document indicates that the preceding and following related objects are in an "or" relationship. In the embodiments of this application, "multiple" refers to two or more.

[0016] In the embodiments of this application, "at least one item" or its similar expression refers to any combination of these items, including any combination of a single item or a plurality of items. "One or more" means one or more, while "multiple" means two or more. For example, "at least one item" of a, b, or c can represent the following seven cases: a, b, c; a and b; a and c; b and c; a, b, and c. Each of a, b, and c can be an element or a set containing one or more elements.

[0017] In this application, the term "connection" refers to various connection methods, such as direct connection or indirect connection, to achieve communication between devices. This application does not impose any limitations on this.

[0018] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0019] The following is an explanation of the relevant terms used in this application: Intelligent weighing instrument: refers to the core processing unit deployed in the weighing lane, which is responsible for receiving and processing the collected data uploaded by the weighing sensing layer, completing online fault diagnosis, and interacting bidirectionally with the operation and maintenance application layer to realize an integrated intelligent control device for weighing data output, status feedback and command execution.

[0020] Dual redundancy sensors refer to weighing sensors with two completely independent force signal links built in. They share the same sensor body to sense the load and output two independent force data synchronously through two independent force measurement units, analog-to-digital conversion units, signal output units and transmission lines, realizing dual redundancy backup at the component level and signal chain level, eliminating the risk of single point of failure.

[0021] Vehicle separator: refers to the front-end sensing device deployed in the weighing lane, used to detect the entry and exit status of vehicles and the axle / vehicle boundary, generate signal trigger data containing vehicle triggering and separation information, provide vehicle timestamps and data segmentation identifiers for the weighing system, and realize accurate division of vehicle data and boundary determination.

[0022] Signal acquisition device: refers to a data transfer and acquisition device that receives force measurement data from dual redundant sensors and trigger signals from the vehicle separator, integrates the data, and then uploads it to the intelligent weighing instrument.

[0023] Guard booth monitoring terminal: refers to a local monitoring and operation terminal deployed at the weighing site that receives equipment status information and can issue low-level permission commands for on-site personnel to handle simple faults.

[0024] Visualized management and control platform: refers to a visual management terminal that summarizes and intuitively displays equipment operation data, links with the weighing equipment operation and maintenance platform to issue intermediate-level permission commands, and realizes the overall planning and scheduling of equipment status (such as the equipment monitoring and alarm system in the monitoring hall).

[0025] Weighing equipment operation and maintenance platform: refers to the back-end management platform that coordinates and manages all weighing equipment in the site, stores operating data, traces faults, issues high-level permission commands, and realizes equipment parameter configuration and operation and maintenance management.

[0026] Currently, highway entrance and exit weighing systems generally employ a traditional architecture using analog sensors and local instruments. These devices lack IP-based networking capabilities and remote status monitoring, resulting in the following significant drawbacks: when equipment malfunctions, the system cannot detect and accurately locate the fault in real time, relying on manual discovery by toll collectors, thus delaying timely intervention; toll collectors lack professional maintenance skills and can only wait for manufacturer technicians to arrive, leading to prolonged interruptions in weighing operations, causing lane congestion, and severely reducing traffic efficiency. Furthermore, the system lacks lightweight remote handling methods, resulting in high maintenance costs, slow response times, and poor reliability, making it difficult to meet the rigid requirements of 24 / 7 uninterrupted rapid weighing and efficient traffic flow at highway entrances and exits. Therefore, improving the efficiency of remote diagnostics and rapid recovery of weighing equipment is an urgent issue to be addressed.

[0027] To address the aforementioned issues, this application provides a remote operation and maintenance method and apparatus for intelligent weighing equipment, applied to the control center layer of a remote operation and maintenance system. The system further includes a weighing sensing layer and an operation and maintenance application layer. The control center layer includes an intelligent weighing instrument; the weighing sensing layer includes *a* dual-redundant sensors, a vehicle separator, and a signal collector, where *a* is an integer greater than 1. First, initial acquisition data collected by the signal collector and initial operating data corresponding to the intelligent weighing instrument are acquired. The initial acquisition data includes *a* initial dual-path force measurement data from the *a* dual-redundant sensors and initial signal trigger data from the vehicle separator. The initial acquisition data and initial operating data are preprocessed to obtain target acquisition data and target operating data. Then, a target state frame is determined based on the target acquisition data and target operating data, and the target state frame is sent to the operation and maintenance application layer. A target remote control command is received from the operation and maintenance application layer in response to the target state frame. Finally, based on the target remote control command, the weighing sensing layer is controlled to perform a fault recovery operation to achieve rapid diagnosis and recovery.

[0028] It is evident that by encapsulating the end-to-end device data of each device in the weighing sensing layer into a target status frame and remotely sending it to the operation and maintenance application layer, the remote control commands can be received and fault recovery operations can be performed, thereby improving the efficiency of remote diagnosis and rapid recovery of weighing equipment.

[0029] For easier understanding, please refer to Figure 1 , Figure 1 This is a schematic diagram of the composition of a remote operation and maintenance system provided in an embodiment of this application. The remote operation and maintenance system includes a weighing sensing layer, a control center layer, and an operation and maintenance application layer.

[0030] The weighing sensing layer includes a dual-redundant sensor, a vehicle separator, and a signal acquisition unit. Each dual-redundant sensor has two sets of independent force measurement units and analog-to-digital conversion units built in, which are used to output dual-channel force measurement data. The vehicle separator is used to output signal trigger data for vehicle triggering and separation. These two types of data are uniformly collected by the signal acquisition unit and then uploaded to the control center layer.

[0031] The control center layer includes intelligent weighing instruments. These instruments receive data uploaded by signal collectors and acquire their own operational data. They preprocess the end-to-end data, perform dual-channel difference calculations and fault diagnosis, and generate a target status frame. The target status frame is then sent to the operations and maintenance application layer, and the control center receives remote control commands from the application layer. Based on these commands, it controls the weighing sensing layer to perform fault recovery operations.

[0032] The operation and maintenance application layer includes a guard booth monitoring terminal, a weighing equipment operation and maintenance platform, and a visual management and control platform. The guard booth monitoring terminal receives status frames, triggers on-site alarms, and provides feedback on low-level fault recovery commands. The visual management and control platform interacts bidirectionally with the weighing equipment operation and maintenance platform to achieve comprehensive equipment status assessment and batch control with intermediate-level permissions. The weighing equipment operation and maintenance platform is used for full-cycle data archiving, fault tracing, high-level permission parameter configuration, and program upgrade command issuance.

[0033] It is evident that the three-level collaborative architecture enables dual-path redundant acquisition of weighing data, online fault diagnosis, and a hierarchical remote self-healing closed loop, significantly improving the reliability, operational efficiency, and business continuity of weighing equipment.

[0034] For easier understanding, please refer to Figure 2 , Figure 2 This is a system architecture diagram of a remote operation and maintenance system provided in this application embodiment. Each of the *a* dual-redundant sensors has two sets of independent force measurement units (A and B) and an analog-to-digital conversion unit built-in. Each sensor is connected to the analog input channel of the signal acquisition unit via an independent signal cable. The vehicle separator is an infrared through-beam vehicle detection device, connected to the digital input channel of the signal acquisition unit via a switch signal line, used to transmit vehicle trigger signals and vehicle separation signals. The signal acquisition unit, as the data aggregation node of the weighing sensing layer, integrates a multi-channel synchronous sampling module, which can simultaneously sample all connected sensor channels and the vehicle separator channel.

[0035] The intelligent weighing instrument and the signal acquisition unit establish a bidirectional communication connection via an internal data bus or serial communication interface. In the data uplink direction, the signal acquisition unit packages the synchronously acquired and pre-processed data and uploads it to the intelligent weighing instrument through this communication connection. In the command downlink direction, the intelligent weighing instrument sends control commands such as channel switching commands and data re-acquisition commands to the signal acquisition unit through this communication connection, which then drives the corresponding dual-redundant sensors to perform the appropriate operations. Furthermore, the intelligent weighing instrument reads the operating data from its built-in self-test module through the internal bus and receives the force status signal of the weighing platform.

[0036] The intelligent weighing instrument and the toll booth monitoring terminal establish a bidirectional TCP / IP communication connection via the toll station's local area network. In the data uplink direction, the intelligent weighing instrument directly pushes the generated target status frame to the toll booth monitoring terminal, allowing toll collectors to view the equipment status in real time. In the command downlink direction, the toll booth monitoring terminal directly sends the first remote control command generated after the toll collector confirms the operation to the intelligent weighing instrument through this direct LAN connection.

[0037] The intelligent weighing instrument and the weighing equipment operation and maintenance platform establish a bidirectional TCP / IP communication connection via a dedicated highway network. In the data uplink direction, the intelligent weighing instrument directly pushes the target status frame to the weighing equipment operation and maintenance platform for persistent data storage and in-depth fault diagnosis. In the command downlink direction, the weighing equipment operation and maintenance platform directly sends the third-party remote control command generated after the operation is confirmed by the maintenance engineer to the intelligent weighing instrument through this dedicated network direct connection channel.

[0038] The visualization control platform and the weighing equipment operation and maintenance platform establish a two-way communication connection via a dedicated highway network. The visualization control platform does not communicate directly with the intelligent weighing instruments. In the data uplink direction, the visualization control platform receives target status frames forwarded by the weighing equipment operation and maintenance platform for centralized monitoring of all equipment. In the command downlink direction, the visualization control platform sends the second remote control command generated after the administrator confirms the batch processing operation to the weighing equipment operation and maintenance platform, which then forwards it to the intelligent weighing instruments.

[0039] It is evident that by implementing end-to-end data acquisition, dual-redundancy self-diagnosis, and three-level remote handling, the system enables second-level fault location and one-click rapid recovery for non-professionals, significantly shortening downtime, reducing reliance on on-site maintenance, and ensuring the continuity of stable weighing operations.

[0040] For easier understanding, please refer to Figure 3 , Figure 3 This is a schematic diagram of a dual-redundant sensor provided in an embodiment of this application. The dual-redundant sensor has two completely independent force measurement channels, namely channel A and channel B. The two channels share the same sensor body but are completely isolated electrically and functionally. Each channel includes the following independent units: a force measurement unit, an analog-to-digital conversion unit, a signal output unit, and a transmission line.

[0041] The force-measuring unit is the core sensing element of the dual-redundant sensor, typically consisting of a resistance strain gauge bonded to the surface of an elastic body to form a Wheatstone bridge. When a vehicle load is applied to the sensor, the elastic body deforms, and the resistance of the strain gauge changes accordingly. The bridge outputs a weak voltage signal proportional to the load. Force-measuring units A and B are either installed at different locations on the same elastic body or use independent elastic body structures, ensuring that the two sets of force-measuring units are physically independent, and the failure of one set does not affect the normal operation of the other.

[0042] Each force measurement unit corresponds to an independent analog-to-digital converter (ADC) chip, which is responsible for converting the analog voltage signal output by the force measurement unit into a high-precision digital signal. ADC units A and B use independent clock sources and reference voltage sources to avoid common-cause failures caused by sharing a clock or reference voltage.

[0043] Each analog-to-digital conversion unit is followed by an independent signal output unit (such as signal output unit A or signal output unit B), which is responsible for packaging the converted digital force measurement value according to a preset communication protocol, adding channel identifiers and check codes, and outputting it outward through an independent signal cable. The digital signals of channels A and B are completely independent at the physical circuit and communication protocol levels, and can be received by the two independent sampling channels of the signal acquisition unit respectively.

[0044] In the dual-redundant sensor, the transmission lines A and B corresponding to the A and B channels are designed to be laid independently. Two independent signal cables are led from inside the sensor body to the external interface and connected to different sampling channels of the signal acquisition unit. This independent design of the transmission lines eliminates the risk of simultaneous failure of both channels due to cable short circuits, open circuits, or other line faults.

[0045] As can be seen, by building two completely independent force measuring units and signal transmission channels, the potential for single-point failures is eliminated at the component level, supporting real-time comparison of dual-channel data and precise location of faulty channels, and enabling seamless switching from faulty channels to redundant channels to ensure uninterrupted weighing operations.

[0046] The following is combined with Figure 4 The electronic devices in the embodiments of this application will be described. Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application, such as... Figure 4 As shown, the electronic device includes one or more processors, a memory, a communication interface, and one or more programs. The processor is connected to the memory and the communication interface via an internal communication bus.

[0047] The processor can be used for: Acquire the initial acquisition data collected by the signal acquisition device and the initial operating data corresponding to the intelligent weighing instrument; the initial acquisition data includes a initial dual-path force measurement data from a dual-redundant sensor and the initial signal trigger data of the vehicle separator; The initial acquired data and initial operational data are preprocessed to obtain the target acquired data and target operational data. The target status frame is determined based on the target collected data and the target operation data, and then the target status frame is sent to the operation and maintenance application layer. Receive remote control commands from the operation and maintenance application layer in response to the target status frame; Based on the target remote control command, the weighing sensing layer is controlled to perform fault recovery operations to achieve rapid diagnosis and recovery.

[0048] The one or more programs are stored in the aforementioned memory and configured to be executed by the aforementioned processor, and the one or more programs include instructions for performing any step in the above method embodiments.

[0049] The processor can be a central processing unit (CPU), a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It can implement or execute the various exemplary logic blocks, cells, and circuits described in conjunction with the disclosure of this application. The processor can also be a combination that implements computational functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc. The communication unit can be a communication interface, transceiver, transceiver circuit, etc., and the storage unit can be a memory.

[0050] The memory can be volatile or non-volatile, or a combination of both. Non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. Volatile memory can be random access memory (RAM), used as an external cache. By way of example, but not limitation, many forms of random access memory (RAM) are available, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate synchronous DRAM (DDR SDRAM), enhanced synchronous DRAM (ESDRAM), synchronous linked DRAM (SLDRAM), and direct rambus RAM (DR RAM).

[0051] It is understood that the electronic device may include more or fewer structural elements than those shown in the block diagram above, such as a power module, physical buttons, a Wi-Fi module, a speaker, a Bluetooth module, sensors, a display module, etc., without limitation. It is understood that the electronic device may be as follows: Figure 2 The aforementioned intelligent weighing instrument.

[0052] After understanding the software and hardware architecture of this application, the following will be combined with... Figure 5 This application describes a remote operation and maintenance method for an intelligent weighing device according to an embodiment. Figure 5 This is a flowchart illustrating a remote operation and maintenance method for intelligent weighing equipment provided in an embodiment of this application. It is applied to the control center layer of a remote operation and maintenance system. The system also includes a weighing sensing layer and an operation and maintenance application layer. The control center layer includes an intelligent weighing instrument; the weighing sensing layer includes *a* dual-redundant sensors, a vehicle separator, and a signal collector, where *a* is an integer greater than 1. The method specifically includes the following steps: Step S501: Obtain the initial acquisition data collected by the signal acquisition device and the initial operating data corresponding to the intelligent weighing instrument.

[0053] The initial acquisition data includes a initial dual-path force measurement data from the a dual-redundant sensors and the initial signal trigger data from the vehicle separator.

[0054] For easier understanding, please refer to Figure 6 , Figure 6 This is a schematic diagram of a data acquisition process provided in an embodiment of this application. The specific steps for acquiring the initial acquisition data collected by the signal acquisition device and the initial operating data corresponding to the intelligent weighing instrument include: A1. Receive the signal acquisition device and, according to a preset acquisition cycle, synchronously acquire the a initial dual-path force measurement data and the initial signal trigger data from the a dual-redundant sensors and the vehicle separator, respectively. A2. According to the acquisition cycle, read the operating data corresponding to the intelligent weighing instrument to obtain the initial operating data.

[0055] In a specific embodiment, the signal acquisition unit (such as a digital signal acquisition unit) integrates a multi-channel synchronous sampling module, which is connected to a dual-redundant sensors and a vehicle separator through independent signal input channels. When the preset acquisition period arrives, the signal acquisition unit simultaneously sends a sampling trigger signal to all connected dual-redundant sensors and the vehicle separator, ensuring that the a initial dual-channel force measurement data and the initial signal trigger data are strictly aligned in time. Each dual-redundant sensor's two independent force measurement units complete analog-to-digital conversion under the same trigger signal, outputting two independent digital force measurement values. The signal acquisition unit packages all data collected within the sampling period and uploads it to the intelligent weighing instrument via an internal bus or serial communication interface.

[0056] The intelligent weighing instrument incorporates a built-in self-test module, which continuously monitors the instrument's operating status parameters, including at least: internal temperature, power supply voltage, communication interface bit error rate, and processor load rate. When the data acquisition cycle arrives, the self-test module outputs a snapshot of the current real-time operating data as initial operating data. This initial operating data, together with the initial acquisition data, constitutes the complete raw data for the current acquisition cycle, providing a comprehensive data foundation for subsequent preprocessing and diagnostics.

[0057] As can be seen, by synchronously acquiring data from the dual redundant sensors and the vehicle separator through the signal acquisition device, and synchronously reading the operating data of the intelligent weighing instrument itself, strict time alignment of the data of the entire link equipment within the same acquisition cycle is ensured, providing a complete and synchronous data foundation for the accurate comparison of subsequent dual-channel force measurement data and fault diagnosis.

[0058] Step S502: Preprocess the initial acquisition data and the initial running data respectively to obtain target acquisition data and target running data.

[0059] The specific steps of preprocessing the initial collected data and the initial running data to obtain the target collected data and the target running data include: B1. Perform time-domain alignment processing on the a initial dual-path force measurement data respectively to obtain a first intermediate data; B2. Perform digital filtering on the a first intermediate data respectively to obtain a second intermediate data; B3. Perform outlier removal processing on the a second intermediate data respectively to obtain a third intermediate data; B4. Normalize the a third intermediate data respectively to obtain the a target dual-path force measurement data; B5. Perform jitter elimination processing on the initial signal trigger data to obtain the target signal trigger data; B6. Perform abnormal jump value removal processing on the initial running data to obtain the target running data.

[0060] In a specific embodiment, due to the slight clock deviation between the analog-to-digital conversion units of the two independent force measurement units within each dual-redundant sensor, the sampling values ​​of channel A and channel B at the same moment may not correspond perfectly in timestamps. Therefore, time-domain alignment processing uses an interpolation algorithm to resample the other data using the timestamp of one data channel as a reference, so that the two data channels form a one-to-one comparable data pair on the same time scale. The aligned data are the *a* first intermediate data. Then, an adaptive digital filtering algorithm adapted to subsequent fault criteria is used to process the *a* first intermediate data to obtain *a* second intermediate data. The cutoff frequency of this filtering algorithm is dynamically adjusted according to the current weighing state: when the vehicle separator indicates no vehicle is passing, a lower cutoff frequency is used to suppress high-frequency noise; when a vehicle is passing and the dynamic weighing stage is in progress, the cutoff frequency is appropriately increased to preserve the transient characteristics of wheel load changes.

[0061] Next, outlier removal is performed on each of the *a* second intermediate data points to obtain *a* third intermediate data points. A sliding window-based statistical discrimination method can be used. A window is formed by taking *m* sampling points before and after the current sampling point as the center, and calculating the mean and standard deviation of the data within the window. If the current sampling point deviates from the mean by more than *k* times (e.g., *k*=3) of the standard deviation, it is identified as an outlier and removed. The window mean is then used for interpolation to fill the gap. The *a* third intermediate data points with different dimensions or ranges are then uniformly mapped to a preset standard value range to eliminate data inconsistencies caused by differences in sensor models or ranges. The processed data constitutes *a* target dual-channel force measurement data, used for subsequent dual-channel difference calculations and fault diagnosis.

[0062] The initial signal trigger data is the switching signal output by the vehicle separator. Due to factors such as vehicle vibration and electromagnetic interference, the edges of the switching signal may exhibit high-frequency jitter, leading to false triggering. By setting a de-jittering time window, the change in state is only confirmed as valid after the signal level remains stable for more than a preset de-jittering time threshold, thus obtaining the target signal trigger data to assist in the judgment of the weighing status.

[0063] The initial operating data consists of status parameters output by the intelligent weighing instrument's internal self-test module, including internal temperature, power supply voltage, and communication error rate. During normal operation, these status parameters may exhibit occasional deviations from the normal range due to momentary power supply fluctuations or short-term sensor noise. By monitoring the data variation amplitude between two adjacent acquisition cycles, if the variation amplitude exceeds a preset reasonable threshold, the current value is determined to be an abnormal fluctuation value, and the normal value from the previous acquisition cycle is used to replace it, thus obtaining the target operating data.

[0064] It is evident that by employing differentiated preprocessing strategies tailored to the characteristics of the dual-channel force measurement data, signal trigger data, and instrument operation data, the interference of time-domain deviation, high-frequency noise, abnormal mutations, and dimensional inconsistencies on the diagnostic results is eliminated, providing high-quality, comparable, and standardized data for subsequent dual-channel difference calculation and fault diagnosis.

[0065] Step S503: Determine the target status frame based on the target collected data and the target running data, and send the target status frame to the operation and maintenance application layer.

[0066] For easier understanding, please refer to Figure 7 , Figure 7 This is a flowchart illustrating a method for determining a target state frame according to an embodiment of this application. The target acquisition data includes *a* target dual-channel force measurement data and one target signal trigger data. The *a* target dual-channel force measurement data includes *a* first force measurement data and *a* second force measurement data. The specific steps for determining the target state frame based on the target acquisition data and the target operation data include: C1. Calculate the difference between the a first force measurement data and the a second force measurement data and take the absolute value to obtain a dual-path difference values; C2. If b out of the a dual-path differences are greater than a preset first fault threshold, then a fault identification result is generated based on the b dual-path differences; b is a positive integer less than or equal to a. C3. Encapsulate the target acquisition data, target operation data, the a dual-channel differences, and the fault identification results into the target status frame.

[0067] In a specific embodiment, *a* first force measurement data points are the pre-processed force values ​​of each of the *a* dual-redundant sensors' A channels, and *a* second force measurement data points are the pre-processed force values ​​of their corresponding B channels. The difference calculation can be performed according to a one-to-one correspondence with the sensor numbers; that is, the i-th first force measurement data point is subtracted from the i-th second force measurement data point, and the absolute value is taken to obtain the i-th dual-channel difference value, where i is an integer from 1 to a. Taking the absolute value aims to eliminate the influence of the subtraction order on the sign of the difference value, ensuring that the difference value uniformly represents the deviation magnitude. After the calculation is completed, *a* dual-channel difference values ​​corresponding one-to-one with the *a* dual-redundant sensors are obtained.

[0068] The first fault threshold is a pre-configured critical value for determining whether the dual-channel deviation of the sensor constitutes a fault. When a dual-channel difference value is greater than the first fault threshold, it indicates that the output data of the two sets of channels inside the dual redundant sensor corresponding to that dual-channel difference value has deviated beyond the allowable range, and there is a possibility of hardware failure. Then, a corresponding fault identification result is generated based on b dual-channel differences.

[0069] Then, all data within this acquisition cycle is uniformly encapsulated to generate a target status frame. The encapsulation structure of this target status frame includes a frame header and a data body. The frame header carries at least the current timestamp, the unique device identifier of the intelligent weighing instrument, and the lane number, used to identify the source, time, and location of the data. The data body contains the following five types of data: target acquisition data (including *a* target dual-channel force measurement data and target signal trigger data), target operation data, *a* dual-channel differences, and fault identification results. The purpose of encapsulating raw data, derived data, and diagnostic conclusions in the same status frame is to enable the receiving end (i.e., the operation and maintenance application layer) to simultaneously obtain fault symptoms and diagnostic conclusions, allowing for direct analysis and decision-making based on complete information without additional time synchronization and data association operations.

[0070] After the target status frame is encapsulated, the intelligent weighing instrument sends the target status frame to the operation and maintenance application layer via a TCP / IP network. Depending on the terminal configuration of the operation and maintenance application layer, the transmission paths include: direct transmission to the guard booth monitoring terminal, direct transmission to the weighing equipment operation and maintenance platform, and forwarding by the visual management platform after receiving the target status frame.

[0071] As can be seen, by performing difference calculation and threshold determination on the force measurement data of the same sensor's dual channels, the initial fault diagnosis can be completed locally on the instrument. The original data, derived data and diagnostic results are uniformly encapsulated into a single status frame, so that the operation and maintenance application layer can directly obtain complete information without repeated calculations, reducing data association overhead and improving the efficiency of fault diagnosis and response.

[0072] The specific steps for generating fault identification results based on the b dual-path differences include: D1. Determine the b dual-redundant sensors corresponding to the b dual-path difference values ​​among the a dual-redundant sensors; D2. Obtain the b fault sensor identifiers corresponding to the b dual-redundant sensors; D3. Obtain the channel state of each of the b dual-redundant sensors to obtain b channel states; D4. Determine the b fault channel identifiers based on the status of the b channels; D5. Obtain the ratio of each of the b dual-path differences to the first fault threshold to obtain b over-limit ratios; D6. Determine b fault levels based on the b over-limit ratios; D7. Determine the fault identification result based on the b fault sensor identifiers, the b fault channel identifiers, and the b fault levels.

[0073] In a specific embodiment, each of the *a* dual-path differential values ​​has a defined location index in the array, and this location index corresponds one-to-one with the numbers of the *a* dual-redundant sensors. The location indices of the *b* out-of-limit differential values ​​in the array can be obtained, and then mapped to the corresponding *b* dual-redundant sensors among the *a* dual-redundant sensors based on these location indices. Each dual-redundant sensor is assigned a unique sensor identification code during system initialization. This sensor identification code contains the sensor number, installation location, and lane information. The sensor identification codes corresponding to the *b* target sensors can be read from a preset system configuration table to obtain the *b* fault sensor identifiers. These fault sensor identifiers are used to accurately indicate the location of the abnormal sensor in the subsequent fault alarm interface, facilitating intuitive location by toll collectors or maintenance personnel.

[0074] Each dual-redundant sensor integrates a channel self-diagnostic circuit, capable of independently monitoring the operating status of channels A and B, including whether the bridge voltage is normal, whether the excitation voltage is within the allowable range, whether the internal temperature exceeds limits, and whether the analog-to-digital conversion unit is functioning correctly. The intelligent weighing instrument can send a channel status query command to each target sensor via a signal acquisition unit, reading the self-diagnostic status register values ​​of channels A and B respectively. The query result includes four possibilities: both channels A and B are normal; both channels A and B are abnormal; both channels A and B are normal; and both channels A and B are abnormal. For each target sensor, the combination of its A and B channel self-diagnostic statuses represents the corresponding channel status for that sensor.

[0075] If the channel status is "Channel A is abnormal and Channel B is normal", then Channel A is determined to be the faulty channel, and the corresponding faulty channel identifier is Channel A identifier; if the channel status is "Channel A is normal and Channel B is abnormal", then Channel B is determined to be the faulty channel, and the corresponding faulty channel identifier is Channel B identifier; if the channel status is "Channel A is abnormal and Channel B is abnormal", then both Channel A and Channel B are determined to be faulty channels, and the corresponding faulty channel identifier is dual-channel identifier; if the channel status is "Channel A is normal and Channel B is normal", it indicates that the self-diagnosis did not detect a clear hardware abnormality, but the difference between the two channels has exceeded the limit. In this case, external information is needed for auxiliary judgment. Specifically, this includes: determining whether there is a vehicle being weighed on the weighing platform based on the target signal trigger data. If there are no vehicles on the scale, the current empty scale output values ​​of channels A and B are read, and the channel that deviates further from zero is identified as the faulty channel. If there are vehicles on the scale, the force values ​​of channels A and B are compared with the force values ​​of other normal sensors on the opposite side of the same weighing platform. The channel with poor consistency and deviates further from the normal value is identified as the faulty channel, and its corresponding faulty channel identifier is obtained.

[0076] Then, the ratio of each of the b dual-path differences to the first fault threshold is calculated and expressed as a percentage to obtain b over-limit ratios (i.e., over-limit ratios). The calculation formula is: Over-limit ratio = Dual-path difference ÷ First fault threshold × 100%. This over-limit ratio reflects the degree to which the dual-path deviation exceeds the fault threshold; the larger the ratio, the more severe the deviation.

[0077] The system pre-sets fault level classification rules, mapping out-of-limit ratios to corresponding fault levels. For example, an out-of-limit ratio between 100% and 150% is classified as a minor fault; between 150% and 200% as a moderate fault; and above 200% as a severe fault. Different handling strategies correspond to different fault levels. For instance, minor faults may not require channel switching, only alarm recording; moderate faults are recommended to switch to redundant channels after the current weighing is completed; and severe faults require immediate switching of redundant channels and reporting to the maintenance platform. Finally, the b fault sensor identifiers, b fault channel identifiers, and b fault levels are integrated to obtain the fault identification result.

[0078] As can be seen, by locating faulty sensors through differential location indexing, accurately determining faulty channels by combining channel self-diagnosis status, and classifying fault levels based on the over-limit ratio, a structured fault identification result containing faulty sensor identifiers, faulty channel identifiers, and fault levels is generated. This achieves accurate fault location, directional identification, and graded assessment, providing precise decision-making basis for the operation and maintenance application layer to formulate differentiated handling strategies.

[0079] Step S504: Receive the target remote control command fed back by the operation and maintenance application layer in response to the target status frame.

[0080] Specifically, the operation and maintenance application layer includes the guard booth monitoring terminal, the weighing equipment operation and maintenance platform, and the visual management and control platform. Different terminals analyze and make decisions based on the diagnostic information in the target status frame, generating corresponding remote control commands. The intelligent weighing instrument, acting as the control execution hub between the weighing perception layer and the operation and maintenance application layer, is responsible for receiving control commands from different terminals.

[0081] Step S505: According to the target remote control command, control the weighing sensing layer to perform fault recovery operation to achieve rapid diagnosis and recovery.

[0082] The specific steps of controlling the weighing sensing layer to perform the fault recovery operation according to the target remote control command include: E1. Perform permission verification on the target remote control command and obtain the verification result; the verification result includes any one of the following: low-level permission, medium-level permission, and high-level permission; E2. Based on the verification result, parse the target remote control command to obtain the target operation type and target device identifier corresponding to the fault recovery operation; E3. Based on the target operation type, control the target device in the weighing sensing layer corresponding to the target device identifier to perform the fault recovery operation.

[0083] In a specific embodiment, firstly, the instruction source identifier field is extracted from the frame header of the target remote control instruction. This instruction source identifier field is written by each terminal when the instruction is generated, and is used to identify whether the instruction was generated by the guard booth monitoring terminal, the visualization management and control platform, or the weighing equipment maintenance platform. The intelligent weighing instrument is pre-configured with a permission mapping table, which maps the instruction source identifier to the permission level: the guard booth monitoring terminal corresponds to low-level permission, the visualization management and control platform corresponds to medium-level permission, and the weighing equipment maintenance platform corresponds to high-level permission. By looking up the table, the instruction source identifier is converted into the corresponding permission level to obtain the verification result. If the instruction source identifier cannot be identified or is not in the permission mapping table, the verification is deemed to have failed, the instruction is discarded, and an exception log is recorded.

[0084] Then, based on the verification results, the target remote control command is parsed to obtain the target operation type and target device identifier corresponding to the fault recovery operation. The parsing process includes extracting the target operation type field and target device identifier field carried in the data body of the target remote control command. The target operation type field indicates the specific type of this fault recovery operation, including channel switching operation, instrument reset operation, and data re-acquisition operation. The target device identifier field indicates the specific device targeted by this operation, including the target sensor number, target channel number, or target data acquisition device number. Simultaneously, the parsed target operation type is matched and verified against the current permission level: low-level permissions allow operations including channel switching and instrument reset; medium-level permissions, in addition to low-level permissions, also allow batch operations on multiple devices; high-level permissions allow all operation types, including remote parameter adjustment and firmware upgrade. If the target operation type exceeds the scope of operations allowed by the current permission level, it is determined to be an unauthorized operation, the command is discarded, an unauthorized alarm record is generated, and uploaded to the weighing equipment maintenance platform. If the operation type is within the allowed range, the target operation type and target device identifier are retained.

[0085] Next, based on the target operation type, the target device corresponding to the target device identifier in the weighing sensing layer is directly driven to perform the corresponding fault recovery operation. The specific execution process can be divided into the following three cases based on the target operation type: Scenario 1: Channel Switching Operation. When the target operation type is channel switching, the target device identifier points to the target sensor where the dual-channel deviation exceeds the limit. The intelligent weighing instrument sends a channel switching command to the signal acquisition unit via the internal bus. The channel switching command carries the target sensor number and the identifier of the faulty channel to be shut down. After receiving the command, the signal acquisition unit modifies the data acquisition configuration register of the sensor, setting the data acquisition enable bit of the faulty channel to the disabled state and keeping the data acquisition enable bit of the redundant channel in the enabled state, so that in subsequent acquisition cycles, only force measurement data is read from the normal channel. After the switch is completed, the signal acquisition unit returns a successful switch confirmation message to the intelligent weighing instrument. The intelligent weighing instrument synchronously updates the internal sensor channel status table, marks the faulty channel as bypassed, and triggers a data re-acquisition to verify whether the data after the switch has returned to normal.

[0086] Scenario 2: Instrument Reset Operation. When the target operation type is instrument reset, the target device identifier points to the intelligent weighing instrument itself. The intelligent weighing instrument executes a soft reset process: First, it saves the current operating status and fault records to non-volatile memory. Then, it writes a reset trigger command to the internal circuit, which generates a reset pulse signal, causing the instrument's main processor to reload the program and initialize each functional module. After the reset is complete, the intelligent weighing instrument automatically restores its communication connection with the signal acquisition unit, the guard booth monitoring terminal, and the weighing equipment maintenance platform, and resumes data acquisition and status frame transmission. During the reset, the signal acquisition unit continues to independently acquire sensor data according to the preset acquisition cycle and caches it in the local buffer. Data is then uploaded uniformly after the instrument reset is complete to avoid data loss.

[0087] Scenario 3: Data Resampling Operation. When the target operation type is data resampling, the target device identifier points to the signal acquisition unit. The intelligent weighing instrument sends a resampling trigger command to the signal acquisition unit, carrying a resampling count parameter. Upon receiving the command, the signal acquisition unit immediately stops the current acquisition cycle, without waiting for the next preset acquisition cycle, and directly sends a sampling trigger signal simultaneously to all connected sensors and the vehicle separator to re-acquire a round of end-to-end data. The re-acquired data is then immediately uploaded to the intelligent weighing instrument. After receiving the re-acquired data, the intelligent weighing instrument re-executes the preprocessing and diagnostic judgment operations to generate a new target status frame. If the difference between the two channels recovers to within the first fault threshold after resampling, the aforementioned exceedance is determined to be caused by transient interference, requiring no further action. If the difference between the two channels still exceeds the limit after resampling, the fault is confirmed to persist, and further control commands or autonomous redundancy switching by the instrument are required.

[0088] After the fault recovery operation is completed, the intelligent weighing instrument encapsulates the operation type, target device, execution result, and execution time into an execution confirmation message and sends it back to the terminal that initiated the command, so that the terminal can update the device status display. At the same time, the execution confirmation message is sent to the weighing equipment operation and maintenance platform, which records the entire lifecycle information of this fault, including the fault occurrence time, fault type, fault channel, handling operation, execution result, recovery time, and operator, generating a full-process operation and maintenance traceability record.

[0089] It is evident that by performing hierarchical permission verification and parsing on remote control commands, it ensures that only legitimate terminals with the corresponding permissions can perform permitted operations on designated devices, thereby guaranteeing system control security while achieving accurate and rapid fault recovery.

[0090] The operation and maintenance application layer includes a guard booth monitoring terminal, a weighing equipment operation and maintenance platform, and a visual management and control platform. The target remote control command includes any one of the following: a first remote control command, a second remote control command, and a third remote control command. The method further includes the following steps: F1. If the target remote control instruction is generated by the guard post monitoring terminal, then the target remote control instruction is determined to be the first remote control instruction, and the low-level permission is assigned to the first remote control instruction; F2. If the target remote control command is generated by the visualization management platform, then the target remote control command is determined to be the second remote control command, and the intermediate-level permission is assigned to the second remote control command; F3. If the target remote control command is generated by the weighing equipment operation and maintenance platform, then the target remote control command is determined to be the third remote control command, and the advanced permissions are assigned to the third remote control command.

[0091] In a specific embodiment, the generating entity of the target remote control command is determined. When the target remote control command originates from the guard post monitoring terminal (i.e., the command source identifier field indicates that it is the guard post monitoring terminal), the command is classified as the first remote control command, and low-level permissions are configured for it. These low-level permissions are suitable for simple on-site fault handling scenarios. If the target remote control command is detected to be issued by the visual management and control platform (i.e., the command source identifier field indicates that it is the visual management and control platform), the command is identified as the second remote control command, and medium-level permissions are assigned accordingly to meet the needs of regional equipment overall management and control. When the target remote control command originates from the weighing equipment operation and maintenance platform (i.e., the command source identifier field indicates that it is the weighing equipment operation and maintenance platform), it is classified as the third remote control command and given high-level permissions to support in-depth operation and maintenance operations such as equipment parameter configuration and program upgrades.

[0092] It is evident that by generating hierarchical matching permissions based on instructions, operation isolation and permission control in different scenarios are achieved, which not only ensures the efficiency of rapid on-site handling, but also avoids the risk of unauthorized operation and improves the security and controllability of remote operation and maintenance.

[0093] In one possible embodiment, the toll booth monitoring terminal is deployed on an industrial control computer or touch screen within the toll booth for use by frontline toll collectors. When the toll booth monitoring terminal receives a target status frame pushed by the intelligent weighing instrument, it graphically displays the real-time status of each sensor on the interface. If the fault identification result in the target status frame indicates an abnormal sensor channel, the interface highlights the fault location and displays a recommended operation prompt button. After reviewing the fault information, the toll collector clicks the confirmation button to trigger the instruction generation process. Based on the current fault type and the recommended operation on the interface, the toll booth monitoring terminal automatically matches the corresponding operation code, combines the current lane number, target sensor number, and target channel identifier, and generates a first remote control instruction according to a preset instruction message format. The header of the first remote control instruction includes an instruction source identifier field, the value of which is set to the toll booth terminal identifier code to identify that the instruction was generated by the toll booth monitoring terminal. The first remote control instruction is sent to the intelligent weighing instrument via a direct local area network connection.

[0094] In one possible embodiment, the visual management and control platform is deployed on a multi-screen display system in the monitoring hall for use by road section or regional equipment administrators. The visual management and control platform does not communicate directly with the intelligent weighing instruments; instead, it obtains target status frames by forwarding them through the weighing equipment maintenance platform. Upon receiving the target status frame forwarded by the weighing equipment maintenance platform, the visual management and control platform highlights the corresponding faulty lane in red and flashes it in the overall equipment list interface, triggering a voice alarm. After viewing the overall equipment status, the administrator can select one or more faulty lanes and initiate batch processing operations via the batch processing button on the interface, such as simultaneously resetting instruments or performing batch diagnostics on multiple lanes. After the administrator confirms the operation, the visual management and control platform generates a second remote control command. The header of the second remote control command includes a command source identifier field, the value of which is set to the visual management and control platform identifier. After the second remote control command is generated, it is first sent to the weighing equipment maintenance platform, which then forwards it to the intelligent weighing instruments. During forwarding, the weighing equipment maintenance platform appends a forwarding flag field to the header to indicate that the command is a forwarding command.

[0095] In one possible embodiment, the weighing equipment maintenance platform is deployed on the system's server cluster for use by professional maintenance engineers. The platform directly receives target status frames pushed by the intelligent weighing instrument and persistently stores the data in a database. Maintenance engineers can use the platform's in-depth diagnostic interface to view historical data curves, over-limit trends, and channel self-diagnostic details of faulty sensors for in-depth fault analysis. Based on the analysis results, engineers can choose to perform remote parameter adjustment operations, such as modifying sensor calibration coefficients, adjusting fault judgment thresholds, and updating diagnostic algorithm parameters, or perform firmware upgrades. After the engineer confirms the operation, the platform generates a third remote control command. The header of the third remote control command includes a command source identifier field, the value of which is set to the platform's identifier. The third remote control command is sent directly to the intelligent weighing instrument via the dedicated highway network. Furthermore, for operations with advanced privileges, the platform performs secondary authentication before generating the command, verifying the maintenance engineer's operating permissions and the validity of their credentials. Only after successful authentication can the command be generated and issued.

[0096] The above primarily describes the solutions of the embodiments of this application from the perspective of the method execution process. It is understood that, in order to achieve the above functions, the electronic device includes corresponding hardware structures and / or software modules for executing each function. Those skilled in the art should readily recognize that, in conjunction with the units and algorithm steps of the various examples described in the embodiments provided herein, this application can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed by hardware or by computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0097] This application embodiment can divide the electronic device into functional units according to the above method example. For example, each function can be divided into a separate functional unit, or two or more functions can be integrated into one processing unit. The integrated unit can be implemented in hardware or as a software functional unit. It should be noted that the unit division in this application embodiment is illustrative and only represents one logical functional division. In actual implementation, there may be other division methods.

[0098] When dividing each function into modules according to its corresponding function. Figure 8This is a functional module block diagram of a remote operation and maintenance device for intelligent weighing equipment provided in this application embodiment. The remote operation and maintenance device 800 for intelligent weighing equipment is applied to the control center layer of a remote operation and maintenance system. The system also includes a weighing sensing layer and an operation and maintenance application layer. The control center layer includes an intelligent weighing instrument; the weighing sensing layer includes *a* dual-redundant sensors, a vehicle separator, and a signal collector, where *a* is an integer greater than 1. The remote operation and maintenance device 800 for intelligent weighing equipment includes an acquisition module 810, a processing module 820, a determination module 830, a receiving module 840, and a control module 850, wherein: The acquisition module 810 is used to acquire the initial acquisition data collected by the signal acquisition device and the initial operating data corresponding to the intelligent weighing instrument; the initial acquisition data includes a initial dual-path force measurement data of the a dual-redundant sensors and the initial signal triggering data of the vehicle separator; The processing module 820 is used to preprocess the initial acquisition data and the initial running data respectively to obtain the target acquisition data and the target running data; The determining module 830 is used to determine a target status frame based on the target collected data and the target running data, and send the target status frame to the operation and maintenance application layer; The receiving module 840 is used to receive the target remote control command fed back by the operation and maintenance application layer in response to the target status frame; The control module 850 is used to control the weighing sensing layer to perform fault recovery operations according to the target remote control command, so as to achieve rapid diagnosis and recovery.

[0099] Optionally, the target acquisition data includes *a* target dual-channel force measurement data and one target signal trigger data. The *a* target dual-channel force measurement data includes *a* first force measurement data and *a* second force measurement data. In determining the target state frame based on the target acquisition data and the target operation data, the determining module 830 is specifically used for: The difference between the a first force measurement data and the a second force measurement data is calculated and the absolute value is taken to obtain a dual-path difference values; If b out of the a dual-path differences are greater than a preset first fault threshold, then a fault identification result is generated based on the b dual-path differences; b is a positive integer less than or equal to a. The target acquisition data, target operation data, the a dual-channel differences, and the fault identification results are encapsulated into the target status frame.

[0100] Optionally, in generating the fault identification result based on the b dual-path differences, the determining module 830 is further specifically used for: Determine the b dual-redundant sensors corresponding to the b dual-path difference values ​​among the a dual-redundant sensors; Obtain the b fault sensor identifiers corresponding to the b dual-redundant sensors; Obtain the channel state of each of the b dual-redundant sensors to obtain b channel states; Based on the status of the b channels, determine the b fault channel identifiers; Obtain the ratio of each of the b dual-path differences to the first fault threshold to obtain b over-limit ratios; Based on the aforementioned b over-limit ratios, b fault levels are determined; The fault identification result is determined based on the b fault sensor identifiers, the b fault channel identifiers, and the b fault levels.

[0101] Optionally, in acquiring the initial acquisition data collected by the signal acquisition device and the initial operating data corresponding to the intelligent weighing instrument, the acquisition module 810 is specifically used for: The signal acquisition device receives the a initial dual-path force measurement data and the initial signal trigger data from the a dual-redundant sensors and the vehicle separator, respectively, according to a preset acquisition cycle. According to the acquisition cycle, the operating data corresponding to the intelligent weighing instrument is read to obtain the initial operating data.

[0102] Optionally, in the process of preprocessing the initial acquisition data and the initial running data to obtain the target acquisition data and the target running data, the processing module 820 is specifically used for: The a initial dual-path force measurement data are time-domain aligned to obtain a first intermediate data; Digital filtering is performed on each of the a first intermediate data to obtain a second intermediate data; Each of the a second intermediate data points is processed to remove outliers, resulting in a third intermediate data point. Normalize the a third intermediate data respectively to obtain the a target dual-path force measurement data; The initial signal trigger data is subjected to jitter elimination processing to obtain the target signal trigger data; The initial running data is processed to remove abnormal jump values, thereby obtaining the target running data.

[0103] Optionally, in controlling the weighing sensing layer to perform the fault recovery operation according to the target remote control command, the control module 850 is specifically used for: The remote control command to the target is subjected to permission verification to obtain a verification result; the verification result includes any one of the following: low-level permission, medium-level permission, and high-level permission; Based on the verification result, the target remote control command is parsed to obtain the target operation type and target device identifier corresponding to the fault recovery operation; Based on the target operation type, the target device in the weighing sensing layer corresponding to the target device identifier is controlled to perform the fault recovery operation.

[0104] Optionally, the operation and maintenance application layer includes a guard booth monitoring terminal, a weighing equipment operation and maintenance platform, and a visual management and control platform. The target remote control command includes any one of the following: a first remote control command, a second remote control command, and a third remote control command. The control module 850 is further specifically used for: If the target remote control command is generated by the guard post monitoring terminal, then the target remote control command is determined to be the first remote control command, and the low-level permission is assigned to the first remote control command; If the target remote control command is generated by the visualization management platform, then the target remote control command is determined to be the second remote control command, and the intermediate-level permission is assigned to the second remote control command; If the target remote control command is generated by the weighing equipment operation and maintenance platform, then the target remote control command is determined to be the third remote control command, and the advanced permissions are assigned to the third remote control command.

[0105] It should be noted that the specific implementation of each operation can be described in the corresponding description of the method embodiments shown above. The remote operation and maintenance device 800 of the intelligent weighing equipment can be used to execute the method embodiments of this application, and will not be described again here.

[0106] This application also provides a computer-readable storage medium storing a computer program for electronic data interchange, which causes a computer to perform some or all of the steps of any of the methods described in the above method embodiments, wherein the computer includes an electronic device.

[0107] This application also provides a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program operable to cause a computer to perform some or all of the steps of any of the methods described in the above method embodiments. The computer program product may be a software installation package, and the computer may include an electronic device.

[0108] It should be noted that, for the sake of simplicity, the above embodiments are all described as a series of actions. Those skilled in the art should understand that this application is not limited to the described order of actions, as some steps in the embodiments of this application can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions, steps, modules, or units involved are not necessarily essential to the embodiments of this application.

[0109] In the above embodiments, the descriptions of each embodiment in this application have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0110] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. This program can be stored in a computer-readable storage medium, and when executed, it can include the processes described in the above method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as ROM or random access memory (RAM), magnetic disks, or optical disks.

[0111] The steps of the methods or algorithms described in the embodiments of this application can be implemented in hardware or by a processor executing software instructions. The software instructions can consist of corresponding software modules, which can be stored in RAM, flash memory, ROM, EPROM, electrically erasable programmable read-only memory (EEPROM), registers, hard disk, portable hard disk, read-only optical disk (CD-ROM), or any other form of storage medium well known in the art. An exemplary storage medium is coupled to a processor, enabling the processor to read information from and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and storage medium can reside in an ASIC. Furthermore, the ASIC can reside in a terminal device or management device. Alternatively, the processor and storage medium can exist as discrete components in the terminal device or management device.

[0112] Those skilled in the art will recognize that, in one or more of the examples above, the functions described in the embodiments of this application can be implemented, in whole or in part, by software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product. This computer program product includes one or more computer instructions. When these computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium accessible to a computer or a data storage device such as a server or data center that integrates one or more available media. The available media can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., digital video discs (DVDs)), or semiconductor media (e.g., solid-state disks (SSDs)).

[0113] The modules / units included in the various devices and products described in the above embodiments can be software modules / units, hardware modules / units, or a combination of both. For example, for devices and products applied to or integrated into a chip, all modules / units can be implemented using hardware methods such as circuits, or at least some modules / units can be implemented using software programs that run on a processor integrated within the chip, while the remaining (if any) modules / units can be implemented using hardware methods such as circuits. For devices and products applied to or integrated into a chip module, all modules / units can be implemented using hardware methods such as circuits. Different modules / units can be located in the same component (e.g., chip, circuit module, etc.) or different components of the chip module, or at least some modules / units can be implemented using hardware methods such as circuits. The implementation is achieved through a software program that runs on the processor integrated within the chip module. The remaining modules / units (if any) can be implemented using hardware methods such as circuits. For various devices and products applied to or integrated into terminal equipment, each of their modules / units can be implemented using hardware methods such as circuits. Different modules / units can be located in the same component (e.g., chip, circuit module, etc.) or different components within the terminal equipment. Alternatively, at least some modules / units can be implemented through a software program that runs on the processor integrated within the terminal equipment, while the remaining modules / units (if any) can be implemented using hardware methods such as circuits.

[0114] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the embodiments of this application. It should be understood that the above descriptions are merely specific embodiments of the embodiments of this application and are not intended to limit the protection scope of the embodiments of this application. Any modifications, equivalent substitutions, improvements, etc., made on the basis of the technical solutions of the embodiments of this application should be included within the protection scope of the embodiments of this application.

Claims

1. A remote operation and maintenance method of an intelligent weighing device, characterized in that, A control center layer is applied to a remote operation and maintenance system. The system further includes a weighing sensing layer and an operation and maintenance application layer. The control center layer includes an intelligent weighing instrument. The weighing sensing layer includes *a* dual-redundant sensors, a vehicle separator, and a signal acquisition unit, where *a* is an integer greater than 1. The method includes: The system acquires the initial acquisition data collected by the signal acquisition device and the initial operating data corresponding to the intelligent weighing instrument. The initial acquisition data includes a initial dual-channel force measurement data of the a dual-redundant sensors and the initial signal trigger data of the vehicle separator. Each of the a dual-redundant sensors has two sets of independent force measurement units (A and B) and an analog-to-digital conversion unit built in. Each dual-redundant sensor is connected to the analog input channel of the signal acquisition device one by one through an independent signal cable. The initial acquisition data and the initial operation data are preprocessed to obtain the target acquisition data and the target operation data; The target status frame is determined based on the target collected data and the target running data, and the target status frame is sent to the operation and maintenance application layer; Receive the target remote control command fed back by the operation and maintenance application layer in response to the target status frame; According to the target remote control command, the weighing sensing layer is controlled to perform fault recovery operations to achieve rapid diagnosis and recovery; The target acquisition data includes *a* target dual-channel force measurement data and one target signal trigger data. The *a* target dual-channel force measurement data includes *a* first force measurement data and *a* second force measurement data. Determining the target state frame based on the target acquisition data and the target operation data includes: The difference between the a first force measurement data and the a second force measurement data is calculated and the absolute value is taken to obtain a dual-path difference values; If b out of the a dual-path differences are greater than a preset first fault threshold, then a fault identification result is generated based on the b dual-path differences; b is a positive integer less than or equal to a. The target acquisition data, target operation data, the a dual-channel differences, and the fault identification results are encapsulated into the target status frame; The step of generating fault identification results based on the b dual-path differences includes: Determine the b dual-redundant sensors corresponding to the b dual-path difference values ​​among the a dual-redundant sensors; Obtain the b fault sensor identifiers corresponding to the b dual-redundant sensors; Obtain the channel state of each of the b dual-redundant sensors to obtain b channel states; Based on the status of the b channels, determine the b fault channel identifiers; Obtain the ratio of each of the b dual-path differences to the first fault threshold to obtain b over-limit ratios; Based on the aforementioned b over-limit ratios, b fault levels are determined; The fault identification result is determined based on the b fault sensor identifiers, the b fault channel identifiers, and the b fault levels.

2. The method of claim 1, wherein, The acquisition of the initial acquisition data collected by the signal acquisition device and the initial operating data corresponding to the intelligent weighing instrument includes: The signal acquisition device receives the a initial dual-path force measurement data and the initial signal trigger data from the a dual-redundant sensors and the vehicle separator, respectively, according to a preset acquisition cycle. According to the acquisition cycle, the operating data corresponding to the intelligent weighing instrument is read to obtain the initial operating data.

3. The method of claim 2, wherein, The preprocessing of the initial acquired data and the initial running data to obtain the target acquired data and the target running data includes: The a initial dual-path force measurement data are time-domain aligned to obtain a first intermediate data; Digital filtering is performed on each of the a first intermediate data to obtain a second intermediate data; Each of the a second intermediate data points is processed to remove outliers, resulting in a third intermediate data point. Normalize the a third intermediate data respectively to obtain the a target dual-path force measurement data; The initial signal trigger data is subjected to jitter elimination processing to obtain the target signal trigger data; The initial running data is processed to remove abnormal jump values, thereby obtaining the target running data.

4. The method according to any one of claims 1 to 3, characterized in that, The step of controlling the weighing sensing layer to perform the fault recovery operation according to the target remote control command includes: The remote control command to the target is subjected to permission verification to obtain a verification result; the verification result includes any one of the following: low-level permission, medium-level permission, and high-level permission; Based on the verification result, the target remote control command is parsed to obtain the target operation type and target device identifier corresponding to the fault recovery operation; Based on the target operation type, the target device in the weighing sensing layer corresponding to the target device identifier is controlled to perform the fault recovery operation.

5. The method of claim 4, wherein, The operation and maintenance application layer includes a guard booth monitoring terminal, a weighing equipment operation and maintenance platform, and a visual management and control platform. The target remote control command includes any one of the following: a first remote control command, a second remote control command, and a third remote control command. The method further includes: If the target remote control command is generated by the guard post monitoring terminal, then the target remote control command is determined to be the first remote control command, and the low-level permission is assigned to the first remote control command; If the target remote control command is generated by the visualization management platform, then the target remote control command is determined to be the second remote control command, and the intermediate-level permission is assigned to the second remote control command; If the target remote control command is generated by the weighing equipment operation and maintenance platform, then the target remote control command is determined to be the third remote control command, and the advanced permissions are assigned to the third remote control command.

6. A remote operation and maintenance device for a smart weighing installation for carrying out the method according to any one of claims 1 to 5, characterized in that The system is applied to a control center layer of a remote operation and maintenance system. The system also includes a weighing sensing layer and an operation and maintenance application layer. The control center layer includes an intelligent weighing instrument. The weighing sensing layer includes *a* dual-redundant sensors, a vehicle separator, and a signal acquisition unit, where *a* is an integer greater than 1. The device includes an acquisition module, a processing module, a determination module, a receiving module, and a control module. The acquisition module is used to acquire the initial acquisition data collected by the signal acquisition device and the initial operating data corresponding to the intelligent weighing instrument; the initial acquisition data includes a initial dual-path force measurement data of the a dual-redundant sensors and the initial signal triggering data of the vehicle separator; The processing module is used to preprocess the initial acquisition data and the initial running data respectively to obtain the target acquisition data and the target running data; The determining module is used to determine a target status frame based on the target collected data and the target running data, and send the target status frame to the operation and maintenance application layer; The receiving module is used to receive the target remote control command fed back by the operation and maintenance application layer in response to the target status frame; The control module is used to control the weighing sensing layer to perform fault recovery operations according to the target remote control command, so as to achieve rapid diagnosis and recovery.

7. An electronic device, characterized in that, include: Processor, memory, communication interface, and one or more programs; The one or more programs are stored in the memory and configured to be executed by the processor, the programs including instructions for performing the steps of the method as described in any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, the computer program including program instructions that, when executed by a processor, cause the processor to perform the method as described in any one of claims 1-5.

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