Method for counting loading and unloading times of mining vehicle, controller, system and medium

Abstract

The application discloses a mining vehicle loading and unloading frequency counting method, a controller, a system and a medium, and relates to the field of mining machinery. The method comprises: executing a loading and unloading state recognition process associated with a sensor signal and a preset state determination condition, and counting the loading and unloading frequency in response to a change in the unloading state. The recognition process comprises: after the unloading completion state of the previous operation is completed and the loading start condition is met, determining that the loading start state is entered; then, when the loading completion condition is met, determining that the loading completion state is entered and enabling the loading transportation state; then, when the unloading lifting condition is met, determining that the unloading lifting state is entered; and then, when the unloading descending condition is met, determining that the unloading descending state is entered and enabling the unloading completion state. The application realizes an automatic recognition process of the loading and unloading state and a closed loop of the loading and unloading frequency counting, and does not need manual assistance or additional sensors.

Description

Technical Field

[0001] This application relates to the field of mining machinery technology, specifically to a method, controller, system, and medium for counting the number of loading and unloading operations of mining vehicles. Background Technology

[0002] In mining operations, especially in open-pit mines, it is necessary to statistically analyze the loading and unloading frequency of mining vehicles (such as mining dump trucks) to quantify output, calculate efficiency, control costs, and manage safety. Existing methods for statistically analyzing the loading and unloading frequency of mining vehicles mainly include the following: First, manual measurement. This method has extremely low efficiency and is prone to problems such as omissions, errors, and false reporting, and the authenticity of the measurement data is not traceable. Furthermore, manual management is costly and cannot meet the needs of intelligent and refined management in mines.

[0003] Second, the inertial navigation sensor measurement method. This method uses inertial navigation sensors installed on the chassis and cargo bed of the mining truck to detect motion and determine the truck's position and loading status. Based on this information, the number of trips made by the mining truck is then counted. However, this method requires the installation of dual inertial navigation sensors, resulting in high vehicle modification costs, difficult hardware maintenance, and stringent requirements for sensor vibration resistance and measurement accuracy.

[0004] Third, the original vehicle single-signal trigger metering method. This method relies on a single lifting / load signal to identify the loading and unloading status. The identification logic is crude and easily affected by mine vibrations and sensor signal jitter, resulting in a high misjudgment rate.

[0005] Furthermore, the methods of the aforementioned existing technologies fail to construct a measurement closed loop where "the next count is triggered only after one count is completed," making it difficult to guarantee the continuity and accuracy of measurement work.

[0006] Therefore, this application proposes a new scheme for counting the number of loading and unloading operations of mining vehicles. Summary of the Invention

[0007] The purpose of this application is to provide a method, controller, system, and medium for counting the number of loading and unloading operations of mining vehicles, so as to at least partially solve the above-mentioned technical problems.

[0008] To achieve the above objectives, a first aspect of this application provides a method for counting the number of loading and unloading operations of a mining vehicle, comprising: acquiring sensor signals of the mining vehicle and pre-set loading start conditions, loading completion conditions, unloading lifting conditions, and unloading lowering conditions based on the sensor signals; executing a loading and unloading status identification process; and counting the number of loading and unloading operations in response to changes in the unloading status during the loading and unloading status identification process. Specifically, executing the loading and unloading status identification process includes: determining that the mining vehicle has entered a loading start state after the mining vehicle has entered the unloading completion state corresponding to the previous loading and unloading operation and the loading start condition is met; determining that the mining vehicle has entered a loading completion state and enabled loading and transportation state after the mining vehicle has entered the loading start state and the loading completion condition is met; determining that the mining vehicle has entered an unloading lifting state after the mining vehicle has entered the loading and transportation state and the unloading lifting condition is met; and determining that the mining vehicle has entered an unloading lowering state and enabled unloading completion state after the mining vehicle has entered the unloading lifting state and the unloading lowering condition is met.

[0009] In this embodiment, the sensor signals include a vehicle speed signal, a loading brake signal, a cargo box lowering signal, and an engine speed signal. The loading start conditions include the vehicle speed signal indicating the vehicle is stationary, the loading brake signal being valid, and the cargo box lowering signal being valid. The loading completion conditions include the vehicle speed signal indicating the vehicle is in motion, the loading brake signal being invalid, and the cargo box lowering signal being valid. The unloading lifting conditions include a valid lifting indicator, the engine speed signal indicating the engine is running, the loading brake signal being valid, and the cargo box lowering signal being invalid. The conditions for determining the validity of the lifting indicator include the cargo box lowering signal changing from valid to invalid, the loading brake signal being valid, the engine speed signal indicating the engine is running, and the mining vehicle being in the loading and transporting state. The unloading lowering conditions include a valid lowering indicator, the engine speed signal indicating the engine is running, the loading brake signal being invalid, the cargo box lowering signal being valid, and the vehicle speed signal indicating the vehicle is in motion. The conditions for determining the validity of the lowering indicator include the cargo box lowering signal changing from invalid to valid, the loading brake signal being valid, and the engine speed signal indicating the engine is running.

[0010] In this embodiment, the sensor signals include vehicle speed, loading brake, cargo box lowering signal, engine speed, and load signal. The loading start conditions include the vehicle speed signal indicating the vehicle is stationary, the loading brake signal being valid, the cargo box lowering signal being valid, and the load signal indicating the load is continuously rising and reaching a first predetermined percentage of the rated load. The loading completion conditions include the vehicle speed signal indicating the vehicle is in motion, the loading brake signal being invalid, the cargo box lowering signal being valid, and the load signal indicating the load has reached a second predetermined percentage of the rated load, where the second predetermined percentage is greater than the first predetermined percentage. The unloading and lifting conditions include a valid lifting indicator, the engine speed signal indicating the engine is operating, the loading brake signal being valid, and the cargo box lowering signal being invalid. The conditions for determining the validity of the lifting indicator include the cargo box lowering signal changing from valid to invalid, the loading brake signal being valid, the engine speed signal indicating the engine is operating, the mining vehicle being in the loading and transportation state, and the load signal indicating the load has reached the second predetermined percentage of the rated load. The unloading and descent conditions include a valid descent indicator, an engine speed signal indicating engine operation, an invalid loading brake signal, a valid cargo box landing signal, and a vehicle speed signal indicating the vehicle is in motion. The conditions for determining a valid descent indicator include the cargo box landing signal changing from invalid to valid, the invalid loading brake signal, an engine speed signal indicating engine operation, and the load signal indicating the load is lower than the first set percentage of the rated load.

[0011] In this embodiment of the application, the counting of loading and unloading times includes: after the mining vehicle changes from the unloading lifting state to the unloading lowering state, determining that a loading and unloading operation has been completed, and starting a time window of a preset duration; determining any sensor signal acquired within the time window as an invalid trigger signal; and after the time window, performing a count of valid loading and unloading times.

[0012] A second aspect of this application provides a controller for counting the number of loading and unloading operations of mining vehicles, comprising: an instruction memory configured to store instructions; and a processor configured to retrieve the instructions from the instruction memory and, when executing the instructions, to implement the loading and unloading count counting method described above.

[0013] In this embodiment of the application, the controller is the vehicle control unit (VCU) of the mining vehicle.

[0014] A third aspect of this application provides a system for counting the number of loading and unloading operations for mining vehicles, comprising: a vehicle sensor group for collecting various sensor signals from the mining vehicle; any of the aforementioned controllers for acquiring the sensor signals to perform loading and unloading count statistics; and a ferroelectric memory. The ferroelectric memory is configured to store any one or more of the following statistical data: loading start state, loading completion state, loading and transportation state, unloading lifting state, unloading lowering state, and unloading completion state determined or enabled in real time during the loading and unloading status identification process; the number of loading and unloading operations, vehicle mileage, and / or fuel consumption counted within a preset period; and time information associated with the loading and unloading operations.

[0015] In this embodiment, the loading and unloading frequency statistics system further includes an in-vehicle display terminal, a GPS (Global Positioning System) module, and a cloud management platform. The controller transmits the statistical data to the in-vehicle display terminal via the in-vehicle CAN bus; and / or the controller transmits the statistical data to the cloud management platform via the GPS module, wherein the GPS module directly transmits the statistical data or transmits the statistical data via a local cache module in response to different network signal strengths.

[0016] In this embodiment, the original vehicle sensor group includes any number of the following sensors: a cargo box landing proximity switch or tilt sensor for detecting the cargo box landing signal; a vehicle speed sensor for detecting the vehicle speed signal; a loading brake sensor for detecting the loading brake signal; an engine speed sensor for detecting the engine speed signal associated with cargo box lifting; a load sensor for detecting the load signal; and a fuel level sensor for detecting the fuel level signal.

[0017] A fourth aspect of this application provides a machine-readable storage medium storing instructions that cause a machine to execute any of the above-described loading and unloading count methods.

[0018] Through the above technical solutions, the embodiments of this application can realize an automated identification process for loading and unloading status and a closed loop for the measurement of loading and unloading times, without the need for manual assistance or the addition of extra sensors, resulting in lower cost and higher measurement accuracy.

[0019] Other features and advantages of the embodiments of this application will be described in detail in the following detailed description section. Attached Figure Description

[0020] The accompanying drawings are provided to further illustrate the embodiments of this application and form part of the specification. They are used together with the following detailed description to explain the embodiments of this application, but do not constitute a limitation on the embodiments of this application. In the drawings: Figure 1 The illustration shows a flowchart of a method for counting the number of loading and unloading operations of a mining vehicle according to Embodiment 1 of this application; Figure 2 This schematic diagram illustrates the overall architecture of the on-board electronic control system of a mining vehicle according to an embodiment of this application; Figure 3 This illustration shows a schematic diagram of the loading and unloading status identification process according to an embodiment of this application; Figure 4 A schematic diagram of a state machine for various loading and unloading states according to embodiments of this application is shown. Figure 5 This schematically illustrates a structural block diagram of a loading and unloading frequency statistics controller for mining vehicles according to Embodiment 2 of this application; and Figure 6 The diagram illustrates the structure of a mining vehicle loading and unloading frequency statistics system according to Embodiment 3 of this application.

[0021] Explanation of reference numerals in the attached figures Detailed Implementation

[0022] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are only for illustration and explanation of the embodiments of this application and are not intended to limit the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0023] It should be noted that the acquisition, transmission, storage, use, and processing of data in the technical solution of this application all comply with relevant laws and regulations. In the embodiments of this application, certain existing industry solutions such as software, components, and models may be mentioned. These should be considered exemplary, intended only to illustrate the feasibility of implementing the technical solution of this application, and do not imply that the applicant has already used or necessarily used such solutions.

[0024] It should be noted that if the embodiments of this application involve directional indicators (such as up, down, left, right, front, back, etc.), the directional indicators are only used to explain the relative positional relationship and movement of each component in a certain specific posture (as shown in the figure). If the specific posture changes, the directional indicators will also change accordingly.

[0025] Furthermore, if the embodiments of this application involve descriptions such as "first" or "second," these descriptions are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, features defined with "first" or "second" may explicitly or implicitly include at least one of those features. Additionally, the technical solutions of various embodiments can be combined with each other, but this must be based on the ability of those skilled in the art to implement them. If the combination of technical solutions is contradictory or impossible to implement, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed in this application.

[0026] Example 1 Figure 1 The illustration shows a flowchart of a method for counting the number of loading and unloading operations of mining vehicles according to Embodiment 1 of this application. The mining vehicle is, for example, a mining dump truck, particularly an electrically driven mining dump truck equipped with an onboard electronic control system. The method for counting the number of loading and unloading operations of mining dump trucks in open-pit mining scenarios aims to meet the metering and statistical needs of the entire operation cycle of loading, transportation, and unloading in open-pit mining, and to achieve the identification of loading and unloading operation status and multi-dimensional intelligent metering and statistics.

[0027] Before introducing the method for counting the number of loading and unloading operations of mining vehicles in the embodiments of this application, the on-board electronic control system of mining vehicles will be introduced first so that those skilled in the art can more clearly understand the embodiments of this application. Figure 2 This diagram illustrates the overall architecture of the onboard electronic control system for mining vehicles, which is divided into a signal acquisition layer, a core computing layer, and a data interaction layer. This will be discussed in detail later. Figure 6 In this embodiment, the signal acquisition layer is the original vehicle sensor group, the core computing layer is the vehicle control unit (VCU), and the data interaction layer is the in-vehicle display screen and GPS module, etc. The original vehicle sensor group, the in-vehicle display screen, and the GPS module all establish signal connections with the VCU through the vehicle CAN bus. The original vehicle sensor group transmits the acquired signals to the VCU in real time, and the VCU sends various processed data (such as statistical data obtained by the VCU executing the method of Embodiment 1 of this application) to the in-vehicle display screen and the GPS module.

[0028] The original vehicle sensor group includes, but is not limited to, a cargo box lowering proximity switch, a cargo box operating handle, a loading brake sensor, a vehicle speed sensor, an engine speed sensor, a load cell, and a fuel level sensor. It should be noted that the original vehicle sensor group in this embodiment does not require the configuration of all the sensors listed herein; rather, sensor configuration can be tailored to actual needs. For example, an example without a load cell will be discussed below.

[0029] Back Figure 1 The loading and unloading count method of Embodiment 1 of this application may include the following steps S100-S300.

[0030] Step S100: Acquire the sensor signals of the mining vehicle and the loading start conditions, loading completion conditions, unloading lifting conditions, and unloading descent conditions preset based on the sensor signals.

[0031] The sensor signals come from the original sensor group of the mining vehicle, so this embodiment of the application does not require the installation of additional inertial navigation sensors or the like on the mining vehicle.

[0032] In contrast to existing technologies that typically only determine loading and unloading states, this application refines the identification of loading and unloading states into loading start conditions, loading completion conditions, unloading lifting conditions, and unloading descent conditions. This facilitates subsequent metering closed-loop control and avoids misjudgments through specific condition configurations. These details will be further explained in subsequent steps and examples, and will not be elaborated upon here.

[0033] Step S200: Execute the loading and unloading status identification process.

[0034] Specifically, such as Figure 3 As shown, the loading / unloading status identification process can be configured as follows: steps S210-S240, and is manifested as follows: Figure 4 The state machine form shown.

[0035] Step S210: After the mining vehicle is in the unloading completed state corresponding to the previous loading and unloading operation and the loading start condition is met, it is determined that the mining vehicle has entered the loading start state.

[0036] Step S220: After the mining vehicle enters the loading start state and the loading completion condition is met, determine that the mining vehicle has entered the loading completion state and enable loading and transportation state.

[0037] Step S230: After the mining vehicle is in the loading and transportation state and the unloading and lifting conditions are met, it is determined that the mining vehicle has entered the unloading and lifting state.

[0038] Step S240: After the mining vehicle enters the unloading lifting state and the unloading lowering condition is met, determine that the mining vehicle is in the unloading lowering state and enable the unloading completion state.

[0039] Combination Figure 4The state machine is as follows: steps S210 and S220 correspond to loading status determination, and steps S230 and S240 correspond to unloading status determination. The loading start state in step S210 follows the unloading completion state of the previous loading / unloading operation, indicating that the current loading operation is only initiated after confirming the completion of the previous unloading. Step S220 enables the loading / transporting state while determining the loading completion state, indicating that the vehicle has completed loading and entered the transportation state. The unloading lifting state in step S230 follows the loading / transporting state, indicating that unloading is only prepared after the vehicle has been loaded and transported, avoiding misjudgments of loading scenarios (e.g., invalid cargo box lifting signal, valid neutral signal, valid loading brake signal, and zero vehicle speed). Step S240 enables the unloading completion state while determining the unloading descent state, corresponding to step S210, preparing to proceed to the determination of the next loading / unloading operation.

[0040] Thus, through steps S210-S240, a closed-loop state machine is formed, which can accurately identify the state boundaries of each operation stage and construct the entire operation state of loading-transportation-unloading, which helps to realize the closed-loop logic of the loading and unloading state identification process.

[0041] Step S300: In response to the change in unloading status in the loading and unloading status identification process, the number of loading and unloading operations is counted.

[0042] Specifically, the completion of one work cycle is determined based on the unloading status (from unloading lifting state to unloading lowering state), and a count of the number of loading and unloading operations is performed. Corresponding to the state machine with consecutive states in the above loading and unloading status identification process, this step S300 ensures that the next count is triggered only after one count is completed, thus forming a fully closed logical loop regarding loading and unloading status identification and loading and unloading count statistics.

[0043] It should be noted that in the actual operation of mining dump trucks, various interference events may occur in the loading and unloading count. For example, the collision of the cargo box during unloading may cause the cargo box landing signal to jump between valid and invalid (the corresponding proximity switch will rapidly shake between "on" and "off"), driver misoperation may trigger the lifting handle, sensor failure (the load sensor may give a brief erroneous signal due to poor contact), and the vehicle may briefly return to the unloading area for some reason when unloading and leaving.

[0044] To address these interference events, in a preferred embodiment, the counting of loading and unloading times in step S300 may include: determining that a loading and unloading operation has been completed after the mining vehicle changes from the unloading lifting state to the unloading lowering state, and initiating a time window of a preset duration; identifying any sensor signal acquired within the time window as an invalid trigger signal; and performing a count of valid loading and unloading times after the time window.

[0045] That is, invalid trigger signals are filtered out through a time window, thereby avoiding the impact of the aforementioned interference events. The time window is not arbitrarily set, but is based on the maximum possible duration of various interference events, and is required to be much shorter than the minimum time required for one work cycle.

[0046] In subsequent examples of this application's embodiments, the time window is set to 3 minutes, which can completely cover all short-term interferences without affecting the determination of normal work cycles, leaving sufficient buffer time. The specific characteristics of the time window setting will be described in detail below with reference to examples, and will not be repeated here.

[0047] In summary, the loading and unloading count method of this application embodiment can realize the automated identification process of loading and unloading status and the closed loop of loading and unloading count measurement without manual assistance or the addition of additional sensors, resulting in lower cost and higher measurement accuracy.

[0048] The following two examples illustrate the loading and unloading status judgment conditions, loading and unloading status identification process, and loading and unloading count statistics scheme involved in steps S100-S300, and provide further implementation details. In these two examples, the entire loading and unloading count statistics method is executed by a VCU, which is equipped with a ferroelectric memory (hereinafter referred to as ferroelectric) to store at least the following information: the loading start status, loading completion status, loading and transportation status, unloading lifting status, unloading lowering status, and unloading completion status determined or enabled in real time during the loading and unloading status identification process; the number of loading and unloading counts within a preset period (e.g., one day); and other data to be mentioned below. The core feature of ferroelectric is that it possesses both the high-speed read and write capabilities of RAM and the data storage capabilities of a USB flash drive (Flash / EEPROM). Its application in the examples of this application embodiment will be described in detail below.

[0049] First example: For mining vehicles that do not have weighing sensors.

[0050] Currently, a large number of mining vehicles in service are not equipped with weighing sensors, and this first example is suitable for such mining vehicles, as it does not rely on load signals when determining the loading and unloading status.

[0051] In the first example, the sensor signals include vehicle speed signal, loading braking signal, cargo box lowering signal, and engine speed signal. Corresponding to these sensor signals, the loading / unloading status judgment conditions are set as follows: (1) The loading start conditions include the vehicle speed signal indicating that the vehicle is stationary, the loading braking signal being valid, and the cargo box being lowered into place signal being valid.

[0052] (2) The loading completion conditions include the vehicle speed signal indicating that the vehicle is in motion, the loading brake signal being invalid, and the cargo box being lowered into place signal being valid.

[0053] (3) The unloading and lifting conditions include a valid lifting indicator, an engine speed signal indicating engine operation, a valid loading brake signal, and an invalid cargo box lowering signal. The conditions for determining a valid lifting indicator include the cargo box lowering signal changing from valid to invalid, the loading brake signal being valid, the engine speed signal indicating engine operation, and the mining vehicle being in the loading and transport state.

[0054] (4) The unloading and descent conditions include a valid descent indicator, an engine speed signal indicating engine operation, an invalid loading brake signal, a valid cargo box landing signal, and a vehicle speed signal indicating the vehicle is in motion. The conditions for a valid descent indicator include the cargo box landing signal changing from invalid to valid, the loading brake signal being valid, and the engine speed signal indicating engine operation.

[0055] After determining the sensor signals and loading / unloading status judgment conditions, the loading / unloading status recognition process corresponding to the first example includes the following loading status judgment and unloading status judgment.

[0056] 1. Loading status determination (loading started, loading completed).

[0057] The VCU receives signals from the original vehicle's sensor group in real time. When the following conditions are met simultaneously: the vehicle is stationary (vehicle speed = 0 km / h, stopped waiting for loading), the loading brake signal is valid, the cargo box is in position (i.e., the cargo box position signal is valid, indicating that the cargo box has been leveled and is ready for loading), the vehicle is in an unloaded transportation state, and the unloading completion state lasts for 10 seconds, loading is determined to have started. At this time, the unloading completion state is reset, and the loading start state and unloading completion state are stored in the VCU ferroelectric.

[0058] After the loading start state takes effect and lasts for 30 seconds, if the following conditions are met simultaneously: the cargo box lowering signal is valid, the loading brake signal is invalid, and the vehicle is in motion (vehicle speed ≥ 10km / h, i.e., the vehicle is in a relatively slow starting motion state), then loading is considered complete. The loading and transportation state is then activated, the loading start state is reset, and the loading completion state and loading and transportation state are stored in the VCU ferroelectric system.

[0059] 2. Uninstallation status determination (uninstallation promotion, uninstallation demotion).

[0060] When the following conditions are met simultaneously: the loading brake signal is valid, the cargo box lowering switch changes from closed to open (i.e., the cargo box lowering signal changes from valid to invalid; this can also be determined using a tilt sensor, indicating that the cargo box may be being lifted), the engine is running (speed > 500 r / min, i.e., the engine is running to lift the cargo box), and the vehicle is in loading and transport mode, the lifting indicator is considered valid. When the lifting indicator is valid, the loading brake signal is valid, the engine is running, and the cargo box lowering signal remains invalid for 5 seconds, the vehicle is considered to be entering the unloading and lifting mode. At this time, the loading and transport mode and the lifting indicator are reset, and the unloading and lifting mode and the loading and transport mode are stored in the VCU ferroelectric system.

[0061] When the loading brake signal is valid, the proximity switch for the cargo box falling into place changes from open to closed (indicating the cargo box is falling back), and the engine is running (speed > 500 r / min), the descent indicator is considered valid. When the descent indicator is valid, the loading brake signal is invalid, the engine is running, the vehicle is moving (speed > 5 km / h, i.e., the departure state after unloading and releasing the brake), and the cargo box falling into place signal is valid for 5 seconds, the unloading descent state is determined to have entered the unloading completion state. At this time, the unloading completion state is enabled, the descent indicator is reset, and the unloading completion state and the unloading descent state are stored in the VCU ferroelectric.

[0062] Here, the choice of a speed of 5 km / h is related to the over-control maneuvering incident. Specifically, the safety principle of mining dump trucks stipulates that the vehicle must not move unless the cargo box is completely back in its original position. However, in actual unloading, sometimes a malfunction occurs where the cargo box gets stuck and cannot be lowered, leaving the vehicle in a state where it "cannot unload normally, nor can it drive safely." To deal with this situation, the driver may resort to over-control maneuvering, which bypasses the normal safety interlock logic and forcibly performs a maneuvering action. This maneuvering action involves slowly moving the vehicle back and forth at an extremely low speed, typically not exceeding 5 km / h according to industry regulations. Furthermore, it is easy to see that the vehicle's brakes are ineffective during the over-control maneuvering process.

[0063] It should be noted that the first example is the same as the second example below regarding the subsequent loading and unloading frequency statistics scheme and other implementation details, so it will be introduced in the second example and will not be repeated here.

[0064] It should also be noted that this first example has passed programming verification. Although it does not involve load signals, it can still ensure the logical closed loop of the entire loading and unloading status identification process and accurately count the number of loading and unloading operations.

[0065] Second example: For mining vehicles equipped with weighing sensors.

[0066] In the second example, in addition to the sensor signals involved in the first example, a load signal is also included. Corresponding to these sensor signals, the loading / unloading status judgment conditions are set as follows: (1) The loading start conditions include the vehicle speed signal indicating that the vehicle is stationary, the loading brake signal being valid, the cargo box falling into place signal being valid, and the load signal indicating that the load is continuously rising and reaching a first set ratio of the rated load.

[0067] (2) The loading completion conditions include the vehicle speed signal indicating that the vehicle is in motion, the loading brake signal being invalid, the cargo box being lowered into place signal being valid, and the load signal indicating that the load has reached a second set ratio of the rated load, wherein the second set ratio is greater than the first set ratio.

[0068] (3) The unloading and lifting conditions include a valid lifting indicator, an engine speed signal indicating engine operation, a valid loading brake signal, and an invalid cargo box lowering signal. The conditions for determining a valid lifting indicator include the cargo box lowering signal changing from valid to invalid, the loading brake signal being valid, the engine speed signal indicating engine operation, the mining vehicle being in the loading and transport state, and the load signal indicating that the load has reached the second set percentage of the rated load.

[0069] (4) The unloading and lowering conditions include a valid lowering indicator, an engine speed signal indicating engine operation, an invalid loading brake signal, a valid cargo box lowering signal, and a vehicle speed signal indicating the vehicle is in motion. The conditions for determining a valid lowering indicator include the cargo box lowering signal changing from invalid to valid, the loading brake signal being invalid, the engine speed signal indicating engine operation, and the load signal indicating the load is lower than the first set percentage of the rated load.

[0070] After determining the sensor signals and loading / unloading status judgment conditions, the loading / unloading status recognition process corresponding to the second example includes the following loading status judgment and unloading status judgment.

[0071] 1. Loading status determination (loading started, loading completed).

[0072] The VCU receives signals from the original vehicle's sensor group in real time. When the following conditions are met simultaneously: the vehicle is stationary (vehicle speed = 0 km / h), the loading brake signal is valid, the cargo box is lowered into place, the load continues to rise and reaches the 20% threshold of the rated load (corresponding to the first set ratio mentioned above), the vehicle is in an unloaded transportation state, and the unloading completion state lasts for 10 seconds, loading is determined to have started. At this time, the unloading completion state is reset, and the loading start state and unloading completion state are stored in the VCU ferroelectric.

[0073] After the loading start state takes effect and lasts for 30 seconds, if the following conditions are met simultaneously: the cargo box is effectively lowered into place, the loading brake signal is invalid, and the vehicle is transporting (speed ≥ 10 km / h) and reaches a threshold of 50% or more of the rated load (corresponding to the second set ratio mentioned above) for 2 seconds, then loading is considered complete. The loading and transportation state is then activated, the loading start state is reset, and the loading completion state and loading and transportation state are stored in the VCU ferroelectric system.

[0074] 2. Uninstallation status determination (uninstallation promotion, uninstallation demotion).

[0075] When the following conditions are met simultaneously: the loading brake signal is valid, the cargo box lowering switch changes from closed to open, the engine is running (speed > 500 r / min), the load reaches more than 50% of the rated load threshold, and the vehicle is in loading and transport mode, the lifting indicator is considered valid. When the lifting indicator is valid, the loading brake signal is valid, the engine is running, and the cargo box lowering signal is invalid for 5 seconds, the vehicle is considered to have entered the unloading lifting state. At this time, the loading and transport state and the lifting indicator are reset, and the unloading lifting state and the loading and transport state are stored in the VCU ferroelectric system.

[0076] When the following conditions are met simultaneously: the loading brake signal is invalid, the cargo box lowering switch changes from open to closed, the engine is running (speed > 500 r / min), and the load is less than 20% of the rated load, the lowering indicator is considered valid. When the lowering indicator is valid, the loading brake signal is invalid, the engine is running, the vehicle is moving (speed > 5 km / h), and the cargo box lowering signal remains valid for 5 seconds, the unloading lowering state is entered. At this time, the unloading completion state is enabled, the lowering indicator is reset, and the unloading completion state and the unloading lowering state are stored in the VCU ferroelectric system.

[0077] Compared to the first example, this second example is applicable to mining vehicles equipped with weighing sensors. The addition of the load signal can deepen the judgment signal dimension, thereby more comprehensively ensuring the accuracy of the loading and unloading count.

[0078] Following on the unloading status determination in point 2 above, the following section will introduce the effective load count statistics and data processing flow for the second example.

[0079] 3. Statistics on the number of effective loads.

[0080] Based on the unloading status (from unloading lifting state to unloading lowering state), a work cycle is determined to be completed. The VCU automatically starts a 3-minute time window. If a suspected work trigger signal (i.e., invalid trigger signal) is detected during the window, such as lifting mechanism trigger or load signal fluctuation, it is determined to be an invalid operation such as accidental contact, trial lifting, or jogging, regardless of whether the work status determination conditions are met. No work count is performed. After the 3-minute time window ends, the normal work status determination and counting function is restored. At this time, it is determined to be a valid work cycle. The VCU accumulates the number of loadings based on the number of valid loadings and stores it in the VCU ferroelectric.

[0081] Here, the 3-minute time window is a specific calibrated threshold based on the operating conditions of open-pit mine dump trucks, and it cannot be obviously determined. Its special characteristics are reflected in: 1) Adapt to the shortest time pattern of effective operations. Even for the shortest haulage operation cycle within the open-pit mine, the shortest time from the completion of unloading and repositioning of the cargo box to the next effective lifting / loading is greater than 3 minutes. The 3-minute time window can completely block invalid operations and will not mistakenly filter out effective operations.

[0082] 2) It aligns with the time characteristics of invalid or erroneous operations. Invalid operations such as accidental touches and trial lifts are all completed within 1 minute, and the 3-minute time window completely covers the time range of all invalid operations; 3) Complies with equipment safety operation specifications. Industry safety operation specifications for the lifting mechanism of mining dump trucks require a 3-minute time window for mechanical stabilization after the cargo box is reset, which is highly consistent with industry standards. 4) Balancing false positive prevention with real-time performance. Three minutes represents the optimal balance between the effectiveness of false positive prevention and the real-time performance of measurement.

[0083] 4. Data processing.

[0084] The current date is determined based on the system clock and the standard clock. If they are different, the daily mileage and daily loading count are set to 0, and the system clock value is assigned to the standard clock. If they are the same, the daily loading count is accumulated based on the number of valid loads per day, and the daily mileage is accumulated based on the single mileage count for that day. Furthermore, the standard date, daily mileage, and daily loading count are all stored in the VCU ferroelectric system.

[0085] Based on the loading and transportation start status, the single-trip mileage is accumulated via the vehicle speed sensor, and the single-trip time is accumulated via the VCU internal clock. Simultaneously, fuel percentage data from the fuel level sensor is collected, and the fuel percentage consumption during transportation is calculated. Furthermore, all relevant data is stored in real-time in the VCU ferroelectric system.

[0086] The two examples above provide intelligent metering solutions for the entire loading and unloading process of mining dump trucks. The core relies on the original electronic control system architecture of the mining dump truck, without the need for additional hardware modules. It collects collaborative signals from multiple sensors on the original vehicle through the vehicle's CAN bus, constructs an automated status judgment logic for the entire operation cycle of loading, transportation, and unloading, and achieves accurate metering of the number of operations by combining an anti-duplication counting algorithm. It can simultaneously complete the real-time collection and statistics of multi-dimensional operation data for single trips, single days, and the entire life cycle.

[0087] Specifically, the loading and unloading frequency counting schemes in the two examples above have advantages over existing technologies in at least the following aspects: 1. Zero hardware modification cost and strong adaptability: Relying on the original vehicle sensor group and VCU, there is no need to add inertial navigation and other hardware. It can be directly adapted to the original vehicle electronic control architecture of various models of electric wheel mining dump trucks, and has strong adaptability to mining working conditions.

[0088] 2. Precise loading and unloading status identification and high anti-interference capability: Relying on the original CAN bus of the mining dump truck to collect multi-dimensional signals such as lifting, speed, load, and braking, a full-process operation state machine is constructed, encompassing "loading start - loading end - transportation - unloading lifting - unloading descent". Through collaborative judgment of signals from multiple sensors on the original vehicle and multi-layer logic of "threshold judgment + delay confirmation + status linkage", the state boundaries of each operation stage are accurately identified. Existing technologies triggered by a single signal lack a full-process operation status identification mechanism, cannot identify incomplete operation cycles, and have insufficient measurement effectiveness. Compared with such existing technologies, the embodiments of this application can effectively avoid interference from mine vibrations, signal jitter, and hardware accuracy drift, resulting in high accuracy in operation status identification.

[0089] For example, existing technologies only trigger counting through a single point signal of lifting / loading, failing to distinguish between the state difference of "transporting to the unloading point for unloading" and "actual loading". However, the embodiments of this application clarify that the subsequent unloading count is only triggered after loading is completed and the vehicle leaves the loading area to enter the transportation state, thus fundamentally solving the problem of misjudging the transportation stage as loading in existing technologies.

[0090] In addition, the state machine in this application is specifically designed for mining operation scenarios. By coordinating multiple signals (such as the completion of loading requiring "unloading in place + vehicle speed > 5km / h + leaving the loading area"), it avoids misjudgment of signal triggering. Existing technologies do not involve such full-process state logic.

[0091] 3. Time-Window Anti-Duplicate Counting for High Measurement Accuracy: Employing a time-window anti-duplicate counting filtering algorithm (e.g., 3 minutes), the algorithm uses the completion of an effective work cycle as the trigger condition. It automatically blocks trigger signals generated by invalid operations such as accidental touches, trial lifts, and jogging within the window, eliminating duplicate counting problems from a technical perspective and ensuring the accuracy of loading and unloading count measurement. In other words, it eliminates duplicate counting problems caused by accidental touches, trial lifts, and jogging at the software level, solving the measurement error pain point of existing technologies. Existing technologies typically lack anti-misjudgment filtering mechanisms, making them prone to duplicate counting due to accidental equipment touches and trial lifts by the lifting mechanism, resulting in insufficient measurement accuracy.

[0092] 4. Comprehensive Data Dimensions Supporting Refined Management: Breaking through the limitations of existing technologies that only count the number of trips, this technology, based on effective work cycles, synchronously collects and stores in real time core operational parameters such as single-trip load, mileage, duration, and fuel consumption. It achieves synchronous collection and associated storage of multi-dimensional operational data across single trips, daily trips, and the entire lifecycle, providing comprehensive data support for mine vehicle efficiency accounting, cost analysis, and task performance evaluation. Existing technologies typically only count the number of loading trips, lacking the collection of core operational parameters such as single-trip distance, transportation time, and fuel consumption. This single data dimension fails to support mine vehicle operating cost accounting.

[0093] 5. High data reliability and no risk of loss: All statistical data are stored in a non-volatile manner, supporting data retention and power-off continuation, ensuring that metering data is not lost and is traceable.

[0094] 6. When the original vehicle is not equipped with a weighing system or a weighing sensor-related system, the core data statistics logic of this application embodiment is also applicable. It can still achieve accurate counting of loading and unloading times without the need for load data and load-related judgment conditions.

[0095] Example 2 Figure 5 The diagram schematically illustrates a structural block diagram of a loading and unloading frequency statistics controller for mining vehicles according to Embodiment 2 of this application. Figure 5 As shown, the controller may include: an instruction memory configured to store instructions; and a processor configured to retrieve instructions from the instruction memory and, when executing instructions, to implement the loading and unloading count method of Embodiment 1 described above.

[0096] The controller can be a VCU or other independently configured controller. Furthermore, the word "instruction" in the instruction memory is intended to highlight its functional difference from ferroelectric memory; in reality, instruction memory can be used to store relevant statistical data, while ferroelectric memory can be used to store instructions.

[0097] For more details on the implementation of the controller in Embodiment 2 and its beneficial effects, please refer to Embodiment 1, which will not be repeated here.

[0098] Example 3 Figure 6 The diagram schematically illustrates a structural block diagram of a mining vehicle loading and unloading frequency statistics system according to Embodiment 3 of this application. Figure 6 As shown, the system includes: a vehicle sensor group 610 for collecting various sensor signals from mining vehicles; a controller 620 of Embodiment 2, for example, a VCU, for acquiring the sensor signals to perform loading and unloading count statistics; and a ferroelectric memory 630.

[0099] In conjunction with Embodiment 1, the ferroelectric memory 630 is configured to store one or more of the following statistical data: loading start status, loading completion status, loading and transportation status, unloading lifting status, unloading lowering status, and unloading completion status, which are determined or enabled in real time during the loading and unloading status identification process; the number of loading and unloading operations, vehicle mileage, and / or fuel consumption within a preset period (e.g., one day); and time information associated with the loading and unloading operation, such as the aforementioned standard date and vehicle one-way travel time. The ferroelectric memory 630 can be integrated into the controller 620.

[0100] Additionally, the original vehicle sensor group 610 includes any and more of the following sensors: a cargo box lowering proximity switch or tilt sensor for detecting a cargo box lowering signal; a vehicle speed sensor for detecting a vehicle speed signal; a loading brake sensor for detecting a loading brake signal; an engine speed sensor for detecting an engine speed signal associated with cargo box lifting; a load sensor for detecting a load signal; and a fuel level sensor for detecting a fuel level signal. Furthermore, it may also include a cargo box operating handle, with a corresponding cargo box operating handle signal used to indicate the cargo box status, functioning similarly to the cargo box lowering proximity switch.

[0101] It is easy to see that the cargo box landing proximity switch can be replaced with a tilt sensor. Using a tilt sensor, especially a dynamic tilt sensor, the continuous changes in the lifting and lowering of the cargo box can be captured in real time. Compared with the "single-point signal trigger + duration correction" scheme of the cargo box landing proximity switch, the determination of the cargo box status is more intuitive and the lifting range of the cargo box can be understood.

[0102] With the adoption of a tilt sensor, in the first and second examples of Embodiment 1, for determining the loading status, the cargo box landing signal can be replaced with a cargo box tilt angle of 0° reference. Additionally, interference from mining slope conditions can be eliminated by calibrating the parking compensation value on-site. For determining the unloading status, the cargo box landing switch can be changed from a closed-to-open condition to a condition where the cargo box tilt angle continuously rises from the 0° reference value to the unloading threshold; the cargo box landing switch can be changed from an open-to-close condition to a condition where the cargo box tilt angle falls back from the unloading threshold to the 0° reference value; and the absence of a cargo box landing signal can be changed to a condition where the cargo box tilt angle > 0°.

[0103] In a preferred embodiment, the loading and unloading count system further includes an on-board display terminal 640, a GPS module 650, and a cloud management platform 660.

[0104] The controller 620 transmits statistical data to the vehicle display terminal 640 via the vehicle CAN bus. The vehicle display terminal 640 can be configured to have data visualization and offline export functions.

[0105] Alternatively, the controller 620 can transmit the statistical data to the cloud management platform 660 via the GPS module 650 for cloud display. The GPS module 650 is a terminal equipped with satellite positioning and data uploading in the vehicle, featuring weak network caching and breakpoint resume functions. Specifically, the GPS module 650 can directly transmit the statistical data or transmit it via a local caching module in response to different network signal strengths. For example, when a weak network signal or network interruption is detected, the GPS module 650 automatically caches the statistical data in the local caching module, and resumes the transmission after the network is restored, ensuring the consistency and integrity of local and cloud-based metering data.

[0106] The controller (VCU) synchronously transmits statistical data to the vehicle display terminal 640 and GPS module 650 via the vehicle CAN bus, realizing end-to-end data distribution of local visualization, offline data export, and remote cloud interaction. This can be manifested in the following two aspects: 1. Onboard Local Visualization and Offline Export. After receiving statistical data, the onboard display terminal 640 visualizes it in a structured list format, covering all operational data for the past month, including loading completion time, single trip load, unloading completion time, number of loading operations per day, single trip mileage, single trip duration, single trip fuel consumption, and total number of loading operations over the entire lifecycle. The data list is arranged in reverse chronological order by operation completion time, with the latest operational data displayed at the top. Simultaneously, the onboard display terminal 640 supports offline export of all metering data via USB flash drive, meeting the needs of on-site data verification and record keeping.

[0107] 2. Cloud Data Upload and Multi-Terminal Display. After receiving statistical data, the GPS module 650 uploads it to the mine's cloud management platform 660 in real time. The mine's cloud management platform 660 supports the synchronous visualization of statistical data on a large-screen monitoring system on a PC and a mobile management app, enabling remote real-time monitoring of operational data.

[0108] Compared to the technical advantages of Embodiment 1, the system of Embodiment 3 of this application further has the following advantages: 1. Establish a local metering closed loop to eliminate signal dependence. Specifically, a three-terminal data interaction link is established: "local display on vehicle screen + offline export + GPS cloud upload." Even without satellite positioning / network signal, normal metering, data viewing, and offline export can still be achieved locally on the vehicle, forming an independent vehicle-mounted local metering closed loop. This solves the problem of excessive reliance on satellite positioning / network in existing technologies, effectively adapting to the complex and harsh working conditions of open-pit mines and ensuring the continuity and accuracy of metering work. The local storage and offline export function (which can store one month's worth of data, for example, exported via USB flash drive) can solve the problem of GPS installation being prohibited in some areas and can also be used by OEMs to understand mine conditions.

[0109] Current technologies typically rely on cloud uploads for data exchange, lacking on-board offline data export capabilities. This means that on-site verification of metering data is impossible during network failures. Furthermore, existing technologies do not establish an independent on-board metering closed loop, relying excessively on satellite positioning / network signals. Metering functionality fails when signals are weak or malfunctioning, and the lack of on-site real-time data export and verification capabilities fails to technically prevent issues such as human error reporting and data transmission distortion.

[0110] Therefore, the offline export function enables this application to be independent of GPS / network dependence. Even when the mine signal is weak or the network is down, data can still be statistically analyzed, viewed, and exported normally locally, solving the defects of existing GPS-dependent solutions, such as "strong network dependence and easy data loss". Furthermore, the offline export function meets the needs of on-site real-time verification, technically eliminating the problems of human false reporting and data distortion.

[0111] 2. The GPS module features weak network caching and breakpoint resume capabilities, ensuring data consistency between the local machine and the mine's cloud management platform. This guarantees that statistical data is not lost or tampered with in the complex satellite positioning / network environment of the mine, and allows for full traceability. Furthermore, the mine's cloud management platform supports remote display on multiple terminals, including PCs and mobile devices, catering to both on-site verification and remote management needs.

[0112] In summary, the loading and unloading frequency statistics method and system of this application addresses the metering needs of the entire operation cycle of loading, transportation, and unloading of mining dump trucks in open-pit mining scenarios. Through signal coordination judgment of the vehicle-mounted electronic control system and software algorithm design, it achieves automated and accurate identification of the operation status, real-time collection and statistics of multi-dimensional operation data, and completes multi-terminal data interaction between the vehicle-mounted local system and the mine cloud. It effectively solves industry pain points such as data distortion, strong dependence on satellite positioning / network signals, and single dimension of metering data in mining operations. It provides accurate and traceable underlying data support for mine production efficiency accounting, single-vehicle operating cost analysis, and quantitative assessment of operation tasks, and is adapted to the complex and harsh operating conditions of open-pit mines and the needs of intelligent and refined mine management.

[0113] This application also provides a machine-readable storage medium storing instructions that cause a machine to execute the loading and unloading count method of Embodiment 1 described above.

[0114] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0115] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, as well as combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0116] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0117] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0118] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0119] Memory may include non-persistent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0120] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0121] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0122] The above are merely embodiments of this application and are not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A method for counting the number of loading and unloading operations on mining vehicles, characterized in that, include: The sensor signals of the mining vehicle are acquired, along with pre-set loading start conditions, loading completion conditions, unloading lifting conditions, and unloading descent conditions based on the sensor signals. The following loading / unloading status identification process shall be executed: When the mining vehicle is in the unloading completed state corresponding to the previous loading and unloading operation and the loading start condition is met, it is determined that the mining vehicle enters the loading start state. After the mining vehicle enters the loading start state and the loading completion condition is met, it is determined that the mining vehicle has entered the loading completion state and is enabled to load and transport. After the mining vehicle is in the loading and transportation state and the unloading and lifting conditions are met, it is determined that the mining vehicle has entered the unloading and lifting state. as well as After the mining vehicle enters the unloading lifting state and the unloading lowering condition is met, it is determined that the mining vehicle is in the unloading lowering state and the unloading is completed. In response to changes in the unloading status during the loading and unloading status identification process, the number of loading and unloading operations is counted.

2. The method for counting the number of loading and unloading operations of mining vehicles according to claim 1, characterized in that, The sensor signals include vehicle speed signal, loading braking signal, cargo box lowering signal, and engine speed signal; The loading start conditions include the vehicle speed signal indicating that the vehicle is stationary, the loading brake signal being valid, and the cargo box being lowered into place signal being valid. The loading completion conditions include the vehicle speed signal indicating that the vehicle is in motion, the loading brake signal being invalid, and the cargo box being lowered into place signal being valid. The unloading and lifting conditions include a valid lifting indicator, an engine speed signal indicating engine operation, a valid loading brake signal, and an invalid cargo box lowering signal. The conditions for determining a valid lifting indicator include the cargo box lowering signal changing from valid to invalid, the loading brake signal being valid, the engine speed signal indicating engine operation, and the mining vehicle being in the loading and transportation state. The unloading and descent conditions include a valid descent indicator, an engine speed signal indicating engine operation, an invalid loading brake signal, a valid cargo box landing signal, and a vehicle speed signal indicating the vehicle is in motion. The conditions for determining that the descent indicator is valid include the cargo box landing signal changing from invalid to valid, the loading brake signal being valid, and the engine speed signal indicating engine operation.

3. The method for counting the number of loading and unloading operations of mining vehicles according to claim 1, characterized in that, The sensor signals include vehicle speed signal, loading braking signal, cargo box lowering signal, engine speed signal, and load signal; The loading start conditions include the vehicle speed signal indicating that the vehicle is stationary, the loading brake signal being valid, the cargo box falling into place signal being valid, and the load signal indicating that the load is continuously rising and reaching a first set percentage of the rated load. The loading completion conditions include the vehicle speed signal indicating that the vehicle is in motion, the loading brake signal being invalid, the cargo box falling into place signal being valid, and the load signal indicating that the load has reached a second set percentage of the rated load, wherein the second set percentage is greater than the first set percentage. The unloading and lifting conditions include a valid lifting indicator, an engine speed signal indicating engine operation, a valid loading brake signal, and an invalid cargo box lowering signal. The conditions for determining a valid lifting indicator include the cargo box lowering signal changing from valid to invalid, the loading brake signal being valid, the engine speed signal indicating engine operation, the mining vehicle being in the loading and transportation state, and the load signal indicating that the load has reached the second set ratio of the rated load. The unloading and descent conditions include a valid descent indicator, an engine speed signal indicating engine operation, an invalid loading brake signal, a valid cargo box landing signal, and a vehicle speed signal indicating the vehicle is in motion. The conditions for determining a valid descent indicator include the cargo box landing signal changing from invalid to valid, the invalid loading brake signal, an engine speed signal indicating engine operation, and the load signal indicating the load is lower than the first set percentage of the rated load.

4. The method for counting the number of loading and unloading operations of mining vehicles according to claim 1, characterized in that, The statistics on the number of loading and unloading operations include: After the mining vehicle changes from the unloading lifting state to the unloading lowering state, it is determined that a loading and unloading operation has been completed, and a preset time window is initiated. Any sensor signal acquired within the time window is determined to be an invalid trigger signal; and After the time window, a count of the number of valid loading and unloading operations is performed.

5. A controller for counting the number of loading and unloading operations on mining vehicles, characterized in that, include: Instruction memory, configured to store instructions; as well as The processor is configured to retrieve the instructions from the instruction memory and, when executing the instructions, to implement the loading / unloading count method according to any one of claims 1 to 4.

6. The controller according to claim 5, characterized in that, The controller is the vehicle control unit (VCU) of the mining vehicle.

7. A system for counting the number of loading and unloading operations of mining vehicles, characterized in that, include: Original vehicle sensor group, used to collect various sensor signals from mining vehicles; The controller according to claim 5 or 6 is used to acquire the sensor signal to perform loading and unloading count statistics; as well as Ferroelectric memory is configured to store one or more of the following statistics: In the loading and unloading status identification process, the loading start status, loading completion status, loading and transportation status, unloading lifting status, unloading lowering status and unloading completion status are determined or enabled in real time. The number of loading and unloading operations, vehicle mileage, and / or fuel consumption are counted within a preset period. as well as Time information related to loading and unloading operations.

8. The mining vehicle loading and unloading frequency statistics system according to claim 7, characterized in that, The loading and unloading frequency statistics system also includes an on-board display terminal, a GPS module, and a cloud management platform; The controller transmits the statistical data to the vehicle display terminal via the vehicle CAN bus; and / or the controller transmits the statistical data to the cloud management platform via the GPS module, wherein the GPS module transmits the statistical data directly or via a local cache module in response to different network signal strengths.

9. The mining vehicle loading and unloading frequency statistics system according to claim 7, characterized in that, The original vehicle sensor group includes any and more of the following sensors: A proximity switch or tilt sensor is used to detect when the cargo box has landed. Vehicle speed sensor, used to detect vehicle speed signals; Loaded brake sensor, used to detect loading brake signal; An engine speed sensor is used to detect engine speed signals associated with cargo box lifting; Load cells are used to detect load signals; as well as A fuel level sensor is used to detect fuel level signals.

10. A machine-readable storage medium, characterized in that, The machine-readable storage medium stores instructions for causing the machine to perform the loading and unloading count method according to any one of claims 1 to 4.

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