A forklift electrical component monitoring method and system

Abstract

The multiple embodiments of this specification relate to a method and system for monitoring electrical components of a forklift. The method includes: setting a vibration sensor on the chassis and wiring harness of the forklift; setting an infrared camera to monitor the temperature of the wiring harness connector; setting a camera in the forklift cab to capture the instrument panel image and the image in front of the forklift; setting a controller, the controller is connected to the vibration sensor, the infrared camera and the camera; the controller obtains the operating time of the forklift according to the instrument panel image and the image in front of the forklift; the operating time, the temperature of the wiring harness connector, the chassis vibration curve, and the wiring harness vibration curve are input into a pre-configured fault prediction model to obtain a wiring harness fault prediction result.

Description

Technical Field

[0001] Multiple embodiments of the present specification relate to, in particular, a method and system for monitoring electrical components of a forklift. Background Art

[0002] Under heavy working conditions, some parts of forklifts are more prone to wear or damage due to frequent use and high loads. For example, frequent movement and carrying of heavy objects will lead to increased tire wear, especially when operating on uneven ground. It also includes components such as oil pumps, control valves, and pipes. These components are subject to huge pressure changes during the lifting and lowering of goods, and may leak or other failures after long-term use. Frequent starting and stopping and emergency braking will cause great wear on brake pads. Therefore, fault monitoring devices are set for tires, hydraulic systems, and brake systems. On the other hand, electrical components such as wires and connectors may cause short circuits or poor contact due to vibration, moisture, etc. Since the probability of failure in the electrical system is relatively low, and there is usually a situation of self-recovery. Therefore, there is currently insufficient fault monitoring for the electrical system. When the electrical system fails and cannot be eliminated in a short time, it will pose a serious threat to the normal operation and safety of the forklift. Therefore, it is necessary to study the fault monitoring technology for the electrical system. Summary of the invention

[0003] Multiple embodiments of this specification describe a forklift electrical component monitoring method and system.

[0004] In a first aspect, an embodiment of the present specification provides a method for monitoring electrical components of a forklift, comprising the steps of:

[0005] Vibration sensors are installed on the forklift chassis and wiring harness;

[0006] Set up an infrared camera to monitor the temperature of the wiring harness connector;

[0007] Set up a camera in the forklift cab to capture images of the dashboard and the front of the forklift;

[0008] Setting a controller, wherein the controller is connected to the vibration sensor, the infrared camera and the camera;

[0009] The controller obtains the running time of the forklift according to the instrument panel image and the image in front of the forklift;

[0010] The running time, the temperature of the wiring harness connector, the chassis vibration curve, and the wiring harness vibration curve are input into a pre-configured fault prediction model to obtain a wiring harness fault prediction result.

[0011] In the second aspect, an embodiment of the present specification provides a forklift electrical component monitoring system, including multiple vibration sensors, infrared cameras, cameras and controllers, wherein the multiple vibration sensors are respectively arranged on the forklift chassis and the wiring harness, the infrared camera monitors the temperature of the wiring harness connector, the camera is arranged in the forklift cab, and takes images of the dashboard and the front of the forklift. The controller is connected to the vibration sensors, infrared cameras and cameras, and the controller obtains the operating time of the forklift based on the dashboard image and the front of the forklift. The controller inputs the operating time, the temperature of the wiring harness connector, the chassis vibration curve, and the wiring harness vibration curve into a pre-configured fault prediction model to obtain a wiring harness fault prediction result.

[0012] The beneficial effects brought by the technical solutions provided by some embodiments of this specification include at least:

[0013] In multiple embodiments of the present specification, a forklift electrical component monitoring method is provided, which collects temperature, image and vibration data by setting up an infrared camera, a camera and a vibration sensor, obtains characteristic data that characterizes the wiring harness failure after data processing, and establishes a wiring harness failure model to predict the wiring harness failure, thereby realizing the monitoring of wiring harness failures in the forklift electrical system, making up for the problem that the prior art lacks fault monitoring of the wiring harness, an important electrical component, and improving the safety of forklift operation.

[0014] Other features and advantages of the various embodiments of the present specification will be further disclosed in the following detailed description and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions in the embodiments of this specification, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this specification. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0016] Figure 1 A schematic flow chart of a forklift electrical component monitoring method provided in an embodiment of this specification.

[0017] Figure 2 This is a schematic diagram of the installation position of the vibration sensor provided in the embodiment of this specification.

[0018] Figure 3 A schematic diagram of a dashboard image provided in an embodiment of this specification.

[0019] Figure 4 Schematic diagram of a forklift electrical component monitoring system provided in an embodiment of this specification.

[0020] Figure 5A schematic diagram of a user interface provided in an embodiment of this specification.

[0021] Figure 6 This is a schematic diagram of a method for obtaining the operating time of a forklift provided in an embodiment of this specification.

[0022] Figure 7 A schematic diagram of the preprocessing method provided in the embodiments of this specification.

[0023] Figure 8 This is a schematic diagram of the structure of the detection platform provided in the embodiments of this specification. DETAILED DESCRIPTION

[0024] The following is an explanation and description of the technical solutions of the embodiments of this specification in conjunction with the drawings of the embodiments of this specification, but the following embodiments are only preferred embodiments of this specification, not all. Based on the embodiments in the implementation mode, other embodiments obtained by those skilled in the art without creative work are all within the scope of protection of this specification.

[0025] The terms "first", "second", "third", etc. in the description and claims of this specification and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally includes steps or units that are not listed, or optionally includes other steps or units inherent to these processes, methods, products or devices.

[0026] In the following description, terms such as "inside", "outside", "up", "down", "left", "right", etc. that indicate directions or positional relationships are only used to facilitate the description of the embodiments and simplify the description, and do not indicate or imply that the device or element referred to must have a specific direction, be constructed and operated in a specific direction, and therefore should not be understood as a limitation of this specification.

[0027] The data involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection of relevant data complies with the relevant laws, regulations and standards of relevant countries and regions.

[0028] Before describing the technical solution in this specification, an introduction is given to the application scenarios and related technologies of the technical solution.

[0029] Forklifts are an important type of industrial handling equipment, widely used in warehouses, factories, logistics centers and other places. Forklifts can efficiently carry and load and unload goods, effectively improve work efficiency and reduce labor costs. And they can handle heavy or large-volume goods. Forklifts carry and carry goods through the forks set in front. The forks can move up and down along the fork frame through the hydraulic system to achieve loading and unloading and handling of goods. The flexibility of forklifts enables them to operate in narrow spaces, and their diverse types (such as electric and internal combustion engine) meet the needs of different working environments. For example, stainless steel electric forklifts with high sanitation requirements are commonly used in the food processing industry; while in outdoor operations, durable diesel-powered forklifts are more preferred. In addition, with the development of technology, modern forklifts are also equipped with advanced safety systems, such as automatic braking functions and anti-collision sensors to ensure safety during operation.

[0030] The instrument panel of a forklift is used to display key status information of the vehicle. Usually, various important parameters of the forklift during operation are displayed through indicator lights, instruments and display screens. The instrument panel 30 of a forklift usually includes a speedometer that displays the current driving speed, an engine tachometer (for internal combustion engine forklifts), a battery power indicator (for electric forklifts), a fuel gauge 21 that displays the amount of fuel in the tank, a water temperature gauge 24 that displays the temperature of the engine coolant, a working time indicator 25 that records the cumulative working time of the engine, a fault indicator light that lights up when a system abnormality is detected, a turn signal 22 that displays the status of the left and right turn signals, and a reverse buzzer switch control. Some models of forklifts may also be equipped with more complex electronic information systems such as LCD screens, which can provide more detailed data analysis and diagnostic information, such as a fault prompt area 23 that can prompt detected faults. It even supports remote monitoring by connecting external devices through wireless technologies such as Bluetooth.

[0031] The wiring harness 10 in the forklift electrical system is a key component that connects various electrical devices and control units, and is used to transmit power and signals. The wiring harness 10 is usually composed of wires, connectors, protective sleeves, etc. The wiring harness 10 is mainly used to provide power for lighting fixtures, instrument panels 30, starters, generators, battery chargers, etc., and to achieve communication between control systems. Failure of the wiring harness 10 will cause communication or power supply failures between various systems of the forklift, directly affecting the operation of the forklift. During the operation of the forklift, the wiring harness 10 may encounter a variety of fault conditions, common faults include short circuits, open circuits, poor contact, etc. These problems may cause the vehicle to fail to start, the lights to not light up, and the instrument display to be abnormal. There are various reasons for the induction of faults. For example, long-term exposure to harsh working environments (such as high temperature, humidity, or places full of corrosive substances) will cause the wiring harness 10 to age faster. Improper operating habits, such as frequent pulling of wires, may also damage the wiring harness 10. In addition, insufficient maintenance and failure to promptly detect and deal with worn or damaged parts will also increase the possibility of failures. In order to reduce the failure of the wiring harness 10, it is necessary to regularly check the status of the forklift's electrical system and replace damaged parts in time.

[0032] Among them, the temperature and humidity of the forklift's working environment are easily felt. The wear or damage of the wiring harness 10 is caused by the vibration of the forklift operation, and vibration is an inevitable result of the normal operation of the forklift. Therefore, the wear and severity caused by vibration are very difficult to detect. The failure of the wiring harness 10 due to wear is often unexpected by the user and directly leads to the operation failure of the forklift. Not only will it cause an unexpected stagnation in the production plan, but the troubleshooting of electrical faults is also very difficult. It is usually necessary to detect multiple parts of the electrical system, and it is inevitable to disassemble some components during the troubleshooting process to view the internal wiring harness 10, connectors, and electrical components. It is not only time-consuming and labor-intensive, but also has relatively high requirements on the professional level of the troubleshooter. Therefore, it is necessary to pay attention to and study the fault monitoring technology of the electrical system and electrical components of the forklift.

[0033] This manual provides a method for monitoring the electrical components of a forklift. Figure 1 , including the steps of:

[0034] Step S101) Vibration sensors 11 are installed on the forklift chassis and the wiring harness 10. The vibration sensor 11 installed on the forklift chassis can detect the vibration of the forklift operation. Because the wiring harness 10 is attached to the chassis, this part of the vibration will be superimposed on the wiring harness 10. However, the wiring harness 10 is not completely fixed on the chassis, so the wiring harness 10 will have more vibration. Installing vibration sensors 11 on the wiring harness 10, please refer to the attached Figure 2, the vibration of the wire harness 10 can be collected. There are multiple wire harnesses 10 in the forklift, and the vibration of different positions of a single wire harness 10 is also different. And the installation of the vibration sensor 11 itself will also change the vibration characteristics of the wire harness 10. However, as long as the vibration data of the wire harness 10 is collected at any position of the wire harness 10, even if the vibration characteristics of the wire harness are changed due to the installation of the vibration sensor 11. Because, in this embodiment, it is only necessary to analyze the vibration of the wire harness and obtain the possibility of wire harness failure, and the collection integrity of the vibration characteristics of the wire harness is relatively low. As long as the vibration sensor 11 can collect the corresponding vibration data when the wire harness 10 has a large vibration or a new vibration frequency, it is sufficient. Preferably, each wire harness is installed with a vibration sensor 11. On the other hand, it is also a feasible solution to install the vibration sensor 11 on the main wire harness and the wire harness with more obvious vibration, and not install other wire harnesses. Step S102) Set an infrared camera to monitor the temperature of the wire harness connector. The temperature of the wire harness connector can be collected by the infrared camera, and the selection of the infrared camera and the process of obtaining the temperature from the infrared image can be carried out by the technology already disclosed in the art.

[0035] Step S103) A camera is installed in the forklift cab to capture the image of the instrument panel and the image in front of the forklift. Figure 3 The forklift dashboard 30 is provided with a working time indicator 25. The working time indicator 25 can be used to obtain the running time of the forklift after starting this time by using the end time of the last start of the forklift and the current time. However, the working time indicator 25 shows the working time of the engine when the forklift is only started and does not move or load or unload goods. This state is the idle running state of the forklift.

[0036] Step S104) Set up a controller, which is connected to the vibration sensor 11, the infrared camera and the camera. Figure 4 , which is a schematic diagram of the controller connection of this embodiment. The selection of the controller can be carried out using the disclosed technology in the art. On the other hand, in another embodiment, the controller can also upload relevant data to a preset server 31 through a communication module, and the server 31 executes the subsequent steps of the method, and sends the finally obtained wiring harness fault prediction result to the controller, and the controller controls the connected alarm device 32 to sound an alarm. Or it is just temporarily stored in the server 31 or the controller, and the terminal device 33 held by the user is connected to the controller or connected to the server 31 to actively pull the wiring harness fault prediction result. The terminal device 33 and the controller can establish a connection through Bluetooth, WIFI, ZigBee, NFC, LoRaWAN, RS485 or other similar disclosed communication connection methods.

[0037] The terminal device 33 is provided with a user interface for viewing and displaying the wiring harness fault prediction results. Figure 5 . The user interface can be run on the terminal device 33 in the form of a browser, or in the form of an independent application (APP), etc. The specific display form of the user interface is not limited here. The server 31 involved in this application can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (Content Delivery Network, CDN), and big data and artificial intelligence platforms. The terminal device 33 can be a smart phone, a tablet computer, a laptop, a PDA, a personal computer, a smart speaker, a smart TV, a smart watch, a car device, a wearable device, etc., but is not limited to this. The terminal device 33 and the server 31 can be directly or indirectly connected by wired or wireless communication, which is not limited in this application. The number of servers 31 and terminal devices 33 is also not limited. The solution provided in this application can be completed independently by the terminal device 33, can also be completed independently by the server 31, or can be completed by the terminal device 33 and the server 31 in cooperation. This application does not make any specific limitations on this.

[0038] Step S105) The controller obtains the running time of the forklift according to the dashboard image and the image in front of the forklift.

[0039] For details, please refer to the attached Figure 6 The method for the controller to obtain the running time of the forklift according to the instrument panel image and the front image of the forklift includes:

[0040] Step S201) Identify the working time display area in the instrument panel image, identify the working time displayed in the working time display area, and obtain the displayed working time; the working time displayed by the working time indicator 25 in the instrument panel image can be identified from the image by using the publicly available image recognition technology. According to the data displayed by the working time indicator 25 at the time of this startup and at the current moment, the working time of the engine after this startup, that is, the displayed working time, can be obtained.

[0041] Step S202) Based on the image in front of the forklift, identify whether the forklift is moving and whether the forklift is in motion; by using the machine vision technology disclosed in the art, it is possible to identify whether the forklift is moving and whether the forklift is in motion. Exemplarily, an area of ​​the image in front of the forklift is manually marked, and when the image of the area changes, it indicates that the forklift is moving. An area of ​​the moving range of the forklift in the image in front of the forklift is manually marked, and when the image of the area changes, it indicates that the forklift is in motion.

[0042] Step S203) marking the time during which the forklift does not move and the fork does not act, and obtaining the rejection time;

[0043] Step S204) Subtract the rejection time from the displayed working time to obtain the forklift operating time.

[0044] After deducting the eliminated time from the displayed working time, the forklift operating time is obtained. The forklift operating time is used as feature data about the time for subsequent processing, which has the advantage of making the subsequent related models have higher accuracy.

[0045] Step S106) The running time, the temperature of the harness connector, the chassis vibration curve, and the harness vibration curve are input into a pre-configured fault prediction model to obtain a harness fault prediction result.

[0046] Among them, the method for configuring a fault prediction model includes: preprocessing the operating time, the temperature of the wiring harness connector, the chassis vibration curve, and the wiring harness vibration curve, and associating the corresponding fault types after preprocessing to obtain sample data; establishing and using the samples to train a machine learning model; and obtaining a fault prediction model based on the machine learning model.

[0047] The machine learning model can adopt the machine learning model disclosed in the art. For example, decision trees, random forest models, support vector machines, neural network models, etc. can be used. Decision tree is an intuitive classification and regression method that segments data through a series of rules. Each internal node represents a test on an attribute, each branch represents a test result, and each leaf node represents a category or output value. Decision trees are easy to understand and explain and are applicable to various types of data sets. Random forests are composed of multiple decision trees. Each decision tree is trained based on a random subsample of the data set and ultimately makes a prediction. It can improve prediction accuracy and reduce the risk of overfitting. The neural network model consists of multiple layers of interconnected artificial neurons. Deep learning is a branch of neural networks that contains many hidden layers and can automatically extract complex features from data. Recurrent neural networks are suitable for sequence data such as text or time series analysis.

[0048] For details, please refer to the attached Figure 7The method for preprocessing the running time, the temperature of the wiring harness connector, the chassis vibration curve, and the wiring harness vibration curve includes:

[0049] Step S301) According to the preset duration interval and duration interval label, the operation duration is converted into the corresponding duration interval label. Changing the operation duration into the duration interval label can simplify the input data and reduce the complexity of the data that the fault prediction model needs to process.

[0050] Step S302) According to the preset temperature range and temperature range label, the temperature of the wiring harness connector is converted into a corresponding temperature range label. Changing the temperature into a temperature range label can simplify the input data and reduce the complexity of the data that the fault prediction model needs to process.

[0051] Step S303) Subtract the chassis vibration curve from the wiring harness vibration curve to obtain a difference vibration curve. Eliminate the chassis vibration from the wiring harness vibration to obtain vibration-related data of the wiring harness 10 itself, thereby eliminating the interference of the chassis vibration and improving the accuracy of wiring harness fault prediction.

[0052] Step S304) Acquire the moment when the amplitude of the chassis vibration curve exceeds a preset threshold, and obtain the harness vibration curve of a preset time length before and after the moment.

[0053] Step S305) Compare the harness vibration curves of a preset time length before and after the moment, and if the difference exceeds a preset second threshold, mark the preset time length before and after.

[0054] Step S306) obtaining the difference vibration curve within the corresponding time according to the preset time length before and after the mark.

[0055] Step S307) extracts the index value of the difference vibration curve according to several preset indexes to obtain several characteristic values. Although the chassis vibration does not directly reflect the characteristics of the wire harness vibration, the moment when the amplitude of the chassis vibration exceeds the preset threshold still has an impact on the occurrence of the wire harness failure. This embodiment incorporates this part of data into the input of the fault prediction model to further improve the accuracy of the wire harness failure prediction. This part of the characteristic data is extracted through four steps of step S304) and step S307). Specifically, the wire harness vibration curve of the preset time length before and after the moment when the amplitude of the chassis vibration curve exceeds the preset threshold is obtained. When this vibration of the chassis does not cause a significant change in the wire harness vibration (significant change refers to the difference of the wire harness vibration curve of the preset time length before and after the moment exceeds the preset second threshold), no processing is performed. When this vibration of the chassis causes a significant change in the wire harness vibration, the preset time length before and after is marked. Then the corresponding difference vibration curve is obtained according to the marked time. The data of the indicators of the difference vibration curve are extracted as the input of the fault prediction model, which can capture one or more of several preset indicators including peak value, root mean square, average value, kurtosis, skewness, standard deviation, zero crossing rate, frequency and amplitude.

[0056] On the other hand, as an improved implementation, please refer to the attached Figure 8 , a special testing platform 40 and a testing tool 41 are used to test the vibrations that the instrument panel 30 and the wiring harness connected to the instrument panel 30 can withstand, so as to obtain the vibration amplitude that the instrument panel 30 and the wiring harness connected to the instrument panel 30 can withstand. Specifically, the instrument panel 30 is installed on the testing tool 41, and the testing tool 41 can power the instrument panel 30 and can exchange data with the control device on the instrument panel 30, so that the instrument panel displays various set working states. At the same time, the testing tool 41 can rotate and can generate vibrations with controllable amplitude. When the testing tool rotates, the instrument panel 30 can be transferred into the dark grid set by the testing platform 40, so that the display content of the instrument panel 30 can be visually identified in the dark grid, and compared with the set working state, to detect whether the instrument panel 30 has a fault. When the cable used to set the working state is directly connected to the instrument panel 30, it is used to detect whether the instrument panel 30 is normal. When the cable connection harness is used to set the working state, the instrument panel 30 is connected through the harness, and it is possible to detect whether the harness itself is faulty (such as damaged or broken) and whether the connection between the harness and the instrument panel 30 is reliable. Set the cable connection harness in the working state to vibrate a certain amplitude before rotating into the dark compartment, and then perform the test. Repeat continuously, and change the amplitude of the vibration during the repetition until the instrument panel 30 fails, and the amplitude of the vibration that the harness connected to the instrument panel 30 can withstand can be obtained. This amplitude is used as a reference when setting the preset threshold in the setting step S304). Exemplarily, it can be used directly as the preset threshold, or it can be used as the preset threshold after being multiplied by a coefficient.

[0057] By comparing the chassis vibration and the vibration of the front and rear wiring harnesses, the corresponding index data is obtained as the input of the fault prediction model to further improve the accuracy of wiring harness fault prediction.

[0058] Step S308) The duration interval label, the temperature interval label and the plurality of characteristic values ​​are taken as the result of preprocessing the operation duration, the temperature of the harness connector, the chassis vibration curve and the harness vibration curve.

[0059] Accordingly, the method of inputting the operating time, the temperature of the wiring harness connector, the chassis vibration curve, and the wiring harness vibration curve into a preconfigured fault prediction model includes:

[0060] According to the preset duration interval and duration interval label, the running time is converted into a corresponding duration interval label;

[0061] According to the preset temperature range and temperature range label, convert the temperature of the wiring harness connector into a corresponding temperature range label;

[0062] Subtracting a chassis vibration curve from the wiring harness vibration curve to obtain a difference vibration curve;

[0063] Acquire the moment when the amplitude of the chassis vibration curve exceeds a preset threshold, and obtain the harness vibration curve of a preset time length before and after the moment;

[0064] Comparing the harness vibration curves of a preset time length before and after the moment, if the difference exceeds a preset second threshold, marking the preset time length before and after;

[0065] Obtain the difference vibration curve within the corresponding time according to the preset time length before and after the mark;

[0066] According to a plurality of preset indices, the index values ​​of the difference vibration curve are extracted to obtain a plurality of characteristic values;

[0067] The time interval label, temperature interval label and several characteristic values ​​are input into a pre-configured fault prediction model.

[0068] On the other hand, the present specification provides a forklift electrical component monitoring system, including multiple vibration sensors 11, infrared cameras, cameras and controllers, wherein the multiple vibration sensors 11 are respectively arranged on the forklift chassis and the wiring harness, the infrared camera monitors the temperature of the wiring harness connector, the camera is arranged in the forklift cab, and takes the instrument panel image and the front image of the forklift, the controller is connected to the vibration sensor 11, the infrared camera and the camera, the controller obtains the running time of the forklift according to the instrument panel image and the front image of the forklift, and the controller inputs the running time, the temperature of the wiring harness connector, the chassis vibration curve, and the wiring harness vibration curve into a pre-configured fault prediction model to obtain the wiring harness fault prediction result.

[0069] Preferably, when the controller obtains the running time of the forklift according to the instrument panel image and the image in front of the forklift, the controller performs the following steps:

[0070] Identify a working time display area in the instrument panel image, identify the working time displayed in the working time display area, and obtain the displayed working time;

[0071] According to the image in front of the forklift, identifying whether the forklift is moving and identifying whether the forks are in motion;

[0072] Mark the time during which the forklift does not move and the fork does not act, and obtain the rejection time;

[0073] The displayed working time is subtracted from the rejection time to obtain the forklift operating time.

[0074] Preferably, when the vibration sensor 11 is disposed on the wire harness 10, the wire harness 10 is fastened with a plurality of cable ties, and then the vibration sensor 11 is disposed on one of the cable ties.

[0075] Preferably, the vibration sensor 11 disposed on the forklift chassis is disposed at the most concentrated part of the wire harness 10. The technical solution described in this specification can also be implemented by obtaining a single wire harness vibration curve through a vibration sensor 11. When multiple vibration sensors 11 are used to collect and obtain multiple wire harness vibration curves, the technical solution described in this specification is executed for each wire harness vibration curve, and finally the wire harness fault prediction results obtained by the multiple wire harness vibration curves can be obtained, and these wire harness fault prediction results are combined as the final wire harness fault prediction result.

[0076] The embodiments described above are merely preferred embodiments of this specification and are not intended to limit the scope of this specification. Without departing from the design spirit of this specification, various modifications and improvements made to the technical solutions of this specification by ordinary technicians in this field should fall within the scope of protection determined by the claims of this specification.

Claims

1. A method for monitoring electrical components of a forklift, characterized in that: Includes steps: Vibration sensors are installed on the forklift chassis and wiring harness; Set up an infrared camera to monitor the temperature of the harness connector; Set up a camera in the forklift cab to capture images of the dashboard and the front of the forklift; Setting a controller, wherein the controller is connected to the vibration sensor, the infrared camera and the camera; The controller obtains the running time of the forklift according to the instrument panel image and the image in front of the forklift; The running time, the temperature of the wiring harness connector, the chassis vibration curve, and the wiring harness vibration curve are input into a pre-configured fault prediction model to obtain a wiring harness fault prediction result.

2. A forklift electrical component monitoring method according to claim 1, characterized in that: The method for the controller to obtain the running time of the forklift according to the instrument panel image and the front image of the forklift includes: Identify a working time display area in the instrument panel image, identify the working time displayed in the working time display area, and obtain the displayed working time; According to the image in front of the forklift, identifying whether the forklift is moving and identifying whether the forks are in motion; Mark the time during which the forklift does not move and the fork does not act, and obtain the rejection time; The displayed working time is subtracted from the rejection time to obtain the forklift operating time.

3. A forklift electrical component monitoring method according to claim 1 or 2, characterized in that: Methods for configuring a fault prediction model include: Preprocessing the running time, the temperature of the harness connector, the chassis vibration curve, and the harness vibration curve, and associating the preprocessed fault types with each other to obtain sample data; Establish and use the samples to train a machine learning model; A fault prediction model is obtained according to the machine learning model.

4. A forklift electrical component monitoring method according to claim 3, characterized in that: The method for preprocessing the running time, the temperature of the wiring harness connector, the chassis vibration curve, and the wiring harness vibration curve comprises: According to the preset duration interval and duration interval label, the running time is converted into a corresponding duration interval label; According to the preset temperature range and temperature range label, convert the temperature of the wiring harness connector into a corresponding temperature range label; Subtracting a chassis vibration curve from the wiring harness vibration curve to obtain a difference vibration curve; Acquire the moment when the amplitude of the chassis vibration curve exceeds a preset threshold, and obtain the harness vibration curve of a preset time length before and after the moment; Comparing the harness vibration curves of a preset time length before and after the moment, if the difference exceeds a preset second threshold, marking the preset time length before and after; Obtain the difference vibration curve within the corresponding time according to the preset time length before and after the mark; According to a plurality of preset indices, the index values ​​of the difference vibration curve are extracted to obtain a plurality of characteristic values; The duration interval label, the temperature interval label and the plurality of characteristic values ​​are taken as the result of preprocessing the operation duration, the temperature of the harness connector, the chassis vibration curve and the harness vibration curve.

5. A forklift electrical component monitoring method according to claim 4, characterized in that: The preset indicators include one or more of peak value, root mean square, average value, kurtosis, skewness, standard deviation, zero crossing rate, frequency and amplitude.

6. A forklift electrical component monitoring method according to claim 4, characterized in that: The method of inputting the operating time, the temperature of the wiring harness connector, the chassis vibration curve, and the wiring harness vibration curve into a pre-configured fault prediction model includes: According to the preset duration interval and duration interval label, the running time is converted into a corresponding duration interval label; According to the preset temperature range and temperature range label, convert the temperature of the wiring harness connector into a corresponding temperature range label; Subtracting a chassis vibration curve from the wiring harness vibration curve to obtain a difference vibration curve; Acquire the moment when the amplitude of the chassis vibration curve exceeds a preset threshold, and obtain the harness vibration curve of a preset time length before and after the moment; Comparing the harness vibration curves of a preset time length before and after the moment, if the difference exceeds a preset second threshold, marking the preset time length before and after; Obtain the difference vibration curve within the corresponding time according to the preset time length before and after the mark; According to a plurality of preset indices, the index values ​​of the difference vibration curve are extracted to obtain a plurality of characteristic values; The time interval label, temperature interval label and several characteristic values ​​are input into a pre-configured fault prediction model.

7. A forklift electrical component monitoring system, characterized in that: The invention comprises a plurality of vibration sensors, an infrared camera, a camera and a controller. The plurality of vibration sensors are respectively arranged on a forklift chassis and a wiring harness. The infrared camera monitors the temperature of the wiring harness connector. The camera is arranged in a forklift cab to take an image of a dashboard and an image in front of the forklift. The controller is connected to the vibration sensors, the infrared camera and the camera. The controller obtains the operation time of the forklift according to the image of the dashboard and the image in front of the forklift. The controller inputs the operation time, the temperature of the wiring harness connector, the chassis vibration curve and the wiring harness vibration curve into a pre-configured fault prediction model to obtain a wiring harness fault prediction result.

8. A forklift electrical component monitoring system according to claim 7, characterized in that: When the controller obtains the running time of the forklift according to the instrument panel image and the image in front of the forklift, the controller performs the following steps: Identify a working time display area in the instrument panel image, identify the working time displayed in the working time display area, and obtain the displayed working time; According to the image in front of the forklift, identifying whether the forklift is moving and identifying whether the forks are in motion; Mark the time during which the forklift does not move and the fork does not act, and obtain the rejection time; The displayed working time is subtracted from the rejection time to obtain the forklift operating time.

9. A forklift electrical component monitoring system according to claim 7 or 8, characterized in that: When the vibration sensor is arranged on the wire harness, the wire harness is fastened with a plurality of cable ties, and then the vibration sensor is arranged on one of the cable ties.

10. A forklift electrical component monitoring system according to claim 7 or 8, characterized in that: The vibration sensor arranged on the forklift chassis is arranged at the location where the wire harness is most concentrated.

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