Electric seat abnormity detection method and device

Abstract

The invention relates to the technical field of automobile data processing, and discloses an electric seat abnormity detection method and device, and the method comprises the steps: monitoring the starting state of an electric seat in real time; when the starting state of the electric seat is a heating state, calculating a temperature rising speed within first preset time; if the temperature rising speed is smaller than the preset temperature rising speed threshold value, it is judged that heating of the electric seat is abnormal; when the starting state of the electric seat is a refrigeration state, calculating a cooling speed and a wind speed noise correlation coefficient within a second preset time; if the cooling speed is smaller than a preset cooling speed threshold value or the wind speed noise correlation coefficient is out of a preset correlation standard range, it is judged that refrigeration of the electric seat is abnormal. The real-time performance of data monitoring is improved, the accuracy of monitored data is improved, and the riding comfort of passengers is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of automobile data processing, and in particular to a method and a device for detecting abnormality of an electric seat. Background Art

[0002] As consumers' requirements for car interior comfort continue to increase, ventilation and heating functions of car seats have become standard features of high-end cars and SUVs. Modern car seat ventilation systems usually use fans to draw air from the seats and circulate it to achieve rapid cooling; while the heating system heats the seat surface through resistance wires or thermoelectric materials to provide a warm riding experience. In recent years, automakers have continued to explore new technologies, such as intelligent temperature control and personalized settings, to further improve seat comfort.

[0003] However, existing technologies often monitor the ventilation effect or heating effect of the car separately, lacking comprehensive consideration, resulting in an imperfect data collection and feedback mechanism. In addition, when the ventilation function of the car seat is activated, the fan will generate noise, and the existing technology does not have the ability to monitor and feedback the noise level in real time, which affects the occupant's experience. Summary of the invention

[0004] The present invention provides an electric seat abnormality detection method and device, which improves the real-time performance of data monitoring, improves the accuracy of monitoring data, and improves the riding comfort of passengers.

[0005] In order to solve the above technical problems, the present invention provides a method for detecting abnormality of an electric seat, comprising:

[0006] Real-time monitoring of the activation status of the electric seat;

[0007] When the start-up state of the electric seat is a heating state, calculating a heating rate within a first preset time;

[0008] If the heating speed is less than a preset heating speed threshold, it is determined that the electric seat is abnormally heated;

[0009] When the start-up state of the electric seat is the cooling state, calculating the cooling speed and the wind speed noise correlation coefficient within the second preset time;

[0010] If the cooling speed is less than a preset cooling speed threshold or the wind speed noise correlation coefficient is outside a preset correlation standard range, it is determined that the electric seat cooling is abnormal.

[0011] The present invention monitors the start-up state of the electric seat in real time. When the start-up state of the electric seat is a heating state, the temperature rise rate of the electric seat is calculated in real time, and whether the electric seat has abnormal heating is determined according to the temperature rise rate of the electric seat; when the start-up state of the electric seat is a cooling state, the temperature drop rate of the electric seat and the wind speed noise correlation coefficient are calculated in real time, and whether the electric seat has abnormal cooling is determined according to the temperature drop rate of the electric seat and the wind speed noise correlation coefficient. The present invention can monitor the heating and cooling anomalies of the electric seat in real time, thereby improving the real-time performance of data monitoring; different indicators are used to determine whether the electric seat is abnormal according to different start-up states of the electric seat, thereby improving the accuracy of the monitoring data and thus improving the riding comfort of the occupants.

[0012] Furthermore, when the start-up state of the electric seat is the heating state, the temperature rise rate within the first preset time is calculated, specifically:

[0013] When the start state of the electric seat is the heating state, the seat temperature and the ambient temperature within a first preset time are collected;

[0014] Calculating temperature difference data within the first preset time based on the seat temperature and the ambient temperature within the first preset time;

[0015] Based on the duration of the first preset time, the temperature rising speed within the first preset time is calculated according to the temperature difference data within the first preset time.

[0016] When the start-up state of the electric seat is the heating state, the present invention calculates temperature difference data by collecting seat temperature and ambient temperature, and then calculates the heating rate of the electric seat based on the temperature difference data. When calculating the heating rate of the electric seat, not only the seat temperature but also the ambient temperature is collected. The heating rate is calculated while considering environmental factors, which can improve the accuracy of the data.

[0017] Furthermore, when the start-up state of the electric seat is the cooling state, calculating the cooling speed and the wind speed noise correlation coefficient within the second preset time includes:

[0018] When the start state of the electric seat is the cooling state, the seat temperature and the ambient temperature within the second preset time are collected;

[0019] Calculating temperature difference data within the second preset time based on the seat temperature and the ambient temperature within the second preset time;

[0020] Based on the duration of the second preset time, the cooling speed within the preset time is calculated according to the temperature difference data within the second preset time.

[0021] When the startup state of the electric seat is the cooling state, the present invention calculates the temperature difference data by collecting the seat temperature and the ambient temperature, and then calculates the heating rate of the electric seat based on the temperature difference data. When calculating the cooling rate of the electric seat, not only the seat temperature but also the ambient temperature is collected. The cooling rate is calculated while considering the environmental factors, which can improve the accuracy of the data.

[0022] Furthermore, when the start-up state of the electric seat is the cooling state, calculating the cooling speed and the wind speed noise correlation coefficient within the second preset time includes:

[0023] When the start-up state of the electric seat is the cooling state, the original wind speed data and the original noise data within the second preset time are synchronously collected;

[0024] Performing data standardization processing on the original wind speed data and the original noise data respectively to form first wind speed data and first noise data;

[0025] A correlation analysis is performed on the first wind speed data and the first noise data to obtain a wind speed noise correlation coefficient.

[0026] When calculating the wind speed noise correlation coefficient, the present invention synchronously collects original wind speed data and original noise data, and performs data standardization processing on the original wind speed data and the original noise data, thereby generating first wind speed data and first noise data corresponding to each other, thereby improving the accuracy of correlation analysis.

[0027] Furthermore, the correlation analysis is performed on the first wind speed data and the first noise data to obtain a wind speed noise correlation coefficient, which is specifically:

[0028] Calculate the wind speed mean based on the first wind speed data;

[0029] Calculate a noise mean based on the first noise data;

[0030] Performing data matching on the first wind speed data and the first noise data to form several groups of observation data;

[0031] Based on the wind speed mean, the noise mean and several groups of observation data, a Pearson correlation analysis is performed to obtain a wind speed noise correlation coefficient.

[0032] Furthermore, when the start-up state of the electric seat is the cooling state, the original wind speed data and the original noise data within the second preset time are synchronously collected, and further includes:

[0033] Get the vent area of ​​the power seat;

[0034] Calculating the ventilation volume within the second preset time based on the ventilation opening area and the original wind speed data within the second preset time;

[0035] If the ventilation volume within the second preset time is greater than the preset ventilation volume threshold, it is determined that the cooling of the electric seat is abnormal.

[0036] The present invention obtains the vent area of ​​the electric seat, and can calculate the ventilation volume of the electric seat according to the collected original wind speed data and the vent area. The ventilation volume can also be used as a judgment condition for abnormal cooling of the electric seat, thereby improving the real-time performance of seat abnormality detection and further improving the riding comfort of the occupants.

[0037] Further, after determining that the electric seat cooling is abnormal, the method further includes:

[0038] Analyzing the raw noise data to obtain noise level fluctuations;

[0039] Based on a preset vehicle state noise library, determining the current vehicle state according to the noise level fluctuation;

[0040] Performing location analysis on the original noise data to determine the noise source;

[0041] Performing spectrum analysis on the original noise data to determine the main frequency band of the noise;

[0042] The current vehicle state, the noise source and the main frequency band of the noise are determined as noise analysis data, and abnormality handling measures are determined based on the noise analysis data.

[0043] After determining that the electric seat cooling is abnormal, the present invention can respectively derive the current vehicle status, noise source and main noise frequency band by performing noise level fluctuation analysis, positioning analysis and spectrum analysis on the original noise data, and determine subsequent abnormality handling measures based on these noise analysis data, which can more accurately solve the abnormal problems of the electric seat and improve the efficiency of electric seat abnormality handling.

[0044] Furthermore, the synchronous collection of the original wind speed data and the original noise data within the second preset time is specifically as follows:

[0045] The original wind speed data within the second preset time is collected by using a wind speed sensor; the wind speed sensor is installed in the middle of the air vent of the electric seat; the installation direction of the wind speed sensor is consistent with the air flow direction of the air vent of the electric seat;

[0046] The original noise data within the second preset time is collected by using a sound level meter; the sound level meter is installed at the bottom of the electric seat.

[0047] The present invention uses a wind speed sensor to collect original wind speed data of the electric seat. The wind speed sensor is installed in the middle position of the air vent of the electric seat, which can ensure that the wind speed sensor is in direct contact with the airflow, and controls the installation direction of the wind speed sensor to be consistent with the airflow direction of the air vent of the electric seat to improve the accuracy of data measurement; uses a sound level meter to collect original noise data of the electric seat, and the sound level meter is installed at the bottom of the electric seat to ensure that it effectively captures noise signals.

[0048] Furthermore, the seat temperature and the ambient temperature are collected based on a temperature sensor; the temperature sensor is installed on the surface of the electric seat.

[0049] The present invention utilizes a temperature sensor to collect seat temperature and ambient temperature. The temperature sensor is installed on the surface of the electric seat, which can ensure the stability of data collection.

[0050] Accordingly, the present invention provides an abnormality detection device for an electric seat, comprising: a monitoring module, a first calculation module, a first determination module, a second calculation module and a second determination module;

[0051] The monitoring module is used to monitor the start-up status of the electric seat in real time;

[0052] The first calculation module is used to calculate the temperature rise rate within a first preset time when the start state of the electric seat is a heating state;

[0053] The first determination module is used to determine that the electric seat heating is abnormal if the heating speed is less than a preset heating speed threshold;

[0054] The second calculation module is used to calculate the cooling speed and the wind speed noise correlation coefficient within the second preset time when the start state of the electric seat is the cooling state;

[0055] The second determination module is used for determining that the electric seat cooling is abnormal if the cooling speed is less than a preset cooling speed threshold or the wind speed noise correlation coefficient is outside a preset correlation standard range. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 A schematic diagram of a flow chart of an embodiment of a method for detecting abnormality of an electric seat provided by the present invention;

[0057] Figure 2 A schematic structural diagram of an embodiment of an electric seat provided by the present invention;

[0058] Figure 3 A schematic flow chart of another embodiment of the method for detecting abnormality of an electric seat provided by the present invention;

[0059] Figure 4A schematic structural diagram of an embodiment of an abnormality detection device for an electric seat provided by the present invention. DETAILED DESCRIPTION

[0060] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0061] The flowcharts shown in the accompanying drawings are only examples and do not necessarily include all the contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps may also be decomposed, combined or partially merged, so the actual execution order may change according to actual conditions.

[0062] Some embodiments of the present invention are described in detail below in conjunction with the accompanying drawings. In the absence of conflict, the following embodiments and features in the embodiments can be combined with each other.

[0063] Example 1

[0064] like Figure 1 FIG. 1 is a flow chart of an embodiment of a method for detecting abnormality of an electric seat provided by the present invention. The method includes steps 101 to 105, and each step is specifically as follows:

[0065] Step 101: Monitor the activation status of the electric seat in real time.

[0066] In the first embodiment of the present invention, the electric seat has a heating function and a cooling function. When the electric seat is started to the heating state, the electric seat will call its heating function; when the electric seat is started to the cooling state, the electric seat will call its ventilation function. If the electric seat is in the heating state, the seat temperature will affect the riding comfort of the members; if the electric seat is in the cooling state, the seat fan will be started to perform the ventilation function, so the fan noise and seat temperature will affect the riding comfort of the members. Therefore, when performing abnormal detection on the electric seat, it is necessary to first determine the start-up state of the electric seat to collect corresponding data for abnormal determination of the electric seat and improve the accuracy of detection.

[0067] Step 102: When the start-up state of the electric seat is a heating state, a heating rate within a first preset time is calculated.

[0068] Further, in the first embodiment of the present invention, when the start-up state of the electric seat is the heating state, the temperature rise rate within the first preset time is calculated, specifically:

[0069] When the start state of the electric seat is the heating state, the seat temperature and the ambient temperature within a first preset time are collected;

[0070] Calculating temperature difference data within the first preset time based on the seat temperature and the ambient temperature within the first preset time;

[0071] Based on the duration of the first preset time, the temperature rising speed within the first preset time is calculated according to the temperature difference data within the first preset time.

[0072] In the first embodiment of the present invention, when the start-up state of the electric seat is the heating state, the seat temperature and the ambient temperature can be collected within the first preset time, and the difference between the seat temperature and the ambient temperature can be calculated to obtain the temperature difference data within the first preset time, and the duration of the first preset time can be obtained. The temperature difference data within the first preset time is divided by the duration of the first preset time to obtain the heating speed within the first preset time. When calculating the heating speed of the electric seat, the present invention not only collects the seat temperature, but also collects the ambient temperature. The heating speed is calculated while considering environmental factors, which can improve the accuracy of the data.

[0073] Step 103: If the heating rate is less than a preset heating rate threshold, it is determined that the electric seat heating is abnormal.

[0074] In the first embodiment of the present invention, historical temperature data of the electric seat and occupant's riding comfort experience feedback are obtained. By analyzing the historical data, a heating rate threshold reflecting riding comfort can be obtained. After obtaining the real-time calculated heating rate of the electric seat, the heating rate is compared with a preset heating rate threshold. If the heating rate is less than the preset heating rate threshold, it is determined that the heating rate cannot meet the riding comfort standard, so the electric seat heating is determined to be abnormal.

[0075] Step 104: When the start-up state of the electric seat is the cooling state, the cooling speed and the wind speed noise correlation coefficient within the second preset time are calculated.

[0076] Further, in the first embodiment of the present invention, when the start-up state of the electric seat is the cooling state, the cooling speed and the wind speed noise correlation coefficient within the second preset time are calculated, including:

[0077] When the start state of the electric seat is the cooling state, the seat temperature and the ambient temperature within the second preset time are collected;

[0078] Calculating temperature difference data within the second preset time based on the seat temperature and the ambient temperature within the second preset time;

[0079] Based on the duration of the second preset time, the cooling speed within the preset time is calculated according to the temperature difference data within the second preset time.

[0080] In the first embodiment of the present invention, when the start-up state of the electric seat is the cooling state, the seat temperature and the ambient temperature can be collected within the second preset time, and the difference between the seat temperature and the ambient temperature can be calculated to obtain the temperature difference data within the second preset time, and the duration of the second preset time can be obtained. The temperature difference data within the second preset time is divided by the duration of the second preset time to obtain the cooling speed within the second preset time. When calculating the cooling speed of the electric seat, the present invention not only collects the seat temperature, but also collects the ambient temperature. The cooling speed is calculated while considering environmental factors, which can improve the accuracy of the data.

[0081] Further, in the first embodiment of the present invention, the seat temperature and the ambient temperature are collected based on a temperature sensor; the temperature sensor is installed on the surface of the electric seat.

[0082] As an example of the first embodiment of the present invention, a temperature sensor with a measuring range of -40°C to 125°C and an accuracy of ±0.5°C can be used to collect seat temperature and ambient temperature. The temperature sensor is installed on the surface of the electric seat using a fixing tape to ensure the stability of data collection. When the electric seat is in a heating state or a cooling state, the temperature sensor is set to record the seat temperature and ambient temperature of the electric seat at the same time every second, and the seat temperature and ambient temperature of the same second are calculated to obtain temperature difference data. According to the data collection time, the formula R=△T / △t can be used to calculate the heating speed or cooling speed, where R is the heating speed or cooling speed, △T is the temperature difference data (℃), and △t is the data collection time (seconds).

[0083] Further, in the first embodiment of the present invention, when the start-up state of the electric seat is the cooling state, the cooling speed and the wind speed noise correlation coefficient within the second preset time are calculated, including:

[0084] When the start-up state of the electric seat is the cooling state, the original wind speed data and the original noise data within the second preset time are synchronously collected;

[0085] Performing data standardization processing on the original wind speed data and the original noise data respectively to form first wind speed data and first noise data;

[0086] A correlation analysis is performed on the first wind speed data and the first noise data to obtain a wind speed noise correlation coefficient.

[0087] In the first embodiment of the present invention, when the start-up state of the electric seat is the cooling state, the original wind speed data and the original noise data are collected at the same time within the second preset time under the same conditions, and the original wind speed data and the original noise data are subjected to data standardization processing to ensure that the data units of the wind speed data and the noise data are consistent, for example, the unit of the wind speed data is meter per second, and the unit of the noise data is decibel (dB) to ensure the accuracy of the correlation analysis. The wind speed-noise correlation coefficient is calculated based on the first wind speed data and the first noise data after the data standardization processing, and the correlation between the wind speed data and the noise data can be obtained.

[0088] Further, in the first embodiment of the present invention, a correlation analysis is performed on the first wind speed data and the first noise data to obtain a wind speed noise correlation coefficient, which is specifically:

[0089] Calculate the wind speed mean based on the first wind speed data;

[0090] Calculate a noise mean based on the first noise data;

[0091] Performing data matching on the first wind speed data and the first noise data to form several groups of observation data;

[0092] Based on the wind speed mean, the noise mean and several groups of observation data, a Pearson correlation analysis is performed to obtain a wind speed noise correlation coefficient.

[0093] In the first embodiment of the present invention, the linear correlation between wind speed and noise can be measured by using the Pearson correlation analysis method. Therefore, the wind speed mean is calculated for the first wind speed data, and the noise mean is calculated for the first noise data. Based on the calculated wind speed mean and noise mean, as well as the collected first wind speed data and first noise data, the Pearson correlation coefficient can be calculated. The Pearson correlation coefficient is calculated as follows:

[0094]

[0095] In the formula, x i is the wind speed data at time point i; y i is the noise data at time point i; is the noise mean; is the noise mean; r is the Pearson correlation coefficient, which is between -1 and 1.

[0096] Step 105: If the cooling speed is less than a preset cooling speed threshold or the wind speed noise correlation coefficient is outside a preset correlation standard range, it is determined that the electric seat cooling is abnormal.

[0097] In the first embodiment of the present invention, historical temperature data of the electric seat and occupant's riding comfort experience feedback are obtained. By analyzing the historical data, a cooling rate threshold reflecting the riding comfort can be obtained. After obtaining the cooling rate of the electric seat calculated in real time, the cooling rate is compared with a preset cooling rate threshold. If the cooling rate is less than the preset cooling rate threshold, it is determined that the cooling rate cannot meet the riding comfort standard, so the electric seat cooling is determined to be abnormal.

[0098] In the first embodiment of the present invention, based on the wind speed noise correlation coefficient, a linear relationship between wind speed and noise can be obtained. If the wind speed noise correlation coefficient is between 0 and 1, it means that there is a positive correlation between wind speed and noise, that is, when the wind speed increases, the noise level tends to increase; and the closer the wind speed noise correlation coefficient is to 1, the stronger the positive correlation between wind speed and noise. If the wind speed noise correlation coefficient is between -1 and 0, it means that there is a negative correlation between wind speed and noise, that is, when the wind speed increases, the noise level tends to decrease; and the closer the wind speed noise correlation coefficient is to -1, the stronger the negative correlation between wind speed and noise. If the wind speed noise correlation coefficient is 0, it means that there is no obvious linear relationship between wind speed and noise.

[0099] In the first embodiment of the present invention, historical wind speed data, historical noise data and passenger ride comfort experience feedback of the electric seat are obtained, and a correlation threshold reflecting ride comfort can be obtained by analyzing the historical data. A correlation standard range is set based on the correlation threshold. If the wind speed noise correlation coefficient obtained by real-time detection suddenly changes and exceeds the correlation standard range, it is determined that the electric seat fan is damaged or the control system of the electric seat is faulty, and then the electric seat cooling is determined to be abnormal.

[0100] Furthermore, if we analyze the historical wind speed data, historical noise data and passengers' riding comfort experience feedback of the electric seats and find that there is a strong correlation between the wind speed and noise of the electric seats, we can consider adding a wind speed adjustment mechanism for noise to the control of the electric seats to improve the comfort of the seats and reduce noise.

[0101] Further, in the first embodiment of the present invention, when the start-up state of the electric seat is the cooling state, the original wind speed data and the original noise data within the second preset time are synchronously collected, and further comprising:

[0102] Get the vent area of ​​the power seat;

[0103] Calculating the ventilation volume within the second preset time based on the ventilation opening area and the original wind speed data within the second preset time;

[0104] If the ventilation volume within the second preset time is greater than the preset ventilation volume threshold, it is determined that the cooling of the electric seat is abnormal.

[0105] In the first embodiment of the present invention, by analyzing the historical ventilation volume data of the electric seat and the riding comfort experience feedback of the occupants, a ventilation volume threshold reflecting the riding comfort can be obtained. By obtaining the ventilation port area of ​​the electric seat and combining it with the original wind speed data collected within the second preset time, the ventilation volume of the electric seat within the second preset time can be calculated, and the real-time collected ventilation volume is compared with the preset ventilation volume threshold. If the ventilation volume is greater than the ventilation volume threshold, it is determined that the ventilation volume cannot meet the riding comfort standard, so the electric seat cooling is abnormal. The present invention can also use the ventilation volume as a judgment condition for the abnormal cooling of the electric seat, which can improve the real-time performance of seat abnormality detection, thereby improving the riding comfort of the occupants.

[0106] Further, in the first embodiment of the present invention, the original wind speed data and the original noise data within the second preset time are synchronously collected, specifically:

[0107] The original wind speed data within the second preset time is collected by using a wind speed sensor; the wind speed sensor is installed in the middle of the air vent of the electric seat; the installation direction of the wind speed sensor is consistent with the air flow direction of the air vent of the electric seat;

[0108] The original noise data within the second preset time is collected by using a sound level meter; the sound level meter is installed at the bottom of the electric seat.

[0109] As an example of the first embodiment of the present invention, a wind speed sensor with a measurement range of 0.1m / s to 10m / s, an accuracy of 0.1m / s, and a response time of less than or equal to 1 second can be used to collect the original wind speed data of the electric seat. The wind speed sensor is fixed in the middle of the vent of the electric seat to ensure that it is in the airflow path of the vent of the electric seat so that it is in direct contact with the airflow; and the installation angle of the wind speed sensor is adjusted to make it consistent with the airflow direction of the vent of the electric seat to improve the measurement accuracy. When the electric seat is in the cooling state, the sampling frequency of the wind speed sensor is set to 1Hz, and the wind speed data is read in real time within the second preset time, and the ventilation volume within the second preset time is calculated based on the formula Q=A x V, where Q is the ventilation volume (m 3 / s), A is the ventilation opening area (m 2 ), V is the wind speed (m / s).

[0110] As an example of the first embodiment of the present invention, a sound level meter with a measurement range of 30dB to 130dB, an accuracy of ±1dB, and a frequency range of 20Hz to 20kHz can be used to collect the original noise data of the electric seat, and the sound level meter is fixed to the bottom of the seat to ensure that it can effectively capture the noise signal; and according to the test environment, the sensitivity setting of the sound level meter is adjusted to adapt to the noise environment when the fan of the electric seat is working. When the electric seat is in the cooling state, the sampling frequency of the sound level meter is set to 1Hz, and the noise data is obtained in real time within the second preset time to form the original noise data.

[0111] Furthermore, in the first embodiment of the present invention, after determining that the electric seat cooling is abnormal, the method further includes:

[0112] Analyzing the raw noise data to obtain noise level fluctuations;

[0113] Based on a preset vehicle state noise library, determining the current vehicle state according to the noise level fluctuation;

[0114] Performing location analysis on the original noise data to determine the noise source;

[0115] Performing spectrum analysis on the original noise data to determine the main frequency band of the noise;

[0116] The current vehicle state, the noise source and the main frequency band of the noise are determined as noise analysis data, and abnormality handling measures are determined based on the noise analysis data.

[0117] In the first embodiment of the present invention, the noise level fluctuation is the change of the sound intensity over time, that is, the dynamic range and stability of the sound. If the noise level fluctuation is too large, it may indicate that there are unstable factors in the electric seat, such as fan vibration, loose components, etc. Therefore, by analyzing the noise level fluctuation, the effectiveness of subsequent abnormal handling measures can be improved. First, the noise data of the vehicle in different states such as the start, operation and shutdown of the ventilation system is recorded, and the noise level fluctuation of the vehicle in different states is obtained by analyzing various noise data, and it is recorded in the preset vehicle state noise library. When the electric seat is detected in real time, the sound level meter captures the sound signal in the environment through the built-in microphone and converts it into an electrical signal. Using the fast (Fast) or slow (Slow) response time setting, the sound level meter can monitor the instantaneous level of the sound in real time. By weighted averaging (such as A weighting) and time weighting of continuous sound signals, the sound level meter can calculate the average noise level (such as Leq) of different time periods, display the fluctuation of the noise level, and determine the current vehicle state based on the preset vehicle state noise library.

[0118] In the first embodiment of the present invention, the noise source refers to the specific location or equipment component that generates the sound. By identifying the noise source, the specific component that generates the abnormal sound can be located. When the electric seat is detected in real time, noise data is collected by using multiple microphones (such as array microphones). Based on beamforming technology and sound source localization algorithm, the time difference of sound wave propagation can be analyzed from the sound signals received by the multiple microphones, thereby locating the position of the noise source.

[0119] In the first embodiment of the present invention, the frequency characteristic refers to the distribution of the sound signal at different frequencies, including the main frequency components and possible harmonics. Normal equipment operation usually has specific frequency characteristics. If the frequency characteristic changes significantly, such as the appearance of a new peak or a change in the intensity of the original peak, it may indicate that changes have occurred inside the equipment, such as wear, damage or imbalance, which may indicate potential failures. When real-time detection of electric seats, a sound level meter is used to collect noise data in real time, and the collected sound signal is converted into the frequency domain using a fast Fourier transform (FFT), and the energy distribution of each frequency component is analyzed to identify the noise characteristics at a specific frequency, such as the resonant frequency or a specific noise type (low-frequency noise, high-frequency noise, etc.).

[0120] In the first embodiment of the present invention, the current vehicle state can be determined by analyzing the noise level fluctuation; the fault point can be located by analyzing the noise source and the scope of fault diagnosis can be narrowed; the detailed characteristics of the noise signal can be determined by analyzing the frequency characteristics, which is helpful to identify and diagnose specific fault types. Therefore, by analyzing the noise data to obtain the current vehicle state, noise source and main frequency band of the noise, it can help relevant personnel to specify more effective abnormality handling measures.

[0121] As an example of the first embodiment of the present invention, see Figure 2 , is a structural schematic diagram of an embodiment of the electric seat provided by the present invention. The temperature sensor is installed on the surface of the electric seat to monitor the seat surface temperature and the ambient temperature. The wind speed sensor (anemometer) is installed at the air outlet of the cooling fan of the electric seat to monitor the cooling air volume of the electric seat. The sound level meter and the radio microphone are fixed at the bottom of the electric seat to monitor the fan and ambient volume. The temperature sensor, wind speed sensor and sound level meter collect analog data through the data board, which are converted into digital data by the data board, and then connected to the host computer via the control USB cable, and the data is transmitted back to the host computer data and feedback system software for recording. The host computer uses a CAN network tool to connect to the controller of the electric seat through the CAN network, sends a corresponding startup message signal, and starts the seat ventilation and heating functions.

[0122] As an example of the first embodiment of the present invention, see Figure 3, is a flow chart of another embodiment of the electric seat abnormality detection method provided by the present invention. When the operator starts the host computer, the host computer uses the CAN network to start the seat function, including the ventilation function or heating function of the electric seat. The operator starts the data and feedback system software of the host computer, sends an enable instruction to the corresponding data board through a USB cable, and starts the data board. The data board is connected to the temperature sensor, wind speed sensor (anemometer) and sound level meter installed in the electric seat stand through a data line. After receiving the enable instruction, the data board starts the temperature sensor, anemometer and sound level meter in the stand and starts monitoring the electric seat. After the electric seat controller receives the CAN message corresponding to the ventilation or heating function sent by the host computer through the CAN network, it executes the ventilation function or the heating function. Executing the ventilation function will start the anemometer acquisition and the sound level meter acquisition, and executing the heating function will start the temperature sensor acquisition. After the anemometer, the sound level meter and the temperature sensor collect data to the data board, they are transmitted back to the data and feedback system software of the host computer through the USB cable. When the test stops, the host computer data and feedback system software generate a corresponding test report to record the temperature data, wind speed data and noise data in this test.

[0123] In summary, the first embodiment of the present invention provides an abnormality detection method for an electric seat, which monitors the start-up state of the electric seat in real time. When the start-up state of the electric seat is a heating state, the heating rate of the electric seat is calculated in real time, and whether the electric seat has abnormal heating is determined based on the heating rate of the electric seat; when the start-up state of the electric seat is a cooling state, the cooling rate of the electric seat and the wind speed noise correlation coefficient are calculated in real time, and whether the electric seat has abnormal cooling is determined based on the cooling rate of the electric seat and the wind speed noise correlation coefficient. The present invention can monitor the heating and cooling anomalies of the electric seat in real time, thereby improving the real-time nature of data monitoring; different indicators are used to determine whether the electric seat is abnormal according to different start-up states of the electric seat, thereby improving the accuracy of the monitoring data and thereby improving the riding comfort of the occupants.

[0124] Example 2

[0125] See also Figure 4 , is a schematic structural diagram of an embodiment of an abnormality detection device for an electric seat provided by the present invention, the device comprises a monitoring module 201, a first calculation module 202, a first determination module 203, a second calculation module 204 and a second determination module 205;

[0126] The monitoring module 201 is used to monitor the start-up status of the electric seat in real time;

[0127] The first calculation module 202 is used to calculate the temperature increase rate within a first preset time when the start state of the electric seat is a heating state;

[0128] The first determination module 203 is used to determine that the electric seat heating is abnormal if the heating speed is less than a preset heating speed threshold;

[0129] The second calculation module 204 is used to calculate the cooling speed and the wind speed noise correlation coefficient within the second preset time when the start state of the electric seat is the cooling state;

[0130] The second determination module 205 is used to determine that the electric seat cooling is abnormal if the cooling speed is less than a preset cooling speed threshold or the wind speed noise correlation coefficient is outside a preset correlation standard range.

[0131] Further, in the second embodiment of the present invention, when the start-up state of the electric seat is the heating state, the temperature rise rate within the first preset time is calculated, specifically:

[0132] When the start state of the electric seat is the heating state, the seat temperature and the ambient temperature within a first preset time are collected;

[0133] Calculating temperature difference data within the first preset time based on the seat temperature and the ambient temperature within the first preset time;

[0134] Based on the duration of the first preset time, the temperature rising speed within the first preset time is calculated according to the temperature difference data within the first preset time.

[0135] Further, in the second embodiment of the present invention, when the start-up state of the electric seat is the cooling state, the cooling speed and the wind speed noise correlation coefficient within the second preset time are calculated, including:

[0136] When the start state of the electric seat is the cooling state, the seat temperature and the ambient temperature within the second preset time are collected;

[0137] Calculating temperature difference data within the second preset time based on the seat temperature and the ambient temperature within the second preset time;

[0138] Based on the duration of the second preset time, the cooling speed within the preset time is calculated according to the temperature difference data within the second preset time.

[0139] Further, in the second embodiment of the present invention, when the start-up state of the electric seat is the cooling state, the cooling speed and the wind speed noise correlation coefficient within the second preset time are calculated, including:

[0140] When the start-up state of the electric seat is the cooling state, the original wind speed data and the original noise data within the second preset time are synchronously collected;

[0141] Performing data standardization processing on the original wind speed data and the original noise data respectively to form first wind speed data and first noise data;

[0142] A correlation analysis is performed on the first wind speed data and the first noise data to obtain a wind speed noise correlation coefficient.

[0143] Further, in the second embodiment of the present invention, a correlation analysis is performed on the first wind speed data and the first noise data to obtain a wind speed noise correlation coefficient, which is specifically:

[0144] Calculate the wind speed mean based on the first wind speed data;

[0145] Calculate a noise mean based on the first noise data;

[0146] Performing data matching on the first wind speed data and the first noise data to form several groups of observation data;

[0147] Based on the wind speed mean, the noise mean and several groups of observation data, a Pearson correlation analysis is performed to obtain a wind speed noise correlation coefficient.

[0148] Further, in the second embodiment of the present invention, when the start-up state of the electric seat is the cooling state, the original wind speed data and the original noise data within the second preset time are synchronously collected, and further comprising:

[0149] Get the vent area of ​​the power seat;

[0150] Calculating the ventilation volume within the second preset time based on the ventilation opening area and the original wind speed data within the second preset time;

[0151] If the ventilation volume within the second preset time is greater than the preset ventilation volume threshold, it is determined that the cooling of the electric seat is abnormal.

[0152] Furthermore, in the second embodiment of the present invention, after determining that the electric seat cooling is abnormal, the method further includes:

[0153] Analyzing the raw noise data to obtain noise level fluctuations;

[0154] Based on a preset vehicle state noise library, determining the current vehicle state according to the noise level fluctuation;

[0155] Performing location analysis on the original noise data to determine the noise source;

[0156] Performing spectrum analysis on the original noise data to determine the main frequency band of the noise;

[0157] The current vehicle state, the noise source and the main frequency band of the noise are determined as noise analysis data, and abnormality handling measures are determined based on the noise analysis data.

[0158] Further, in the second embodiment of the present invention, the original wind speed data and the original noise data within the second preset time are synchronously collected, specifically:

[0159] The original wind speed data within the second preset time is collected by using a wind speed sensor; the wind speed sensor is installed in the middle of the air vent of the electric seat; the installation direction of the wind speed sensor is consistent with the air flow direction of the air vent of the electric seat;

[0160] The original noise data within the second preset time is collected by using a sound level meter; the sound level meter is installed at the bottom of the electric seat.

[0161] Further, in a second embodiment of the present invention, the seat temperature and the ambient temperature are collected based on a temperature sensor; the temperature sensor is installed on the surface of the electric seat.

[0162] In summary, the second embodiment of the present invention provides an abnormality detection device for an electric seat, which monitors the start-up state of the electric seat in real time based on the organic combination of modules. When the start-up state of the electric seat is the heating state, the heating rate of the electric seat is calculated in real time, and whether the electric seat has abnormal heating is determined according to the heating rate of the electric seat; when the start-up state of the electric seat is the cooling state, the cooling rate of the electric seat and the wind speed noise correlation coefficient are calculated in real time, and whether the electric seat has abnormal cooling is determined according to the cooling rate of the electric seat and the wind speed noise correlation coefficient. The present invention can monitor the heating and cooling anomalies of the electric seat in real time, and improves the real-time nature of data monitoring; different indicators are used to determine whether the electric seat is abnormal according to different start-up states of the electric seat, which improves the accuracy of the monitoring data and thus improves the riding comfort of the occupants.

[0163] The specific embodiments described above further illustrate the purpose, technical solutions and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. It is particularly pointed out that for those skilled in the art, any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for detecting abnormality of an electric seat, characterized in that: include: Real-time monitoring of the activation status of the electric seat; When the start-up state of the electric seat is a heating state, calculating a heating rate within a first preset time; If the heating speed is less than a preset heating speed threshold, it is determined that the electric seat is abnormally heated; When the start-up state of the electric seat is the cooling state, calculating the cooling speed and the wind speed noise correlation coefficient within the second preset time; If the cooling speed is less than a preset cooling speed threshold or the wind speed noise correlation coefficient is outside a preset correlation standard range, it is determined that the electric seat cooling is abnormal.

2. The method for detecting abnormality of an electric seat according to claim 1, characterized in that: When the start-up state of the electric seat is the heating state, the temperature rise rate within the first preset time is calculated, specifically: When the start state of the electric seat is the heating state, the seat temperature and the ambient temperature within a first preset time are collected; Calculating temperature difference data within the first preset time based on the seat temperature and the ambient temperature within the first preset time; Based on the duration of the first preset time, the temperature rising speed within the first preset time is calculated according to the temperature difference data within the first preset time.

3. The method for detecting abnormality of an electric seat according to claim 1, characterized in that: When the start-up state of the electric seat is the cooling state, calculating the cooling speed and the wind speed noise correlation coefficient within the second preset time includes: When the start state of the electric seat is the cooling state, the seat temperature and the ambient temperature within the second preset time are collected; Calculating temperature difference data within the second preset time based on the seat temperature and the ambient temperature within the second preset time; Based on the duration of the second preset time, the cooling speed within the preset time is calculated according to the temperature difference data within the second preset time.

4. The method for detecting abnormality of an electric seat according to claim 1, characterized in that: When the start-up state of the electric seat is the cooling state, calculating the cooling speed and the wind speed noise correlation coefficient within the second preset time includes: When the start-up state of the electric seat is the cooling state, the original wind speed data and the original noise data within the second preset time are synchronously collected; Performing data standardization processing on the original wind speed data and the original noise data respectively to form first wind speed data and first noise data; A correlation analysis is performed on the first wind speed data and the first noise data to obtain a wind speed noise correlation coefficient.

5. The method for detecting abnormality of an electric seat according to claim 4, characterized in that: The correlation analysis is performed on the first wind speed data and the first noise data to obtain a wind speed noise correlation coefficient, which is specifically: Calculate the wind speed mean based on the first wind speed data; Calculate a noise mean based on the first noise data; Performing data matching on the first wind speed data and the first noise data to form several groups of observation data; Based on the wind speed mean, the noise mean and several groups of observation data, a Pearson correlation analysis is performed to obtain a wind speed noise correlation coefficient.

6. The method for detecting abnormality of an electric seat according to claim 4, characterized in that: When the start-up state of the electric seat is the cooling state, the original wind speed data and the original noise data within the second preset time are synchronously collected, and the method further includes: Get the vent area of ​​the power seat; Calculating the ventilation volume within the second preset time based on the ventilation opening area and the original wind speed data within the second preset time; If the ventilation volume within the second preset time is greater than the preset ventilation volume threshold, it is determined that the cooling of the electric seat is abnormal.

7. The method for detecting abnormality of an electric seat according to claim 1 or 6, characterized in that: After determining that the electric seat cooling is abnormal, the method further includes: Analyzing the raw noise data to obtain noise level fluctuations; Based on a preset vehicle state noise library, determining the current vehicle state according to the noise level fluctuation; Performing location analysis on the original noise data to determine the noise source; Performing spectrum analysis on the original noise data to determine the main frequency band of the noise; The current vehicle state, the noise source and the main frequency band of the noise are determined as noise analysis data, and abnormality handling measures are determined based on the noise analysis data.

8. The method for detecting abnormality of an electric seat according to claim 4, characterized in that: The synchronous collection of the original wind speed data and the original noise data within the second preset time is specifically as follows: The original wind speed data within the second preset time is collected by using a wind speed sensor; the wind speed sensor is installed in the middle of the air vent of the electric seat; the installation direction of the wind speed sensor is consistent with the air flow direction of the air vent of the electric seat; The original noise data within the second preset time is collected by using a sound level meter; the sound level meter is installed at the bottom of the electric seat.

9. The method for detecting abnormality of an electric seat according to claim 2 or 3, characterized in that: The seat temperature and the ambient temperature are collected based on a temperature sensor; the temperature sensor is installed on the surface of the electric seat.

10. An abnormality detection device for an electric seat, characterized in that: include: A monitoring module, a first calculation module, a first determination module, a second calculation module and a second determination module; The monitoring module is used to monitor the start-up status of the electric seat in real time; The first calculation module is used to calculate the temperature rise rate within a first preset time when the start state of the electric seat is a heating state; The first determination module is used to determine that the electric seat heating is abnormal if the heating speed is less than a preset heating speed threshold; The second calculation module is used to calculate the cooling speed and the wind speed noise correlation coefficient within the second preset time when the start state of the electric seat is the cooling state; The second determination module is used for determining that the electric seat cooling is abnormal if the cooling speed is less than a preset cooling speed threshold or the wind speed noise correlation coefficient is outside a preset correlation standard range.

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