fix some mistake

This commit is contained in:
Gitshaoxiang
2020-12-23 16:37:15 +08:00
parent 86bcdbba8a
commit 507faeee82
29 changed files with 754 additions and 34 deletions
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@@ -155,8 +155,8 @@ If you need to add an RS485 or RS232 interface, make sure to solder the RS485 or
<td>MOSI</td>
<td>CS</td>
<td>INT</td>
<th>RX/A</th>
<th>TX/B</th>
<th>RX</th>
<th>TX</th>
</tr>
</tbody>
</table>
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@@ -73,7 +73,7 @@ It is able to perform convolutional neural network calculations at low power con
</tr>
<tr>
<td>SRAM</td>
<td>8Mbit</td>
<td>8MiB</td>
</tr>
<tr>
<td>Flash</td>
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@@ -214,7 +214,8 @@
{"a":"/#/en/accessory/battery_base", "img":"https://static-cdn.m5stack.com/image/m5-docs_homepage/accessory/battery_base_01.webp", "p":"M5CameraBattery", "sku":"A068" ,"kw":"BATTERY"}
],
"AI-Cameras": [
{"a":"/#/en/unit/unitv", "img":"https://static-cdn.m5stack.com/image/m5-docs_homepage/unit/unit-v-01.webp", "p":"UNIT-V", "sku":"U078", "qs":"/#/en/quick_start/unitv/unitv_quick_start" ,"kw":"K210 CAMERA", "category":"AI-Cameras"},
{"a":"/#/en/unit/unitv", "img":"https://static-cdn.m5stack.com/image/m5-docs_homepage/unit/unit-v-01.webp", "p":"UNIT-V(OV2640)", "sku":"U078", "qs":"/#/en/quick_start/unitv/unitv_quick_start" ,"kw":"K210 CAMERA OV2640", "category":"AI-Cameras"},
{"a":"/#/zh_CN/unit/unitv_ov7740", "img":"https://static-cdn.m5stack.com/image/m5-docs_homepage/unit/unitv_ov7740.webp", "p":"UNIT-V(OV7740)", "sku":"U078-C", "qs":"/#/zh_CN/quick_start/unitv/unitv_quick_start" ,"kw":"K210 CAMERA OV7740"},
{"a":"/#/en/core/m5stickv", "img":"https://static-cdn.m5stack.com/image/m5-docs_homepage/core/m5stickv_01.webp", "p":"M5StickV", "sku":"K027" , "qs":"/#/en/quick_start/m5stickv/m5stickv_quick_start", "kw":"K210 CAMERA AXP192 MPU6886"}
]
},
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@@ -122,8 +122,8 @@ It has some obvious advantages in the following aspects: High speed low failure
### Pin Map
<table>
<tr><td>M5Core(GROVE A)</td><td>GPIO22</td><td>GPIO21</td><td>5V</td><td>GND</td></tr>
<tr><td>CAN Unit</td><td>SCL</td><td>SDA</td><td>5V</td><td>GND</td></tr>
<tr><td>M5Core(PORT C)</td><td>GPIO16</td><td>GPIO17</td><td>5V</td><td>GND</td></tr>
<tr><td>CAN Unit</td><td>RXD</td><td>TXD</td><td>5V</td><td>GND</td></tr>
</table>
## Schematic
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@@ -220,13 +220,13 @@ what this software can do?
<img src="https://m5stack.oss-cn-shenzhen.aliyuncs.com/image/m5-docs_schematic/unit/m5camera_sch_03.webp">
<el-divider content-position="right">Last updated: 2020-12-14</el-divider>
<el-divider content-position="right">Last updated: 2020-12-22</el-divider>
<script>
var purchase_link = 'https://docs.m5stack.com/#/en/quick_start/m5camera/m5camera_quick_start';
var purchase_link = 'https://m5stack.com/collections/m5-unit/products/psram-camera-module';
var quickstart_link = 'https://m5stack.com/collections/m5-core/products/basic-core-iot-development-kit';
var quickstart_link = '/#/en/quick_start/m5camera/m5camera_quick_start';
anchor_search(purchase_link,quickstart_link);
scrollFunc();
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@@ -2,7 +2,7 @@
<el-tag effect="plain">SKU:U041</el-tag>
<div class="product_pic"><img src="assets/img/product_pics/unit/pbhub/pbhub_p1.webp"><img src="assets/img/product_pics/unit/pbhub/pbhub_p2.webp"></div>
<div class="product_pic"><img src="assets/img/product_pics/unit/pbhub/pbhub_p1.webp"></div>
## Description
@@ -60,7 +60,7 @@ Similar to the PaHub Unit, the PbHub provides solution for multiple devices cont
## Change I2C Address
The Default I2C address of the unit is 0x61 (which can be changed by using solder resistors A0 ~ A2, the address range is 0x61~0x68).
The Default I2C address of the unit is 0x61 (which can be changed by using solder resistors A0 ~ A2, the address range is 0x61 ~ 0x68).
<img src="assets/img/product_pics/unit/pbhub/pbhub_i2c_addr.webp" width="300px">
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@@ -100,7 +100,7 @@ In sleep mode, the current consumption of the whole machine is only 2μA. After
## EasyLoader
>EasyLoader is a concise and fast program writer, which has a built-in case program related to the product. It can be burned to the main control by simple steps to perform a series of function verification. Please install the corresponding driver according to the device type. M5Core host [Please click here to view the CP210X driver installation tutorial](en/arduino/arduino_development), M5StickC/V/T/ATOM series can be used without driver)
>EasyLoader is a concise and fast program writer, which has a built-in case program related to the product. It can be burned to the main control by simple steps to perform a series of function verification.
<div class="easyloader-box">
<div style="background-color:white;">
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@@ -110,7 +110,7 @@ The **Timer Camera F** is a fisheye camera module based on ESP32-D0WDQ6-V3 with
## EasyLoader
>EasyLoader is a concise and fast program writer, which has a built-in case program related to the product. It can be burned to the main control by simple steps to perform a series of function verification. Please install the corresponding driver according to the device type. M5Core host [Please click here to view the CP210X driver installation tutorial](en/arduino/arduino_development), M5StickC/V/T/ATOM series can be used without driver)
>EasyLoader is a concise and fast program writer, which has a built-in case program related to the product. It can be burned to the main control by simple steps to perform a series of function verification.
<div class="easyloader-box">
<div style="background-color:white;">
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@@ -106,7 +106,7 @@ Choose the development platform you want to use, view the corresponding tutorial
## EasyLoader
>EasyLoader is a concise and fast program writer, which has a built-in case program related to the product. It can be burned to the main control by simple steps to perform a series of function verification. Please install the corresponding driver according to the device type. M5Core host [Please click here to view the CP210X driver installation tutorial](en/arduino/arduino_development), M5StickC/V/T/ATOM series can be used without driver)
>EasyLoader is a concise and fast program writer, which has a built-in case program related to the product. It can be burned to the main control by simple steps to perform a series of function verification.
<div class="easyloader-box">
<div style="background-color:white;">
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@@ -71,7 +71,7 @@ It is equipped with two programmable keys and an RGB LED indicator on the front
</tr>
<tr>
<td>SRAM</td>
<td>8Mbit</td>
<td>8MiB</td>
</tr>
<tr>
<td>Flash</td>
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# UnitV(OV7740)
<el-tag effect="plain">SKU:U078-C</el-tag>
<div class="product_pic"><img src="assets/img/product_pics/unit/unit-v/unitv_ov7740.webp"></div>
## Tutorial&Quick-Start
Choose the development platform you want to use, view the corresponding tutorial&quick-Start.
<a href="/#/zh_CN/quick_start/unitv/v_function"><el-tag effect="plain">V-Function</el-tag></a>
<a href="/#/zh_CN/related_documents/v-training"><el-tag effect="plain">V-Training</el-tag></a>
<a href="/#/zh_CN/quick_start/unitv/unitv_quick_start_maixpy"><el-tag effect="plain">Maixpy</el-tag></a>
## Description
**UnitV(OV7740)** is the new AI Camera powered by Kendryte K210, an edge computing system-on-chip(SoC) with dual-core 64bit RISC-V CPU and state-of-art neural network processor.
UNIT-V AI Camera features its integration with machine vision capabilities, featuring the unprocessed acceptability to AI Visioning with high energy efficiency and low cost. We co-oped with Sipeed providing the MicroPython environment makes programming on UNIT-V easier.
Support MicroPython development environment, which makes the program code more concise when you use UNIT-V for project development.Equipped with OV7740 image sensor, it is an ideal choice for machine vision project.
It is equipped with two programmable keys and an RGB LED indicator on the front for convenient status display.At the bottom, there is a HY2.0*4P interface and a type-C interface compatible with grove, which is convenient to connect with the main controller. Support TF card to expand memory, related material and model file call more convenient.
## Product Features
- Dual-Core 64-bit RISC-V RV64IMAFDC (RV64GC) CPU / 400Mhz(Normal)
- Dual Independent Double Precision FPU
- 8MiB 64bit width On-Chip SRAM
- Neural Network Processor(KPU) / 0.8Tops
- Field-Programmable IO Array (FPIOA)
- AES, SHA256 Accelerator
- Direct Memory Access Controller (DMAC)
- Micropython Support
- Firmware encryption support
- On-board Hardware resources:
- Flash: 16M
- Camera :OV7740
- Button: button * 2
- Indicator light: WS2812 LED
- External storage: TF card/Micro SD
- Interface: HY2.0/compatible GROVE
## Include
- 1x UNIT-V(include 20cm 4P cable and USB-C cable)
## Applications
- Face recognition/detection
- Object detection/classification
- Obtaining size and coordinates of the target in real-time
- Obtaining the type of detected target in real-time
- Shape recognition
- Video recoder
## Specification
<table>
<tr style="font-weight:bold">
<td>Resources</td>
<td>Parameter</td>
</tr>
<tr>
<td>Kendryte K210</td>
<td>Dual-Core 64-bit RISC-V RV64IMAFDC (RV64GC) CPU / 400Mhz(Normal)</td>
</tr>
<tr>
<td>SRAM</td>
<td>8MiB</td>
</tr>
<tr>
<td>Flash</td>
<td>16M</td>
</tr>
<tr>
<td>Input voltage</td>
<td>5V @ 500mA</td>
</tr>
<tr>
<td>KPU Neural network parameter size</td>
<td>5.5MiB - 5.9MiB</td>
</tr>
<tr>
<td>Interface</td>
<td>TypeC x 1, GROVE(I2C+I/0+UART) x 1</td>
</tr>
<tr>
<td>RGB LED</td>
<td>WS2812 x 1</td>
</tr>
<tr>
<td>Button</td>
<td>x 2</td>
</tr>
<tr>
<td>Image Sensor</td>
<td>OV2640</td>
</tr>
<tr>
<td>FOV</td>
<td>65deg</td>
</tr>
<tr>
<td>External storage</td>
<td>TF Card/Micro SD</td>
</tr>
<tr>
<td>Net weight</td>
<td>8g</td>
</tr>
<tr>
<td>Gross weight</td>
<td>45g</td>
</tr>
<tr>
<td>Product Size</td>
<td>40mm * 24mm * 13mm</td>
</tr>
<tr>
<td>Package Size</td>
<td>70mm * 50mm * 30mm</td>
</tr>
<tr>
<td>shell material</td>
<td>Plastic ( PC )</td>
</tr>
</table>
### About KENDRYTE K210
The Kendryte K210 is a system-on-chip (SoC) that integrates machine vision. Using TSMCs ultra-low-power 28-nm advanced process with dualcore 64-bit processors for better power efficiency, stability and reliability. The SoC strives for ”zero threshold” development and to be deployable in the users products in the shortest possible time, giving the product artificial intelligence
- Machine Vision
- Better low power vision processing speed and accuracy
- KPU high performance Convolutional Neural Network (CNN) hardware accelerator
- Advanced TSMC 28nm process, temperature range -40°C to 125°C
- Firmware encryption support
- Unique programmable IO array maximises design flexibility
- Low voltage, reduced power consumption compared to other systems with the same processing power
- 3.3V/1.8V dual voltage IO support eliminates need for level shifters
The chip contains a high-performance, low power RISC-V ISA-based dual core 64-bit CPU with the following features:
- Core Count Dual-core processor
- Bit Width: 64-bit CPU 400MHz
- Frequency: 400MHz
- ISA extensions: IMAFDC
- FPU: Double Precision
- Platform Interrupts: PLIC
- Local Interrupts: CLINT
- I-Cache: 32KiB x 2
- D-Cache: 32KiB x 2
- On-Chip SRAM: 8MiB
### OV7740
- support for output formats: RAW RGB and YUV
- support for image sizes: VGA, QVGA, CIF and any size smaller
- support for black sun cancellation
- support for internal and external frame synchronization
- standard SCCB serial interface
- digital video port (DVP) parallel output interface
- embedded one-time programmable (OTP) memory
- on-chip phase lock loop (PLL)
- embedded 1.5 V regulator for core
- Sophisticated Edge Rate Control Enables Filterless Class D Outputs
- 77dB PSRR at 1kHz
- Low RF Susceptibility Rejects TDMA Noise from GSM Radios
- Extensive Click-and-Pop Reduction Circuitry
- array size: 656 x 488
- power supply: core: 1.5VDC ± 5% analog: 3.3V ± 5% I/O: 1.7 ~ 3.47V
- temperature range: operating: -30° C to 70°C stable image: 0° C to 50° C
- output format: 8-/10-bit raw RGB data 8-bit YUV
- lens size: 1/5"
- input clock frequency: 6 ~ 27 MHz
- max image transfer rate: VGA (640x480): 60 fps QVGA (320 x 240): 120 fp
- sensitivity: 6800 mV/(Lux-sec)
- maximum exposure interval: 502 x tROW
- pixel size: 4.2 μm x 4.2 μm
- image area: 2755.2 μm x 2049.6 μm
- package/die dimensions: CSP3: 4185 μm x 4345 μm COB: 4200 μm x 4360 μm
### SD card test
UNIT-V does not currently recognize all types of MicroSD cards. We have tested some common SD cards. The test results are as follows.
<img src="assets\img\product_pics\unit\unit-v/unit-v-08.webp" width="40%" height="40%"><br>
<table class="table_center">
<tr style="font-weight:bold" >
<td>Brand</td>
<td>Storage</td>
<td>Type</td>
<td>Class</td>
<td>Format</td>
<td>Test Results</td>
</tr>
<tr>
<td>Kingston</td>
<td>8G</td>
<td>HC</td>
<td>Class4</td>
<td>FAT32</td>
<td>OK</td>
</tr>
<tr>
<td>Kingston</td>
<td>16G</td>
<td>HC</td>
<td>Class10</td>
<td>FAT32</td>
<td>OK</td>
</tr>
<tr>
<td>Kingston</td>
<td>32G</td>
<td>HC</td>
<td>Class10</td>
<td>FAT32</td>
<td>NO</td>
</tr>
<tr>
<td>Kingston</td>
<td>64G</td>
<td>XC</td>
<td>Class10</td>
<td>exFAT</td>
<td>OK</td>
</tr>
<tr>
<td>SanDisk</td>
<td>16G</td>
<td>HC</td>
<td>Class10</td>
<td>FAT32</td>
<td>OK</td>
</tr>
<tr>
<td>SanDisk</td>
<td>32G</td>
<td>HC</td>
<td>Class10</td>
<td>FAT32</td>
<td>OK</td>
</tr>
<tr>
<td>SanDisk</td>
<td>64G</td>
<td>XC</td>
<td>Class10</td>
<td>/</td>
<td>NO</td>
</tr>
<tr>
<td>SanDisk</td>
<td>128G</td>
<td>XC</td>
<td>Class10</td>
<td>/</td>
<td>NO</td>
</tr>
<tr>
<td>XIAKE</td>
<td>16G</td>
<td>HC</td>
<td>Class10</td>
<td>FAT32</td>
<td>OK(purple)</td>
</tr>
<tr>
<td>XIAKE</td>
<td>32G</td>
<td>HC</td>
<td>Class10</td>
<td>FAT32</td>
<td>OK</td>
</tr>
<tr>
<td>XIAKE</td>
<td>64G</td>
<td>XC</td>
<td>Class10</td>
<td>/</td>
<td>NO</td>
</tr>
<tr>
<td>TURYE</td>
<td>32G</td>
<td>HC</td>
<td>Class10</td>
<td>/</td>
<td>NO</td>
</tr>
</table>
## Related Link
- **Web page** - [sipeed](https://maixpy.sipeed.com/en/)
- **datasheet** - [K210](https://m5stack.oss-cn-shenzhen.aliyuncs.com/resource/docs/datasheet/core/kendryte_datasheet_en.pdf)
## PinMap
<img src="assets/img/product_pics/unit/unit-v/unitv_ov7740_sticker.webp" width="30%">
## Example
If you want the complete code, please click [here](https://github.com/m5stack/M5-ProductExampleCodes/tree/master/App/UnitV/track_ball)
## Video
<video class="video_size" controls>
<source src="https://m5stack.oss-cn-shenzhen.aliyuncs.com/video/Product_example_video/Unit/unitV.mp4" type="video/mp4">
</video>
<el-divider content-position="right">Last updated: 2020-12-14</el-divider>
<script>
var purchase_link = 'https://m5stack.com/collections/m5-unit/products/unitv-ai-camera';
var quickstart_link = '/#/en/quick_start/unitv/unitv_quick_start';
anchor_search(purchase_link,quickstart_link);
scrollFunc();
</script>
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# ATOM HDriver
<el-tag effect="plain">SKU:K039</el-tag>
## 描述
**ATOM HDriver** 是一款适配ATOM控制器的`H桥`电机驱动器。内置DRV8876电机驱动芯片,支持`9-24V/DC电源输入`(内嵌DC/DC电路为整机设备供电,ADC引脚G33直连分压电路可随时监测电源输入情况), 输出电流可达`1.5A`, `峰值2A`, 能够用于直流电机调速与正反转控制。驱动内部集成了N沟道H桥、充电泵稳压器、电流检测和调节、电流比例输出和保护电路(保护功能集成:电源欠压锁定 (UVLO)、充电泵欠压 (CPUV)、输出过流 (OCP) 和器件超温 (TSD), 故障情况并通过`FAULT`引脚指示)。
## 产品特性
- N沟道H桥电机驱动器
* 驱动一台双向有刷直流电机
* 其他阻性和感性负载
DRV8876700mΩ(高侧+低侧)
- 高输出电流能力
* 实际输出1.5A, 峰值2A
H桥控制模式
- 3.3V逻辑输入
- 扩频时钟可降低电磁干扰
- 集成保护功能
* 欠压锁定(UVLO)
* 电荷泵欠压(CPUV)
* 过电流保护(OCP)
* 自动重试或锁存输出(IMODE)
* 热关机(TSD)
* 自动故障恢复
* 故障指示器引脚(nFAULT)
## 相关链接
- **Datasheet**
- [DRV8876PWPR](https://m5stack.oss-cn-shenzhen.aliyuncs.com/resource/docs/datasheet/atombase/atom_hdriver/C575551_DRV8876PWPR_2020-06-01.PDF)
## 管脚映射
<table>
<tr><td>ATOM</td><td>G22</td><td>G19</td><td>G23</td><td>G33</td></tr>
<tr><td>Hdriver</td><td>FAULT</td><td>IN1</td><td>IN2</td><td>VIN-1/10</td></tr>
</table>
?>提示:当故障发生时,将触发FAULT(G22)引脚下拉,G33能够获取输入电压的1/10,能够用于检测当前的电源输入情况。
## 案例程序
- [Arduino代码示例](https://github.com/m5stack/M5-ProductExampleCodes/tree/master/AtomBase/AtomFLY)
## 原理图
<img src="assets/img/product_pics/atom_base/atom_hdriver/atom_hdriver_sch.webp">
<script>
var purchase_link = 'https://m5stack.com/collections/all/products/atomic-proto-kit';
anchor_search(purchase_link);
scrollFunc();
</script>
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@@ -103,9 +103,6 @@
var purchase_link = 'https://m5stack.com/collections/all/products/atomic-proto-kit';
var quickstart_link = '';
anchor_search(purchase_link);
scrollFunc();
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# ATOM HDriver
<el-tag effect="plain">SKU:K039</el-tag>
+2 -2
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@@ -154,8 +154,8 @@ HT3.96连接器的 6 个引脚默认悬空,你可以根据需求选择连接RS
<td>MOSI</td>
<td>CS</td>
<td>INT</td>
<th>RX/A</th>
<th>TX/B</th>
<th>RX</th>
<th>TX</th>
</tr>
</tbody>
</table>
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@@ -67,7 +67,7 @@ M5stickV AI 摄像头具备机器视觉能力,配备OmniVision OV7740图像传
</tr>
<tr>
<td>SRAM</td>
<td>8Mbit</td>
<td>8MiB</td>
</tr>
<tr>
<td>Flash</td>
@@ -283,7 +283,9 @@ M5StickV目前并不能识别所有类型的TF-card(microSD),我们对一些
</div>
## 功能描述
### KENDRYTE K210
Kendryte K210 是集成机器视觉能力的系统级芯片 (SoC)。使用台积电 (TSMC) 超低功耗的 28 纳米先进制程,具有双核 64 位处理器,拥有较好的功耗性能,稳定性与可靠性。该方案力求零门槛开发,可在最短时效部署于用户的产品中,赋予产品人工智能.<br><br>
- 具备机器视觉能力
- 更好的低功耗视觉处理速度与准确率
@@ -295,6 +297,7 @@ Kendryte K210 是集成机器视觉能力的系统级芯片 (SoC)。使用台积
- 3.3V/1.8V 双电压支持,无需电平转换,节约成本
### CPU
本芯片搭载基于 RISC-V ISA 的双核心 64 位的高性能低功耗 CPU,具备以下特性:
- 核心数量: 双核处理器
@@ -309,6 +312,7 @@ Kendryte K210 是集成机器视觉能力的系统级芯片 (SoC)。使用台积
- 片上 SRAM: 8MiB
### OV7740
- 支持输出格式:RAW RGB和YUV
- 支持图像尺寸:VGA,QVGA,CIF或其他更小尺寸
- 支持太阳黑子消除
@@ -332,6 +336,7 @@ Kendryte K210 是集成机器视觉能力的系统级芯片 (SoC)。使用台积
- 封装/管芯尺寸: - CSP34185μm×4345 μm-COB4200μm×4360μm
### MAX98357
- 单电源工作(2.5V至5.5V)
- 3.2W输出功率:4Ω,5V
- 2.4mA静态电流
@@ -347,6 +352,7 @@ Kendryte K210 是集成机器视觉能力的系统级芯片 (SoC)。使用台积
- 喀嗒声抑制电路
### AXP192
- 工作电压: 2.9V - 6.3V(AMR-0.3V~15V)
- 可配置的智能电源选择系统
- 自适应USB或AC适配器输入的电流和电压限制
@@ -355,6 +361,7 @@ Kendryte K210 是集成机器视觉能力的系统级芯片 (SoC)。使用台积
### MPU6886
#### 陀螺仪功能
- 数字输出X,Y和Z轴角速率传感器(陀螺仪),用户可编程满量程范围为±250 dps,±500 dps,±1000 dps和±2000 dps,集成16- 位ADC
- 数字可编程低通滤波器
- 低功率陀螺仪操作
@@ -363,6 +370,7 @@ Kendryte K210 是集成机器视觉能力的系统级芯片 (SoC)。使用台积
- 自我测试
#### 加速度计功能
- 数字输出X,Y和Z轴加速度计,可编程满量程范围为±2g,±4g,±8g和±16g,集成16位ADC
- 用户可编程中断
- 唤醒动作中断,用于应用处理器的低功耗操作

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