PCB Piezotronics, a leading manufacturer of sensors and instrumentation, has recently introduced a new signal conditioner designed specifically for DC sensors. This innovative product is set to revolutionize the way engineers and technicians work with DC sensors, offering enhanced performance, flexibility, and ease of use.
What is a Signal Conditioner?
A signal conditioner is an electronic device that converts the output of a sensor into a form that can be easily read by a data acquisition system or other monitoring equipment. It performs various functions such as amplification, filtering, linearization, and isolation to ensure that the sensor signal is accurate, stable, and compatible with the connected devices.
The Importance of Signal Conditioning in DC Sensor Applications
DC sensors, such as those used for measuring displacement, pressure, or force, often produce low-level signals that are susceptible to noise, interference, and other environmental factors. Without proper signal conditioning, these sensors may provide inaccurate or unreliable data, leading to incorrect measurements and potentially costly errors in industrial processes or research applications.
Features and Benefits of the PCB Signal Conditioner
Advanced Signal Processing Capabilities
The PCB signal conditioner incorporates state-of-the-art signal processing technology to ensure optimal performance and accuracy. Some of its key features include:
High-precision amplification: The device provides adjustable gain settings to amplify low-level sensor signals while maintaining a high signal-to-noise ratio.
Configurable filtering: Users can select from various filter options to remove unwanted noise and interference from the sensor signal.
Linearization: The signal conditioner can compensate for non-linear sensor outputs, ensuring a linear relationship between the measured parameter and the output signal.
Isolation: Galvanic isolation protects the sensor and connected devices from ground loops and other electrical disturbances.
Versatile Connectivity Options
The PCB signal conditioner offers a range of connectivity options to accommodate different sensor types and data acquisition systEMS . It supports both analog and digital outputs, including:
Voltage output: The device can provide a standard voltage output (e.g., 0-5V, 0-10V) compatible with most data acquisition systems.
Current output: For applications requiring long-distance signal transmission, the signal conditioner can generate a 4-20mA current loop output.
Digital communication: The device supports various digital communication protocols, such as RS-232, RS-485, and Modbus, for seamless integration with industrial control systems and software.
User-Friendly Configuration and Control
Configuring and controlling the PCB signal conditioner is simple and intuitive, thanks to its user-friendly interface and software tools. The device features:
Front-panel controls: Users can easily adjust gain, filter, and other settings using the front-panel buttons and display.
PC software: The included PC software allows for advanced configuration, real-time monitoring, and data logging capabilities.
Remote control: The signal conditioner can be remotely controlled via digital communication protocols, enabling integration with automated systems and remote monitoring applications.
Rugged and Reliable Design
The PCB signal conditioner is designed to withstand harsh industrial environments and provide reliable operation over an extended period. Its key design features include:
Robust enclosure: The device is housed in a rugged, industrial-grade enclosure that protects against dust, moisture, and mechanical damage.
Wide operating temperature range: The signal conditioner can operate in temperatures ranging from -40°C to +85°C, making it suitable for a variety of industrial applications.
Electromagnetic compatibility: The device is designed to meet stringent EMC standards, ensuring reliable operation in the presence of electromagnetic interference.
Long-term stability: The signal conditioner utilizes high-quality components and advanced circuit design techniques to maintain accuracy and performance over time.
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” 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Applications of the PCB Signal Conditioner
The PCB signal conditioner is suitable for a wide range of applications across various industries, including:
Industrial Automation and Process Control
In industrial automation and process control applications, the PCB signal conditioner can be used to interface with various DC sensors, such as:
Pressure sensors: Monitoring and controlling fluid pressure in hydraulic and pneumatic systems.
Force sensors: Measuring force and load in manufacturing processes, such as stamping, forming, and assembly.
Displacement sensors: Tracking the position and movement of machine components, such as actuators and valves.
By providing accurate and reliable sensor data, the PCB signal conditioner enables improved process efficiency, quality control, and safety.
Structural Health Monitoring
The PCB signal conditioner is also well-suited for structural health monitoring applications, where DC sensors are used to detect and monitor the condition of buildings, bridges, and other infrastructure. Some common applications include:
Strain measurement: Monitoring the strain in structural components to detect stress, fatigue, and potential failure points.
Crack detection: Using displacement sensors to track the growth and propagation of cracks in concrete structures.
Tilt monitoring: Measuring the tilt and settlement of foundations, walls, and other structural elements.
By enabling accurate and continuous monitoring of structural health, the PCB signal conditioner helps to ensure the safety and integrity of critical infrastructure.
Test and Measurement
In test and measurement applications, the PCB signal conditioner can be used to enhance the performance and functionality of DC sensor-based measurement systems. Some examples include:
Materials testing: Measuring the mechanical properties of materials, such as elasticity, strength, and hardness, using force and displacement sensors.
Product testing: Evaluating the performance and durability of products, such as automotive components, consumer electronics, and medical devices, using various DC sensors.
Research and development: Supporting sensor-based research and development activities in fields such as aerospace, robotics, and biomedical engineering.
The PCB signal conditioner’s advanced signal processing capabilities and flexible connectivity options make it an essential tool for accurate and reliable data acquisition in test and measurement applications.
Comparison with Other Signal Conditioning Solutions
When compared to other signal conditioning solutions on the market, the PCB signal conditioner offers several key advantages:
Performance and Accuracy
The PCB signal conditioner’s advanced signal processing capabilities, including high-precision amplification, configurable filtering, and linearization, ensure superior performance and accuracy compared to basic signal conditioning modules or integrated sensor solutions.
Flexibility and Customization
With its wide range of connectivity options and user-configurable settings, the PCB signal conditioner provides greater flexibility and customization than fixed-function signal conditioners or sensor-specific solutions. This allows users to adapt the device to their specific application requirements and sensor characteristics.
Ease of Use and Integration
The PCB signal conditioner’s user-friendly interface, PC software, and support for standard communication protocols make it easy to configure, control, and integrate into existing data acquisition systems and industrial control networks. This reduces installation time and costs while minimizing the need for specialized training or support.
Cost-Effectiveness
Despite its advanced features and performance, the PCB signal conditioner is competitively priced compared to other high-end signal conditioning solutions. Its versatility and reliability also contribute to lower overall system costs by reducing the need for multiple specialized devices and minimizing maintenance and downtime.
DFTg04DjB/Cjpx2ozntQA3B6jOO1HOAeOadx1/DpSHP4j2pAT5PU49qPXIPHvURM/OFWjNx6Ke/BqvIrqS7c9f/1UfIvJIqBjdMMAKD3qE287dSfU88UgLD3MSdBk1GLtW65GfekFmOrNTxaxD1z+dLULkisrcgg/jTtq8881D9mUfdLCjyp1ztcEUwJsHn0o2545qMGZeqqRn1p+9xk7CT060Ei7cde1GBTN0x5KHjpzTgZCOU/WgYdelAC8FiBxTXE5GAFXPfPNRfZ2PLyE85I6UCLG5exA5/2aNy93Hp1qMQx8jBNL5EJwMGgofnsMH8aftAC5xlhkYqLycfdZgfSmmOcYxID9aCbE578Gm4yOc/4VBm8Gc7T9Kd5lyOsfWgY/GOaXAPA/lUfmyjrE3oaXzX6mNh+FAD9vcfypcMelNEq91YH6UvnIB91v4h0agQmD05zS4c4zn8u1RG5A6Rtn6U37VO3Cxn370XGTEH8qAvTJA9aiAvX64UH1FOFuxx5krH2FGoh+UB5PfjFOB6YQ496csca/dAz6kZpT7GgCNpGHOw/hSC4ibIJwfelJIJqKSFJM4AB+nWgCdWRs4Knv60m0Z4PNZ7xypnG4c06O4mTqMilcZfwfam85Ixx3qJLuNuoI/pUwkjPAZcmjQmwZ6YJox34p2UPQr+dGPxpjQ3GOcD0o9xS46+tG1uuD6UANI9MHNJyMflT9hPPQUFeOTQBGc5OB1PNGAccU8Lj8adtXseRQBFg/rSHjnrU2zHPOKbgc56dqAIh70HHAwakKjvRtHGOtAWIvfn8aMMcdcVJjHU/jRgHvgCgOpIQPxxRjp6mnYA5xmlznGKoNxoGOw6UYPTA9qdg9+KMAZ/pSAZjPX8aDjI6n6U7HqOPagd6AuN59CBSYJzkj86fgnODijYT06/SgNxuFHXn07UZXsOOlP2D0BNJsz0x9KYDN3p19KXJPYcfrT/LJyeBS+Ue5HFT1Ajye4x6U3jHTr3q3FZvJHeSoFItYY5p8yrHII/N8nPlSdef7tSPZOkFjcs0flXjXKQ7X5/0Vo1k3L2+9QwKGBx196Ucen5Vs/wBjlLvXLOSRPM0m2vLl2KyrG/2fZx++8t1+9VWWHTo9NtL03QEs91fWzRbl+VbfysPtX97/ABGgZROT0696btb8P5V1Y0BW1LWbW2sdTuLSGyvZLFo4LmQy3MMMbR7X+zxofmZv4fT1FCeFPEN1p9uYdAulu4r2+W58/wAq2kK+VC0O37Tc/Nxv5WId6AOUwRRzVj92yq64IZcq1GE4wB/hTVyXYgye4P8AjTsegOf/AIqpcA9hSggdhQBEFfggUvlk9cVIT6H3pOcE5/WgLkZRB169OeaUIB0A/AUrHOPamg4PWjyC9xcdyDntzSYxzipCQck9+KQBTjJIHc9aQEfPU0E9MDmn4HOAeOP8rTT6YoAjZSeQTn60zBHTFT57EDpik2A9BQBF1GCKQxxnqo5qXY3Tim7X5HIoGQ+RD6UeRD1+bI96m2EYyeKCnHHSgVyMQR8Y3D8aBARnEjD9afgjjtTgccDvQMYEcciQn2NGJM8OB7VJx2PX8aMLnnPvTFcjxLzhxg03E2Qcqc/71TbR2NG3tzSAixP0BXNGLn1X86m2qOeaCOmOhoC5CzXJxwvHv1phNzzkLU4BBP8Aj+tL16EUAVi112UfnSbrr+7+tWSGGOmD0pcdAcUDKZa55+Ugf1qNjdHrkVewR3z2pMAYznmgehOAPwox9eKCSPp9MUZ6euOabEJnqAPagDqT1owTycAUZHQ0IBeOmB780blGOOf5U3Oc8cdOtGR1IoAdn0owx6Um70/wpd2eucfnQhjsep7UbgMYpODnkYpCVHUijYVx+W560AMfXNM3qP8APSp0vLaGKNnhaXM86Sb/ACgEjzH88B6rLt3ff8xfnq4Q5mTJ2Oo8HaZa6m3iOG8kvBELCxXZayiON4/tTtIrSbHl+9Ev3f8AarfvdE8LWejyebpsl6dMl1NbJZ72eSR3km+0fdhlSPZ/z0PXajH1ql4StAkvibULZ4IrZSdMksoy020rMl3FP533SdpdP9761N4l8uXRtWIO5o57bVMjs0MqwyH3+V6yqe7ojow/LKcVPZ7hpOo6Nd6zbRz6RoIku7aVUuLSyw3nzgSG3uFkY7mHlsGf/wBB8yuojmigXVba2WGKLdnZbRpGGee2jaR9ij1Jryyztta22OqWtjfNDHd2JWVI2CP5z+WPIEnJX7yZ+7XatLJHJOEBCF/mb+A/wx/xf3awjV/mZ6GOoUYyTobeRQ8SaxLLcWcU008tuunLOIUeeKN5JxiO63rL1DD93Wl4M1ae4SSG7mMjwXltBDLJ88zQsnkoznv/AHN1Ymtaet7PpzwTwwJFb/Z7pvLY+XHu48qGH723/eq5pmnroF7Ky6hHdwT21rdBgixy/a4LyT5I1jkki+75lZRqxcm072OmrUofVVTa95+R5yFMRdG58qSWIg9/Jcx/0q+W0+VtRhWHyXghWWKW2aTMsnmxgh0mmk42n+CtS70ywVrmVC5kke5lEciYKFpJGk2t5v8AyzzVS38NeJnlcvCIBcQbJmeWLJSUL+78n943Za76FenKP+Z81UTjJqWnz/yuZSq7kqilm/uhc1attL1e7ivJrWxu54bFlF08K5EPyeZ8yf63pz8tbOJoC9s5bfAfJmXP3Sq812PglyYtbkGQ4vLDkd/9FMf8qjmTehxUMa6tT2bjb5/8A86gsGu7W0a0Mhu33AxjbKt2ZpmhjitVhi4OA4lZpduVrPYMrSxscPG7RyDukityK9e1LwzbzSNqGlpHBdlWmmtAyRwXjtFMuU/hWTDk+jY/g3eYvGX9lbusouluIn023kgcrDM8tnZWVvZ/6PBD5scWZWkk81n4/u02z0kciT6nmkGMHJOM+tWbuxvrOSZJ41zA/kzyQlZreK52bjA03+q3x/xrVbkcEGhBayHZODyaAf5U3Oc57fpS5xjNNiHZP50ZXv6U3jjGcUZz169qQDvkHpz05o3DPGKZkDtzR1zwaAtckzjril3ZyMVF6cmjOc+lMNyXAPpk03av403cR0IoyT65zQGwu0Z5xTSijPWnZPAPpQMEck5z+dIdxmCOgNLgnjsPalyeO2OfrSFjzj1piuL065pMnt0NOznGMc0ZJ64xSGN3HsDShvUGjIPJFBIHTv70agIGzk45+lBHcde1KPccfSl+XqMDHTmmIZjv+A9qPlGSRj2p2PpR8vII5oGJlecdOlIdvbNLx1AFNz+BpASjPXnrxSZ703OeuaMg4+lAxOcnJz3+lHOeSKXA69qMpyfyprzAdkdRg9ulByemBx6U3cB0zRuHOQTQAuB3J45pcjtmmZz1z7e1NweSCOPegDQsrE3UE1wJ1UQyrFImzn95F50Z+/8AckwyVO2kqqb/ALQpRDjDsqv/AN+vnl/hqvo9zHb3oSVykN5H9kmJ7Zf91Jyez7f+Alq15oXV3RhhgWHNS73PIxderQqJ30MXyEAIRC56D5v/AGaop4IkjuSEZXX7MVPttkz+q1s+U5Iyodsrjn/gOKkS2SS5sHuFjNvAtzEYrh40hl8mN7nyWSH97h5Nqf7W+qhU5ZWHSxarOxteElkisbuS2KNa6kloVjUzM8N3APKkJ9au3UlxAI2e8it4pX4aWTbGvly2+/8A8dff/wBs65K/Z7Oya0+329yba7n8xtOdYbCSb5GxAsflqQNzjPlbTtaubkuFZ2KhQ7ds9a56sFVfvbHp0+aHws9XW5ea1hSbUGkRo432qqmWJfN87y5W/wA/LWbcM5gcxSKzyCdLcwSxSSGRW+57N/vVk6Lb3dxa2U8w00W6iS3aO6NyJH8slTtS2CbXUMjRMOflXkYq4sQgkGnwSJdyS2jXDMI8TyCCKTzdpn8v/rpt/irgqQozmop6o2jKvBOSV0yT7QsMSYiuXMccbSLmKTy3b/VxtL5v36hvNSfSnunsYrW6QSzxl2EogWTvuT93LuzUUMsUkbXMLbYo25cn7vpupt/JFfraxTXEssaW+ycGRPM+0tNcXEssW6OPO9n/AIsf79bUcPGLckrnNLETn7tRbeRj3viHWr8RpPdCKAFvLhtI1tlSOU/9Mf3p6fxy1sWHiQeXHbzWVw0c6QQrcW93Pbm2dvl837P/AKp/mzJtaqkGg2u2WRI7mYwJFLOgI8xIf+e/+r+5/wA9P7taUVjc2SP/AKOiCK5gPnOizeXPD/pAVLjnb92uxxny6R0OOpioQfLysjkknkdhMSZY7hrVjDFuwF7b/wCJ/wDWfLXVeC/L8rWypYv9ptN+7aMfuZcFRXFXTTyTXEzvK5mkaQs7t85m+bP1rS0K7nspJZYJSkgKkjPEg+6Q1TFWOKnUj7ZTPUB9ao6ro9jrFrJFPuiuWtpbWK+jWJ7iOKb98VI+6Y+ny/lRpupW+oxB1AjnUL58B/5Zn/Z9RWhWm57qknqjzvV7G7tHnS/gt3byNev7QzK1xp8l1e6pCsZVbn91mNHbg/MPyrmL3Q54p3j02K6nT7fd6Xa2zGS51C5NgP8ASbhFhjjiCBtnyt83PavaZ4La6hntruCO4tpV2yQzDdE/v7H3Fcfrvh67tre/udP868iNh4jkZHXzr9LrVWhY7BCnzKCCcj5hu5JFG2xV7nle45cd84I9DSjaeSO2K67U9ItbyWaOyXbcrf6R4f0mOFILe0hSazW8lkujDD5rn76/3uvGf3dcrNayIJ5EVp7OO5e1F7DHL9ikk/13lrJNEPm2/wALfNVXuBGCAOB9KQ9iRRgc445o60CEz1AzSg9aCM8Gkx1zk/jQCQuc8nrS4PYe1Nx0JpehznnPNACYI6Z9aMtxTsnrxikwOv50ALkHHQ4FLn0pmV9hS5Pft3oEKd3AH55pOc8nmlyOM9TQT19e9AMOnGBxx1pfXOKb0wc+9G4+nNA0OwPQYz6UnJximFif507B6nOT70ALn0x7UmG6mlHck9aC3oBx+lABg+4/rSbepzzQCSQegpc9iPpQAoUdzzj8qMKPSky3XBx+tGQaA1DPbmkwMn8qQkD6UvPX8aB9RCT3HNGRScnqT/Kj0AxQgDPTpxupM5/Kl47/AFpcdMYxQAn0I9/ejpgEf1p+3uMZo2kcDHX1oERSIrKwPQ11sFx9usrO9ZlMjbra8+9n7VAkceW/66riT6765faOQSOK09Cl2XU1iSFTURFHH6C7hy0B/wCB/PF/20o8zhxtD21J23Rp5CghmAHvTyoZJCtvEi+Wq+YkfKlW87zN7fxVLEtw0dybMRx3sUMs0U+N0iqkcjjyopvM+f3SLcv+xWtJo2k6zobX+nRRWc7YmikuJJ/O+2x/uWtJrm8uHwGk3j5sH54/WnSUJv3nb5X/AFPGw2CnJc0ZGHfXH26a7nma1Mt/KrOJms0BlVRDHw3lqPu/epi2d3CYCXRDdBhELJPtET7iVgTzbBRA3mONnyS8N96rmgTWVld2Ua3NrMdUSzaylWJTeWWpLJ5L2ssbSb0yW8vd0zsfaU3bpNRtorFo71ba1k0++kvA9oJYTFZ37eYksO7y22pJt8yL5TtaMpgc10VsNFaU7/5noRotK83dkUMiG0WYCYwIsDysIGzGcRwyfJuk53sUiH8Xy9duayr+/wBDleGT+z9U3xloY5Ly8+yxgN5mf3KxSSk/8CqW4k+0wPCZbRGf7NA203IJ2ybop5f3PlfJ8iS/7n3K1PCTW0t1fG308W9/FBaxxs0/2hhNKklu8lvJMplTzWGT+9wueM5rw5UoUnKq0210Pcw1bniqd7GFpKxCx1kXMTLDNp6q0ksUM2YZ5hZi7C3CbisbJ99M7Tu71b0qwa8h0Se5v9Xhtb7WX0pLa2tpAXEcDyJPBNcN5RbeGjYbONz/APbTU8WxSRrpepxTs7SxtpN4d8r7YZJJLqKMj+7lZPu/w1jQ22vvp+iiPUL6K2j8SfYobeFsRWE0z/8AHxDM0v3ss38Xylvmf9583Th6qqwUloFSPJJxZdi0fTov7Nlnh1e5z4sm8N3Sz3cFvbujGa3Ct5C+ajnbGZTuIPzc/PS6dPPZ3NuigRTSWaw3sbTLMJP7O/0eIyr/AKpThV+WoLHw5HeTX0c+oSvFZa5crMY7xZZ3hWITGZoV+QSy5RN/m9nyP3dal1pvh+0uLMaMbuO4Fz9kjtrZ57gXYn3f8sriXcG4zKem3+DmubE1acn7C+r/AK9fwLp05251sQ3N3CZ7hJrcyOwy5Etz+9dk/eSeTc/ddN37pl+7TLFF3SlQQCeO/wD49Ul5YayspSbTFgCmUGa6nZAJYDIskcUs/lxFHWNnjq62kzWcwVLqOSHzPLkZ4WikiZZfs6NcQrMcAnCI6fL03bMVtQj7ONmeBicPW5+dR0+QkUk0EiTW7mOeMYjkUfc/+tXZ6Tq8WobIHUR3oD4iVcB44QvK/wCFci8RVFfcrAFkkwP9UVm8n5/3v3JP+WTUxmdgql2IThcnBH/Aq6FLmV0OlWcNGei/hTlZlOVJB9uK5rS/EMbAxapKsbDe32qSSGOL/lngT/3W9/b5q6YqVJBGCKs9OE1JXRi6lotg8kOo25NtPbX39qTKke+C9mhhdT5it92Tbn5x6/Nv6V5NfsBo3hQK8o3WuoylZH+882qXWC6/3tq17VenFpeHjJtLoLn+80Mi15RrWh6ikdjaWNvLc2+i6NYNfzQ+U4iS/muboTeVB8xAZn+7E+Am/NC3LOWwTgY+tGB0GaFZCoKsCp6EHrSjB681QCY7YPHvSYY8cjFPPHJP0/woxnAoGM5GMDOTSYx1qTa3HFNKnJ45piGc9BnGKXp1p2COo9qMZxxSDcTANPEjokkQWIgnlvLzIP8Adf0puCOB/s0fzoATHQ96bnsByKd05xSdehOCaAEyB65H6UmSe1O55zmm+1AaB+AqQH0AxTP5/Slyw4IFADvwFJnoABQDnGc/40c9v14pgJn6HvRjr1zS4I5zxjP0o9f1pAHJx70v0JwOKbwDg+lLk9v50ANOeOnNJ178g4NGMckmjI5GPpRsUL/n1o5PTHFHJ9MUYPHJp3FYcB0zjJ4pcL1A/rSD0Gc0uR14JpAJ65xx1pe+QRR15IHpSg9c4oATk9e3NNZWxlGKlGUq2OQVbcD+Yp+T2780ZGCABzu96CTrYLtpBZ6nEWh+1rvuPJOwxzfduR/c+8u//ddKt6fcyaVqLWENst9Bqk1o9lBJqH2VEuFcwgrNgwYbYUPy/Ntj29q53QJy51DT3OS8bX1t/wBd4E/ej8Y/n/7ZiuhtrdL6wvLaN40l/wBGizBbwRsTJJ5ltL50cW8vIybN3m/e21n7RUpc79Dx4xdGu49HqV/EWn3UtzLqQtNPMOr3a20tvpE7XwW/YfclbyUw8h/u8M6DNXtOWLW7LUk1q71GS901/Kms7u9WwtWf547czv8AZ/8AWbx5Y3yu24E961NN1HRtZ0m7t9b1nT45LyKaw1eC/uoIZFuI24uLVJFSIAn98hER+ZyN37uuVt9TEWr2V7dWou3gH9m6w9tIslpqkSkQpdW/mRDEmFSUMZfmKcbK9ulUqVaaio7bP/gs7JxinzN2uUtMNjeMkUyGW8UGVw1x5cNzHGu6SFTDDJKsn333btvyVs2E+nRqLaNrKK5v44Hs7lk1OaM3ULNai2v4oXTCAuU3eUMs+/Z0qfxBqGg65/Z5tobixuLV5Cb3V2Voo7RQ2+J7a3eac4KqYVKj5s+p8yq1rLHdzQiG/khj1C3v4RqDx6XBKn7m1eaW0WKPbvORHjO1X+ZP73jYrl5m3bzVwhy0/eiy1qMk2jvr8cNrdi8byJLOK+tp7lrdGvFZIQgSSJxIpZPMEv3oAN+SNuA2tXyWkl7BdQ2FwBCDGDiW6uWmm3/ZYYgYUj2vmbcuPlVBn+LYnbfba/su72Oa30uUNYJe+e10LLfceYs3mlQsWTKfuf6w7U6bucaDT1/taxis3vrq1mkay1K1mnjg8mFOk1tIkkXl5ViPmU5GPdcYQglokj0KdWdRb6HTR+IJ9WiuljuZZLqIRCa4vbaKDdDNGP3kstuogWUMBHFu+98n8a+XVdb6yt3s5IDeRTxIqX8XmSxSy3VukluboXWzzwGYBPKVkVVU9PM+XmYbi+eyvktriOOdIpY3VJPJubq11KVIZI2eNwWXdsOx8gByRVvW71zcwNMFXUrWxFrPdRHy49QSG3hmiu5TN+9eVssN7ZVsKVzRGhCMnJLcJSn8N9DSlVrtg4ktY5XKzvMLG+upUKnzh5txdybf9ite2ka3+234t7W1+zrPBq9qsCzxFJtmRPYxrCzpKr5iCttxGu6sSbSlebxKJdevbv8AszT4761kjhmxeGaymvP38VxKzhMrhiFOd4Ykdani0LQpDpXl2OqTNqGhXl4Ev5kiRLny7aRHtTZRIzBRIzOpwCuGz2rXlitkRLmlZzd7G5CJja2N1BewyWUkCbJbjTZ4Li2jnSNUjZJHcMhzt3K5UMg+cUkcaeS2+TZIkf75W8oRRr5X7zdJD5mE/gib7rVmaTqt7HNqdv8AK3kfZ3i323lLFxtlC2n+oQSN8+3aPm3VMmoyRsYSI4zby4iWSPEYgh/0ceVM37oRSbPu/Ov364oVJupKCsv69DgxVKFOKqK9mW2RkZ1YMrqce4rT0vW5rFkguDJPZDzTlN0lxbfLx5C94+v7v2+XtFWXHIs3cZPXAUYP+e1TeSvcnNdlrep51PFKDujuVuLe4gt7iCVXikRZYZERSknG3Denv/dPWktoIrae9vYo7h573yBNNcP1SAS7EUKioAm5+K4yGSe2E4hluEE6/vjbXHkh2jheFGlby5Nu3+8uz/b31VYWUjob0PMo6veS319IP9vyruXyv+A+VU8z7HY8ypRRi+ObW3ttXjmtbe3ihu7KOa7+xIptzfNJOpXK/Lv2bPNC43ff21zAHoRz7V2l06MslvER9hZ97Wxhjht5JP8Ano1v61g3Wk/6yWyVmXGTbl/3qevkf3h7fe/360i21qPD5nSqy5HozJx65penI6d6Tcp5BUj0FIskUhwjqx6lVO7FUj0tx289un0o3MOQa0n02D7FohtxfzavqhhuIYI1tXtzaM00KQqn+v8AM3Kzf3dtU72xvdOuZ7O+heG6tm2zQySRnG6OOX71sxX5lZej0bj1IC2eSD+VJkckj9KTHrnn2pQBk54H50DHAjvnmjAPAxQAo5Bzmj0wRQLRCEAdQRR7jpSnPXNJkdccUAGOuc+tNI5B46UbuoOfx7UvXqDzQCG49Mfl2pceuc9KXjIHGKdj8+1ANjcHuDijgcc/40uMcA9KTAGeaAEz0x+NHPoKOOh+tLn6ZJ4oAT6d6MDoTj8aXI+hFJ3JPWgCPnoelOx1PHWm8npn86XJJ7UDuKCe3QU/BPJP/wBekxnrmlx+B7/SgBRtGc9ulJyewpcegPpQB3GaYgAJwcDijHXOMd6d6njkYpM5744xRYLiYUc88mjpkgDP5UdM06IR728x4lAhkb96ksm513SInlQ/xn7nz/L/AHqLAMimltp7e5iYCe2kW4gPT94p8zH0PQ/Wu2t5YRLBdxErZX9upUt5p2wXPl7/APU/xxsv/kKuHbJ7DOP8iuh0G4aa0urAgb7Mtf245+aCby4biMf7p2Sf99VnOCkuVnnY6m3D2kd4m5qbXL4CT339mzyyzokizx263E0skkjQmYfP5g/efLK/3mrJMSDnArQbUpfs32OW3mlKrEI5XuIgg8jGGijMf8arsk/e/Nvb/npWfJIc7V6/yrKjGSjyvoeBWnzy5oyJ7OxmvrlLSAAErK5kYNiNP9oQ/vWb/nktXrrTW0r+zJHjs7y186b98tvELh5ZvMWNbiK7kkiMefkizs+4f+ulN0eQ2iXkqO0c/wC6ZHzghF8z7rfWq02pRTF4laK5eMxzGLy2miVF/fb2b/Vf+Ra82pXrTr+ygnZeX9P8UfT4XBUvqntN5D7i9urNY8RRI2nrJayRT3sbST2z/wCrhlt18mUp/wA9GXf/AB1zFzpN5ZK1xE1tcac80drBfrKsdo8zQ/aIwy3Gxw6qRww6r3rXF1LE9t5SpC7F7i3Y23lHDf7c8X3f+eW+rdmRay6cb+6s5LGZ2lEUl3HJDGSPIfcsJEsT/NncvzKyr98x7F71zRjayM8PVlCVpqx0sQ0e0srbTo4Ivsn2ePzVK4ljPmKyXazQr5vmY+bcf4vuV5pfSXNvcSrdfvZrS8a1mluDvZJoLjdtPpnafwzXa/aVW1sBI7F/I8pCzSOZUt/9F3iTyo2Zfl+8kRrBvbu0XUdYlNytr9qsvtDslu1w91MsdvJ86NF5CtI6vsYfdY/jXm4BzVWamezXUJQjKNrkstz4wu9R8Uw+fDFdvZsdRjtA0wmWPzYRBEbNDlz5jjNRwadrdxJ4SW6vNT8nUNLvDbRgC38i3is/litpLpvKKuiR+mavQ6jfXutXklvHrOoWx8uEzWUc8Mgt1fzgd9v5aq0bkv8AeRd2fkq+9ha6ZcaUZ7O7n0s+ZHHbX1zGJbKWPPmC4it4pbNzt/eKowP3Y3elev7SF+VtXOCTkldf1+Bh2VrDY3E0hvo5IoomBSKWUyzKpVmtYGEfkvJHt3bk3r81aEkttcK7W2nzCAK15HNclhcAW/lw3ESCaWGJvmZfl+9+8qxd+f5Vu7bpdN86a4sUt1jti0fmtiDUNUvzJIkkuN7jad2SM7MNbt1S/wBMdmWzsdIsE3T2Yaw07zrxn8iZF3tbN5SY3L/y13bow3SPFZtRjK9tQ9hGvHknL8v8iSKHZHbyRXFlIJIJZ5UW8sxcQRwv5chmhmlRht+fzCm9T5daCZG4NLE2weYxtHW5Hk/8tJl8n90Ujz+9qjYarfSi2vf7Q1CW9knlZ7K2iitF3tN5hXzp4ppQkjb2H3B87J8nSrV7AbZFe4tdQtbW3YyK1tbXlzBocn3o0tru7mjgZCT+9/dbcfJ6Vam5bHl1sup0/ejckuVliyjoysU3jPGY26H6VmSZO0A9KlS6NziCKzm8+QnyoYE2R/avm88wQwx/NG6r5mzzflbd7VFJHKkdtI8bIlzH5sDbfkkSqi/5j57F0XF3jqvn/kRYJppXPNO+n86CR37VWqPOT1M7U9PjvI52UrHcsojLY/d3DZ/5aD+E/wC1/wB9V61q2kaPrVubPUrdXVGdLWSIKlxZsz7Ue3fbuB4XjkHbyCteaR5knso1zhr3T1I/vf6THxXrLf6yT/eP86o+wyirKdNqT2ODk0C90rW/C9zzPpGmWtxm8Qc2qWFhPJGbtFXyhksMEMQ2P4f4uRtra1tvDupag9rYSyy3yaRHLcJv+yx/2W+oSyWi5j2yhtuGC/g/8XtaSOmNpIyen/Aq5PxF4TjvdLuLbQIltriS8vNSe3lkcW91dXafZ5Cdz/K2zLIAuBjBApHtLyPMb/TW06O0a4urQ3N1bLcyWsDSNLZC4TzIBK/3SGB+XDZG4ZDVnBwwyhVgf4lrvtSiC+MdYmEDKmkaVqeoQxXVvhXSw0qG3gulWb90R5m7YwXHyVxd9NNdXl7cXMxkuLi4Zp5mSBGZ+7sLcADp2Wn6gV8nkUhyOT9aOegNGQetMBCSaOvIHOM04D04z7UY9OmOe1AhApPXPHWnbe4JzScnHYfLTxgbemPr3oC43GMHnPajBHXpmnMCeBkZ/SmkMOo5oAPlFNx60vU4/wAilwB0A696AGAd8GlPOMUpPPFIc44zQAn5Umece3enDHfNIByccnvQMb1PHXFKF7YJFIq9MEjmpMADBxnvQAD0JFHI7H/GkxjBAIp2QOoPPWnYQeoyAPQ9/akznjBz3o6k5AzijJ7gelABnpkUZPQAZ6Uf0NLnHJ4/GgQYJz/n+GjaOM85/nQpOevBP1yaUGhAB9gKdZ3T6feQXgQt9ncOY8YEsDfuZYG/66IzUw9snimyKCB1zSsK11ZnX3SqhYQyFoXVZbdzyJYWG6OT8jVOJk7EZzz9aTSZ4p9PEbBZJNMkiDxsZBusJ5eB+5/e/JJuT/dnWpLm2ngbUD9ltYB9n+1GCcwtLtspP3n2eWf/AJa/K/mp/F83yVMpW0PmZYLlqSg2TxOyxXdzEQuy2vtr/fzI1rJJhdvU7d3mN/Csm+oootGeGQ22sXFsJH8waXqukz3qHcyNta8tHMDpvwPnxkgbulOdrmOW88y8t7mG+gWS7TTpY4Y7n/lj5eyGOOISbS3mKv8AwKkjtvDQ+ePxFbRlS0jWut2V1bXKc8RySWzGFvqiisoS+89vBRjShyJj4bWxMey8nv5vtHmAJp9tBZCV4W85BdXlw8k4jAz8qQcdcHHzNS+EU6BlkCuZ7S4hgkgtkltv+eOfJklz1+b7zKdu81a0m40cXYuL3WYL77LJ54s9N0nVLozJsmh/1zIigfN1OfuVVuplQPJCL2CC43W7QXU1tNK8NtN5o82K36dS/wDsN9you3pOxeKkorcuo19qEXk3aajPLbz3VtZCdp7rUY7lkXUA72920cAEcYbb8qbsjAPl1VjtdKumS6C28kjadeX9xAq26GLyDJGitc+bPEhYDzI91vt+ZU3/ALyoYhdzx6he+dM4hgVbljI00rR7ZPvLP95FCv5X+5Vq4sdUxe2vnSSG002DWIUWPy7e8tPMJlmTzvLRfK3f7dS2r2bOeM5SW1y3DqWoWWm6ZDE0RjYSzmKaBW8v97J+7ii/dxL/AN+qqXN/f3MLxXF00keYn8ox2yRCSF/3cnlQxR0vlD7PpyHzmeOC8kP2KznuvNh86TdL9pmmjgX7hSJfK/g/2hUCz2Uc13bXAgldw9tLFd3qZjeWSOaK7gi0aGZQIV3bv3v8f/TOuGnhv3vOkvU9e06mH5Vv6jIJ50MtulwkMN7Jbm5e4ObdjA/DzLN5nQlPm+9V+SYia4W3vbS7uFLC3vbxWkmvRDD2upLdcOdw+X5/ubGf7lZX9t2itJGdB094o2dIyLrV4rgOreSrNP50hdMA/KV7/wDfWedUvRBcQgwRCcWwlcRL5jJDK8wCzM0jLHz82OvOeh8z1ZQU0eZRoVaerepsz22uTCT7brQaKL/W7pp0ijWU+SmYmt/maTb+7Cxbm2NmptLn02223NreJFqlhJqBS9stNe9e5t5YdyTRS3Pl26iPdL52dgwP+B1AJLC0m+0yai13cXAWSV98d9EjRvbctLbw+QJ48zbGWUEKnDp5imoZtb02MxlnllMUzqTJJBbyGGHzvK8pYfO2Sbijv9zbs+XHmfuXGiurOx801aV2/V/8MXpLiI2K3Eepale6VBcuJYwsbvp8+xTbzzot35I3tu8llbaGB3bnylOtxZrBaXBgunhuoNTlAaa0tWuZLKaOH/RB+8fzPveYjN3+V3/5eMODVZItQa9sIJ5JbpntvskUEcltdeciQvZ3ETYVzKR+9QRJuPzKqfLVmws9Vt59TWbRmsrWO3il1iKSZft8enSvJMjW8V6/JUquxgryKyjB5AolH3bJnLVwcJrVffqabwzRoZdyT24SKT7Vbxz/AGYiT/bmjjxULOAMZwf5Vd0rW2nFxHMpnURu7pK/mORL+5/ey/7f/LX+9WNqTQJdN5ET28EsUTLEJJZolLeZ5gidv4P9n+GuGhipSk4TjZnlYnJ4U4+0g/l/kamkmNtU0VZNhibUrMOD0P7793/49sr1PJy27O/LZzXjdgrme2dJQkqvE8I+YOX7bG9a6TT9c1m1aKzjS2ktLM/ZhFcRTyTtLtkzBFN5ud/+x/wBf+eVdftYnfl1GVKFmvmd/wBNoPUHmkyQcgkEba5iG51DW9QMtjqN5psMGmQXECReRNb3V207x3LzbhvcIBGn3cofvKmfLk0INWkjlFrq8KWl265jljfdY3adpIGboO/0HzbMin7RHqcrMDxKdQS71i8ZZTZt4RudNWZSxVbq91iKNo92/dkKUOM9Pyry+RsySE9SzYr2fX1hurOy02FvPurnUNJFzBEGLfZ/t0M0rMf4VUL973rlPEPw8vbU3V3oaC5tA07myUyNdwQ7OEilkyJMEOcbd4GF/eZxWi1JscDkng4ox154pqsrBXAyG+YVJj0I9qoYnI6/zowOo60uOxz0o/AH8etAheTwOnU04Dqc8j/Py0zp0I/lTgTzyDQIeoDA8dqXg5AFMDEZxgDGKbubPB6+/WmA/YMjjBxxQFPcj/P96mbnHQ//AFqTc54zkmgNRzAAnpz07Uzkdccn8vagluRk/nSdc885pDDvkdaAxBOPSkPHP50HGRyefamMcMjqee3FOHfrTOT36H6U/H5/XFAbB1z0/wAB/s008YyaXHqOfypflOMfT04o2JGjA5JpflOD67u9JgDgGlx0+vWgaDn2/KjGQM54oyCcdyaXIBIGSKQgAXjj680mQM5JGKMZI9KXaO+MAYoAQADk9+aUgHg45GKOOScgdBSDjsDTAm069WxvIZHybVxLbXyfMu+3uP3Mvy+o4P8A2zWtq7R0kniBGUdU3oPkIbo+5v4ZAyf991zbA9SOTXR2BW+0xXI3TWLrp9xkfegeKb7PN/3zvi/7ZpS1ex5uOpqyq9iO3hmF7DZySxb5HkRfKnimHmRrJ+43w/ut8jbE/wCBpVjzy0FyEk2PDEZZkYYltVik8kvPE33djNs+b1qO5EsyqtxPK6RfdSaX92P3Xk/In+6q0jMZElDpDPIU8pRND5kzbf8Allu2c/wfL5tclWg56s4lOjUadvyOq83w5CqqdHaRjFA7Cdt8ZLW8c2YvOlk+T/tlWdqUq3UViLXSLfdbXGI4o4fMMwaLHlyxWsUe/wCZU+Vf/RdF5PbR3It55UW6WG08yCINPKP3Imxi1En+xUFxbSSw3Ksbi0e323Eb30bWpk8sSfdH/Hx/5Crx6NKUKqbv87/5n0U1SVHlilf5DVSCxkihmudQhabyDqMJtZ7KaFTH8q5uN4YgyOm3+JT9/wDefM9JXszKIrO5gWG3gl1ZLq88u1u7eaSGP57abBEUoOzaC/8ArF/551StL2C1jmt7qV5LaVJfNt0u/sgd5fveaVaSX50ykn/fXz0QXhtpdPk8vT5Z7SKWOJpY1cXKT8gSwtLsOP8AlmV2ffr3Ywb1X9f16HjKpGLujXnKXKGby47iK7n+05SHW7jdqRF1cGxg+zSbfLgUskjJ2wf4PLrPvmu4UvreYXUjwtbpcRC3lstOh8pyshn8iLzXSTLJu81Plkaq2NRlBtYoLueOPdcG2hjkaMBv9H3tFD+6xt+Td/6HTbSSa9ZLPzZcNFKbSAS/uprj+G1Xd+6TzeUz5X3tqUnGzudNLF1E7QW5kLN9ruCkSWltLJci2ijmMsVsizSfZxGxboFDbMt/CnzDtWkulOo8QC6120guNK3QwQ2UElz9smWF7xGSWPywA4Uje3OfwqvI2k2uqzzwW0s2nR3IYW1zJIHmhVUxG7wtHkBxn7xIMa7hncav2OoRSy+IrmGxhtrR7a0eZH2XkiRywrp0v71miULIGZ5T5X3gvH7utG1GN2d0XzEUWn+H5IvDE6jVb66vdQ0qDUIbyeCKzkjuImklSKW1/fgqQOSRx2rRsoILHUNXWPR9Ftre5s9GuraPWlS9l8u5Ro2ew8xpJSshLFxtfHQ461DB/agBguNTmm02PSGOkStKvlRJHLDbxKv/ACyDBWkRm/us1OsrYXd7Y3EltFFrWlzaVfXS2arJDfwMFEUyGP8AdeZlkT5f4qx9rfVbGnL0Ip7ueHQ/DEd9qt5NBpuo6bLBHZxtgpC80kjQXeOHjV0VCWHbt922IopJ9ft0jW41aaJrVrW7ma3ea1hkLDyJoW5MmVkkT/dqlbwJaae1151rdQalqcmn6lpEkq7wN80MdwieT8rrs3793ftVwWdsmo3F9d28moQSpi3mhdYjFcwTSZF1N5JlEuBjcnu67+NqlJ6Xdh80empS0W1mma2tkUw3l5NdxJBcfu980cf7uNi33Puv/wACdauGaWKKZk8uWCR83ltqT4jlHmJ5cKwwxb1lj+b5t6fKKuRJFcSn+1LX/SrVoreXz7yW1eWS4ik2R3Dr+9MqL/F5Xzb/APnp/wAfEdraXdzJdJaCKaSOe+jNqFu0aZIy/wBxpYfKyV3PFunRuK5kuaXn/WxMnNR0Tt/W5EtrbvHHLYnfaQ7hNDP5X2i08yKPy0l/vD/aT/npViGSF/tCXSh4YmtowzJ5kohkSOb5/wDlq/y/u9331/6af6qr9p4Z11Z/MJiszu3pJLcRG4jSYRw7GC+Z/q9n+61bEfhmzJaWeaQPIyzSx2afZoHlVPJynneZKqbNvy1uqUnZM5+Vptrft0/4BzIa4tpLmcOqTOYJIppJ5fskv/TzLeQfx/wef/e+/wDx109lqltqqy2V/bSXJD7dwidGWRf3IefyV+ST5f3cq7F/655HnXrfR9ItlAisoC3m+eHn825KSeX5XmRfavMC/wDAav5YKEBwi9EUYjH/AAFa0hScd2aptf1+pmW0esWc0UVvNHLYMGeL7QWW5t0kK/Jt2c9c7unyfMEfMtXZlkuY5UlmlKyR3Kblb5wlwsil4l+7nafkqXn060Y71rGKjsNu55J4h8LXGglpoi11pOfKjuUTm2X5fLjvRH9x8nG8cNkfczXPbSck4xmvewWXeVwdwaNgwUhw3UMrdRXA+I/BWBdX+gRccSSaYGyf7pNk36+Uffb/AM86tBc4I7RnGc/NSD0wcjg+9CFSHADZQsGDDBUr1DK3zZoIHYnn2oEJ656fnR04ByafbRXF5J5VrFLcznkx20c1xIf977MslEiFHlikRkljbZJHNG0UsZ/6axN8ymmAzPuc0mR3x/jRjnOBTTzyegoAUHvngd/Wl3HOBn2o25xnOKULRcAznGe3pRgdqOO+enNHsB3pAIV7559KZ045p/XGe1GB0NAEYcjJzzTvNPfJFVwMjIPGefangkdc5JpjJ9zHGDzinfTr8uajjIJPcd+KkIxwf9rOKQgz6np+NHPvn/2Wk4HHccden+9S4+mB0oAU9iBx+VNzzg5p+ewFJxk5xkdKYACcZ4zRz2z+NJkd+1LgHOCPw4oFYXqDz+nemkMRyeAPyp2Rzxk/WjgcAgHoeaQDMjGCM9ulXtDvYrTUIluXVLS8VtPvGPIijmcNHP8A9snCP+Bqmc8Y61C6L8wYZDdaCZRUk4vqdzP51rJbqkENveafIEaWE/vXmg/c5Ik8yJs7d/zb/wDgFEMqzwPZzXEkNnHd747aNozbC6nLzYii2+Uh+/LzKAob6CmW102padZ3jMxnRV0/UN77ibiBI/KkPzbv3qYf/ejarthdeWwgvNTMOm20ctwlvJb/AGq3edZfMjDW0ONxDnzNxbrGP4KlwR89Tm4V3SqOy+5fmifzNQkc2atqdx9st1kNxLd3qRRBfPhni/1UcQfcv8P3v9us6WGSFpNsdvMN0DAxL5IxN5lx1mn8ovHt/e7P7601RK1tJFc6rNBNeRwSabNeSQRxTmB3tRstt8k7QPG0hz8i5Hyo+RSvFoxtlNpHLfM6xFbm9eaWOV45Y8/ufN8nv/zy+XfXI/cZ9fhZ3jy9v682y+NVkLCWPVdVF+52X0Wk/wBn3MjtHJ5McsSzRea+Aw8xf/iaL1J4ll1G2hgtE1Jo7TULS+sbNLmHCN5lx9mhmm2xyK5F1+6DYw+zH3atjd3EcqiJbJIpV+yqrWsSQRbvMh/evaJuVPm8uVhL8v8A2zp8UWmiW5gvE8MxwncI5H/s7Q2QElRJBc24knbDK68wbTt7pJVwd9Hr/X9dDnxNPXTrsZ7xQ2sNwn9tB3tLWRdMawE8kbO0jCSD7R/rUBKl8fc+66uPMrOvLXTS22xlZ7Z48GO98oSkStJ5YiMP7r7uz/gSNt+Stvyxa2ipOmm/aYZ4Zo7s+e93fQLIs3n2+3y7UwOrPHF91Zdv3keMU26uLMyeII1u53/tA20kL2MXl2rz+ZHNiawn3coyk7kn9Nv+sarWjtbT+uyPHleGkml/XnqVoIoL67ttQ1Gzu5PKuY49WWztYHg1E7NqyT3E80cCSS/KkibiSw3L/rjVewfR1XWZvKLWmNEa4hlKo/l7pLe6Vfsku5cMXkC+aCVUln5rRv7GGayhubK71+bQrR7DTbOxtrVI/NvrZPLLSeZ+4jUuwG5kZzJI3yN5YLV7u0m0+w1DzLKTT4XttGSKG4uPtGoS+ddSTSTTxbfPz1TlFXdu20T2sj1qCVlfcrabIsJntoWZrTT7eW4gvLS1ktPtMdteeXFdK0ZLF2JjfJ5wgXsDW5Fpv9pXEl5FcXV7c262G9NTMVxPLDKJplNjP9rk/dhhu2vEvUfx1h2RC2ctzb/bGis7GxjeW88p4ItSl1KGGSOEzQ8RyoBJj0yueK7vQ2gt7KFIYI4DMZLieOF/MiEzP5ZEJ7x/L8lRC/MzSrCMtzOt/DWr3sVjJqksNrcIAbtYnFwbiby/vNt/dK+//WmtG18L2kCsLi5uLncJTIqRxWkZZriS6WV5Y/MuC8e792fN+XZW+jK4yDTx3rb2a6mUdHdaGfb6JoFthodLsjKu3bPPH9puAV/jWW58zmtIySMpDOxH91n4puPSirSS0He+rDFH0o/KjFMQnvij8uaWjgdqAEwaPTpR/k1FNc2tuC088SATwWwTOZGmuP8AVw7F+ffJ/dpDJDTT6VUe/jZNRSyWG8vrPzYzameK2Z5ouvNx0X3qKw1S31HzhBFIoU7ldkl8uWNVjHnbZovkfdu8pX+ZlQMfkp2FoUNa8K6RrcqXEhe0uy0ay3NrFHIbiPd9yXzvkZ8E+U/3un39tNtPBvhC12M1g97IrMd+qTSS/e/h8mPy4R/36rXl1LTYxeO9zFtspFjvsGWRLR5o/Oj+0eRF8q/7X3aoRa5bSz3qSKkKwLvjDebLcXUXl7ZGWG3SSBhubZGqT/NzTF5GtEFgiSC2C28EYwkNoq28S/7qWyisfW/D2la4BJeZhvY1aOK+iGZ13L8glT+OPp8r/N12uc1rhmY4VZATHFIGKYzu/wCWe3/W7v7608KzHaqlmPAC96nZjPF9V0PVdGlCXtuBE77bW6jZja3A+biKTs/B+RvmrO2dx1717feSWIhubfUWhEMyyCW1ulkuDOJP+neHe+fyavMtf0jSrILe6VczGye6W1a2vI5ftNrJNFLNGYpv44/lfr8y8f3jVbjs9znsEdabg9ckc1ISB0zxu9qTOMdP8aQhuD2I/hpcL0Gc0D1wce1L17jGcdelMQ0qRjPXvScHII+v1p2SOhNNznqMH36fhRoMr7SODjB96VUY4OD6UoGeSB1pykjAI4BpDHoNuccZGDjvS4br7/lSDHzZPXkf407PGec9qYhvr15H507GB1A/Gm89zz/KjGOvPrSBigjuRRgE8evHakz14pQfQH8+nvQCEweo/KlwDkHOc0voDj/x00nPGMflQG4qjGRgE9c+n+7S4Geh560nsc+3tS5xyc4PfpTAcc44PIPpUTjIAyc5p2QcZPPy0v0IpAafhu4EN89lNIEg1QfZGeX/AFaXUP762l3/AO9+7/3ZK2biF1LxuJEcfIwziRD/AL1cZLGGBJPB+U7eCD6rXdLcDVLGw1QAedcL5Go+1/b7VkP/AAMbJP8AgdNHhZpRslXj0LTPf3drea8IbOPyJLPS40spLTTgZlZI0nvbqZ/tIQEqgCSKzYPKrg1SnOuzWsLWFhFdxtJds7WUcL29ncjb5ys0Fv5Q/hl/uNv/AI/LqF4wSDgEp9055qCRVwysAwJyUJ4J/wB37uaxdO7ujGjm7jZRj+K/yGrZ6yzO15qNrbnbtMct7FMQP+uNp58v/fdaELx2sEiRXE81wZ4JobpLaCIW6/8ALVYpbjzJcSLs5WJNrIrVUjHfj+VWFRBG00skUUKnBkmdUj/3ctU+zs7yZlPMa1WfLEfDM7yxi9Bvi0a21mL+8nEEM8jDyz5nmcRj7ki/7X8FWS0sIntYm0y2vrB5L7STGiz3cjySTQrafaWXcXTlMNC7bo97bNlVIjpV0rpa6jZyTCNj5RlXLbf32xP+Wv8A3xTWu3RLJYo7eJ7UQokscXlu+1SsjyNu+dJFI81W+Vtgb/lo1RJczuv6+81o1pU1+9Wvf+tfxLv2qO1uzrcFpquoW88UvnLOn2EwX0yC3llilsVDiRd0iSFYOHf75eRaz7qG0tLa7slXT4rj7To819fLfrcR3UkzyL5x8vzsQKwD4c72wGIH3aqyf2letexx/apZbvdc3KQnYju0keZpkWWOIc7Du/vBayfIubQatazFoni8uOa3Ii/ePHNJ8jH/AIFvqkrrlb1/r+tj2sLWVRX/AK/zJdKuLp08Sme6kkY6Tbyu0pMo3/2pZw5Ak4/jf/vuu80R2/sjQpNzM76fbSOznq9cHpZ8qHVrsRxsLePTla3l4juYZ76JTH/30qPXoGnLANP0tbYsYBYWj24fmQRtFujEvlfx/wANXDdnVN6XNu1uOgP0rSUhhkdaxILe7JBWNgD/AHuK1oY5UA3EZH41qSrsm+vpR60fU0fTGccfWgpC0YbAJBAJ29MVkXM2tskSrEtp85juZmkBgt0gZrjz0u/7sipsx5W5d9UGtjLfWlzqN5GRevZwXFvbrcvE0P8ADC13D+6Efyl9w2b+EZP7rQjoJJ/KEJEc0hlbankx+b/yz87Leif7VZkmtF3kjsrW6uStvdSyy28DzPC8cvkpmFWj3JzuwsuWUfLVUXMSyT2VtFd286TNI+mXUkgsrZI5fmmnitfupJn/AEePz9rVItxqM0rRWf8Ax7zRq889tp8tjLDN5n+sZ7uX78f9z59yiiwb7E3/ABM2tre5vp1tp1nlSNJpnitr5LhPkk2rFwf+ea+U+3+LeadZ6XGkBeQW7vKdtzHaxrHb3sELfuo7zz4fnkj4+dIkbgUselXG5mae2G98332eC5MV6Vi2xXEUUk3mxSR8fMkvb6bbQa0tJHkuLx98qRoftU7SbIl3eXGkf8P+9s+agEjEuPL+0SQyaTDJfvDvuUu5Z7+5SGBnhiubOW7SSKVApPmqNjcHO8tVm1g8URi3S6ngm8qaRpJ5b2W4E8Mki3B323leaHCgrEy7NufuYqa68R6XaxvmUspuFhj3v5Ebyf7PnpzWM/ime4s7i7tIfOhjjnMUVtbT/aJJofl/iXcrL/GegXcalstQbOkuba2keOa4kdHt5Fa3njma2ljTdxC0sEvmmOT+6fl6e1QTajp9irxI6hoeUgtQoI8z98fK9v4/krjbXUdR1JXuLuEFIYkVA4nP735/NVhbfvSB8v3It3LVVsNNlE8l7eXEs8Udxcy2Uk8D263Mkn+j+dAnyssePuqVx6VHMnsV7Pq2b994ytLWUW6226fyoGlg/wBdKrT4WI/uv3XG7ft+9VK6v7hfNu766uHh0+0lmmeN8HLSx2pMUUPlRb5N+ygWVpFcm5ZbMTjZuitrRk3XC+bHJdXDTMX8w7uVHH+9TLuwj1CHVbKSeOGQ3WnxNJGfNH7iH7Rsb/Y3SJ/37ppsemyOWim1XV7to4ne2t9u/wAmzdo47eHzPvSywffbP8T/AHmq94llCQadbl2Mrz3Nw4H8UarGqF/+BM9blvplvpavAjrJOnEjKMVyniSRpNS8vd+7tbW2hz/CJmH2qTb/AN/BTRLv1Mnex6jGOvH/ALNRuPYCmcnGD29aXI7EeuM96ozH5I5HUUEnPI6nPRaYGJJBBp+M9Q1AC8nsBnr/APs0ccnnP060mD1z/wDr9aAdpzz0x1oD1IwMdMZ60AkZJH19qd8p5wOKPUYOPrQPoJk85A475p2ccHHHSkyBjFKQD3Of50wFHUcAAfjmm4HAPBJpx4wCOO9Nz2Gc0rgABB/hxSgkevPHX9KAex25HNL1yARj5jQJiqM4z1HQUHr2GPfNABOOnG6l+U5BJHqfSgBAT1BOaQnOPb3pTjjBwMdx/nik47ZJI+uaAQgB7DjrS9cZJx6GkGT2xil+Y5wTx0o0AaRnA9f5Vt+F7n/Sp9JlYBNTX/R/+md/Au6I/wDAwWi/4EKxfqcnP+dtNJYMskblJI2WVHXrGVbdGfzFBjVpqrBxZ2rgjPBHLcdKpyfeBPToKvm5TUILbUo/lF9GzSKo+5er+7uYfz+f/deqciHsP/rU4nxDpujVcJCpgY5ps8FtcosVzCksYbcoLyAxn7uVZW4NMViMAg+1Sbgc1LXQPepy5olSKw062fzYLcB1O9ZJpGmMfuu7p9anbHHNKWABBP0qF5VBxyc1Njfmq1neTb9Q3OhLRvJG+GTdEzRnDDFM 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” 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Conclusion
The PCB signal conditioner for DC sensors represents a significant advancement in signal conditioning technology, offering enhanced performance, flexibility, and ease of use for a wide range of industrial, structural health monitoring, and test and measurement applications. By providing accurate, reliable, and compatible sensor data, this device enables engineers and technicians to make informed decisions, optimize processes, and ensure the safety and efficiency of their systems.
As the demand for high-quality sensor data continues to grow across industries, the PCB signal conditioner is well-positioned to become an essential tool for professionals seeking to unlock the full potential of their DC sensor applications.
Frequently Asked Questions (FAQ)
What types of DC sensors are compatible with the PCB signal conditioner?
The PCB signal conditioner is designed to work with a wide variety of DC sensors, including those used for measuring displacement, pressure, force, strain, and tilt. It can accommodate sensors with different output characteristics, such as voltage, current, or resistance.
Can the PCB signal conditioner be used with multiple sensors simultaneously?
Yes, the PCB signal conditioner can be configured to support multiple sensor inputs, allowing users to monitor and process data from several sensors simultaneously. The device’s advanced signal processing capabilities ensure that each sensor’s data is accurately conditioned and transmitted.
How does the PCB signal conditioner handle non-linear sensor outputs?
The PCB signal conditioner features built-in linearization functions that can compensate for non-linear sensor outputs. This ensures a linear relationship between the measured parameter and the output signal, providing accurate and consistent data across the sensor’s measurement range.
Is the PCB signal conditioner easy to install and configure?
Yes, the PCB signal conditioner is designed for easy installation and configuration. It features a user-friendly front-panel interface and PC software that allows users to quickly set up and adjust the device’s settings. The support for standard communication protocols also simplifies integration with existing data acquisition systems and industrial control networks.
What level of technical support is available for the PCB signal conditioner?
PCB Piezotronics provides comprehensive technical support for the PCB signal conditioner, including detailed product documentation, application notes, and direct access to their knowledgeable support team. Users can rely on PCB’s expertise to help them optimize their signal conditioning setup and troubleshoot any issues that may arise.